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Teknium 1e6285c53d feat: compression eval harness for agent/context_compressor.py
Ships a complete offline eval harness at scripts/compression_eval/. Runs
a real conversation fixture through ContextCompressor.compress(), asks
the compressor model to answer probe questions from the compressed
state, then has a judge model score each answer 0-5 on six dimensions
(accuracy, context_awareness, artifact_trail, completeness, continuity,
instruction_following). Methodology adapted from Factory's Dec 2025
write-up (https://factory.ai/news/evaluating-compression); the
scoreboard framing is not adopted.

Motivation: we edit context_compressor.py prompts and _template_sections
by hand and ship with no automated check that compression still
preserves file paths, error codes, or the active task. Until now there
has been no signal between 'test suite green' and 'a user hits a bad
summary in production.'

What's shipped
- DESIGN.md — full architecture, fixture/probe format, scrubber
  pipeline, grading rubric, open follow-ups
- README.md — usage, cost expectations, when to run it
- scrub_fixtures.py — reproducible pipeline that converts real sessions
  from ~/.hermes/sessions/*.jsonl into public-safe JSON fixtures. Applies
  agent.redact.redact_sensitive_text + username path normalisation +
  personal handle scrubbing + email/git-author normalisation + reasoning
  scratchpad stripping + platform-mention scrubbing + first-user
  paraphrase + system-prompt placeholder + orphan-message pruning + 2KB
  tool-output truncation
- fixtures/ — three scrubbed session snapshots covering three session
  shapes:
    feature-impl-context-priority  (75 msgs / ~17k tokens)
    debug-session-feishu-id-model  (59 msgs / ~13k tokens)
    config-build-competitive-scouts (61 msgs / ~23k tokens)
- probes/ — three probe banks (10-11 probes each) covering all four
  types (recall/artifact/continuation/decision) with expected_facts
  anchors (PR numbers, file paths, error codes, commands)
- rubric.py — six-dimension grading rubric, judge-prompt builder,
  JSON-with-fallback response parser
- compressor_driver.py — thin wrapper around ContextCompressor for
  forced single-shot compression (fixtures are below the default
  100k threshold so we force compress() to attribute score deltas
  to prompt changes, not threshold-fire variance)
- grader.py — two-phase continuation + grading calls via the OpenAI
  SDK directly against the resolved provider endpoint
- report.py — markdown report renderer (paste-ready for PR bodies),
  --compare-to delta mode, per-run JSON dumper
- run_eval.py — fire-style CLI (--fixtures, --runs, --judge-model,
  --compressor-model, --label, --focus-topic, --compare-to, --verbose)
- tests/scripts/test_compression_eval.py — 33 hermetic unit tests
  covering rubric parsing edge cases, judge-prompt building, report
  rendering, summariser medians, per-run JSON roundtrip, fixture and
  probe loading, and a PII smoke check on the checked-in fixtures

Non-LLM paths are covered by the 33-test suite that runs in CI. The
LLM paths (continuation + grading) require credentials and real API
calls, so they're exercised by running the eval itself — not by CI.

Validation
- 33/33 unit tests pass in 0.33s via scripts/run_tests.sh
- 50/50 adjacent tests (tests/agent/test_context_compressor.py) still
  pass — no regression introduced
- End-to-end dry run against debug-session-feishu-id-model with
  openai/gpt-5.4-mini via Nous Portal:
    Compression: 13081 -> 3055 tokens (76.6% ratio), 59 -> 10 messages
    Overall score: 3.25 (artifact_trail 1.50 is the weak spot,
    matching Factory's published observation)
    Specific probe misses surfaced with concrete judge notes

Noise floor (one empirical data point)
Same inputs re-run: overall 3.25 -> 3.17 (delta -0.08). Individual
dimensions varied up to ±0.5 between two single-run medians. Confirms
the DESIGN.md < 0.3 noise guidance is the right order of magnitude
for single-run comparisons. Tighter noise measurement (N=10) is
tracked as an open follow-up in DESIGN.md.

Why scripts/ and not tests/
Requires API credentials, costs ~$0.50-1.50 per run, minutes to
execute, LLM-graded (non-deterministic). Incompatible with
scripts/run_tests.sh which is hermetic, parallel, credential-free.
scripts/sample_and_compress.py is the existing precedent for offline
credentialed tooling.

Open follow-ups (tracked in DESIGN.md, not blocking this PR)
1. Iterative-merge fixture (two chained compressions on one session)
2. Precise noise-floor measurement at N=10
3. Scripted scrubber helpers to lower the cost of fixture #4+
4. Judge model selection policy (pin vs. per-user)
2026-04-25 06:17:44 -07:00
496 changed files with 11648 additions and 53982 deletions
+4
View File
@@ -52,6 +52,10 @@ ignored/
.worktrees/
environments/benchmarks/evals/
# Compression eval run outputs (harness lives in scripts/compression_eval/)
scripts/compression_eval/results/*
!scripts/compression_eval/results/.gitkeep
# Web UI build output
hermes_cli/web_dist/
-13
View File
@@ -240,19 +240,6 @@ npm run fmt # prettier
npm test # vitest
```
### TUI in the Dashboard (`hermes dashboard` → `/chat`)
The dashboard embeds the real `hermes --tui`**not** a rewrite. See `hermes_cli/pty_bridge.py` + the `@app.websocket("/api/pty")` endpoint in `hermes_cli/web_server.py`.
- Browser loads `web/src/pages/ChatPage.tsx`, which mounts xterm.js's `Terminal` with the WebGL renderer, `@xterm/addon-fit` for container-driven resize, and `@xterm/addon-unicode11` for modern wide-character widths.
- `/api/pty?token=…` upgrades to a WebSocket; auth uses the same ephemeral `_SESSION_TOKEN` as REST, via query param (browsers can't set `Authorization` on WS upgrade).
- The server spawns whatever `hermes --tui` would spawn, through `ptyprocess` (POSIX PTY — WSL works, native Windows does not).
- Frames: raw PTY bytes each direction; resize via `\x1b[RESIZE:<cols>;<rows>]` intercepted on the server and applied with `TIOCSWINSZ`.
**Do not re-implement the primary chat experience in React.** The main transcript, composer/input flow (including slash-command behavior), and PTY-backed terminal belong to the embedded `hermes --tui` — anything new you add to Ink shows up in the dashboard automatically. If you find yourself rebuilding the transcript or composer for the dashboard, stop and extend Ink instead.
**Structured React UI around the TUI is allowed when it is not a second chat surface.** Sidebar widgets, inspectors, summaries, status panels, and similar supporting views (e.g. `ChatSidebar`, `ModelPickerDialog`, `ToolCall`) are fine when they complement the embedded TUI rather than replacing the transcript / composer / terminal. Keep their state independent of the PTY child's session and surface their failures non-destructively so the terminal pane keeps working unimpaired.
---
## Adding New Tools
+4 -41
View File
@@ -390,16 +390,7 @@ def build_anthropic_client(api_key: str, base_url: str = None, timeout: float =
"timeout": Timeout(timeout=float(_read_timeout), connect=10.0),
}
if normalized_base_url:
# Azure Anthropic endpoints require an ``api-version`` query parameter.
# Pass it via default_query so the SDK appends it to every request URL
# without corrupting the base_url (appending it directly produces
# malformed paths like /anthropic?api-version=.../v1/messages).
_is_azure_endpoint = "azure.com" in normalized_base_url.lower()
if _is_azure_endpoint and "api-version" not in normalized_base_url:
kwargs["base_url"] = normalized_base_url.rstrip("/")
kwargs["default_query"] = {"api-version": "2025-04-15"}
else:
kwargs["base_url"] = normalized_base_url
kwargs["base_url"] = normalized_base_url
common_betas = _common_betas_for_base_url(normalized_base_url)
if _is_kimi_coding_endpoint(base_url):
@@ -995,26 +986,6 @@ def read_hermes_oauth_credentials() -> Optional[Dict[str, Any]]:
# ---------------------------------------------------------------------------
def _is_bedrock_model_id(model: str) -> bool:
"""Detect AWS Bedrock model IDs that use dots as namespace separators.
Bedrock model IDs come in two forms:
- Bare: ``anthropic.claude-opus-4-7``
- Regional (inference profiles): ``us.anthropic.claude-sonnet-4-5-v1:0``
In both cases the dots separate namespace components, not version
numbers, and must be preserved verbatim for the Bedrock API.
"""
lower = model.lower()
# Regional inference-profile prefixes
if any(lower.startswith(p) for p in ("global.", "us.", "eu.", "ap.", "jp.")):
return True
# Bare Bedrock model IDs: provider.model-family
if lower.startswith("anthropic."):
return True
return False
def normalize_model_name(model: str, preserve_dots: bool = False) -> str:
"""Normalize a model name for the Anthropic API.
@@ -1022,19 +993,11 @@ def normalize_model_name(model: str, preserve_dots: bool = False) -> str:
- Converts dots to hyphens in version numbers (OpenRouter uses dots,
Anthropic uses hyphens: claude-opus-4.6 → claude-opus-4-6), unless
preserve_dots is True (e.g. for Alibaba/DashScope: qwen3.5-plus).
- Preserves Bedrock model IDs (``anthropic.claude-opus-4-7``) and
regional inference profiles (``us.anthropic.claude-*``) whose dots
are namespace separators, not version separators.
"""
lower = model.lower()
if lower.startswith("anthropic/"):
model = model[len("anthropic/"):]
if not preserve_dots:
# Bedrock model IDs use dots as namespace separators
# (e.g. "anthropic.claude-opus-4-7", "us.anthropic.claude-*").
# These must not be converted to hyphens. See issue #12295.
if _is_bedrock_model_id(model):
return model
# OpenRouter uses dots for version separators (claude-opus-4.6),
# Anthropic uses hyphens (claude-opus-4-6). Convert dots to hyphens.
model = model.replace(".", "-")
@@ -1689,9 +1652,9 @@ def build_anthropic_kwargs(
# ── Strip sampling params on 4.7+ ─────────────────────────────────
# Opus 4.7 rejects any non-default temperature/top_p/top_k with a 400.
# Callers (auxiliary_client, etc.) may set these for older models;
# drop them here as a safety net so upstream 4.6 → 4.7 migrations
# don't require coordinated edits everywhere.
# Callers (auxiliary_client, flush_memories, etc.) may set these for
# older models; drop them here as a safety net so upstream 4.6 → 4.7
# migrations don't require coordinated edits everywhere.
if _forbids_sampling_params(model):
for _sampling_key in ("temperature", "top_p", "top_k"):
kwargs.pop(_sampling_key, None)
+13 -167
View File
@@ -42,7 +42,6 @@ import time
from pathlib import Path # noqa: F401 — used by test mocks
from types import SimpleNamespace
from typing import Any, Dict, List, Optional, Tuple
from urllib.parse import urlparse, parse_qs, urlunparse
from openai import OpenAI
@@ -53,17 +52,6 @@ from utils import base_url_host_matches, base_url_hostname, normalize_proxy_env_
logger = logging.getLogger(__name__)
def _extract_url_query_params(url: str):
"""Extract query params from URL, return (clean_url, default_query dict or None)."""
parsed = urlparse(url)
if parsed.query:
clean = urlunparse(parsed._replace(query=""))
params = {k: v[0] for k, v in parse_qs(parsed.query).items()}
return clean, params
return url, None
# Module-level flag: only warn once per process about stale OPENAI_BASE_URL.
_stale_base_url_warned = False
@@ -402,7 +390,7 @@ class _CodexCompletionsAdapter:
# Note: the Codex endpoint (chatgpt.com/backend-api/codex) does NOT
# support max_output_tokens or temperature — omit to avoid 400 errors.
# Tools support for auxiliary callers (e.g. skills_hub) that pass function schemas
# Tools support for flush_memories and similar callers
tools = kwargs.get("tools")
if tools:
converted = []
@@ -1169,10 +1157,8 @@ def _try_custom_endpoint() -> Tuple[Optional[Any], Optional[str]]:
return None, None
model = _read_main_model() or "gpt-4o-mini"
logger.debug("Auxiliary client: custom endpoint (%s, api_mode=%s)", model, custom_mode or "chat_completions")
_clean_base, _dq = _extract_url_query_params(custom_base)
_extra = {"default_query": _dq} if _dq else {}
if custom_mode == "codex_responses":
real_client = OpenAI(api_key=custom_key, base_url=_clean_base, **_extra)
real_client = OpenAI(api_key=custom_key, base_url=custom_base)
return CodexAuxiliaryClient(real_client, model), model
if custom_mode == "anthropic_messages":
# Third-party Anthropic-compatible gateway (MiniMax, Zhipu GLM,
@@ -1186,12 +1172,12 @@ def _try_custom_endpoint() -> Tuple[Optional[Any], Optional[str]]:
"Custom endpoint declares api_mode=anthropic_messages but the "
"anthropic SDK is not installed — falling back to OpenAI-wire."
)
return OpenAI(api_key=custom_key, base_url=_clean_base, **_extra), model
return OpenAI(api_key=custom_key, base_url=custom_base), model
return (
AnthropicAuxiliaryClient(real_client, model, custom_key, custom_base, is_oauth=False),
model,
)
return OpenAI(api_key=custom_key, base_url=_clean_base, **_extra), model
return OpenAI(api_key=custom_key, base_url=custom_base), model
def _try_codex() -> Tuple[Optional[Any], Optional[str]]:
@@ -1363,49 +1349,6 @@ def _is_auth_error(exc: Exception) -> bool:
return "error code: 401" in err_lower or "authenticationerror" in type(exc).__name__.lower()
def _is_unsupported_parameter_error(exc: Exception, param: str) -> bool:
"""Detect provider 400s for an unsupported request parameter.
Different OpenAI-compatible endpoints phrase the same class of error a few
ways: ``Unsupported parameter: X``, ``unsupported_parameter`` with a
``param`` field, ``X is not supported``, ``unknown parameter: X``,
``unrecognized request argument: X``. We match on both the parameter
name and a generic "unsupported/unknown/unrecognized parameter" marker so
call sites can reactively retry without the offending key instead of
surfacing a noisy auxiliary failure.
Generalizes the temperature-specific detector that originally shipped
with PR #15621 so the same retry strategy can cover ``max_tokens``,
``seed``, ``top_p``, and any future quirk. Credit @nicholasrae (PR #15416)
for the generalization pattern.
"""
param_lower = (param or "").lower()
if not param_lower:
return False
err_lower = str(exc).lower()
if param_lower not in err_lower:
return False
return any(marker in err_lower for marker in (
"unsupported parameter",
"unsupported_parameter",
"not supported",
"does not support",
"unknown parameter",
"unrecognized request argument",
"unrecognized parameter",
"invalid parameter",
))
def _is_unsupported_temperature_error(exc: Exception) -> bool:
"""Back-compat wrapper: detect API errors where the model rejects ``temperature``.
Delegates to :func:`_is_unsupported_parameter_error`; kept as a separate
public symbol because existing tests and call sites import it by name.
"""
return _is_unsupported_parameter_error(exc, "temperature")
def _evict_cached_clients(provider: str) -> None:
"""Drop cached auxiliary clients for a provider so fresh creds are used."""
normalized = _normalize_aux_provider(provider)
@@ -1839,15 +1782,12 @@ def resolve_provider_client(
provider,
)
extra = {}
_clean_base, _dq = _extract_url_query_params(custom_base)
if _dq:
extra["default_query"] = _dq
if base_url_host_matches(custom_base, "api.kimi.com"):
extra["default_headers"] = {"User-Agent": "claude-code/0.1.0"}
elif base_url_host_matches(custom_base, "api.githubcopilot.com"):
from hermes_cli.models import copilot_default_headers
extra["default_headers"] = copilot_default_headers()
client = OpenAI(api_key=custom_key, base_url=_clean_base, **extra)
client = OpenAI(api_key=custom_key, base_url=custom_base, **extra)
client = _wrap_if_needed(client, final_model, custom_base)
return (_to_async_client(client, final_model) if async_mode
else (client, final_model))
@@ -1884,8 +1824,6 @@ def resolve_provider_client(
model or custom_entry.get("model") or _read_main_model() or "gpt-4o-mini",
provider,
)
_clean_base2, _dq2 = _extract_url_query_params(custom_base)
_extra2 = {"default_query": _dq2} if _dq2 else {}
logger.debug(
"resolve_provider_client: named custom provider %r (%s, api_mode=%s)",
provider, final_model, entry_api_mode or "chat_completions")
@@ -1903,7 +1841,7 @@ def resolve_provider_client(
"installed — falling back to OpenAI-wire.",
provider,
)
client = OpenAI(api_key=custom_key, base_url=_clean_base2, **_extra2)
client = OpenAI(api_key=custom_key, base_url=custom_base)
return (_to_async_client(client, final_model) if async_mode
else (client, final_model))
sync_anthropic = AnthropicAuxiliaryClient(
@@ -1912,7 +1850,7 @@ def resolve_provider_client(
if async_mode:
return AsyncAnthropicAuxiliaryClient(sync_anthropic), final_model
return sync_anthropic, final_model
client = OpenAI(api_key=custom_key, base_url=_clean_base2, **_extra2)
client = OpenAI(api_key=custom_key, base_url=custom_base)
# codex_responses or inherited auto-detect (via _wrap_if_needed).
# _wrap_if_needed reads the closed-over `api_mode` (the task-level
# override). Named-provider entry api_mode=codex_responses also
@@ -2055,39 +1993,6 @@ def resolve_provider_client(
"directly supported", provider)
return None, None
elif pconfig.auth_type == "aws_sdk":
# AWS SDK providers (Bedrock) — use the Anthropic Bedrock client via
# boto3's credential chain (IAM roles, SSO, env vars, instance metadata).
try:
from agent.bedrock_adapter import has_aws_credentials, resolve_bedrock_region
from agent.anthropic_adapter import build_anthropic_bedrock_client
except ImportError:
logger.warning("resolve_provider_client: bedrock requested but "
"boto3 or anthropic SDK not installed")
return None, None
if not has_aws_credentials():
logger.debug("resolve_provider_client: bedrock requested but "
"no AWS credentials found")
return None, None
region = resolve_bedrock_region()
default_model = "anthropic.claude-haiku-4-5-20251001-v1:0"
final_model = _normalize_resolved_model(model or default_model, provider)
try:
real_client = build_anthropic_bedrock_client(region)
except ImportError as exc:
logger.warning("resolve_provider_client: cannot create Bedrock "
"client: %s", exc)
return None, None
client = AnthropicAuxiliaryClient(
real_client, final_model, api_key="aws-sdk",
base_url=f"https://bedrock-runtime.{region}.amazonaws.com",
)
logger.debug("resolve_provider_client: bedrock (%s, %s)", final_model, region)
return (_to_async_client(client, final_model) if async_mode
else (client, final_model))
elif pconfig.auth_type in ("oauth_device_code", "oauth_external"):
# OAuth providers — route through their specific try functions
if provider == "nous":
@@ -2822,8 +2727,8 @@ def _build_call_kwargs(
temperature = fixed_temperature
# Opus 4.7+ rejects any non-default temperature/top_p/top_k — silently
# drop here so auxiliary callers that hardcode temperature (e.g. 0 on
# structured-JSON extraction) don't 400 the moment
# drop here so auxiliary callers that hardcode temperature (e.g. 0.3 on
# flush_memories, 0 on structured-JSON extraction) don't 400 the moment
# the aux model is flipped to 4.7.
if temperature is not None:
from agent.anthropic_adapter import _forbids_sampling_params
@@ -2911,7 +2816,7 @@ def call_llm(
Args:
task: Auxiliary task name ("compression", "vision", "web_extract",
"session_search", "skills_hub", "mcp", "title_generation").
"session_search", "skills_hub", "mcp", "flush_memories").
Reads provider:model from config/env. Ignored if provider is set.
provider: Explicit provider override.
model: Explicit model override.
@@ -3014,45 +2919,13 @@ def call_llm(
if _is_anthropic_compat_endpoint(resolved_provider, _client_base):
kwargs["messages"] = _convert_openai_images_to_anthropic(kwargs["messages"])
# Handle unsupported temperature, max_tokens vs max_completion_tokens retry,
# then payment fallback.
# Handle max_tokens vs max_completion_tokens retry, then payment fallback.
try:
return _validate_llm_response(
client.chat.completions.create(**kwargs), task)
except Exception as first_err:
if "temperature" in kwargs and _is_unsupported_temperature_error(first_err):
retry_kwargs = dict(kwargs)
retry_kwargs.pop("temperature", None)
logger.info(
"Auxiliary %s: provider rejected temperature; retrying once without it",
task or "call",
)
try:
return _validate_llm_response(
client.chat.completions.create(**retry_kwargs), task)
except Exception as retry_err:
retry_err_str = str(retry_err)
# If retry still fails, fall through to the max_tokens /
# payment / auth chains below using the temperature-stripped
# kwargs. Re-raise only if the retry hit something those
# chains won't handle.
if not (
_is_payment_error(retry_err)
or _is_connection_error(retry_err)
or _is_auth_error(retry_err)
or "max_tokens" in retry_err_str
or "unsupported_parameter" in retry_err_str
):
raise
first_err = retry_err
kwargs = retry_kwargs
err_str = str(first_err)
if max_tokens is not None and (
"max_tokens" in err_str
or "unsupported_parameter" in err_str
or _is_unsupported_parameter_error(first_err, "max_tokens")
):
if "max_tokens" in err_str or "unsupported_parameter" in err_str:
kwargs.pop("max_tokens", None)
kwargs["max_completion_tokens"] = max_tokens
try:
@@ -3315,35 +3188,8 @@ async def async_call_llm(
return _validate_llm_response(
await client.chat.completions.create(**kwargs), task)
except Exception as first_err:
if "temperature" in kwargs and _is_unsupported_temperature_error(first_err):
retry_kwargs = dict(kwargs)
retry_kwargs.pop("temperature", None)
logger.info(
"Auxiliary %s (async): provider rejected temperature; retrying once without it",
task or "call",
)
try:
return _validate_llm_response(
await client.chat.completions.create(**retry_kwargs), task)
except Exception as retry_err:
retry_err_str = str(retry_err)
if not (
_is_payment_error(retry_err)
or _is_connection_error(retry_err)
or _is_auth_error(retry_err)
or "max_tokens" in retry_err_str
or "unsupported_parameter" in retry_err_str
):
raise
first_err = retry_err
kwargs = retry_kwargs
err_str = str(first_err)
if max_tokens is not None and (
"max_tokens" in err_str
or "unsupported_parameter" in err_str
or _is_unsupported_parameter_error(first_err, "max_tokens")
):
if "max_tokens" in err_str or "unsupported_parameter" in err_str:
kwargs.pop("max_tokens", None)
kwargs["max_completion_tokens"] = max_tokens
try:
+2 -130
View File
@@ -87,114 +87,6 @@ def reset_client_cache():
_bedrock_control_client_cache.clear()
def invalidate_runtime_client(region: str) -> bool:
"""Evict the cached ``bedrock-runtime`` client for a single region.
Per-region counterpart to :func:`reset_client_cache`. Used by the converse
call wrappers to discard clients whose underlying HTTP connection has
gone stale, so the next call allocates a fresh client (with a fresh
connection pool) instead of reusing a dead socket.
Returns True if a cached entry was evicted, False if the region was not
cached.
"""
existed = region in _bedrock_runtime_client_cache
_bedrock_runtime_client_cache.pop(region, None)
return existed
# ---------------------------------------------------------------------------
# Stale-connection detection
# ---------------------------------------------------------------------------
#
# boto3 caches its HTTPS connection pool inside the client object. When a
# pooled connection is killed out from under us (NAT timeout, VPN flap,
# server-side TCP RST, proxy idle cull, etc.), the next use surfaces as
# one of a handful of low-level exceptions — most commonly
# ``botocore.exceptions.ConnectionClosedError`` or
# ``urllib3.exceptions.ProtocolError``. urllib3 also trips an internal
# ``assert`` in a couple of paths (connection pool state checks, chunked
# response readers) which bubbles up as a bare ``AssertionError`` with an
# empty ``str(exc)``.
#
# In all of these cases the client is the problem, not the request: retrying
# with the same cached client reproduces the failure until the process
# restarts. The fix is to evict the region's cached client so the next
# attempt builds a new one.
_STALE_LIB_MODULE_PREFIXES = (
"urllib3.",
"botocore.",
"boto3.",
)
def _traceback_frames_modules(exc: BaseException):
"""Yield ``__name__``-style module strings for each frame in exc's traceback."""
tb = getattr(exc, "__traceback__", None)
while tb is not None:
frame = tb.tb_frame
module = frame.f_globals.get("__name__", "")
yield module or ""
tb = tb.tb_next
def is_stale_connection_error(exc: BaseException) -> bool:
"""Return True if ``exc`` indicates a dead/stale Bedrock HTTP connection.
Matches:
* ``botocore.exceptions.ConnectionError`` and subclasses
(``ConnectionClosedError``, ``EndpointConnectionError``,
``ReadTimeoutError``, ``ConnectTimeoutError``).
* ``urllib3.exceptions.ProtocolError`` / ``NewConnectionError`` /
``ConnectionError`` (best-effort import — urllib3 is a transitive
dependency of botocore so it is always available in practice).
* Bare ``AssertionError`` raised from a frame inside urllib3, botocore,
or boto3. These are internal-invariant failures (typically triggered
by corrupted connection-pool state after a dropped socket) and are
recoverable by swapping the client.
Non-library ``AssertionError``s (from application code or tests) are
intentionally not matched — only library-internal asserts signal stale
connection state.
"""
# botocore: the canonical signal — HTTPClientError is the umbrella for
# ConnectionClosedError, ReadTimeoutError, EndpointConnectionError,
# ConnectTimeoutError, and ProxyConnectionError. ConnectionError covers
# the same family via a different branch of the hierarchy.
try:
from botocore.exceptions import (
ConnectionError as BotoConnectionError,
HTTPClientError,
)
botocore_errors: tuple = (BotoConnectionError, HTTPClientError)
except ImportError: # pragma: no cover — botocore always present with boto3
botocore_errors = ()
if botocore_errors and isinstance(exc, botocore_errors):
return True
# urllib3: low-level transport failures
try:
from urllib3.exceptions import (
ProtocolError,
NewConnectionError,
ConnectionError as Urllib3ConnectionError,
)
urllib3_errors = (ProtocolError, NewConnectionError, Urllib3ConnectionError)
except ImportError: # pragma: no cover
urllib3_errors = ()
if urllib3_errors and isinstance(exc, urllib3_errors):
return True
# Library-internal AssertionError (urllib3 / botocore / boto3)
if isinstance(exc, AssertionError):
for module in _traceback_frames_modules(exc):
if any(module.startswith(prefix) for prefix in _STALE_LIB_MODULE_PREFIXES):
return True
return False
# ---------------------------------------------------------------------------
# AWS credential detection
# ---------------------------------------------------------------------------
@@ -895,17 +787,7 @@ def call_converse(
guardrail_config=guardrail_config,
)
try:
response = client.converse(**kwargs)
except Exception as exc:
if is_stale_connection_error(exc):
logger.warning(
"bedrock: stale-connection error on converse(region=%s, model=%s): "
"%s — evicting cached client so the next call reconnects.",
region, model, type(exc).__name__,
)
invalidate_runtime_client(region)
raise
response = client.converse(**kwargs)
return normalize_converse_response(response)
@@ -937,17 +819,7 @@ def call_converse_stream(
guardrail_config=guardrail_config,
)
try:
response = client.converse_stream(**kwargs)
except Exception as exc:
if is_stale_connection_error(exc):
logger.warning(
"bedrock: stale-connection error on converse_stream(region=%s, "
"model=%s): %s — evicting cached client so the next call reconnects.",
region, model, type(exc).__name__,
)
invalidate_runtime_client(region)
raise
response = client.converse_stream(**kwargs)
return normalize_converse_stream_events(response)
+11 -197
View File
@@ -23,52 +23,26 @@ from agent.prompt_builder import DEFAULT_AGENT_IDENTITY
logger = logging.getLogger(__name__)
# Matches Codex/Harmony tool-call serialization that occasionally leaks into
# assistant-message content when the model fails to emit a structured
# ``function_call`` item. Accepts the common forms:
#
# to=functions.exec_command
# assistant to=functions.exec_command
# <|channel|>commentary to=functions.exec_command
#
# ``to=functions.<name>`` is the stable marker — the optional ``assistant`` or
# Harmony channel prefix varies by degeneration mode. Case-insensitive to
# cover lowercase/uppercase ``assistant`` variants.
_TOOL_CALL_LEAK_PATTERN = re.compile(
r"(?:^|[\s>|])to=functions\.[A-Za-z_][\w.]*",
re.IGNORECASE,
)
# ---------------------------------------------------------------------------
# Multimodal content helpers
# ---------------------------------------------------------------------------
def _chat_content_to_responses_parts(content: Any, *, role: str = "user") -> List[Dict[str, Any]]:
def _chat_content_to_responses_parts(content: Any) -> List[Dict[str, Any]]:
"""Convert chat-style multimodal content to Responses API input parts.
Input: ``[{"type":"text"|"image_url", ...}]`` (native OpenAI Chat format)
Output: ``[{"type":"input_text"|"output_text"|"input_image", ...}]`` (Responses format)
The ``role`` parameter controls the text content type:
- ``"user"`` (default) → ``"input_text"``
- ``"assistant"`` → ``"output_text"``
The Responses API rejects ``input_text`` inside assistant messages and
``output_text`` inside user messages, so callers MUST pass the correct
role for the message being converted.
Output: ``[{"type":"input_text"|"input_image", ...}]`` (Responses format)
Returns an empty list when ``content`` is not a list or contains no
recognized parts — callers fall back to the string path.
"""
text_type = "output_text" if role == "assistant" else "input_text"
if not isinstance(content, list):
return []
converted: List[Dict[str, Any]] = []
for part in content:
if isinstance(part, str):
if part:
converted.append({"type": text_type, "text": part})
converted.append({"type": "input_text", "text": part})
continue
if not isinstance(part, dict):
continue
@@ -76,7 +50,7 @@ def _chat_content_to_responses_parts(content: Any, *, role: str = "user") -> Lis
if ptype in {"text", "input_text", "output_text"}:
text = part.get("text")
if isinstance(text, str) and text:
converted.append({"type": text_type, "text": text})
converted.append({"type": "input_text", "text": text})
continue
if ptype in {"image_url", "input_image"}:
image_ref = part.get("image_url")
@@ -227,23 +201,6 @@ def _responses_tools(tools: Optional[List[Dict[str, Any]]] = None) -> Optional[L
# Message format conversion
# ---------------------------------------------------------------------------
_RESPONSE_MESSAGE_STATUSES = {"completed", "incomplete", "in_progress"}
def _normalize_responses_message_status(value: Any, *, default: str = "completed") -> str:
"""Normalize a Responses assistant message status for replay.
The API accepts completed/incomplete/in_progress on replayed assistant
output messages. Preserve those exactly (modulo case/hyphen spelling) so
incomplete Codex continuation turns don't get falsely marked completed.
"""
if isinstance(value, str):
status = value.strip().lower().replace("-", "_").replace(" ", "_")
if status in _RESPONSE_MESSAGE_STATUSES:
return status
return default
def _chat_messages_to_responses_input(messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
"""Convert internal chat-style messages to Responses input items."""
items: List[Dict[str, Any]] = []
@@ -259,10 +216,9 @@ def _chat_messages_to_responses_input(messages: List[Dict[str, Any]]) -> List[Di
if role in {"user", "assistant"}:
content = msg.get("content", "")
if isinstance(content, list):
content_parts = _chat_content_to_responses_parts(content, role=role)
text_type = "output_text" if role == "assistant" else "input_text"
content_parts = _chat_content_to_responses_parts(content)
content_text = "".join(
p.get("text", "") for p in content_parts if p.get("type") == text_type
p.get("text", "") for p in content_parts if p.get("type") == "input_text"
)
else:
content_parts = []
@@ -289,57 +245,7 @@ def _chat_messages_to_responses_input(messages: List[Dict[str, Any]]) -> List[Di
seen_item_ids.add(item_id)
has_codex_reasoning = True
# Replay exact assistant message items (with id/phase) from
# previous turns so the API can maintain prefix-cache hits.
# OpenAI docs: "preserve and resend phase on all assistant
# messages — dropping it can degrade performance."
codex_message_items = msg.get("codex_message_items")
replayed_message_items = 0
if isinstance(codex_message_items, list):
for raw_item in codex_message_items:
if not isinstance(raw_item, dict):
continue
if raw_item.get("type") != "message" or raw_item.get("role") != "assistant":
continue
raw_content_parts = raw_item.get("content")
if not isinstance(raw_content_parts, list):
continue
normalized_content_parts = []
for part in raw_content_parts:
if not isinstance(part, dict):
continue
part_type = str(part.get("type") or "").strip()
if part_type not in {"output_text", "text"}:
continue
text = part.get("text", "")
if text is None:
text = ""
if not isinstance(text, str):
text = str(text)
normalized_content_parts.append({"type": "output_text", "text": text})
if not normalized_content_parts:
continue
replay_item = {
"type": "message",
"role": "assistant",
"status": _normalize_responses_message_status(raw_item.get("status")),
"content": normalized_content_parts,
}
item_id = raw_item.get("id")
if isinstance(item_id, str) and item_id.strip():
replay_item["id"] = item_id.strip()
phase = raw_item.get("phase")
if isinstance(phase, str) and phase.strip():
replay_item["phase"] = phase.strip()
items.append(replay_item)
replayed_message_items += 1
if replayed_message_items > 0:
pass
elif content_parts:
if content_parts:
items.append({"role": "assistant", "content": content_parts})
elif content_text.strip():
items.append({"role": "assistant", "content": content_text})
@@ -499,47 +405,6 @@ def _preflight_codex_input_items(raw_items: Any) -> List[Dict[str, Any]]:
normalized.append(reasoning_item)
continue
if item_type == "message":
role = item.get("role")
if role != "assistant":
raise ValueError(f"Codex Responses input[{idx}] message items must have role='assistant'.")
content = item.get("content")
if not isinstance(content, list):
raise ValueError(f"Codex Responses input[{idx}] message item must have content list.")
normalized_content = []
for part_idx, part in enumerate(content):
if not isinstance(part, dict):
raise ValueError(
f"Codex Responses input[{idx}] message content[{part_idx}] must be an object."
)
part_type = part.get("type")
if part_type not in {"output_text", "text"}:
raise ValueError(
f"Codex Responses input[{idx}] message content[{part_idx}] has unsupported type {part_type!r}."
)
text = part.get("text", "")
if text is None:
text = ""
if not isinstance(text, str):
text = str(text)
normalized_content.append({"type": "output_text", "text": text})
if not normalized_content:
raise ValueError(f"Codex Responses input[{idx}] message item must contain at least one text part.")
normalized_item: Dict[str, Any] = {
"type": "message",
"role": "assistant",
"status": _normalize_responses_message_status(item.get("status")),
"content": normalized_content,
}
item_id = item.get("id")
if isinstance(item_id, str) and item_id.strip():
normalized_item["id"] = item_id.strip()
phase = item.get("phase")
if isinstance(phase, str) and phase.strip():
normalized_item["phase"] = phase.strip()
normalized.append(normalized_item)
continue
role = item.get("role")
if role in {"user", "assistant"}:
content = item.get("content", "")
@@ -547,16 +412,13 @@ def _preflight_codex_input_items(raw_items: Any) -> List[Dict[str, Any]]:
content = ""
if isinstance(content, list):
# Multimodal content from ``_chat_messages_to_responses_input``
# is already in Responses format (``input_text`` / ``output_text``
# / ``input_image``). Validate each part and pass through.
# Use the correct text type for the role — ``output_text`` for
# assistant messages, ``input_text`` for user messages.
text_type = "output_text" if role == "assistant" else "input_text"
# is already in Responses format (``input_text`` / ``input_image``).
# Validate each part and pass through.
validated: List[Dict[str, Any]] = []
for part_idx, part in enumerate(content):
if isinstance(part, str):
if part:
validated.append({"type": text_type, "text": part})
validated.append({"type": "input_text", "text": part})
continue
if not isinstance(part, dict):
raise ValueError(
@@ -567,7 +429,7 @@ def _preflight_codex_input_items(raw_items: Any) -> List[Dict[str, Any]]:
text = part.get("text", "")
if not isinstance(text, str):
text = str(text or "")
validated.append({"type": text_type, "text": text})
validated.append({"type": "input_text", "text": text})
elif ptype in {"input_image", "image_url"}:
image_ref = part.get("image_url", "")
detail = part.get("detail")
@@ -824,7 +686,6 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
content_parts: List[str] = []
reasoning_parts: List[str] = []
reasoning_items_raw: List[Dict[str, Any]] = []
message_items_raw: List[Dict[str, Any]] = []
tool_calls: List[Any] = []
has_incomplete_items = response_status in {"queued", "in_progress", "incomplete"}
saw_commentary_phase = False
@@ -843,7 +704,6 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
if item_type == "message":
item_phase = getattr(item, "phase", None)
normalized_phase = None
if isinstance(item_phase, str):
normalized_phase = item_phase.strip().lower()
if normalized_phase in {"commentary", "analysis"}:
@@ -853,18 +713,6 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
message_text = _extract_responses_message_text(item)
if message_text:
content_parts.append(message_text)
raw_message_item: Dict[str, Any] = {
"type": "message",
"role": "assistant",
"status": _normalize_responses_message_status(item_status),
"content": [{"type": "output_text", "text": message_text}],
}
item_id = getattr(item, "id", None)
if isinstance(item_id, str) and item_id:
raw_message_item["id"] = item_id
if normalized_phase:
raw_message_item["phase"] = normalized_phase
message_items_raw.append(raw_message_item)
elif item_type == "reasoning":
reasoning_text = _extract_responses_reasoning_text(item)
if reasoning_text:
@@ -939,37 +787,6 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
if isinstance(out_text, str):
final_text = out_text.strip()
# ── Tool-call leak recovery ──────────────────────────────────
# gpt-5.x on the Codex Responses API sometimes degenerates and emits
# what should be a structured `function_call` item as plain assistant
# text using the Harmony/Codex serialization (``to=functions.foo
# {json}`` or ``assistant to=functions.foo {json}``). The model
# intended to call a tool, but the intent never made it into
# ``response.output`` as a ``function_call`` item, so ``tool_calls``
# is empty here. If we pass this through, the parent sees a
# confident-looking summary with no audit trail (empty ``tool_trace``)
# and no tools actually ran — the Taiwan-embassy-email incident.
#
# Detection: leaked tokens always contain ``to=functions.<name>`` and
# the assistant message has no real tool calls. Treat it as incomplete
# so the existing Codex-incomplete continuation path (3 retries,
# handled in run_agent.py) gets a chance to re-elicit a proper
# ``function_call`` item. The existing loop already handles message
# append, dedup, and retry budget.
leaked_tool_call_text = False
if final_text and not tool_calls and _TOOL_CALL_LEAK_PATTERN.search(final_text):
leaked_tool_call_text = True
logger.warning(
"Codex response contains leaked tool-call text in assistant content "
"(no structured function_call items). Treating as incomplete so the "
"continuation path can re-elicit a proper tool call. Leaked snippet: %r",
final_text[:300],
)
# Clear the text so downstream code doesn't surface the garbage as
# a summary. The encrypted reasoning items (if any) are preserved
# so the model keeps its chain-of-thought on the retry.
final_text = ""
assistant_message = SimpleNamespace(
content=final_text,
tool_calls=tool_calls,
@@ -977,13 +794,10 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
reasoning_content=None,
reasoning_details=None,
codex_reasoning_items=reasoning_items_raw or None,
codex_message_items=message_items_raw or None,
)
if tool_calls:
finish_reason = "tool_calls"
elif leaked_tool_call_text:
finish_reason = "incomplete"
elif has_incomplete_items or (saw_commentary_phase and not saw_final_answer_phase):
finish_reason = "incomplete"
elif reasoning_items_raw and not final_text:
-15
View File
@@ -294,7 +294,6 @@ class ContextCompressor(ContextEngine):
self._context_probed = False
self._context_probe_persistable = False
self._previous_summary = None
self._last_summary_error = None
self._last_compression_savings_pct = 100.0
self._ineffective_compression_count = 0
@@ -318,13 +317,6 @@ class ContextCompressor(ContextEngine):
int(context_length * self.threshold_percent),
MINIMUM_CONTEXT_LENGTH,
)
# Recalculate token budgets for the new context length so the
# compressor stays calibrated after a model switch (e.g. 200K → 32K).
target_tokens = int(self.threshold_tokens * self.summary_target_ratio)
self.tail_token_budget = target_tokens
self.max_summary_tokens = min(
int(context_length * 0.05), _SUMMARY_TOKENS_CEILING,
)
def __init__(
self,
@@ -397,7 +389,6 @@ class ContextCompressor(ContextEngine):
self._last_compression_savings_pct: float = 100.0
self._ineffective_compression_count: int = 0
self._summary_failure_cooldown_until: float = 0.0
self._last_summary_error: Optional[str] = None
def update_from_response(self, usage: Dict[str, Any]):
"""Update tracked token usage from API response."""
@@ -821,12 +812,10 @@ The user has requested that this compaction PRIORITISE preserving all informatio
self._previous_summary = summary
self._summary_failure_cooldown_until = 0.0
self._summary_model_fallen_back = False
self._last_summary_error = None
return self._with_summary_prefix(summary)
except RuntimeError:
# No provider configured — long cooldown, unlikely to self-resolve
self._summary_failure_cooldown_until = time.monotonic() + _SUMMARY_FAILURE_COOLDOWN_SECONDS
self._last_summary_error = "no auxiliary LLM provider configured"
logging.warning("Context compression: no provider available for "
"summary. Middle turns will be dropped without summary "
"for %d seconds.",
@@ -864,10 +853,6 @@ The user has requested that this compaction PRIORITISE preserving all informatio
# Transient errors (timeout, rate limit, network) — shorter cooldown
_transient_cooldown = 60
self._summary_failure_cooldown_until = time.monotonic() + _transient_cooldown
err_text = str(e).strip() or e.__class__.__name__
if len(err_text) > 220:
err_text = err_text[:217].rstrip() + "..."
self._last_summary_error = err_text
logging.warning(
"Failed to generate context summary: %s. "
"Further summary attempts paused for %d seconds.",
+3 -6
View File
@@ -14,7 +14,6 @@ from datetime import datetime
from typing import Any, Dict, List, Optional, Set, Tuple
from hermes_constants import OPENROUTER_BASE_URL
from hermes_cli.config import get_env_value
import hermes_cli.auth as auth_mod
from hermes_cli.auth import (
CODEX_ACCESS_TOKEN_REFRESH_SKEW_SECONDS,
@@ -1274,8 +1273,7 @@ def _seed_from_env(provider: str, entries: List[PooledCredential]) -> Tuple[bool
def _is_source_suppressed(_p, _s): # type: ignore[misc]
return False
if provider == "openrouter":
# Check both os.environ and ~/.hermes/.env file
token = (get_env_value("OPENROUTER_API_KEY") or "").strip()
token = os.getenv("OPENROUTER_API_KEY", "").strip()
if token:
source = "env:OPENROUTER_API_KEY"
if _is_source_suppressed(provider, source):
@@ -1301,7 +1299,7 @@ def _seed_from_env(provider: str, entries: List[PooledCredential]) -> Tuple[bool
env_url = ""
if pconfig.base_url_env_var:
env_url = (get_env_value(pconfig.base_url_env_var) or "").strip().rstrip("/")
env_url = os.getenv(pconfig.base_url_env_var, "").strip().rstrip("/")
env_vars = list(pconfig.api_key_env_vars)
if provider == "anthropic":
@@ -1312,8 +1310,7 @@ def _seed_from_env(provider: str, entries: List[PooledCredential]) -> Tuple[bool
]
for env_var in env_vars:
# Check both os.environ and ~/.hermes/.env file
token = (get_env_value(env_var) or "").strip()
token = os.getenv(env_var, "").strip()
if not token:
continue
source = f"env:{env_var}"
+2 -43
View File
@@ -31,7 +31,6 @@ from __future__ import annotations
import json
import logging
import re
import inspect
from typing import Any, Dict, List, Optional
from agent.memory_provider import MemoryProvider
@@ -313,39 +312,7 @@ class MemoryManager:
)
return "\n\n".join(parts)
@staticmethod
def _provider_memory_write_metadata_mode(provider: MemoryProvider) -> str:
"""Return how to pass metadata to a provider's memory-write hook."""
try:
signature = inspect.signature(provider.on_memory_write)
except (TypeError, ValueError):
return "keyword"
params = list(signature.parameters.values())
if any(p.kind == inspect.Parameter.VAR_KEYWORD for p in params):
return "keyword"
if "metadata" in signature.parameters:
return "keyword"
accepted = [
p for p in params
if p.kind in (
inspect.Parameter.POSITIONAL_ONLY,
inspect.Parameter.POSITIONAL_OR_KEYWORD,
inspect.Parameter.KEYWORD_ONLY,
)
]
if len(accepted) >= 4:
return "positional"
return "legacy"
def on_memory_write(
self,
action: str,
target: str,
content: str,
metadata: Optional[Dict[str, Any]] = None,
) -> None:
def on_memory_write(self, action: str, target: str, content: str) -> None:
"""Notify external providers when the built-in memory tool writes.
Skips the builtin provider itself (it's the source of the write).
@@ -354,15 +321,7 @@ class MemoryManager:
if provider.name == "builtin":
continue
try:
metadata_mode = self._provider_memory_write_metadata_mode(provider)
if metadata_mode == "keyword":
provider.on_memory_write(
action, target, content, metadata=dict(metadata or {})
)
elif metadata_mode == "positional":
provider.on_memory_write(action, target, content, dict(metadata or {}))
else:
provider.on_memory_write(action, target, content)
provider.on_memory_write(action, target, content)
except Exception as e:
logger.debug(
"Memory provider '%s' on_memory_write failed: %s",
+3 -12
View File
@@ -26,7 +26,7 @@ Optional hooks (override to opt in):
on_turn_start(turn, message, **kwargs) per-turn tick with runtime context
on_session_end(messages) end-of-session extraction
on_pre_compress(messages) -> str extract before context compression
on_memory_write(action, target, content, metadata=None) mirror built-in memory writes
on_memory_write(action, target, content) mirror built-in memory writes
on_delegation(task, result, **kwargs) parent-side observation of subagent work
"""
@@ -34,7 +34,7 @@ from __future__ import annotations
import logging
from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional
from typing import Any, Dict, List
logger = logging.getLogger(__name__)
@@ -220,21 +220,12 @@ class MemoryProvider(ABC):
should all have ``env_var`` set and this method stays no-op).
"""
def on_memory_write(
self,
action: str,
target: str,
content: str,
metadata: Optional[Dict[str, Any]] = None,
) -> None:
def on_memory_write(self, action: str, target: str, content: str) -> None:
"""Called when the built-in memory tool writes an entry.
action: 'add', 'replace', or 'remove'
target: 'memory' or 'user'
content: the entry content
metadata: structured provenance for the write, when available. Common
keys include ``write_origin``, ``execution_context``, ``session_id``,
``parent_session_id``, ``platform``, and ``tool_name``.
Use to mirror built-in memory writes to your backend.
"""
+21 -61
View File
@@ -106,11 +106,9 @@ _endpoint_model_metadata_cache_time: Dict[str, float] = {}
_ENDPOINT_MODEL_CACHE_TTL = 300
# Descending tiers for context length probing when the model is unknown.
# We start at 256K (covers GPT-5.x, many current large-context models) and
# step down on context-length errors until one works. Tier[0] is also the
# default fallback when no detection method succeeds.
# We start at 128K (a safe default for most modern models) and step down
# on context-length errors until one works.
CONTEXT_PROBE_TIERS = [
256_000,
128_000,
64_000,
32_000,
@@ -145,11 +143,10 @@ DEFAULT_CONTEXT_LENGTHS = {
"claude": 200000,
# OpenAI — GPT-5 family (most have 400k; specific overrides first)
# Source: https://developers.openai.com/api/docs/models
# GPT-5.5 (launched Apr 23 2026) is 1.05M on the direct OpenAI API and
# ChatGPT Codex OAuth caps it at 272K; both paths resolve via their own
# provider-aware branches (_resolve_codex_oauth_context_length + models.dev).
# This hardcoded value is only reached when every probe misses.
"gpt-5.5": 1050000,
# GPT-5.5 (launched Apr 23 2026). 400k is the fallback for providers we
# can't probe live. ChatGPT Codex OAuth actually caps lower (272k as of
# Apr 2026) and is resolved via _resolve_codex_oauth_context_length().
"gpt-5.5": 400000,
"gpt-5.4-nano": 400000, # 400k (not 1.05M like full 5.4)
"gpt-5.4-mini": 400000, # 400k (not 1.05M like full 5.4)
"gpt-5.4": 1050000, # GPT-5.4, GPT-5.4 Pro (1.05M context)
@@ -165,17 +162,7 @@ DEFAULT_CONTEXT_LENGTHS = {
"gemma-4-31b": 256000,
"gemma-3": 131072,
"gemma": 8192, # fallback for older gemma models
# DeepSeek — V4 family ships with a 1M context window. The legacy
# aliases ``deepseek-chat`` / ``deepseek-reasoner`` are server-side
# mapped to the non-thinking / thinking modes of ``deepseek-v4-flash``
# and inherit the same 1M window. The ``deepseek`` substring entry
# below remains as a 128K fallback for older / unknown DeepSeek model
# ids (e.g. via custom endpoints).
# https://api-docs.deepseek.com/zh-cn/quick_start/pricing
"deepseek-v4-pro": 1_000_000,
"deepseek-v4-flash": 1_000_000,
"deepseek-chat": 1_000_000,
"deepseek-reasoner": 1_000_000,
# DeepSeek
"deepseek": 128000,
# Meta
"llama": 131072,
@@ -1206,14 +1193,12 @@ def get_model_context_length(
api_key: str = "",
config_context_length: int | None = None,
provider: str = "",
custom_providers: list | None = None,
) -> int:
"""Get the context length for a model.
Resolution order:
0. Explicit config override (model.context_length or custom_providers per-model)
1. Persistent cache (previously discovered via probing)
1b. AWS Bedrock static table (must precede custom-endpoint probe)
2. Active endpoint metadata (/models for explicit custom endpoints)
3. Local server query (for local endpoints)
4. Anthropic /v1/models API (API-key users only, not OAuth)
@@ -1227,23 +1212,6 @@ def get_model_context_length(
if config_context_length is not None and isinstance(config_context_length, int) and config_context_length > 0:
return config_context_length
# 0b. custom_providers per-model override — check before any probe.
# This closes the gap where /model switch and display paths used to fall
# back to 128K despite the user having a per-model context_length set.
# See #15779.
if custom_providers and base_url and model:
try:
from hermes_cli.config import get_custom_provider_context_length
cp_ctx = get_custom_provider_context_length(
model=model,
base_url=base_url,
custom_providers=custom_providers,
)
if cp_ctx:
return cp_ctx
except Exception:
pass # fall through to probing
# Normalise provider-prefixed model names (e.g. "local:model-name" →
# "model-name") so cache lookups and server queries use the bare ID that
# local servers actually know about. Ollama "model:tag" colons are preserved.
@@ -1269,26 +1237,6 @@ def get_model_context_length(
else:
return cached
# 1b. AWS Bedrock — use static context length table.
# Bedrock's ListFoundationModels API doesn't expose context window sizes,
# so we maintain a curated table in bedrock_adapter.py that reflects
# AWS-imposed limits (e.g. 200K for Claude models vs 1M on the native
# Anthropic API). This must run BEFORE the custom-endpoint probe at
# step 2 — bedrock-runtime.<region>.amazonaws.com is not in
# _URL_TO_PROVIDER, so it would otherwise be treated as a custom endpoint,
# fail the /models probe (Bedrock doesn't expose that shape), and fall
# back to the 128K default before reaching the original step 4b branch.
if provider == "bedrock" or (
base_url
and base_url_hostname(base_url).startswith("bedrock-runtime.")
and base_url_host_matches(base_url, "amazonaws.com")
):
try:
from agent.bedrock_adapter import get_bedrock_context_length
return get_bedrock_context_length(model)
except ImportError:
pass # boto3 not installed — fall through to generic resolution
# 2. Active endpoint metadata for truly custom/unknown endpoints.
# Known providers (Copilot, OpenAI, Anthropic, etc.) skip this — their
# /models endpoint may report a provider-imposed limit (e.g. Copilot
@@ -1334,7 +1282,19 @@ def get_model_context_length(
if ctx:
return ctx
# 4b. (Bedrock handled earlier at step 1b — before custom-endpoint probe.)
# 4b. AWS Bedrock — use static context length table.
# Bedrock's ListFoundationModels doesn't expose context window sizes,
# so we maintain a curated table in bedrock_adapter.py.
if provider == "bedrock" or (
base_url
and base_url_hostname(base_url).startswith("bedrock-runtime.")
and base_url_host_matches(base_url, "amazonaws.com")
):
try:
from agent.bedrock_adapter import get_bedrock_context_length
return get_bedrock_context_length(model)
except ImportError:
pass # boto3 not installed — fall through to generic resolution
# 5. Provider-aware lookups (before generic OpenRouter cache)
# These are provider-specific and take priority over the generic OR cache,
@@ -1383,7 +1343,7 @@ def get_model_context_length(
# 6. OpenRouter live API metadata (provider-unaware fallback)
metadata = fetch_model_metadata()
if model in metadata:
return metadata[model].get("context_length", DEFAULT_FALLBACK_CONTEXT)
return metadata[model].get("context_length", 128000)
# 8. Hardcoded defaults (fuzzy match — longest key first for specificity)
# Only check `default_model in model` (is the key a substring of the input).
-142
View File
@@ -180,145 +180,3 @@ def format_remaining(seconds: float) -> str:
h, remainder = divmod(s, 3600)
m = remainder // 60
return f"{h}h {m}m" if m else f"{h}h"
# Buckets with reset windows shorter than this are treated as transient
# (upstream jitter, secondary throttling) rather than a genuine quota
# exhaustion worth a cross-session breaker trip.
_MIN_RESET_FOR_BREAKER_SECONDS = 60.0
def is_genuine_nous_rate_limit(
*,
headers: Optional[Mapping[str, str]] = None,
last_known_state: Optional[Any] = None,
) -> bool:
"""Decide whether a 429 from Nous Portal is a real account rate limit.
Nous Portal multiplexes multiple upstream providers (DeepSeek, Kimi,
MiMo, Hermes, ...) behind one endpoint. A 429 can mean either:
(a) The caller's own RPM / RPH / TPM / TPH bucket on Nous is
exhausted a genuine rate limit that will last until the
bucket resets.
(b) The upstream provider is out of capacity for a specific model
transient, clears in seconds, and has nothing to do with
the caller's quota on Nous.
Tripping the cross-session breaker on (b) blocks ALL Nous requests
(and all models, since Nous is one provider key) for minutes even
though the caller's account is healthy and a different model would
have worked. That's the bug users hit when DeepSeek V4 Pro 429s
trigger a breaker that then blocks Kimi 2.6 and MiMo V2.5 Pro.
We tell the two apart by looking at:
1. The 429 response's own ``x-ratelimit-*`` headers. Nous emits
the full suite on every response including 429s. An exhausted
bucket (``remaining == 0`` with a reset window >= 60s) is
proof of (a).
2. The last-known-good rate-limit state captured by
``_capture_rate_limits()`` on the previous successful
response. If any bucket there was already near-exhausted with
a substantial reset window, the current 429 is almost
certainly (a) continuing from that condition.
If neither signal fires, we treat the 429 as (b): fail the single
request, let the retry loop or model-switch proceed, and do NOT
write the cross-session breaker file.
Returns True when the evidence points at (a).
"""
# Signal 1: current 429 response headers.
state = _parse_buckets_from_headers(headers)
if _has_exhausted_bucket(state):
return True
# Signal 2: last-known-good state from a recent successful response.
# Accepts either a RateLimitState (dataclass from rate_limit_tracker)
# or a dict of bucket snapshots.
if last_known_state is not None and _has_exhausted_bucket_in_object(last_known_state):
return True
return False
def _parse_buckets_from_headers(
headers: Optional[Mapping[str, str]],
) -> dict[str, tuple[Optional[int], Optional[float]]]:
"""Extract (remaining, reset_seconds) per bucket from x-ratelimit-* headers.
Returns empty dict when no rate-limit headers are present.
"""
if not headers:
return {}
lowered = {k.lower(): v for k, v in headers.items()}
if not any(k.startswith("x-ratelimit-") for k in lowered):
return {}
def _maybe_int(raw: Optional[str]) -> Optional[int]:
if raw is None:
return None
try:
return int(float(raw))
except (TypeError, ValueError):
return None
def _maybe_float(raw: Optional[str]) -> Optional[float]:
if raw is None:
return None
try:
return float(raw)
except (TypeError, ValueError):
return None
result: dict[str, tuple[Optional[int], Optional[float]]] = {}
for tag in ("requests", "requests-1h", "tokens", "tokens-1h"):
remaining = _maybe_int(lowered.get(f"x-ratelimit-remaining-{tag}"))
reset = _maybe_float(lowered.get(f"x-ratelimit-reset-{tag}"))
if remaining is not None or reset is not None:
result[tag] = (remaining, reset)
return result
def _has_exhausted_bucket(
buckets: Mapping[str, tuple[Optional[int], Optional[float]]],
) -> bool:
"""Return True when any bucket has remaining == 0 AND a meaningful reset window."""
for remaining, reset in buckets.values():
if remaining is None or remaining > 0:
continue
if reset is None:
continue
if reset >= _MIN_RESET_FOR_BREAKER_SECONDS:
return True
return False
def _has_exhausted_bucket_in_object(state: Any) -> bool:
"""Check a RateLimitState-like object for an exhausted bucket.
Accepts the dataclass from ``agent.rate_limit_tracker`` (buckets
exposed as attributes ``requests_min``, ``requests_hour``,
``tokens_min``, ``tokens_hour``) and falls back gracefully for any
object missing those attributes.
"""
for attr in ("requests_min", "requests_hour", "tokens_min", "tokens_hour"):
bucket = getattr(state, attr, None)
if bucket is None:
continue
limit = getattr(bucket, "limit", 0) or 0
remaining = getattr(bucket, "remaining", 0) or 0
# Prefer the adjusted "remaining_seconds_now" property when present;
# fall back to raw reset_seconds.
reset = getattr(bucket, "remaining_seconds_now", None)
if reset is None:
reset = getattr(bucket, "reset_seconds", 0.0) or 0.0
if limit <= 0:
continue
if remaining > 0:
continue
if reset >= _MIN_RESET_FOR_BREAKER_SECONDS:
return True
return False
-191
View File
@@ -1,191 +0,0 @@
"""
Contextual first-touch onboarding hints.
Instead of blocking first-run questionnaires, show a one-time hint the *first*
time a user hits a behavior fork message-while-running, first long-running
tool, etc. Each hint is shown once per install (tracked in ``config.yaml`` under
``onboarding.seen.<flag>``) and then never again.
Keep this module tiny and dependency-free so both the CLI and gateway can import
it without pulling in heavy modules.
"""
from __future__ import annotations
import logging
from pathlib import Path
from typing import Any, Mapping, Optional
logger = logging.getLogger(__name__)
# -------------------------------------------------------------------------
# Flag names (stable — used as config.yaml keys under onboarding.seen)
# -------------------------------------------------------------------------
BUSY_INPUT_FLAG = "busy_input_prompt"
TOOL_PROGRESS_FLAG = "tool_progress_prompt"
OPENCLAW_RESIDUE_FLAG = "openclaw_residue_cleanup"
# -------------------------------------------------------------------------
# Hint content
# -------------------------------------------------------------------------
def busy_input_hint_gateway(mode: str) -> str:
"""Hint shown the first time a user messages while the agent is busy.
``mode`` is the effective busy_input_mode that was just applied, so the
message matches reality ("I just interrupted…" vs "I just queued…").
"""
if mode == "queue":
return (
"💡 First-time tip — I queued your message instead of interrupting. "
"Send `/busy interrupt` to make new messages stop the current task "
"immediately, or `/busy status` to check. This notice won't appear again."
)
if mode == "steer":
return (
"💡 First-time tip — I steered your message into the current run; "
"it will arrive after the next tool call instead of interrupting. "
"Send `/busy interrupt` or `/busy queue` to change this, or "
"`/busy status` to check. This notice won't appear again."
)
return (
"💡 First-time tip — I just interrupted my current task to answer you. "
"Send `/busy queue` to queue follow-ups for after the current task instead, "
"`/busy steer` to inject them mid-run without interrupting, or "
"`/busy status` to check. This notice won't appear again."
)
def busy_input_hint_cli(mode: str) -> str:
"""CLI version of the busy-input hint (plain text, no markdown)."""
if mode == "queue":
return (
"(tip) Your message was queued for the next turn. "
"Use /busy interrupt to make Enter stop the current run instead, "
"or /busy steer to inject mid-run. This tip only shows once."
)
if mode == "steer":
return (
"(tip) Your message was steered into the current run; it arrives "
"after the next tool call. Use /busy interrupt or /busy queue to "
"change this. This tip only shows once."
)
return (
"(tip) Your message interrupted the current run. "
"Use /busy queue to queue messages for the next turn instead, "
"or /busy steer to inject mid-run. This tip only shows once."
)
def tool_progress_hint_gateway() -> str:
return (
"💡 First-time tip — that tool took a while and I'm streaming every step. "
"If the progress messages feel noisy, send `/verbose` to cycle modes "
"(all → new → off). This notice won't appear again."
)
def tool_progress_hint_cli() -> str:
return (
"(tip) That tool ran for a while. Use /verbose to cycle tool-progress "
"display modes (all -> new -> off -> verbose). This tip only shows once."
)
def openclaw_residue_hint_cli() -> str:
"""Banner shown the first time Hermes starts and finds ``~/.openclaw/``.
OpenClaw-era config, memory, and skill paths in ``~/.openclaw/`` will
otherwise attract the agent (memory entries like ``~/.openclaw/config.yaml``
get carried forward and the agent dutifully reads them). ``hermes claw
cleanup`` renames the directory so the agent stops finding it.
"""
return (
"Heads up — an OpenClaw workspace was detected at ~/.openclaw/.\n"
"After migrating, the agent can still get confused and read that "
"directory's config/memory instead of Hermes's.\n"
"Run `hermes claw cleanup` to archive it (rename → .openclaw.pre-migration). "
"This tip only shows once; rerun it any time with `hermes claw cleanup`."
)
def detect_openclaw_residue(home: Optional[Path] = None) -> bool:
"""Return True if an OpenClaw workspace directory is present in ``$HOME``.
Pure filesystem check no side effects. ``home`` override exists for tests.
"""
base = home or Path.home()
try:
return (base / ".openclaw").is_dir()
except OSError:
return False
# -------------------------------------------------------------------------
# State read / write
# -------------------------------------------------------------------------
def _get_seen_dict(config: Mapping[str, Any]) -> Mapping[str, Any]:
onboarding = config.get("onboarding") if isinstance(config, Mapping) else None
if not isinstance(onboarding, Mapping):
return {}
seen = onboarding.get("seen")
return seen if isinstance(seen, Mapping) else {}
def is_seen(config: Mapping[str, Any], flag: str) -> bool:
"""Return True if the user has already been shown this first-touch hint."""
return bool(_get_seen_dict(config).get(flag))
def mark_seen(config_path: Path, flag: str) -> bool:
"""Persist ``onboarding.seen.<flag> = True`` to ``config_path``.
Uses the atomic YAML writer so a concurrent process can't observe a
partially-written file. Returns True on success, False on any error
(including the config file being absent onboarding is best-effort).
"""
try:
import yaml
from utils import atomic_yaml_write
except Exception as e: # pragma: no cover — dependency issue
logger.debug("onboarding: failed to import yaml/utils: %s", e)
return False
try:
cfg: dict = {}
if config_path.exists():
with open(config_path, encoding="utf-8") as f:
cfg = yaml.safe_load(f) or {}
if not isinstance(cfg.get("onboarding"), dict):
cfg["onboarding"] = {}
seen = cfg["onboarding"].get("seen")
if not isinstance(seen, dict):
seen = {}
cfg["onboarding"]["seen"] = seen
if seen.get(flag) is True:
return True # already marked — nothing to do
seen[flag] = True
atomic_yaml_write(config_path, cfg)
return True
except Exception as e:
logger.debug("onboarding: failed to mark flag %s: %s", flag, e)
return False
__all__ = [
"BUSY_INPUT_FLAG",
"TOOL_PROGRESS_FLAG",
"OPENCLAW_RESIDUE_FLAG",
"busy_input_hint_gateway",
"busy_input_hint_cli",
"tool_progress_hint_gateway",
"tool_progress_hint_cli",
"openclaw_residue_hint_cli",
"detect_openclaw_residue",
"is_seen",
"mark_seen",
]
-28
View File
@@ -422,29 +422,6 @@ PLATFORM_HINTS = {
"your response. Images are sent as native photos, and other files arrive as downloadable "
"documents."
),
"yuanbao": (
"You are on Yuanbao (腾讯元宝), a Chinese AI assistant platform. "
"Markdown formatting is supported (code blocks, tables, bold/italic). "
"You CAN send media files natively — to deliver a file to the user, include "
"MEDIA:/absolute/path/to/file in your response. The file will be sent as a native "
"Yuanbao attachment: images (.jpg, .png, .webp, .gif) are sent as photos, "
"and other files (.pdf, .docx, .txt, .zip, etc.) arrive as downloadable documents "
"(max 50 MB). You can also include image URLs in markdown format ![alt](url) and "
"they will be downloaded and sent as native photos. "
"Do NOT tell the user you lack file-sending capability — use MEDIA: syntax "
"whenever a file delivery is appropriate.\n\n"
"Stickers (贴纸 / 表情包 / TIM face): Yuanbao has a built-in sticker catalogue. "
"When the user sends a sticker (you see '[emoji: 名称]' in their message) or asks "
"you to send/reply-with a 贴纸/表情/表情包, you MUST use the sticker tools:\n"
" 1. Call yb_search_sticker with a Chinese keyword (e.g. '666', '比心', '吃瓜', "
" '捂脸', '合十') to discover matching sticker_ids.\n"
" 2. Call yb_send_sticker with the chosen sticker_id or name — this sends a real "
" TIMFaceElem that renders as a native sticker in the chat.\n"
"DO NOT draw sticker-like PNGs with execute_code/Pillow/matplotlib and then send "
"them via MEDIA: or send_image_file. That produces a fake low-quality 'sticker' "
"image and is the WRONG path. Bare Unicode emoji in text is also not a substitute "
"— when a sticker is the right response, use yb_send_sticker."
),
}
# ---------------------------------------------------------------------------
@@ -848,11 +825,6 @@ def build_skills_system_prompt(
"Skills also encode the user's preferred approach, conventions, and quality standards "
"for tasks like code review, planning, and testing — load them even for tasks you "
"already know how to do, because the skill defines how it should be done here.\n"
"Whenever the user asks you to configure, set up, install, enable, disable, modify, "
"or troubleshoot Hermes Agent itself — its CLI, config, models, providers, tools, "
"skills, voice, gateway, plugins, or any feature — load the `hermes-agent` skill "
"first. It has the actual commands (e.g. `hermes config set …`, `hermes tools`, "
"`hermes setup`) so you don't have to guess or invent workarounds.\n"
"If a skill has issues, fix it with skill_manage(action='patch').\n"
"After difficult/iterative tasks, offer to save as a skill. "
"If a skill you loaded was missing steps, had wrong commands, or needed "
+1 -5
View File
@@ -754,11 +754,7 @@ def _resolve_effective_accept(
if env in ("1", "true", "yes", "on"):
return True
cfg_val = cfg.get("hooks_auto_accept", False)
if isinstance(cfg_val, bool):
return cfg_val
if isinstance(cfg_val, str):
return cfg_val.strip().lower() in ("1", "true", "yes", "on")
return False
return bool(cfg_val)
# ---------------------------------------------------------------------------
+109 -10
View File
@@ -7,15 +7,11 @@ can invoke skills via /skill-name commands.
import json
import logging
import re
import subprocess
from pathlib import Path
from typing import Any, Dict, Optional
from hermes_constants import display_hermes_home
from agent.skill_preprocessing import (
expand_inline_shell as _expand_inline_shell,
load_skills_config as _load_skills_config,
substitute_template_vars as _substitute_template_vars,
)
logger = logging.getLogger(__name__)
@@ -24,6 +20,111 @@ _skill_commands: Dict[str, Dict[str, Any]] = {}
_SKILL_INVALID_CHARS = re.compile(r"[^a-z0-9-]")
_SKILL_MULTI_HYPHEN = re.compile(r"-{2,}")
# Matches ${HERMES_SKILL_DIR} / ${HERMES_SESSION_ID} tokens in SKILL.md.
# Tokens that don't resolve (e.g. ${HERMES_SESSION_ID} with no session) are
# left as-is so the user can debug them.
_SKILL_TEMPLATE_RE = re.compile(r"\$\{(HERMES_SKILL_DIR|HERMES_SESSION_ID)\}")
# Matches inline shell snippets like: !`date +%Y-%m-%d`
# Non-greedy, single-line only — no newlines inside the backticks.
_INLINE_SHELL_RE = re.compile(r"!`([^`\n]+)`")
# Cap inline-shell output so a runaway command can't blow out the context.
_INLINE_SHELL_MAX_OUTPUT = 4000
def _load_skills_config() -> dict:
"""Load the ``skills`` section of config.yaml (best-effort)."""
try:
from hermes_cli.config import load_config
cfg = load_config() or {}
skills_cfg = cfg.get("skills")
if isinstance(skills_cfg, dict):
return skills_cfg
except Exception:
logger.debug("Could not read skills config", exc_info=True)
return {}
def _substitute_template_vars(
content: str,
skill_dir: Path | None,
session_id: str | None,
) -> str:
"""Replace ${HERMES_SKILL_DIR} / ${HERMES_SESSION_ID} in skill content.
Only substitutes tokens for which a concrete value is available
unresolved tokens are left in place so the author can spot them.
"""
if not content:
return content
skill_dir_str = str(skill_dir) if skill_dir else None
def _replace(match: re.Match) -> str:
token = match.group(1)
if token == "HERMES_SKILL_DIR" and skill_dir_str:
return skill_dir_str
if token == "HERMES_SESSION_ID" and session_id:
return str(session_id)
return match.group(0)
return _SKILL_TEMPLATE_RE.sub(_replace, content)
def _run_inline_shell(command: str, cwd: Path | None, timeout: int) -> str:
"""Execute a single inline-shell snippet and return its stdout (trimmed).
Failures return a short ``[inline-shell error: ...]`` marker instead of
raising, so one bad snippet can't wreck the whole skill message.
"""
try:
completed = subprocess.run(
["bash", "-c", command],
cwd=str(cwd) if cwd else None,
capture_output=True,
text=True,
timeout=max(1, int(timeout)),
check=False,
)
except subprocess.TimeoutExpired:
return f"[inline-shell timeout after {timeout}s: {command}]"
except FileNotFoundError:
return f"[inline-shell error: bash not found]"
except Exception as exc:
return f"[inline-shell error: {exc}]"
output = (completed.stdout or "").rstrip("\n")
if not output and completed.stderr:
output = completed.stderr.rstrip("\n")
if len(output) > _INLINE_SHELL_MAX_OUTPUT:
output = output[:_INLINE_SHELL_MAX_OUTPUT] + "…[truncated]"
return output
def _expand_inline_shell(
content: str,
skill_dir: Path | None,
timeout: int,
) -> str:
"""Replace every !`cmd` snippet in ``content`` with its stdout.
Runs each snippet with the skill directory as CWD so relative paths in
the snippet work the way the author expects.
"""
if "!`" not in content:
return content
def _replace(match: re.Match) -> str:
cmd = match.group(1).strip()
if not cmd:
return ""
return _run_inline_shell(cmd, skill_dir, timeout)
return _INLINE_SHELL_RE.sub(_replace, content)
def _load_skill_payload(skill_identifier: str, task_id: str | None = None) -> tuple[dict[str, Any], Path | None, str] | None:
"""Load a skill by name/path and return (loaded_payload, skill_dir, display_name)."""
raw_identifier = (skill_identifier or "").strip()
@@ -42,9 +143,7 @@ def _load_skill_payload(skill_identifier: str, task_id: str | None = None) -> tu
else:
normalized = raw_identifier.lstrip("/")
loaded_skill = json.loads(
skill_view(normalized, task_id=task_id, preprocess=False)
)
loaded_skill = json.loads(skill_view(normalized, task_id=task_id))
except Exception:
return None
@@ -329,7 +428,7 @@ def build_skill_invocation_message(
loaded_skill, skill_dir, skill_name = loaded
activation_note = (
f'[IMPORTANT: The user has invoked the "{skill_name}" skill, indicating they want '
f'[SYSTEM: The user has invoked the "{skill_name}" skill, indicating they want '
"you to follow its instructions. The full skill content is loaded below.]"
)
return _build_skill_message(
@@ -368,7 +467,7 @@ def build_preloaded_skills_prompt(
loaded_skill, skill_dir, skill_name = loaded
activation_note = (
f'[IMPORTANT: The user launched this CLI session with the "{skill_name}" skill '
f'[SYSTEM: The user launched this CLI session with the "{skill_name}" skill '
"preloaded. Treat its instructions as active guidance for the duration of this "
"session unless the user overrides them.]"
)
-131
View File
@@ -1,131 +0,0 @@
"""Shared SKILL.md preprocessing helpers."""
import logging
import re
import subprocess
from pathlib import Path
logger = logging.getLogger(__name__)
# Matches ${HERMES_SKILL_DIR} / ${HERMES_SESSION_ID} tokens in SKILL.md.
# Tokens that don't resolve (e.g. ${HERMES_SESSION_ID} with no session) are
# left as-is so the user can debug them.
_SKILL_TEMPLATE_RE = re.compile(r"\$\{(HERMES_SKILL_DIR|HERMES_SESSION_ID)\}")
# Matches inline shell snippets like: !`date +%Y-%m-%d`
# Non-greedy, single-line only -- no newlines inside the backticks.
_INLINE_SHELL_RE = re.compile(r"!`([^`\n]+)`")
# Cap inline-shell output so a runaway command can't blow out the context.
_INLINE_SHELL_MAX_OUTPUT = 4000
def load_skills_config() -> dict:
"""Load the ``skills`` section of config.yaml (best-effort)."""
try:
from hermes_cli.config import load_config
cfg = load_config() or {}
skills_cfg = cfg.get("skills")
if isinstance(skills_cfg, dict):
return skills_cfg
except Exception:
logger.debug("Could not read skills config", exc_info=True)
return {}
def substitute_template_vars(
content: str,
skill_dir: Path | None,
session_id: str | None,
) -> str:
"""Replace ${HERMES_SKILL_DIR} / ${HERMES_SESSION_ID} in skill content.
Only substitutes tokens for which a concrete value is available --
unresolved tokens are left in place so the author can spot them.
"""
if not content:
return content
skill_dir_str = str(skill_dir) if skill_dir else None
def _replace(match: re.Match) -> str:
token = match.group(1)
if token == "HERMES_SKILL_DIR" and skill_dir_str:
return skill_dir_str
if token == "HERMES_SESSION_ID" and session_id:
return str(session_id)
return match.group(0)
return _SKILL_TEMPLATE_RE.sub(_replace, content)
def run_inline_shell(command: str, cwd: Path | None, timeout: int) -> str:
"""Execute a single inline-shell snippet and return its stdout (trimmed).
Failures return a short ``[inline-shell error: ...]`` marker instead of
raising, so one bad snippet can't wreck the whole skill message.
"""
try:
completed = subprocess.run(
["bash", "-c", command],
cwd=str(cwd) if cwd else None,
capture_output=True,
text=True,
timeout=max(1, int(timeout)),
check=False,
)
except subprocess.TimeoutExpired:
return f"[inline-shell timeout after {timeout}s: {command}]"
except FileNotFoundError:
return "[inline-shell error: bash not found]"
except Exception as exc:
return f"[inline-shell error: {exc}]"
output = (completed.stdout or "").rstrip("\n")
if not output and completed.stderr:
output = completed.stderr.rstrip("\n")
if len(output) > _INLINE_SHELL_MAX_OUTPUT:
output = output[:_INLINE_SHELL_MAX_OUTPUT] + "...[truncated]"
return output
def expand_inline_shell(
content: str,
skill_dir: Path | None,
timeout: int,
) -> str:
"""Replace every !`cmd` snippet in ``content`` with its stdout.
Runs each snippet with the skill directory as CWD so relative paths in
the snippet work the way the author expects.
"""
if "!`" not in content:
return content
def _replace(match: re.Match) -> str:
cmd = match.group(1).strip()
if not cmd:
return ""
return run_inline_shell(cmd, skill_dir, timeout)
return _INLINE_SHELL_RE.sub(_replace, content)
def preprocess_skill_content(
content: str,
skill_dir: Path | None,
session_id: str | None = None,
skills_cfg: dict | None = None,
) -> str:
"""Apply configured SKILL.md template and inline-shell preprocessing."""
if not content:
return content
cfg = skills_cfg if isinstance(skills_cfg, dict) else load_skills_config()
if cfg.get("template_vars", True):
content = substitute_template_vars(content, skill_dir, session_id)
if cfg.get("inline_shell", False):
timeout = int(cfg.get("inline_shell_timeout", 10) or 10)
content = expand_inline_shell(content, skill_dir, timeout)
return content
+2 -7
View File
@@ -23,14 +23,9 @@ def get_transport(api_mode: str):
This allows gradual migration call sites can check for None
and fall back to the legacy code path.
"""
cls = _REGISTRY.get(api_mode)
if cls is None:
# The registry can be partially populated when a specific transport
# module was imported directly (for example chat_completions before
# codex). Discover on misses, not only when the registry is empty, so
# test/order-dependent imports do not make valid api_modes unavailable.
if not _REGISTRY:
_discover_transports()
cls = _REGISTRY.get(api_mode)
cls = _REGISTRY.get(api_mode)
if cls is None:
return None
return cls()
+4 -5
View File
@@ -31,15 +31,15 @@ class ChatCompletionsTransport(ProviderTransport):
def convert_messages(self, messages: List[Dict[str, Any]], **kwargs) -> List[Dict[str, Any]]:
"""Messages are already in OpenAI format — sanitize Codex leaks only.
Strips Codex Responses API fields (``codex_reasoning_items`` /
``codex_message_items`` on the message, ``call_id``/``response_item_id``
on tool_calls) that strict chat-completions providers reject with 400/422.
Strips Codex Responses API fields (``codex_reasoning_items`` on the
message, ``call_id``/``response_item_id`` on tool_calls) that strict
chat-completions providers reject with 400/422.
"""
needs_sanitize = False
for msg in messages:
if not isinstance(msg, dict):
continue
if "codex_reasoning_items" in msg or "codex_message_items" in msg:
if "codex_reasoning_items" in msg:
needs_sanitize = True
break
tool_calls = msg.get("tool_calls")
@@ -59,7 +59,6 @@ class ChatCompletionsTransport(ProviderTransport):
if not isinstance(msg, dict):
continue
msg.pop("codex_reasoning_items", None)
msg.pop("codex_message_items", None)
tool_calls = msg.get("tool_calls")
if isinstance(tool_calls, list):
for tc in tool_calls:
-20
View File
@@ -120,24 +120,6 @@ class ResponsesApiTransport(ProviderTransport):
if request_overrides:
kwargs.update(request_overrides)
if is_codex_backend:
prompt_cache_key = kwargs.get("prompt_cache_key")
cache_scope_id = str(prompt_cache_key or session_id or "").strip()
if cache_scope_id:
existing_extra_headers = kwargs.get("extra_headers")
merged_extra_headers: Dict[str, str] = {}
if isinstance(existing_extra_headers, dict):
merged_extra_headers.update(
{
str(key): str(value)
for key, value in existing_extra_headers.items()
if key and value is not None
}
)
merged_extra_headers["session_id"] = cache_scope_id
merged_extra_headers["x-client-request-id"] = cache_scope_id
kwargs["extra_headers"] = merged_extra_headers
max_tokens = params.get("max_tokens")
if max_tokens is not None and not is_codex_backend:
kwargs["max_output_tokens"] = max_tokens
@@ -178,8 +160,6 @@ class ResponsesApiTransport(ProviderTransport):
provider_data = {}
if msg and hasattr(msg, "codex_reasoning_items") and msg.codex_reasoning_items:
provider_data["codex_reasoning_items"] = msg.codex_reasoning_items
if msg and hasattr(msg, "codex_message_items") and msg.codex_message_items:
provider_data["codex_message_items"] = msg.codex_message_items
if msg and hasattr(msg, "reasoning_details") and msg.reasoning_details:
provider_data["reasoning_details"] = msg.reasoning_details
+1 -6
View File
@@ -97,7 +97,7 @@ class NormalizedResponse:
Response-level ``provider_data`` examples:
* Anthropic: ``{"reasoning_details": [...]}``
* Codex: ``{"codex_reasoning_items": [...], "codex_message_items": [...]}``
* Codex: ``{"codex_reasoning_items": [...]}``
* Others: ``None``
"""
@@ -126,11 +126,6 @@ class NormalizedResponse:
pd = self.provider_data or {}
return pd.get("codex_reasoning_items")
@property
def codex_message_items(self):
pd = self.provider_data or {}
return pd.get("codex_message_items")
# ---------------------------------------------------------------------------
# Factory helpers
+6 -2
View File
@@ -951,9 +951,13 @@ class BatchRunner:
root_logger.setLevel(original_level)
# Aggregate all batch statistics and update checkpoint
all_completed_prompts = list(completed_prompts_set)
total_reasoning_stats = {"total_assistant_turns": 0, "turns_with_reasoning": 0, "turns_without_reasoning": 0}
for batch_result in results:
# Add newly completed prompts
all_completed_prompts.extend(batch_result.get("completed_prompts", []))
# Aggregate tool stats
for tool_name, stats in batch_result.get("tool_stats", {}).items():
if tool_name not in total_tool_stats:
@@ -973,7 +977,7 @@ class BatchRunner:
# Save final checkpoint (best-effort; incremental writes already happened)
try:
checkpoint_data["completed_prompts"] = sorted(completed_prompts_set)
checkpoint_data["completed_prompts"] = all_completed_prompts
self._save_checkpoint(checkpoint_data, lock=checkpoint_lock)
except Exception as ckpt_err:
print(f"⚠️ Warning: Failed to save final checkpoint: {ckpt_err}")
+10 -37
View File
@@ -606,7 +606,6 @@ platform_toolsets:
signal: [hermes-signal]
homeassistant: [hermes-homeassistant]
qqbot: [hermes-qqbot]
yuanbao: [hermes-yuanbao]
# =============================================================================
# Gateway Platform Settings
@@ -791,16 +790,9 @@ code_execution:
# Supports single tasks and batch mode (default 3 parallel, configurable).
delegation:
max_iterations: 50 # Max tool-calling turns per child (default: 50)
# max_concurrent_children: 3 # Max parallel child agents per batch (default: 3, floor: 1, no ceiling).
# WARNING: values above 10 multiply API cost linearly.
# max_spawn_depth: 1 # Delegation tree depth cap (range: 1-3, default: 1 = flat).
# Raise to 2 to allow workers to spawn their own subagents.
# Requires role="orchestrator" on intermediate agents.
# max_concurrent_children: 3 # Max parallel child agents (default: 3)
# max_spawn_depth: 1 # Tree depth cap (1-3, default: 1 = flat). Raise to 2 or 3 to allow orchestrator children to spawn their own workers.
# orchestrator_enabled: true # Kill switch for role="orchestrator" children (default: true).
# subagent_auto_approve: false # When a subagent hits a dangerous-command approval prompt, auto-deny (default: false)
# or auto-approve "once" (true) instead of blocking on stdin.
# The parent TUI owns stdin, so blocking would deadlock; non-interactive resolution is required.
# Both choices emit a logger.warning audit line. Flip to true only for cron/batch pipelines.
# inherit_mcp_toolsets: true # When explicit child toolsets are narrowed, also keep the parent's MCP toolsets (default: true). Set false for strict intersection.
# model: "google/gemini-3-flash-preview" # Override model for subagents (empty = inherit parent)
# provider: "openrouter" # Override provider for subagents (empty = inherit parent)
@@ -825,9 +817,7 @@ delegation:
# Display
# =============================================================================
display:
# Use compact banner mode (hides the ASCII-art banner, shows a single line).
# true: Compact single-line banner
# false: Full ASCII banner with tool/skill summary (default)
# Use compact banner mode
compact: false
# Tool progress display level (CLI and gateway)
@@ -841,19 +831,12 @@ display:
# Gateway-only natural mid-turn assistant updates.
# When true, completed assistant status messages are sent as separate chat
# messages. This is independent of tool_progress and gateway streaming.
# true: Send mid-turn assistant updates as separate messages (default)
# false: Only send the final response
interim_assistant_messages: true
# What Enter does when Hermes is already busy (CLI and gateway platforms).
# What Enter does when Hermes is already busy in the CLI.
# interrupt: Interrupt the current run and redirect Hermes (default)
# queue: Queue your message for the next turn
# steer: Inject your message mid-run via /steer, arriving at the agent
# after the next tool call — no interrupt, no role violation.
# Falls back to 'queue' if the agent isn't running yet or if
# images are attached (steer only carries text).
# Ctrl+C (or /stop in gateway) always interrupts regardless of this setting.
# Toggle at runtime with /busy <interrupt|queue|steer>.
# Ctrl+C always interrupts regardless of this setting.
busy_input_mode: interrupt
# Background process notifications (gateway/messaging only).
@@ -869,22 +852,17 @@ display:
# Play terminal bell when agent finishes a response.
# Useful for long-running tasks — your terminal will ding when the agent is done.
# Works over SSH. Most terminals can be configured to flash the taskbar or play a sound.
# true: Ring the terminal bell on each response
# false: Silent (default)
bell_on_complete: false
# Show model reasoning/thinking before each response.
# When enabled, a dim box shows the model's thought process above the response.
# Toggle at runtime with /reasoning show or /reasoning hide.
# true: Show the reasoning box
# false: Hide reasoning (default)
show_reasoning: false
# Stream tokens to the terminal as they arrive instead of waiting for the
# full response. The response box opens on first token and text appears
# line-by-line. Tool calls are still captured silently.
# true: Stream tokens as they arrive (default)
# false: Wait for the full response before rendering
# Stream tokens to the terminal in real-time. Disable to wait for full responses.
streaming: true
# ───────────────────────────────────────────────────────────────────────────
@@ -894,15 +872,10 @@ display:
# response box label, and branding text. Change at runtime with /skin <name>.
#
# Built-in skins:
# default — Classic Hermes gold/kawaii
# ares — Crimson/bronze war-god theme with spinner wings
# mono — Clean grayscale monochrome
# slate — Cool blue developer-focused
# daylight — Bright light-mode theme
# warm-lightmode — Warm paper-tone light-mode theme
# poseidon — Sea-green/teal Olympian theme
# sisyphus — Earthy stone-and-moss theme
# charizard — Fiery orange dragon theme
# default — Classic Hermes gold/kawaii
# ares — Crimson/bronze war-god theme with spinner wings
# mono — Clean grayscale monochrome
# slate — Cool blue developer-focused
#
# Custom skins: drop a YAML file in ~/.hermes/skins/<name>.yaml
# Schema (all fields optional, missing values inherit from default):
+242 -352
View File
@@ -22,7 +22,6 @@ import re
import concurrent.futures
import base64
import atexit
import errno
import tempfile
import time
import uuid
@@ -417,11 +416,6 @@ def load_cli_config() -> Dict[str, Any]:
"base_url": "", # Direct OpenAI-compatible endpoint for subagents
"api_key": "", # API key for delegation.base_url (falls back to OPENAI_API_KEY)
},
"onboarding": {
# First-touch hint flags (see agent/onboarding.py). Each hint is
# shown once per install then latched here.
"seen": {},
},
}
# Track whether the config file explicitly set terminal config.
@@ -974,7 +968,6 @@ def _run_state_db_auto_maintenance(session_db) -> None:
return
try:
from hermes_cli.config import load_config as _load_full_config
from hermes_constants import get_hermes_home as _get_hermes_home
cfg = (_load_full_config().get("sessions") or {})
if not cfg.get("auto_prune", False):
return
@@ -982,35 +975,11 @@ def _run_state_db_auto_maintenance(session_db) -> None:
retention_days=int(cfg.get("retention_days", 90)),
min_interval_hours=int(cfg.get("min_interval_hours", 24)),
vacuum=bool(cfg.get("vacuum_after_prune", True)),
sessions_dir=_get_hermes_home() / "sessions",
)
except Exception as exc:
logger.debug("state.db auto-maintenance skipped: %s", exc)
def _run_checkpoint_auto_maintenance() -> None:
"""Call ``checkpoint_manager.maybe_auto_prune_checkpoints`` using current config.
Reads the ``checkpoints:`` section from config.yaml via
:func:`hermes_cli.config.load_config`. Honours ``auto_prune`` /
``retention_days`` / ``delete_orphans`` / ``min_interval_hours``.
Never raises maintenance must never block interactive startup.
"""
try:
from hermes_cli.config import load_config as _load_full_config
cfg = (_load_full_config().get("checkpoints") or {})
if not cfg.get("auto_prune", False):
return
from tools.checkpoint_manager import maybe_auto_prune_checkpoints
maybe_auto_prune_checkpoints(
retention_days=int(cfg.get("retention_days", 7)),
min_interval_hours=int(cfg.get("min_interval_hours", 24)),
delete_orphans=bool(cfg.get("delete_orphans", True)),
)
except Exception as exc:
logger.debug("checkpoint auto-maintenance skipped: %s", exc)
def _prune_stale_worktrees(repo_root: str, max_age_hours: int = 24) -> None:
"""Remove stale worktrees and orphaned branches on startup.
@@ -1403,7 +1372,7 @@ def _resolve_attachment_path(raw_path: str) -> Path | None:
def _format_process_notification(evt: dict) -> "str | None":
"""Format a process notification event into a [IMPORTANT: ...] message.
"""Format a process notification event into a [SYSTEM: ...] message.
Handles both completion events (notify_on_complete) and watch pattern
match events from the unified completion_queue.
@@ -1413,14 +1382,14 @@ def _format_process_notification(evt: dict) -> "str | None":
_cmd = evt.get("command", "unknown")
if evt_type == "watch_disabled":
return f"[IMPORTANT: {evt.get('message', '')}]"
return f"[SYSTEM: {evt.get('message', '')}]"
if evt_type == "watch_match":
_pat = evt.get("pattern", "?")
_out = evt.get("output", "")
_sup = evt.get("suppressed", 0)
text = (
f"[IMPORTANT: Background process {_sid} matched "
f"[SYSTEM: Background process {_sid} matched "
f"watch pattern \"{_pat}\".\n"
f"Command: {_cmd}\n"
f"Matched output:\n{_out}"
@@ -1434,7 +1403,7 @@ def _format_process_notification(evt: dict) -> "str | None":
_exit = evt.get("exit_code", "?")
_out = evt.get("output", "")
return (
f"[IMPORTANT: Background process {_sid} completed "
f"[SYSTEM: Background process {_sid} completed "
f"(exit code {_exit}).\n"
f"Command: {_cmd}\n"
f"Output:\n{_out}]"
@@ -1873,16 +1842,9 @@ class HermesCLI:
self.bell_on_complete = CLI_CONFIG["display"].get("bell_on_complete", False)
# show_reasoning: display model thinking/reasoning before the response
self.show_reasoning = CLI_CONFIG["display"].get("show_reasoning", False)
# busy_input_mode: "interrupt" (Enter interrupts current run),
# "queue" (Enter queues for next turn), or "steer" (Enter injects
# mid-run via /steer, arriving after the next tool call).
_bim = str(CLI_CONFIG["display"].get("busy_input_mode", "interrupt")).strip().lower()
if _bim == "queue":
self.busy_input_mode = "queue"
elif _bim == "steer":
self.busy_input_mode = "steer"
else:
self.busy_input_mode = "interrupt"
# busy_input_mode: "interrupt" (Enter interrupts current run) or "queue" (Enter queues for next turn)
_bim = CLI_CONFIG["display"].get("busy_input_mode", "interrupt")
self.busy_input_mode = "queue" if str(_bim).strip().lower() == "queue" else "interrupt"
self.verbose = verbose if verbose is not None else (self.tool_progress_mode == "verbose")
@@ -2077,11 +2039,6 @@ class HermesCLI:
# Never blocks startup on failure.
_run_state_db_auto_maintenance(self._session_db)
# Opportunistic shadow-repo cleanup — deletes orphan/stale
# checkpoint repos under ~/.hermes/checkpoints/. Opt-in via
# checkpoints.auto_prune, idempotent via .last_prune marker.
_run_checkpoint_auto_maintenance()
# Deferred title: stored in memory until the session is created in the DB
self._pending_title: Optional[str] = None
@@ -3219,14 +3176,7 @@ class HermesCLI:
# the configured model (e.g. "qwen3.6-plus"), causing 400 errors.
runtime_model = runtime.get("model")
if runtime_model and isinstance(runtime_model, str):
# Only use runtime model if: model is unset, or model equals provider name
should_use_runtime_model = (
not self.model or # No model configured yet
self.model == self.provider or # Model is the provider slug
self.model == runtime.get("name") # Model matches provider display name
)
if should_use_runtime_model:
self.model = runtime_model
self.model = runtime_model
# If model is still empty (e.g. user ran `hermes auth add openai-codex`
# without `hermes model`), fall back to the provider's first catalog
@@ -4361,7 +4311,7 @@ class HermesCLI:
_cprint(f"\n {_DIM}Tip: Just type your message to chat with Hermes!{_RST}")
_cprint(f" {_DIM}Multi-line: Alt+Enter for a new line{_RST}")
_cprint(f" {_DIM}Draft editor: Ctrl+G (Alt+G in VSCode/Cursor){_RST}")
_cprint(f" {_DIM}Draft editor: Ctrl+G{_RST}")
if _is_termux_environment():
_cprint(f" {_DIM}Attach image: /image {_termux_example_image_path()} or start your prompt with a local image path{_RST}\n")
else:
@@ -4711,6 +4661,10 @@ class HermesCLI:
def new_session(self, silent=False):
"""Start a fresh session with a new session ID and cleared agent state."""
if self.agent and self.conversation_history:
try:
self.agent.flush_memories(self.conversation_history)
except (Exception, KeyboardInterrupt):
pass
# Trigger memory extraction on the old session before session_id rotates.
self.agent.commit_memory_session(self.conversation_history)
self._notify_session_boundary("on_session_finalize")
@@ -4952,12 +4906,6 @@ class HermesCLI:
if self.agent:
self.agent.session_id = new_session_id
self.agent.session_start = now
# Redirect the JSON session log to the new branch session file so
# messages written after branching land in the correct file.
if hasattr(self.agent, "session_log_file") and hasattr(self.agent, "logs_dir"):
self.agent.session_log_file = (
self.agent.logs_dir / f"session_{new_session_id}.json"
)
self.agent.reset_session_state()
if hasattr(self.agent, "_last_flushed_db_idx"):
self.agent._last_flushed_db_idx = len(self.conversation_history)
@@ -4979,37 +4927,22 @@ class HermesCLI:
_cprint(f" Branch session: {new_session_id}")
def save_conversation(self):
"""Save the current conversation to a JSON snapshot under ~/.hermes/sessions/saved/.
The snapshot is a convenience export for sharing or off-line inspection;
every message is already persisted incrementally to the SQLite session
DB, so the live session remains resumable via ``hermes --resume <id>``
regardless of whether the user ever runs ``/save``.
"""
"""Save the current conversation to a file."""
if not self.conversation_history:
print("(;_;) No conversation to save.")
return
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
saved_dir = get_hermes_home() / "sessions" / "saved"
filename = f"hermes_conversation_{timestamp}.json"
try:
saved_dir.mkdir(parents=True, exist_ok=True)
except Exception as e:
print(f"(x_x) Failed to create save directory {saved_dir}: {e}")
return
path = saved_dir / f"hermes_conversation_{timestamp}.json"
try:
with open(path, "w", encoding="utf-8") as f:
with open(filename, "w", encoding="utf-8") as f:
json.dump({
"model": self.model,
"session_id": self.session_id,
"session_start": self.session_start.isoformat(),
"messages": self.conversation_history,
}, f, indent=2, ensure_ascii=False)
print(f"(^_^)v Conversation snapshot saved to: {path}")
if self.session_id:
print(f" Resume the live session with: hermes --resume {self.session_id}")
print(f"(^_^)v Conversation saved to: {filename}")
except Exception as e:
print(f"(x_x) Failed to save: {e}")
@@ -5216,29 +5149,27 @@ class HermesCLI:
_cprint(f" ✓ Model switched: {result.new_model}")
_cprint(f" Provider: {provider_label}")
# Context: always resolve via the provider-aware chain so Codex OAuth,
# Copilot, and Nous-enforced caps win over the raw models.dev entry
# (e.g. gpt-5.5 is 1.05M on openai but 272K on Codex OAuth).
mi = result.model_info
try:
from hermes_cli.model_switch import resolve_display_context_length
ctx = resolve_display_context_length(
result.new_model,
result.target_provider,
base_url=result.base_url or self.base_url or "",
api_key=result.api_key or self.api_key or "",
model_info=mi,
)
if ctx:
_cprint(f" Context: {ctx:,} tokens")
except Exception:
pass
if mi:
if mi.context_window:
_cprint(f" Context: {mi.context_window:,} tokens")
if mi.max_output:
_cprint(f" Max output: {mi.max_output:,} tokens")
if mi.has_cost_data():
_cprint(f" Cost: {mi.format_cost()}")
_cprint(f" Capabilities: {mi.format_capabilities()}")
else:
try:
from agent.model_metadata import get_model_context_length
ctx = get_model_context_length(
result.new_model,
base_url=result.base_url or self.base_url,
api_key=result.api_key or self.api_key,
provider=result.target_provider,
)
_cprint(f" Context: {ctx:,} tokens")
except Exception:
pass
cache_enabled = (
(base_url_host_matches(result.base_url or "", "openrouter.ai") and "claude" in result.new_model.lower())
@@ -5339,22 +5270,24 @@ class HermesCLI:
# Parse --provider and --global flags
model_input, explicit_provider, persist_global = parse_model_flags(raw_args)
# Load providers for switch_model (picker path needs them below)
user_provs = None
custom_provs = None
try:
from hermes_cli.config import get_compatible_custom_providers, load_config
cfg = load_config()
user_provs = cfg.get("providers")
custom_provs = get_compatible_custom_providers(cfg)
except Exception:
pass
# No args at all: open prompt_toolkit-native picker modal
if not model_input and not explicit_provider:
model_display = self.model or "unknown"
provider_display = get_label(self.provider) if self.provider else "unknown"
user_provs = None
custom_provs = None
try:
from hermes_cli.config import get_compatible_custom_providers, load_config
cfg = load_config()
user_provs = cfg.get("providers")
custom_provs = get_compatible_custom_providers(cfg)
except Exception:
pass
try:
providers = list_authenticated_providers(
current_provider=self.provider or "",
@@ -5441,26 +5374,29 @@ class HermesCLI:
_cprint(f" ✓ Model switched: {result.new_model}")
_cprint(f" Provider: {provider_label}")
# Context: always resolve via the provider-aware chain so Codex OAuth,
# Copilot, and Nous-enforced caps win over the raw models.dev entry
# (e.g. gpt-5.5 is 1.05M on openai but 272K on Codex OAuth).
# Rich metadata from models.dev
mi = result.model_info
from hermes_cli.model_switch import resolve_display_context_length
ctx = resolve_display_context_length(
result.new_model,
result.target_provider,
base_url=result.base_url or self.base_url or "",
api_key=result.api_key or self.api_key or "",
model_info=mi,
)
if ctx:
_cprint(f" Context: {ctx:,} tokens")
if mi:
if mi.context_window:
_cprint(f" Context: {mi.context_window:,} tokens")
if mi.max_output:
_cprint(f" Max output: {mi.max_output:,} tokens")
if mi.has_cost_data():
_cprint(f" Cost: {mi.format_cost()}")
_cprint(f" Capabilities: {mi.format_capabilities()}")
else:
# Fallback to old context length lookup
try:
from agent.model_metadata import get_model_context_length
ctx = get_model_context_length(
result.new_model,
base_url=result.base_url or self.base_url,
api_key=result.api_key or self.api_key,
provider=result.target_provider,
)
_cprint(f" Context: {ctx:,} tokens")
except Exception:
pass
# Cache notice
cache_enabled = (
@@ -6187,6 +6123,8 @@ class HermesCLI:
self._handle_agents_command()
elif canonical == "background":
self._handle_background_command(cmd_original)
elif canonical == "btw":
self._handle_btw_command(cmd_original)
elif canonical == "queue":
# Extract prompt after "/queue " or "/q "
parts = cmd_original.split(None, 1)
@@ -6227,8 +6165,6 @@ class HermesCLI:
self._handle_skin_command(cmd_original)
elif canonical == "voice":
self._handle_voice_command(cmd_original)
elif canonical == "busy":
self._handle_busy_command(cmd_original)
else:
# Check for user-defined quick commands (bypass agent loop, no LLM call)
base_cmd = cmd_lower.split()[0]
@@ -6365,12 +6301,6 @@ class HermesCLI:
turn_route = self._resolve_turn_agent_config(prompt)
def run_background():
set_sudo_password_callback(self._sudo_password_callback)
set_approval_callback(self._approval_callback)
try:
set_secret_capture_callback(self._secret_capture_callback)
except Exception:
pass
try:
bg_agent = AIAgent(
model=turn_route["model"],
@@ -6468,12 +6398,6 @@ class HermesCLI:
print()
_cprint(f" ❌ Background task #{task_num} failed: {e}")
finally:
try:
set_sudo_password_callback(None)
set_approval_callback(None)
set_secret_capture_callback(None)
except Exception:
pass
self._background_tasks.pop(task_id, None)
# Clear spinner only if no foreground agent owns it
if not self._agent_running:
@@ -6485,6 +6409,122 @@ class HermesCLI:
self._background_tasks[task_id] = thread
thread.start()
def _handle_btw_command(self, cmd: str):
"""Handle /btw <question> — ephemeral side question using session context.
Snapshots the current conversation history, spawns a no-tools agent in
a background thread, and prints the answer without persisting anything
to the main session.
"""
parts = cmd.strip().split(maxsplit=1)
if len(parts) < 2 or not parts[1].strip():
_cprint(" Usage: /btw <question>")
_cprint(" Example: /btw what module owns session title sanitization?")
_cprint(" Answers using session context. No tools, not persisted.")
return
question = parts[1].strip()
task_id = f"btw_{datetime.now().strftime('%H%M%S')}_{uuid.uuid4().hex[:6]}"
if not self._ensure_runtime_credentials():
_cprint(" (>_<) Cannot start /btw: no valid credentials.")
return
turn_route = self._resolve_turn_agent_config(question)
history_snapshot = list(self.conversation_history)
preview = question[:60] + ("..." if len(question) > 60 else "")
_cprint(f' 💬 /btw: "{preview}"')
def run_btw():
try:
btw_agent = AIAgent(
model=turn_route["model"],
api_key=turn_route["runtime"].get("api_key"),
base_url=turn_route["runtime"].get("base_url"),
provider=turn_route["runtime"].get("provider"),
api_mode=turn_route["runtime"].get("api_mode"),
acp_command=turn_route["runtime"].get("command"),
acp_args=turn_route["runtime"].get("args"),
max_iterations=8,
enabled_toolsets=[],
quiet_mode=True,
verbose_logging=False,
session_id=task_id,
platform="cli",
reasoning_config=self.reasoning_config,
service_tier=self.service_tier,
request_overrides=turn_route.get("request_overrides"),
providers_allowed=self._providers_only,
providers_ignored=self._providers_ignore,
providers_order=self._providers_order,
provider_sort=self._provider_sort,
provider_require_parameters=self._provider_require_params,
provider_data_collection=self._provider_data_collection,
fallback_model=self._fallback_model,
session_db=None,
skip_memory=True,
skip_context_files=True,
persist_session=False,
)
btw_prompt = (
"[Ephemeral /btw side question. Answer using the conversation "
"context. No tools available. Be direct and concise.]\n\n"
+ question
)
result = btw_agent.run_conversation(
user_message=btw_prompt,
conversation_history=history_snapshot,
task_id=task_id,
)
response = (result.get("final_response") or "") if result else ""
if not response and result and result.get("error"):
response = f"Error: {result['error']}"
# TUI refresh before printing
if self._app:
self._app.invalidate()
time.sleep(0.05)
print()
if response:
try:
from hermes_cli.skin_engine import get_active_skin
_skin = get_active_skin()
_resp_color = _skin.get_color("response_border", "#4F6D4A")
except Exception:
_resp_color = "#4F6D4A"
ChatConsole().print(Panel(
_render_final_assistant_content(response, mode=self.final_response_markdown),
title=f"[{_resp_color} bold]⚕ /btw[/]",
title_align="left",
border_style=_resp_color,
box=rich_box.HORIZONTALS,
padding=(1, 4),
))
else:
_cprint(" 💬 /btw: (no response)")
if self.bell_on_complete:
sys.stdout.write("\a")
sys.stdout.flush()
except Exception as e:
if self._app:
self._app.invalidate()
time.sleep(0.05)
print()
_cprint(f" ❌ /btw failed: {e}")
finally:
if self._app:
self._invalidate(min_interval=0)
thread = threading.Thread(target=run_btw, daemon=True, name=f"btw-{task_id}")
thread.start()
@staticmethod
def _try_launch_chrome_debug(port: int, system: str) -> bool:
"""Try to launch Chrome/Chromium with remote debugging enabled.
@@ -6861,48 +6901,6 @@ class HermesCLI:
else:
_cprint(f" {_ACCENT}✓ Reasoning effort set to '{arg}' (session only){_RST}")
def _handle_busy_command(self, cmd: str):
"""Handle /busy — control what Enter does while Hermes is working.
Usage:
/busy Show current busy input mode
/busy status Show current busy input mode
/busy queue Queue input for the next turn instead of interrupting
/busy steer Inject Enter mid-run via /steer (after next tool call)
/busy interrupt Interrupt the current run on Enter (default)
"""
parts = cmd.strip().split(maxsplit=1)
if len(parts) < 2 or parts[1].strip().lower() == "status":
_cprint(f" {_ACCENT}Busy input mode: {self.busy_input_mode}{_RST}")
if self.busy_input_mode == "queue":
_behavior = "queues for next turn"
elif self.busy_input_mode == "steer":
_behavior = "steers into current run (after next tool call)"
else:
_behavior = "interrupts current run"
_cprint(f" {_DIM}Enter while busy: {_behavior}{_RST}")
_cprint(f" {_DIM}Usage: /busy [queue|steer|interrupt|status]{_RST}")
return
arg = parts[1].strip().lower()
if arg not in {"queue", "interrupt", "steer"}:
_cprint(f" {_DIM}(._.) Unknown argument: {arg}{_RST}")
_cprint(f" {_DIM}Usage: /busy [queue|steer|interrupt|status]{_RST}")
return
self.busy_input_mode = arg
if save_config_value("display.busy_input_mode", arg):
if arg == "queue":
behavior = "Enter will queue follow-up input while Hermes is busy."
elif arg == "steer":
behavior = "Enter will steer your message into the current run (after the next tool call)."
else:
behavior = "Enter will interrupt the current run while Hermes is busy."
_cprint(f" {_ACCENT}✓ Busy input mode set to '{arg}' (saved to config){_RST}")
_cprint(f" {_DIM}{behavior}{_RST}")
else:
_cprint(f" {_ACCENT}✓ Busy input mode set to '{arg}' (session only){_RST}")
def _handle_fast_command(self, cmd: str):
"""Handle /fast — toggle fast mode (OpenAI Priority Processing / Anthropic Fast Mode)."""
if not self._fast_command_available():
@@ -6981,52 +6979,51 @@ class HermesCLI:
focus_topic = parts[1].strip()
original_count = len(self.conversation_history)
with self._busy_command("Compressing context..."):
try:
from agent.model_metadata import estimate_messages_tokens_rough
from agent.manual_compression_feedback import summarize_manual_compression
original_history = list(self.conversation_history)
approx_tokens = estimate_messages_tokens_rough(original_history)
if focus_topic:
print(f"🗜️ Compressing {original_count} messages (~{approx_tokens:,} tokens), "
f"focus: \"{focus_topic}\"...")
else:
print(f"🗜️ Compressing {original_count} messages (~{approx_tokens:,} tokens)...")
try:
from agent.model_metadata import estimate_messages_tokens_rough
from agent.manual_compression_feedback import summarize_manual_compression
original_history = list(self.conversation_history)
approx_tokens = estimate_messages_tokens_rough(original_history)
if focus_topic:
print(f"🗜️ Compressing {original_count} messages (~{approx_tokens:,} tokens), "
f"focus: \"{focus_topic}\"...")
else:
print(f"🗜️ Compressing {original_count} messages (~{approx_tokens:,} tokens)...")
compressed, _ = self.agent._compress_context(
original_history,
self.agent._cached_system_prompt or "",
approx_tokens=approx_tokens,
focus_topic=focus_topic or None,
)
self.conversation_history = compressed
# _compress_context ends the old session and creates a new child
# session on the agent (run_agent.py::_compress_context). Sync the
# CLI's session_id so /status, /resume, exit summary, and title
# generation all point at the live continuation session, not the
# ended parent. Without this, subsequent end_session() calls target
# the already-closed parent and the child is orphaned.
if (
getattr(self.agent, "session_id", None)
and self.agent.session_id != self.session_id
):
self.session_id = self.agent.session_id
self._pending_title = None
new_tokens = estimate_messages_tokens_rough(self.conversation_history)
summary = summarize_manual_compression(
original_history,
self.conversation_history,
approx_tokens,
new_tokens,
)
icon = "🗜️" if summary["noop"] else ""
print(f" {icon} {summary['headline']}")
print(f" {summary['token_line']}")
if summary["note"]:
print(f" {summary['note']}")
compressed, _ = self.agent._compress_context(
original_history,
self.agent._cached_system_prompt or "",
approx_tokens=approx_tokens,
focus_topic=focus_topic or None,
)
self.conversation_history = compressed
# _compress_context ends the old session and creates a new child
# session on the agent (run_agent.py::_compress_context). Sync the
# CLI's session_id so /status, /resume, exit summary, and title
# generation all point at the live continuation session, not the
# ended parent. Without this, subsequent end_session() calls target
# the already-closed parent and the child is orphaned.
if (
getattr(self.agent, "session_id", None)
and self.agent.session_id != self.session_id
):
self.session_id = self.agent.session_id
self._pending_title = None
new_tokens = estimate_messages_tokens_rough(self.conversation_history)
summary = summarize_manual_compression(
original_history,
self.conversation_history,
approx_tokens,
new_tokens,
)
icon = "🗜️" if summary["noop"] else ""
print(f" {icon} {summary['headline']}")
print(f" {summary['token_line']}")
if summary["note"]:
print(f" {summary['note']}")
except Exception as e:
print(f" ❌ Compression failed: {e}")
except Exception as e:
print(f" ❌ Compression failed: {e}")
def _handle_debug_command(self):
"""Handle /debug — upload debug report + logs and print paste URLs."""
@@ -7299,7 +7296,7 @@ class HermesCLI:
change_detail = ". ".join(change_parts) + ". " if change_parts else ""
self.conversation_history.append({
"role": "user",
"content": f"[IMPORTANT: MCP servers have been reloaded. {change_detail}{tool_summary}. The tool list for this conversation has been updated accordingly.]",
"content": f"[SYSTEM: MCP servers have been reloaded. {change_detail}{tool_summary}. The tool list for this conversation has been updated accordingly.]",
})
# Persist session immediately so the session log reflects the
@@ -7381,31 +7378,6 @@ class HermesCLI:
_cprint(f" {line}")
except Exception:
pass
# First-touch onboarding: on the first tool in this process
# that takes longer than the threshold while we're in the
# noisiest progress mode, print a one-time hint about
# /verbose. Latched on self so it fires at most once per
# process; persisted to config.yaml so it never fires again
# across processes either.
try:
if (
not getattr(self, "_long_tool_hint_fired", False)
and self.tool_progress_mode == "all"
and duration >= 30.0
):
from agent.onboarding import (
TOOL_PROGRESS_FLAG,
is_seen,
mark_seen,
tool_progress_hint_cli,
)
if not is_seen(CLI_CONFIG, TOOL_PROGRESS_FLAG):
self._long_tool_hint_fired = True
_cprint(f" {_DIM}{tool_progress_hint_cli()}{_RST}")
mark_seen(_hermes_home / "config.yaml", TOOL_PROGRESS_FLAG)
CLI_CONFIG.setdefault("onboarding", {}).setdefault("seen", {})[TOOL_PROGRESS_FLAG] = True
except Exception:
pass
self._invalidate()
return
if event_type != "tool.started":
@@ -9073,30 +9045,6 @@ class HermesCLI:
_welcome_text = "Welcome to Hermes Agent! Type your message or /help for commands."
_welcome_color = "#FFF8DC"
self._console_print(f"[{_welcome_color}]{_welcome_text}[/]")
# First-time OpenClaw-residue banner — fires once if ~/.openclaw/ exists
# after an OpenClaw→Hermes migration (especially migrations done by
# OpenClaw's own tool, which doesn't archive the source directory).
try:
from agent.onboarding import (
OPENCLAW_RESIDUE_FLAG,
detect_openclaw_residue,
is_seen,
mark_seen,
openclaw_residue_hint_cli,
)
if not is_seen(self.config, OPENCLAW_RESIDUE_FLAG) and detect_openclaw_residue():
try:
_resid_color = _welcome_skin.get_color("banner_dim", "#B8860B")
except Exception:
_resid_color = "#B8860B"
self._console_print(f"[{_resid_color}]{openclaw_residue_hint_cli()}[/]")
try:
from hermes_cli.config import get_config_path as _get_cfg_path_resid
mark_seen(_get_cfg_path_resid(), OPENCLAW_RESIDUE_FLAG)
except Exception:
pass # best-effort — banner will fire again next session
except Exception:
pass # banner is non-critical — never break startup
# Show a random tip to help users discover features
try:
from hermes_cli.tips import get_random_tip
@@ -9298,34 +9246,12 @@ class HermesCLI:
# Bundle text + images as a tuple when images are present
payload = (text, images) if images else text
if self._agent_running and not (text and _looks_like_slash_command(text)):
_effective_mode = self.busy_input_mode
if _effective_mode == "steer":
# Route Enter through /steer — inject mid-run after the
# next tool call. Images can't ride along (steer only
# appends text), so fall back to queue when images are
# attached. If the agent lacks steer() or rejects the
# payload, also fall back to queue so nothing is lost.
if images or not text:
_effective_mode = "queue"
else:
accepted = False
try:
if self.agent is not None and hasattr(self.agent, "steer"):
accepted = bool(self.agent.steer(text))
except Exception as exc:
_cprint(f" {_DIM}Steer failed ({exc}) — queued for next turn.{_RST}")
accepted = False
if accepted:
preview = text[:80] + ("..." if len(text) > 80 else "")
_cprint(f" {_ACCENT}⏩ Steered: '{preview}'{_RST}")
else:
_effective_mode = "queue"
if _effective_mode == "queue":
if self.busy_input_mode == "queue":
# Queue for the next turn instead of interrupting
self._pending_input.put(payload)
preview = text if text else f"[{len(images)} image{'s' if len(images) != 1 else ''} attached]"
_cprint(f" Queued for the next turn: {preview[:80]}{'...' if len(preview) > 80 else ''}")
elif _effective_mode == "interrupt":
else:
self._interrupt_queue.put(payload)
# Debug: log to file when message enters interrupt queue
try:
@@ -9335,24 +9261,6 @@ class HermesCLI:
f"agent_running={self._agent_running}\n")
except Exception:
pass
# First-touch onboarding: on the very first busy-while-running
# event for this install, print a one-line tip explaining the
# /busy knob. Flag persists to config.yaml and never fires
# again. Guarded for exceptions so onboarding can't break
# the input loop.
try:
from agent.onboarding import (
BUSY_INPUT_FLAG,
busy_input_hint_cli,
is_seen,
mark_seen,
)
if not is_seen(CLI_CONFIG, BUSY_INPUT_FLAG):
_cprint(f" {_DIM}{busy_input_hint_cli(self.busy_input_mode)}{_RST}")
mark_seen(_hermes_home / "config.yaml", BUSY_INPUT_FLAG)
CLI_CONFIG.setdefault("onboarding", {}).setdefault("seen", {})[BUSY_INPUT_FLAG] = True
except Exception:
pass
else:
self._pending_input.put(payload)
event.app.current_buffer.reset(append_to_history=True)
@@ -9367,18 +9275,14 @@ class HermesCLI:
"""Ctrl+Enter (c-j) inserts a newline. Most terminals send c-j for Ctrl+Enter."""
event.current_buffer.insert_text('\n')
# VSCode/Cursor bind Ctrl+G to "Find Next" at the editor level, so
# the keystroke never reaches the embedded terminal. Alt+G is unbound
# in those IDEs and arrives here as ('escape', 'g') — register it as
# a fallback so the editor handoff works inside Cursor/VSCode too.
_editor_filter = Condition(
lambda: not self._clarify_state and not self._approval_state and not self._sudo_state and not self._secret_state
@kb.add(
'c-g',
filter=Condition(
lambda: not self._clarify_state and not self._approval_state and not self._sudo_state and not self._secret_state
),
)
@kb.add('c-g', filter=_editor_filter)
@kb.add('escape', 'g', filter=_editor_filter)
def handle_open_in_editor(event):
"""Ctrl+G (or Alt+G in VSCode/Cursor) opens the current draft in an external editor."""
"""Ctrl+G opens the current draft in an external editor."""
cli_ref._open_external_editor(event.current_buffer)
@kb.add('tab', eager=True)
@@ -9621,20 +9525,9 @@ class HermesCLI:
@kb.add('c-d')
def handle_ctrl_d(event):
"""Ctrl+D: delete char under cursor (standard readline behaviour).
Only exit when the input is empty same as bash/zsh. Pending
attached images count as input and block the EOF-exit so the
user doesn't lose them silently.
"""
buf = event.app.current_buffer
if buf.text:
buf.delete()
elif self._attached_images:
# Empty text but pending attachments — no-op, don't exit.
return
else:
self._should_exit = True
event.app.exit()
"""Handle Ctrl+D - exit."""
self._should_exit = True
event.app.exit()
_modal_prompt_active = Condition(
lambda: bool(self._secret_state or self._sudo_state)
@@ -9842,11 +9735,6 @@ class HermesCLI:
completer=_completer,
),
)
# Keep prompt_toolkit on its simple tempfile path. Setting
# buffer.tempfile = "prompt.md" triggers its complex-tempfile branch,
# which tries to mkdir() the mkdtemp() directory again and raises
# EEXIST. The suffix keeps markdown highlighting without that bug.
input_area.buffer.tempfile_suffix = '.md'
# Dynamic height: accounts for both explicit newlines AND visual
# wrapping of long lines so the input area always fits its content.
@@ -9969,7 +9857,7 @@ class HermesCLI:
status = cli_ref._command_status or "Processing command..."
return f"{frame} {status}"
if cli_ref._agent_running:
return "msg=interrupt · /queue · /bg · /steer · Ctrl+C cancel"
return "type a message + Enter to interrupt, Ctrl+C to cancel"
if cli_ref._voice_mode:
return "type or Ctrl+B to record"
return ""
@@ -10799,8 +10687,6 @@ class HermesCLI:
return # silently suppress
if isinstance(exc, KeyError) and "is not registered" in str(exc):
return # suppress selector registration failures (#6393)
if isinstance(exc, OSError) and getattr(exc, "errno", None) == errno.EIO:
return # suppress I/O errors from broken stdout on interrupt (#13710)
# Fall back to default handler for everything else
loop.default_exception_handler(context)
@@ -10833,11 +10719,9 @@ class HermesCLI:
except (EOFError, KeyboardInterrupt, BrokenPipeError):
pass
except (KeyError, OSError) as _stdin_err:
# Catch selector registration failures from broken stdin (#6393)
# and I/O errors from broken stdout during interrupt (#13710).
if isinstance(_stdin_err, OSError) and getattr(_stdin_err, "errno", None) == errno.EIO:
pass # suppress broken-stdout I/O errors on interrupt (#13710)
elif "is not registered" in str(_stdin_err) or "Bad file descriptor" in str(_stdin_err):
# Catch selector registration failures from broken stdin (#6393).
# This is the fallback for cases that slip past the fstat() guard.
if "is not registered" in str(_stdin_err) or "Bad file descriptor" in str(_stdin_err):
print(
f"\nError: stdin is not usable ({_stdin_err}).\n"
"This can happen with certain Python installations (e.g. uv-managed cPython on macOS).\n"
@@ -10856,6 +10740,12 @@ class HermesCLI:
self.agent.interrupt()
except Exception:
pass
# Flush memories before exit (only for substantial conversations)
if self.agent and self.conversation_history:
try:
self.agent.flush_memories(self.conversation_history)
except (Exception, KeyboardInterrupt):
pass
# Shut down voice recorder (release persistent audio stream)
if hasattr(self, '_voice_recorder') and self._voice_recorder:
try:
+1 -14
View File
@@ -16,7 +16,7 @@ import uuid
from datetime import datetime, timedelta
from pathlib import Path
from hermes_constants import get_hermes_home
from typing import Optional, Dict, List, Any, Union
from typing import Optional, Dict, List, Any
logger = logging.getLogger(__name__)
@@ -417,7 +417,6 @@ def create_job(
provider: Optional[str] = None,
base_url: Optional[str] = None,
script: Optional[str] = None,
context_from: Optional[Union[str, List[str]]] = None,
enabled_toolsets: Optional[List[str]] = None,
workdir: Optional[str] = None,
) -> Dict[str, Any]:
@@ -439,9 +438,6 @@ def create_job(
script: Optional path to a Python script whose stdout is injected into the
prompt each run. The script runs before the agent turn, and its output
is prepended as context. Useful for data collection / change detection.
context_from: Optional job ID (or list of job IDs) whose most recent output
is injected into the prompt as context before each run.
Useful for chaining cron jobs: job A finds data, job B processes it.
enabled_toolsets: Optional list of toolset names to restrict the agent to.
When set, only tools from these toolsets are loaded, reducing
token overhead. When omitted, all default tools are loaded.
@@ -485,14 +481,6 @@ def create_job(
normalized_toolsets = normalized_toolsets or None
normalized_workdir = _normalize_workdir(workdir)
# Normalize context_from: accept str or list of str, store as list or None
if isinstance(context_from, str):
context_from = [context_from.strip()] if context_from.strip() else None
elif isinstance(context_from, list):
context_from = [str(j).strip() for j in context_from if str(j).strip()] or None
else:
context_from = None
label_source = (prompt or (normalized_skills[0] if normalized_skills else None)) or "cron job"
job = {
"id": job_id,
@@ -504,7 +492,6 @@ def create_job(
"provider": normalized_provider,
"base_url": normalized_base_url,
"script": normalized_script,
"context_from": context_from,
"schedule": parsed_schedule,
"schedule_display": parsed_schedule.get("display", schedule),
"repeat": {
+4 -57
View File
@@ -77,7 +77,7 @@ _KNOWN_DELIVERY_PLATFORMS = frozenset({
"telegram", "discord", "slack", "whatsapp", "signal",
"matrix", "mattermost", "homeassistant", "dingtalk", "feishu",
"wecom", "wecom_callback", "weixin", "sms", "email", "webhook", "bluebubbles",
"qqbot", "yuanbao",
"qqbot",
})
# Platforms that support a configured cron/notification home target, mapped to
@@ -337,7 +337,6 @@ def _deliver_result(job: dict, content: str, adapters=None, loop=None) -> Option
"sms": Platform.SMS,
"bluebubbles": Platform.BLUEBUBBLES,
"qqbot": Platform.QQBOT,
"yuanbao": Platform.YUANBAO,
}
# Optionally wrap the content with a header/footer so the user knows this
@@ -672,51 +671,10 @@ def _build_job_prompt(job: dict, prerun_script: Optional[tuple] = None) -> str:
f"{prompt}"
)
# Inject output from referenced cron jobs as context.
context_from = job.get("context_from")
if context_from:
from cron.jobs import OUTPUT_DIR
if isinstance(context_from, str):
context_from = [context_from]
for source_job_id in context_from:
# Guard against path traversal — valid job IDs are 12-char hex strings
if not source_job_id or not all(c in "0123456789abcdef" for c in source_job_id):
logger.warning("context_from: skipping invalid job_id %r", source_job_id)
continue
try:
job_output_dir = OUTPUT_DIR / source_job_id
if not job_output_dir.exists():
continue # silent skip — no output yet
output_files = sorted(
job_output_dir.glob("*.md"),
key=lambda f: f.stat().st_mtime,
reverse=True,
)
if not output_files:
continue # silent skip — no output yet
latest_output = output_files[0].read_text(encoding="utf-8").strip()
# Truncate to 8K characters to avoid prompt bloat
_MAX_CONTEXT_CHARS = 8000
if len(latest_output) > _MAX_CONTEXT_CHARS:
latest_output = latest_output[:_MAX_CONTEXT_CHARS] + "\n\n[... output truncated ...]"
if latest_output:
prompt = (
f"## Output from job '{source_job_id}'\n"
"The following is the most recent output from a preceding "
"cron job. Use it as context for your analysis.\n\n"
f"```\n{latest_output}\n```\n\n"
f"{prompt}"
)
else:
continue # silent skip — empty output
except (OSError, PermissionError) as e:
logger.warning("context_from: failed to read output for job %r: %s", source_job_id, e)
# silent skip — do not pollute the prompt with error messages
# Always prepend cron execution guidance so the agent knows how
# delivery works and can suppress delivery when appropriate.
cron_hint = (
"[IMPORTANT: You are running as a scheduled cron job. "
"[SYSTEM: You are running as a scheduled cron job. "
"DELIVERY: Your final response will be automatically delivered "
"to the user — do NOT use send_message or try to deliver "
"the output yourself. Just produce your report/output as your "
@@ -752,7 +710,7 @@ def _build_job_prompt(job: dict, prerun_script: Optional[tuple] = None) -> str:
parts.append("")
parts.extend(
[
f'[IMPORTANT: The user has invoked the "{skill_name}" skill, indicating they want you to follow its instructions. The full skill content is loaded below.]',
f'[SYSTEM: The user has invoked the "{skill_name}" skill, indicating they want you to follow its instructions. The full skill content is loaded below.]',
"",
content,
]
@@ -760,7 +718,7 @@ def _build_job_prompt(job: dict, prerun_script: Optional[tuple] = None) -> str:
if skipped:
notice = (
f"[IMPORTANT: The following skill(s) were listed for this job but could not be found "
f"[SYSTEM: The following skill(s) were listed for this job but could not be found "
f"and were skipped: {', '.join(skipped)}. "
f"Start your response with a brief notice so the user is aware, e.g.: "
f"'⚠️ Skill(s) not found and skipped: {', '.join(skipped)}']"
@@ -1309,17 +1267,6 @@ def tick(verbose: bool = True, adapters=None, loop=None) -> int:
_futures.append(_tick_pool.submit(_ctx.run, _process_job, job))
_results.extend(f.result() for f in _futures)
# Best-effort sweep of MCP stdio subprocesses that survived their
# session teardown during this tick. Runs AFTER every job has
# finished so active sessions (including live user chats) are
# never touched — only PIDs explicitly detected as orphans in
# tools.mcp_tool._run_stdio's finally block are reaped.
try:
from tools.mcp_tool import _kill_orphaned_mcp_children
_kill_orphaned_mcp_children()
except Exception as _e:
logger.debug("Post-tick MCP orphan cleanup failed: %s", _e)
return sum(_results)
finally:
if fcntl:
+7 -9
View File
@@ -41,15 +41,6 @@ if [ "$(id -u)" = "0" ]; then
echo "Warning: chown failed (rootless container?) — continuing anyway"
fi
# Ensure config.yaml is readable by the hermes runtime user even if it was
# edited on the host after initial ownership setup. Must run here (as root)
# rather than after the gosu drop, otherwise a non-root caller like
# `docker run -u $(id -u):$(id -g)` hits "Operation not permitted" (#15865).
if [ -f "$HERMES_HOME/config.yaml" ]; then
chown hermes:hermes "$HERMES_HOME/config.yaml" 2>/dev/null || true
chmod 640 "$HERMES_HOME/config.yaml" 2>/dev/null || true
fi
echo "Dropping root privileges"
exec gosu hermes "$0" "$@"
fi
@@ -76,6 +67,13 @@ if [ ! -f "$HERMES_HOME/config.yaml" ]; then
cp "$INSTALL_DIR/cli-config.yaml.example" "$HERMES_HOME/config.yaml"
fi
# Ensure the main config file remains accessible to the hermes runtime user
# even if it was edited on the host after initial ownership setup.
if [ -f "$HERMES_HOME/config.yaml" ]; then
chown hermes:hermes "$HERMES_HOME/config.yaml"
chmod 640 "$HERMES_HOME/config.yaml"
fi
# SOUL.md
if [ ! -f "$HERMES_HOME/SOUL.md" ]; then
cp "$INSTALL_DIR/docker/SOUL.md" "$HERMES_HOME/SOUL.md"
+14 -67
View File
@@ -57,7 +57,7 @@ def _session_entry_name(origin: Dict[str, Any]) -> str:
# Build / refresh
# ---------------------------------------------------------------------------
async def build_channel_directory(adapters: Dict[Any, Any]) -> Dict[str, Any]:
def build_channel_directory(adapters: Dict[Any, Any]) -> Dict[str, Any]:
"""
Build a channel directory from connected platform adapters and session data.
@@ -72,7 +72,7 @@ async def build_channel_directory(adapters: Dict[Any, Any]) -> Dict[str, Any]:
if platform == Platform.DISCORD:
platforms["discord"] = _build_discord(adapter)
elif platform == Platform.SLACK:
platforms["slack"] = await _build_slack(adapter)
platforms["slack"] = _build_slack(adapter)
except Exception as e:
logger.warning("Channel directory: failed to build %s: %s", platform.value, e)
@@ -136,66 +136,21 @@ def _build_discord(adapter) -> List[Dict[str, str]]:
return channels
async def _build_slack(adapter) -> List[Dict[str, Any]]:
"""List Slack channels the bot has joined across all workspaces.
Uses ``users.conversations`` against each workspace's web client. Pulls
public + private channels the bot is a member of, then merges in DMs
discovered from session history (IMs aren't useful to enumerate
proactively).
"""
team_clients = getattr(adapter, "_team_clients", None) or {}
if not team_clients:
def _build_slack(adapter) -> List[Dict[str, str]]:
"""List Slack channels the bot has joined."""
# Slack adapter may expose a web client
client = getattr(adapter, "_app", None) or getattr(adapter, "_client", None)
if not client:
return _build_from_sessions("slack")
channels: List[Dict[str, Any]] = []
seen_ids: set = set()
try:
from tools.send_message_tool import _send_slack # noqa: F401
# Use the Slack Web API directly if available
except Exception:
pass
for team_id, client in team_clients.items():
try:
cursor: Optional[str] = None
for _page in range(20): # safety cap on pagination
response = await client.users_conversations(
types="public_channel,private_channel",
exclude_archived=True,
limit=200,
cursor=cursor,
)
if not response.get("ok"):
logger.warning(
"Channel directory: users.conversations not ok for team %s: %s",
team_id,
response.get("error", "unknown"),
)
break
for ch in response.get("channels", []):
cid = ch.get("id")
name = ch.get("name")
if not cid or not name or cid in seen_ids:
continue
seen_ids.add(cid)
channels.append({
"id": cid,
"name": name,
"type": "private" if ch.get("is_private") else "channel",
})
cursor = (response.get("response_metadata") or {}).get("next_cursor")
if not cursor:
break
except Exception as e:
logger.warning(
"Channel directory: failed to list Slack channels for team %s: %s",
team_id, e,
)
continue
# Merge in DM/group entries discovered from session history.
for entry in _build_from_sessions("slack"):
if entry.get("id") not in seen_ids:
channels.append(entry)
seen_ids.add(entry.get("id"))
return channels
# Fallback to session data
return _build_from_sessions("slack")
def _build_from_sessions(platform_name: str) -> List[Dict[str, str]]:
@@ -268,14 +223,6 @@ def resolve_channel_name(platform_name: str, name: str) -> Optional[str]:
if not channels:
return None
# 0. Exact ID match — case-sensitive, no normalization. Lets callers pass
# raw platform IDs (e.g. Slack "C0B0QV5434G") even when the format guard
# in _parse_target_ref hasn't recognized them as explicit.
raw = name.strip()
for ch in channels:
if ch.get("id") == raw:
return ch["id"]
query = _normalize_channel_query(name)
# 1. Exact name match, including the display labels shown by send_message(action="list")
+5 -76
View File
@@ -67,7 +67,6 @@ class Platform(Enum):
WEIXIN = "weixin"
BLUEBUBBLES = "bluebubbles"
QQBOT = "qqbot"
YUANBAO = "yuanbao"
@dataclass
@@ -136,7 +135,7 @@ class SessionResetPolicy:
mode=mode if mode is not None else "both",
at_hour=at_hour if at_hour is not None else 4,
idle_minutes=idle_minutes if idle_minutes is not None else 1440,
notify=_coerce_bool(notify, True),
notify=notify if notify is not None else True,
notify_exclude_platforms=tuple(exclude) if exclude is not None else ("api_server", "webhook"),
)
@@ -179,7 +178,7 @@ class PlatformConfig:
home_channel = HomeChannel.from_dict(data["home_channel"])
return cls(
enabled=_coerce_bool(data.get("enabled"), False),
enabled=data.get("enabled", False),
token=data.get("token"),
api_key=data.get("api_key"),
home_channel=home_channel,
@@ -196,14 +195,6 @@ class StreamingConfig:
edit_interval: float = 1.0 # Seconds between message edits (Telegram rate-limits at ~1/s)
buffer_threshold: int = 40 # Chars before forcing an edit
cursor: str = "" # Cursor shown during streaming
# Ported from openclaw/openclaw#72038. When >0, the final edit for
# a long-running streamed response is delivered as a fresh message
# if the original preview has been visible for at least this many
# seconds, so the platform's visible timestamp reflects completion
# time instead of the preview creation time. Currently applied to
# Telegram only (other platforms ignore the setting). Default 60s
# matches the OpenClaw rollout. Set to 0 to disable.
fresh_final_after_seconds: float = 60.0
def to_dict(self) -> Dict[str, Any]:
return {
@@ -212,7 +203,6 @@ class StreamingConfig:
"edit_interval": self.edit_interval,
"buffer_threshold": self.buffer_threshold,
"cursor": self.cursor,
"fresh_final_after_seconds": self.fresh_final_after_seconds,
}
@classmethod
@@ -225,9 +215,6 @@ class StreamingConfig:
edit_interval=float(data.get("edit_interval", 1.0)),
buffer_threshold=int(data.get("buffer_threshold", 40)),
cursor=data.get("cursor", ""),
fresh_final_after_seconds=float(
data.get("fresh_final_after_seconds", 60.0)
),
)
@@ -327,9 +314,6 @@ class GatewayConfig:
# QQBot uses extra dict for app credentials
elif platform == Platform.QQBOT and config.extra.get("app_id") and config.extra.get("client_secret"):
connected.append(platform)
# Yuanbao uses extra dict for app credentials
elif platform == Platform.YUANBAO and config.extra.get("app_id") and config.extra.get("app_secret"):
connected.append(platform)
# DingTalk uses client_id/client_secret from config.extra or env vars
elif platform == Platform.DINGTALK and (
config.extra.get("client_id") or os.getenv("DINGTALK_CLIENT_ID")
@@ -451,7 +435,7 @@ class GatewayConfig:
reset_triggers=data.get("reset_triggers", ["/new", "/reset"]),
quick_commands=quick_commands,
sessions_dir=sessions_dir,
always_log_local=_coerce_bool(data.get("always_log_local"), True),
always_log_local=data.get("always_log_local", True),
stt_enabled=_coerce_bool(stt_enabled, True),
group_sessions_per_user=_coerce_bool(group_sessions_per_user, True),
thread_sessions_per_user=_coerce_bool(thread_sessions_per_user, False),
@@ -586,8 +570,6 @@ def load_gateway_config() -> GatewayConfig:
)
if "reply_prefix" in platform_cfg:
bridged["reply_prefix"] = platform_cfg["reply_prefix"]
if "reply_in_thread" in platform_cfg:
bridged["reply_in_thread"] = platform_cfg["reply_in_thread"]
if "require_mention" in platform_cfg:
bridged["require_mention"] = platform_cfg["require_mention"]
if "free_response_channels" in platform_cfg:
@@ -602,7 +584,7 @@ def load_gateway_config() -> GatewayConfig:
bridged["group_policy"] = platform_cfg["group_policy"]
if "group_allow_from" in platform_cfg:
bridged["group_allow_from"] = platform_cfg["group_allow_from"]
if plat in (Platform.DISCORD, Platform.SLACK) and "channel_skill_bindings" in platform_cfg:
if plat == Platform.DISCORD and "channel_skill_bindings" in platform_cfg:
bridged["channel_skill_bindings"] = platform_cfg["channel_skill_bindings"]
if "channel_prompts" in platform_cfg:
channel_prompts = platform_cfg["channel_prompts"]
@@ -627,8 +609,6 @@ def load_gateway_config() -> GatewayConfig:
if isinstance(slack_cfg, dict):
if "require_mention" in slack_cfg and not os.getenv("SLACK_REQUIRE_MENTION"):
os.environ["SLACK_REQUIRE_MENTION"] = str(slack_cfg["require_mention"]).lower()
if "strict_mention" in slack_cfg and not os.getenv("SLACK_STRICT_MENTION"):
os.environ["SLACK_STRICT_MENTION"] = str(slack_cfg["strict_mention"]).lower()
if "allow_bots" in slack_cfg and not os.getenv("SLACK_ALLOW_BOTS"):
os.environ["SLACK_ALLOW_BOTS"] = str(slack_cfg["allow_bots"]).lower()
frc = slack_cfg.get("free_response_channels")
@@ -707,11 +687,6 @@ def load_gateway_config() -> GatewayConfig:
os.environ["TELEGRAM_REACTIONS"] = str(telegram_cfg["reactions"]).lower()
if "proxy_url" in telegram_cfg and not os.getenv("TELEGRAM_PROXY"):
os.environ["TELEGRAM_PROXY"] = str(telegram_cfg["proxy_url"]).strip()
if "group_allowed_chats" in telegram_cfg and not os.getenv("TELEGRAM_GROUP_ALLOWED_USERS"):
gac = telegram_cfg["group_allowed_chats"]
if isinstance(gac, list):
gac = ",".join(str(v) for v in gac)
os.environ["TELEGRAM_GROUP_ALLOWED_USERS"] = str(gac)
if "disable_link_previews" in telegram_cfg:
plat_data = platforms_data.setdefault(Platform.TELEGRAM.value, {})
if not isinstance(plat_data, dict):
@@ -938,12 +913,8 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
slack_token = os.getenv("SLACK_BOT_TOKEN")
if slack_token:
if Platform.SLACK not in config.platforms:
# No yaml config for Slack — env-only setup, enable it
config.platforms[Platform.SLACK] = PlatformConfig()
config.platforms[Platform.SLACK].enabled = True
# If yaml config exists, respect its enabled flag (don't override
# explicit enabled: false). Token is still stored so skills that
# send Slack messages can use it without activating the gateway adapter.
config.platforms[Platform.SLACK].enabled = True
config.platforms[Platform.SLACK].token = slack_token
slack_home = os.getenv("SLACK_HOME_CHANNEL")
if slack_home and Platform.SLACK in config.platforms:
@@ -1300,48 +1271,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
name=os.getenv("QQBOT_HOME_CHANNEL_NAME") or os.getenv(qq_home_name_env, "Home"),
)
# Yuanbao — YUANBAO_APP_ID preferred
yuanbao_app_id = os.getenv("YUANBAO_APP_ID") or os.getenv("YUANBAO_APP_KEY")
yuanbao_app_secret = os.getenv("YUANBAO_APP_SECRET")
if yuanbao_app_id and yuanbao_app_secret:
if Platform.YUANBAO not in config.platforms:
config.platforms[Platform.YUANBAO] = PlatformConfig()
config.platforms[Platform.YUANBAO].enabled = True
extra = config.platforms[Platform.YUANBAO].extra
extra["app_id"] = yuanbao_app_id
extra["app_secret"] = yuanbao_app_secret
yuanbao_bot_id = os.getenv("YUANBAO_BOT_ID")
if yuanbao_bot_id:
extra["bot_id"] = yuanbao_bot_id
yuanbao_ws_url = os.getenv("YUANBAO_WS_URL")
if yuanbao_ws_url:
extra["ws_url"] = yuanbao_ws_url
yuanbao_api_domain = os.getenv("YUANBAO_API_DOMAIN")
if yuanbao_api_domain:
extra["api_domain"] = yuanbao_api_domain
yuanbao_route_env = os.getenv("YUANBAO_ROUTE_ENV")
if yuanbao_route_env:
extra["route_env"] = yuanbao_route_env
yuanbao_home = os.getenv("YUANBAO_HOME_CHANNEL")
if yuanbao_home:
config.platforms[Platform.YUANBAO].home_channel = HomeChannel(
platform=Platform.YUANBAO,
chat_id=yuanbao_home,
name=os.getenv("YUANBAO_HOME_CHANNEL_NAME", "Home"),
)
yuanbao_dm_policy = os.getenv("YUANBAO_DM_POLICY")
if yuanbao_dm_policy:
extra["dm_policy"] = yuanbao_dm_policy.strip().lower()
yuanbao_dm_allow_from = os.getenv("YUANBAO_DM_ALLOW_FROM")
if yuanbao_dm_allow_from:
extra["dm_allow_from"] = yuanbao_dm_allow_from
yuanbao_group_policy = os.getenv("YUANBAO_GROUP_POLICY")
if yuanbao_group_policy:
extra["group_policy"] = yuanbao_group_policy.strip().lower()
yuanbao_group_allow_from = os.getenv("YUANBAO_GROUP_ALLOW_FROM")
if yuanbao_group_allow_from:
extra["group_allow_from"] = yuanbao_group_allow_from
# Session settings
idle_minutes = os.getenv("SESSION_IDLE_MINUTES")
if idle_minutes:
+1 -3
View File
@@ -79,9 +79,7 @@ _PLATFORM_DEFAULTS: dict[str, dict[str, Any]] = {
"discord": _TIER_HIGH,
# Tier 2 — edit support, often customer/workspace channels
# Slack: tool_progress off by default — Bolt posts cannot be edited like CLI;
# "new"/"all" spam permanent lines in channels (hermes-agent#14663).
"slack": {**_TIER_MEDIUM, "tool_progress": "off"},
"slack": _TIER_MEDIUM,
"mattermost": _TIER_MEDIUM,
"matrix": _TIER_MEDIUM,
"feishu": _TIER_MEDIUM,
+11 -57
View File
@@ -28,7 +28,6 @@ def mirror_to_session(
message_text: str,
source_label: str = "cli",
thread_id: Optional[str] = None,
user_id: Optional[str] = None,
) -> bool:
"""
Append a delivery-mirror message to the target session's transcript.
@@ -40,20 +39,9 @@ def mirror_to_session(
All errors are caught -- this is never fatal.
"""
try:
session_id = _find_session_id(
platform,
str(chat_id),
thread_id=thread_id,
user_id=user_id,
)
session_id = _find_session_id(platform, str(chat_id), thread_id=thread_id)
if not session_id:
logger.debug(
"Mirror: no session found for %s:%s:%s:%s",
platform,
chat_id,
thread_id,
user_id,
)
logger.debug("Mirror: no session found for %s:%s:%s", platform, chat_id, thread_id)
return False
mirror_msg = {
@@ -71,33 +59,17 @@ def mirror_to_session(
return True
except Exception as e:
logger.debug(
"Mirror failed for %s:%s:%s:%s: %s",
platform,
chat_id,
thread_id,
user_id,
e,
)
logger.debug("Mirror failed for %s:%s:%s: %s", platform, chat_id, thread_id, e)
return False
def _find_session_id(
platform: str,
chat_id: str,
thread_id: Optional[str] = None,
user_id: Optional[str] = None,
) -> Optional[str]:
def _find_session_id(platform: str, chat_id: str, thread_id: Optional[str] = None) -> Optional[str]:
"""
Find the active session_id for a platform + chat_id pair.
Scans sessions.json entries and matches where origin.chat_id == chat_id
on the right platform. DM session keys don't embed the chat_id
(e.g. "agent:main:telegram:dm"), so we check the origin dict.
When *user_id* is provided, prefer exact sender matches. If multiple
same-chat candidates exist and none matches the user, return None instead
of guessing and contaminating another participant's session.
"""
if not _SESSIONS_INDEX.exists():
return None
@@ -109,7 +81,8 @@ def _find_session_id(
return None
platform_lower = platform.lower()
candidates = []
best_match = None
best_updated = ""
for _key, entry in data.items():
origin = entry.get("origin") or {}
@@ -123,31 +96,12 @@ def _find_session_id(
origin_thread_id = origin.get("thread_id")
if thread_id is not None and str(origin_thread_id or "") != str(thread_id):
continue
candidates.append(entry)
updated = entry.get("updated_at", "")
if updated > best_updated:
best_updated = updated
best_match = entry.get("session_id")
if not candidates:
return None
if user_id:
exact_user_matches = [
entry for entry in candidates
if str((entry.get("origin") or {}).get("user_id") or "") == str(user_id)
]
if exact_user_matches:
candidates = exact_user_matches
elif len(candidates) > 1:
return None
elif len(candidates) > 1:
distinct_user_ids = {
str((entry.get("origin") or {}).get("user_id") or "").strip()
for entry in candidates
if str((entry.get("origin") or {}).get("user_id") or "").strip()
}
if len(distinct_user_ids) > 1:
return None
best_entry = max(candidates, key=lambda entry: entry.get("updated_at", ""))
return best_entry.get("session_id")
return best_match
def _append_to_jsonl(session_id: str, message: dict) -> None:
-2
View File
@@ -10,12 +10,10 @@ Each adapter handles:
from .base import BasePlatformAdapter, MessageEvent, SendResult
from .qqbot import QQAdapter
from .yuanbao import YuanbaoAdapter
__all__ = [
"BasePlatformAdapter",
"MessageEvent",
"SendResult",
"QQAdapter",
"YuanbaoAdapter",
]
+22 -150
View File
@@ -9,7 +9,6 @@ Exposes an HTTP server with endpoints:
- GET /v1/models lists hermes-agent as an available model
- POST /v1/runs start a run, returns run_id immediately (202)
- GET /v1/runs/{run_id}/events SSE stream of structured lifecycle events
- POST /v1/runs/{run_id}/stop interrupt a running agent
- GET /health health check
- GET /health/detailed rich status for cross-container dashboard probing
@@ -587,9 +586,6 @@ class APIServerAdapter(BasePlatformAdapter):
self._run_streams: Dict[str, "asyncio.Queue[Optional[Dict]]"] = {}
# Creation timestamps for orphaned-run TTL sweep
self._run_streams_created: Dict[str, float] = {}
# Active run agent/task references for stop support
self._active_run_agents: Dict[str, Any] = {}
self._active_run_tasks: Dict[str, "asyncio.Task"] = {}
self._session_db: Optional[Any] = None # Lazy-init SessionDB for session continuity
@staticmethod
@@ -1208,12 +1204,10 @@ class APIServerAdapter(BasePlatformAdapter):
If the client disconnects mid-stream, ``agent.interrupt()`` is
called so the agent stops issuing upstream LLM calls, then the
asyncio task is cancelled. When ``store=True`` an initial
``in_progress`` snapshot is persisted immediately after
``response.created`` and disconnects update it to an
``incomplete`` snapshot so GET /v1/responses/{id} and
``previous_response_id`` chaining still have something to
recover from.
asyncio task is cancelled. When ``store=True`` the full response
is persisted to the ResponseStore in a ``finally`` block so GET
/v1/responses/{id} and ``previous_response_id`` chaining work the
same as the batch path.
"""
import queue as _q
@@ -1275,60 +1269,6 @@ class APIServerAdapter(BasePlatformAdapter):
final_response_text = ""
agent_error: Optional[str] = None
usage: Dict[str, int] = {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
terminal_snapshot_persisted = False
def _persist_response_snapshot(
response_env: Dict[str, Any],
*,
conversation_history_snapshot: Optional[List[Dict[str, Any]]] = None,
) -> None:
if not store:
return
if conversation_history_snapshot is None:
conversation_history_snapshot = list(conversation_history)
conversation_history_snapshot.append({"role": "user", "content": user_message})
self._response_store.put(response_id, {
"response": response_env,
"conversation_history": conversation_history_snapshot,
"instructions": instructions,
"session_id": session_id,
})
if conversation:
self._response_store.set_conversation(conversation, response_id)
def _persist_incomplete_if_needed() -> None:
"""Persist an ``incomplete`` snapshot if no terminal one was written.
Called from both the client-disconnect (``ConnectionResetError``)
and server-cancellation (``asyncio.CancelledError``) paths so
GET /v1/responses/{id} and ``previous_response_id`` chaining keep
working after abrupt stream termination.
"""
if not store or terminal_snapshot_persisted:
return
incomplete_text = "".join(final_text_parts) or final_response_text
incomplete_items: List[Dict[str, Any]] = list(emitted_items)
if incomplete_text:
incomplete_items.append({
"type": "message",
"role": "assistant",
"content": [{"type": "output_text", "text": incomplete_text}],
})
incomplete_env = _envelope("incomplete")
incomplete_env["output"] = incomplete_items
incomplete_env["usage"] = {
"input_tokens": usage.get("input_tokens", 0),
"output_tokens": usage.get("output_tokens", 0),
"total_tokens": usage.get("total_tokens", 0),
}
incomplete_history = list(conversation_history)
incomplete_history.append({"role": "user", "content": user_message})
if incomplete_text:
incomplete_history.append({"role": "assistant", "content": incomplete_text})
_persist_response_snapshot(
incomplete_env,
conversation_history_snapshot=incomplete_history,
)
try:
# response.created — initial envelope, status=in_progress
@@ -1338,7 +1278,6 @@ class APIServerAdapter(BasePlatformAdapter):
"type": "response.created",
"response": created_env,
})
_persist_response_snapshot(created_env)
last_activity = time.monotonic()
async def _open_message_item() -> None:
@@ -1595,18 +1534,6 @@ class APIServerAdapter(BasePlatformAdapter):
"output_tokens": usage.get("output_tokens", 0),
"total_tokens": usage.get("total_tokens", 0),
}
_failed_history = list(conversation_history)
_failed_history.append({"role": "user", "content": user_message})
if final_response_text or agent_error:
_failed_history.append({
"role": "assistant",
"content": final_response_text or agent_error,
})
_persist_response_snapshot(
failed_env,
conversation_history_snapshot=_failed_history,
)
terminal_snapshot_persisted = True
await _write_event("response.failed", {
"type": "response.failed",
"response": failed_env,
@@ -1619,24 +1546,30 @@ class APIServerAdapter(BasePlatformAdapter):
"output_tokens": usage.get("output_tokens", 0),
"total_tokens": usage.get("total_tokens", 0),
}
full_history = list(conversation_history)
full_history.append({"role": "user", "content": user_message})
if isinstance(result, dict) and result.get("messages"):
full_history.extend(result["messages"])
else:
full_history.append({"role": "assistant", "content": final_response_text})
_persist_response_snapshot(
completed_env,
conversation_history_snapshot=full_history,
)
terminal_snapshot_persisted = True
await _write_event("response.completed", {
"type": "response.completed",
"response": completed_env,
})
# Persist for future chaining / GET retrieval, mirroring
# the batch path behavior.
if store:
full_history = list(conversation_history)
full_history.append({"role": "user", "content": user_message})
if isinstance(result, dict) and result.get("messages"):
full_history.extend(result["messages"])
else:
full_history.append({"role": "assistant", "content": final_response_text})
self._response_store.put(response_id, {
"response": completed_env,
"conversation_history": full_history,
"instructions": instructions,
"session_id": session_id,
})
if conversation:
self._response_store.set_conversation(conversation, response_id)
except (ConnectionResetError, ConnectionAbortedError, BrokenPipeError, OSError):
_persist_incomplete_if_needed()
# Client disconnected — interrupt the agent so it stops
# making upstream LLM calls, then cancel the task.
agent = agent_ref[0] if agent_ref else None
@@ -1652,22 +1585,6 @@ class APIServerAdapter(BasePlatformAdapter):
except (asyncio.CancelledError, Exception):
pass
logger.info("SSE client disconnected; interrupted agent task %s", response_id)
except asyncio.CancelledError:
# Server-side cancellation (e.g. shutdown, request timeout) —
# persist an incomplete snapshot so GET /v1/responses/{id} and
# previous_response_id chaining still work, then re-raise so the
# runtime's cancellation semantics are respected.
_persist_incomplete_if_needed()
agent = agent_ref[0] if agent_ref else None
if agent is not None:
try:
agent.interrupt("SSE task cancelled")
except Exception:
pass
if not agent_task.done():
agent_task.cancel()
logger.info("SSE task cancelled; persisted incomplete snapshot for %s", response_id)
raise
return response
@@ -2445,7 +2362,6 @@ class APIServerAdapter(BasePlatformAdapter):
stream_delta_callback=_text_cb,
tool_progress_callback=event_cb,
)
self._active_run_agents[run_id] = agent
def _run_sync():
r = agent.run_conversation(
user_message=user_message,
@@ -2485,11 +2401,8 @@ class APIServerAdapter(BasePlatformAdapter):
q.put_nowait(None)
except Exception:
pass
self._active_run_agents.pop(run_id, None)
self._active_run_tasks.pop(run_id, None)
task = asyncio.create_task(_run_and_close())
self._active_run_tasks[run_id] = task
try:
self._background_tasks.add(task)
except TypeError:
@@ -2548,44 +2461,6 @@ class APIServerAdapter(BasePlatformAdapter):
return response
async def _handle_stop_run(self, request: "web.Request") -> "web.Response":
"""POST /v1/runs/{run_id}/stop — interrupt a running agent."""
auth_err = self._check_auth(request)
if auth_err:
return auth_err
run_id = request.match_info["run_id"]
agent = self._active_run_agents.get(run_id)
task = self._active_run_tasks.get(run_id)
if agent is None and task is None:
return web.json_response(_openai_error(f"Run not found: {run_id}", code="run_not_found"), status=404)
if agent is not None:
try:
agent.interrupt("Stop requested via API")
except Exception:
pass
if task is not None and not task.done():
task.cancel()
# Bounded wait: run_conversation() executes in the default
# executor thread which task.cancel() cannot preempt — we rely on
# agent.interrupt() above to break the loop. Cap the wait so a
# slow/unresponsive interrupt can't hang this handler.
try:
await asyncio.wait_for(asyncio.shield(task), timeout=5.0)
except asyncio.TimeoutError:
logger.warning(
"[api_server] stop for run %s timed out after 5s; "
"agent may still be finishing the current step",
run_id,
)
except (asyncio.CancelledError, Exception):
pass
return web.json_response({"run_id": run_id, "status": "stopping"})
async def _sweep_orphaned_runs(self) -> None:
"""Periodically clean up run streams that were never consumed."""
while True:
@@ -2600,8 +2475,6 @@ class APIServerAdapter(BasePlatformAdapter):
logger.debug("[api_server] sweeping orphaned run %s", run_id)
self._run_streams.pop(run_id, None)
self._run_streams_created.pop(run_id, None)
self._active_run_agents.pop(run_id, None)
self._active_run_tasks.pop(run_id, None)
# ------------------------------------------------------------------
# BasePlatformAdapter interface
@@ -2637,7 +2510,6 @@ class APIServerAdapter(BasePlatformAdapter):
# Structured event streaming
self._app.router.add_post("/v1/runs", self._handle_runs)
self._app.router.add_get("/v1/runs/{run_id}/events", self._handle_run_events)
self._app.router.add_post("/v1/runs/{run_id}/stop", self._handle_stop_run)
# Start background sweep to clean up orphaned (unconsumed) run streams
sweep_task = asyncio.create_task(self._sweep_orphaned_runs())
try:
+8 -264
View File
@@ -148,102 +148,7 @@ def _detect_macos_system_proxy() -> str | None:
return None
def _split_host_port(value: str) -> tuple[str, int | None]:
raw = str(value or "").strip()
if not raw:
return "", None
if "://" in raw:
parsed = urlsplit(raw)
return (parsed.hostname or "").lower().rstrip("."), parsed.port
if raw.startswith("[") and "]" in raw:
host, _, rest = raw[1:].partition("]")
port = None
if rest.startswith(":") and rest[1:].isdigit():
port = int(rest[1:])
return host.lower().rstrip("."), port
if raw.count(":") == 1:
host, _, maybe_port = raw.rpartition(":")
if maybe_port.isdigit():
return host.lower().rstrip("."), int(maybe_port)
return raw.lower().strip("[]").rstrip("."), None
def _no_proxy_entries() -> list[str]:
entries: list[str] = []
for key in ("NO_PROXY", "no_proxy"):
raw = os.environ.get(key, "")
entries.extend(part.strip() for part in raw.split(",") if part.strip())
return entries
def _no_proxy_entry_matches(entry: str, host: str, port: int | None = None) -> bool:
token = str(entry or "").strip().lower()
if not token:
return False
if token == "*":
return True
token_host, token_port = _split_host_port(token)
if token_port is not None and port is not None and token_port != port:
return False
if token_port is not None and port is None:
return False
if not token_host:
return False
try:
network = ipaddress.ip_network(token_host, strict=False)
try:
return ipaddress.ip_address(host) in network
except ValueError:
return False
except ValueError:
pass
try:
token_ip = ipaddress.ip_address(token_host)
try:
return ipaddress.ip_address(host) == token_ip
except ValueError:
return False
except ValueError:
pass
if token_host.startswith("*."):
suffix = token_host[1:]
return host.endswith(suffix)
if token_host.startswith("."):
return host == token_host[1:] or host.endswith(token_host)
return host == token_host or host.endswith(f".{token_host}")
def should_bypass_proxy(target_hosts: str | list[str] | tuple[str, ...] | set[str] | None) -> bool:
"""Return True when NO_PROXY/no_proxy matches at least one target host.
Supports exact hosts, domain suffixes, wildcard suffixes, IP literals,
CIDR ranges, optional host:port entries, and ``*``.
"""
entries = _no_proxy_entries()
if not entries or not target_hosts:
return False
if isinstance(target_hosts, str):
candidates = [target_hosts]
else:
candidates = list(target_hosts)
for candidate in candidates:
host, port = _split_host_port(str(candidate))
if not host:
continue
if any(_no_proxy_entry_matches(entry, host, port) for entry in entries):
return True
return False
def resolve_proxy_url(
platform_env_var: str | None = None,
*,
target_hosts: str | list[str] | tuple[str, ...] | set[str] | None = None,
) -> str | None:
def resolve_proxy_url(platform_env_var: str | None = None) -> str | None:
"""Return a proxy URL from env vars, or macOS system proxy.
Check order:
@@ -251,26 +156,18 @@ def resolve_proxy_url(
1. HTTPS_PROXY / HTTP_PROXY / ALL_PROXY (and lowercase variants)
2. macOS system proxy via ``scutil --proxy`` (auto-detect)
Returns *None* if no proxy is found, or if NO_PROXY/no_proxy matches one
of ``target_hosts``.
Returns *None* if no proxy is found.
"""
if platform_env_var:
value = (os.environ.get(platform_env_var) or "").strip()
if value:
if should_bypass_proxy(target_hosts):
return None
return normalize_proxy_url(value)
for key in ("HTTPS_PROXY", "HTTP_PROXY", "ALL_PROXY",
"https_proxy", "http_proxy", "all_proxy"):
value = (os.environ.get(key) or "").strip()
if value:
if should_bypass_proxy(target_hosts):
return None
return normalize_proxy_url(value)
detected = normalize_proxy_url(_detect_macos_system_proxy())
if detected and should_bypass_proxy(target_hosts):
return None
return detected
return normalize_proxy_url(_detect_macos_system_proxy())
def proxy_kwargs_for_bot(proxy_url: str | None) -> dict:
@@ -336,39 +233,6 @@ def proxy_kwargs_for_aiohttp(proxy_url: str | None) -> tuple[dict, dict]:
return {}, {"proxy": proxy_url}
def is_host_excluded_by_no_proxy(hostname: str, no_proxy_value: str | None = None) -> bool:
"""Return True when ``hostname`` matches a ``NO_PROXY`` entry.
Supports comma- or whitespace-separated entries with optional leading dots
and ``*.`` wildcards, which match both the apex domain and subdomains.
"""
raw = no_proxy_value
if raw is None:
raw = os.environ.get("NO_PROXY") or os.environ.get("no_proxy") or ""
raw = raw.strip()
if not raw:
return False
lower_hostname = hostname.lower()
for entry in re.split(r"[\s,]+", raw):
normalized = entry.strip().lower()
if not normalized:
continue
if normalized == "*":
return True
if normalized.startswith("*."):
normalized = normalized[2:]
elif normalized.startswith("."):
normalized = normalized[1:]
if lower_hostname == normalized or lower_hostname.endswith(f".{normalized}"):
return True
return False
from dataclasses import dataclass, field
from datetime import datetime
from pathlib import Path
@@ -726,15 +590,7 @@ SUPPORTED_DOCUMENT_TYPES = {
".pdf": "application/pdf",
".md": "text/markdown",
".txt": "text/plain",
".csv": "text/csv",
".log": "text/plain",
".json": "application/json",
".xml": "application/xml",
".yaml": "application/yaml",
".yml": "application/yaml",
".toml": "application/toml",
".ini": "text/plain",
".cfg": "text/plain",
".zip": "application/zip",
".docx": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
".xlsx": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
@@ -1023,61 +879,6 @@ def resolve_channel_prompt(
return None
def resolve_channel_skills(
config_extra: dict,
channel_id: str,
parent_id: str | None = None,
) -> list[str] | None:
"""Resolve auto-loaded skill(s) for a channel/thread from platform config.
Looks up ``channel_skill_bindings`` in the adapter's ``config.extra`` dict.
Config format::
channel_skill_bindings:
- id: "C0123" # Slack channel ID or Discord channel/forum ID
skills: ["skill-a", "skill-b"]
- id: "D0ABCDE"
skill: "solo-skill" # single string also accepted
Prefers an exact match on *channel_id*; falls back to *parent_id*
(useful for forum threads / Slack threads inheriting the parent channel's
binding).
Returns a deduplicated list of skill names (order preserved), or None if
no match is found.
"""
bindings = config_extra.get("channel_skill_bindings") or []
if not isinstance(bindings, list) or not bindings:
return None
ids_to_check: set[str] = set()
if channel_id:
ids_to_check.add(str(channel_id))
if parent_id:
ids_to_check.add(str(parent_id))
if not ids_to_check:
return None
for entry in bindings:
if not isinstance(entry, dict):
continue
entry_id = str(entry.get("id", ""))
if entry_id in ids_to_check:
skills = entry.get("skills") or entry.get("skill")
if isinstance(skills, str):
s = skills.strip()
return [s] if s else None
if isinstance(skills, list) and skills:
seen: list[str] = []
for name in skills:
if not isinstance(name, str):
continue
nm = name.strip()
if nm and nm not in seen:
seen.append(nm)
return seen or None
return None
class BasePlatformAdapter(ABC):
"""
Base class for platform adapters.
@@ -1121,20 +922,7 @@ class BasePlatformAdapter(ABC):
self._post_delivery_callbacks: Dict[str, Any] = {}
self._expected_cancelled_tasks: set[asyncio.Task] = set()
self._busy_session_handler: Optional[Callable[[MessageEvent, str], Awaitable[bool]]] = None
# Auto-TTS on voice input: ``_auto_tts_default`` is the global default
# (``voice.auto_tts`` in config.yaml, pushed by GatewayRunner on connect).
# Per-chat overrides live in two sets populated from ``_voice_mode``:
# - ``_auto_tts_enabled_chats``: chat explicitly opted in via ``/voice on``
# or ``/voice tts`` (mode is ``voice_only`` or ``all``). Fires even when
# the global default is False.
# - ``_auto_tts_disabled_chats``: chat explicitly opted out via
# ``/voice off`` (mode is ``off``). Suppresses auto-TTS even when the
# global default is True.
# The gate in _process_message() is:
# fire if chat in _auto_tts_enabled_chats
# OR (_auto_tts_default and chat not in _auto_tts_disabled_chats)
self._auto_tts_default: bool = False
self._auto_tts_enabled_chats: set = set()
# Chats where auto-TTS on voice input is disabled (set by /voice off)
self._auto_tts_disabled_chats: set = set()
# Chats where typing indicator is paused (e.g. during approval waits).
# _keep_typing skips send_typing when the chat_id is in this set.
@@ -1156,21 +944,6 @@ class BasePlatformAdapter(ABC):
def fatal_error_retryable(self) -> bool:
return self._fatal_error_retryable
def _should_auto_tts_for_chat(self, chat_id: str) -> bool:
"""Whether auto-TTS on voice input should fire for ``chat_id``.
Decision layers (Issue #16007):
1. Explicit ``/voice on`` or ``/voice tts`` always fire (even if
``voice.auto_tts`` is False).
2. Explicit ``/voice off`` never fire.
3. Fall back to the global ``voice.auto_tts`` config default.
"""
if chat_id in self._auto_tts_enabled_chats:
return True
if chat_id in self._auto_tts_disabled_chats:
return False
return bool(self._auto_tts_default)
def set_fatal_error_handler(self, handler: Callable[["BasePlatformAdapter"], Awaitable[None] | None]) -> None:
self._fatal_error_handler = handler
@@ -1354,27 +1127,6 @@ class BasePlatformAdapter(ABC):
"""
return SendResult(success=False, error="Not supported")
async def delete_message(
self,
chat_id: str,
message_id: str,
) -> bool:
"""
Delete a previously sent message. Optional platforms that don't
support deletion return ``False`` and callers fall back to leaving
the message in place.
Used by the stream consumer's fresh-final cleanup path (see
openclaw/openclaw#72038) to remove long-lived preview messages
after sending the completed reply as a fresh message so the
platform's visible timestamp reflects completion time.
Returns ``True`` on successful deletion, ``False`` otherwise.
Subclasses should override for platforms with a deletion API
(e.g. Telegram ``deleteMessage``).
"""
return False
async def send_typing(self, chat_id: str, metadata=None) -> None:
"""
Send a typing indicator.
@@ -2359,14 +2111,12 @@ class BasePlatformAdapter(ABC):
logger.info("[%s] extract_local_files found %d file(s) in response", self.name, len(local_files))
# Auto-TTS: if voice message, generate audio FIRST (before sending text)
# Gated via ``_should_auto_tts_for_chat``: fires when the chat has
# an explicit ``/voice on|tts`` opt-in OR when ``voice.auto_tts`` is
# True globally and no ``/voice off`` has been issued.
# Skipped when the chat has voice mode disabled (/voice off)
_tts_path = None
if (self._should_auto_tts_for_chat(event.source.chat_id)
and event.message_type == MessageType.VOICE
if (event.message_type == MessageType.VOICE
and text_content
and not media_files):
and not media_files
and event.source.chat_id not in self._auto_tts_disabled_chats):
try:
from tools.tts_tool import text_to_speech_tool, check_tts_requirements
if check_tts_requirements():
@@ -2690,9 +2440,6 @@ class BasePlatformAdapter(ABC):
user_id_alt: Optional[str] = None,
chat_id_alt: Optional[str] = None,
is_bot: bool = False,
guild_id: Optional[str] = None,
parent_chat_id: Optional[str] = None,
message_id: Optional[str] = None,
) -> SessionSource:
"""Helper to build a SessionSource for this platform."""
# Normalize empty topic to None
@@ -2710,9 +2457,6 @@ class BasePlatformAdapter(ABC):
user_id_alt=user_id_alt,
chat_id_alt=chat_id_alt,
is_bot=is_bot,
guild_id=str(guild_id) if guild_id else None,
parent_chat_id=str(parent_chat_id) if parent_chat_id else None,
message_id=str(message_id) if message_id else None,
)
@abstractmethod
+2 -19
View File
@@ -99,7 +99,6 @@ def _normalize_server_url(raw: str) -> str:
class BlueBubblesAdapter(BasePlatformAdapter):
platform = Platform.BLUEBUBBLES
SUPPORTS_MESSAGE_EDITING = False
MAX_MESSAGE_LENGTH = MAX_TEXT_LENGTH
def __init__(self, config: PlatformConfig):
@@ -392,13 +391,6 @@ class BlueBubblesAdapter(BasePlatformAdapter):
# Text sending
# ------------------------------------------------------------------
@staticmethod
def truncate_message(content: str, max_length: int = MAX_TEXT_LENGTH) -> List[str]:
# Use the base splitter but skip pagination indicators — iMessage
# bubbles flow naturally without "(1/3)" suffixes.
chunks = BasePlatformAdapter.truncate_message(content, max_length)
return [re.sub(r"\s*\(\d+/\d+\)$", "", c) for c in chunks]
async def send(
self,
chat_id: str,
@@ -406,19 +398,10 @@ class BlueBubblesAdapter(BasePlatformAdapter):
reply_to: Optional[str] = None,
metadata: Optional[Dict[str, Any]] = None,
) -> SendResult:
text = self.format_message(content)
text = strip_markdown(content or "")
if not text:
return SendResult(success=False, error="BlueBubbles send requires text")
# Split on paragraph breaks first (double newlines) so each thought
# becomes its own iMessage bubble, then truncate any that are still
# too long.
paragraphs = [p.strip() for p in re.split(r'\n\s*\n', text) if p.strip()]
chunks: List[str] = []
for para in (paragraphs or [text]):
if len(para) <= self.MAX_MESSAGE_LENGTH:
chunks.append(para)
else:
chunks.extend(self.truncate_message(para, max_length=self.MAX_MESSAGE_LENGTH))
chunks = self.truncate_message(text, max_length=self.MAX_MESSAGE_LENGTH)
last = SendResult(success=True)
for chunk in chunks:
guid = await self._resolve_chat_guid(chat_id)
+20 -6
View File
@@ -2315,6 +2315,11 @@ class DiscordAdapter(BasePlatformAdapter):
async def slash_background(interaction: discord.Interaction, prompt: str):
await self._run_simple_slash(interaction, f"/background {prompt}", "Background task started~")
@tree.command(name="btw", description="Ephemeral side question using session context")
@discord.app_commands.describe(question="Your side question (no tools, not persisted)")
async def slash_btw(interaction: discord.Interaction, question: str):
await self._run_simple_slash(interaction, f"/btw {question}")
# ── Auto-register any gateway-available commands not yet on the tree ──
# This ensures new commands added to COMMAND_REGISTRY in
# hermes_cli/commands.py automatically appear as Discord slash
@@ -2679,8 +2684,21 @@ class DiscordAdapter(BasePlatformAdapter):
skills: ["skill-a", "skill-b"]
Also checks parent_id so forum threads inherit the forum's bindings.
"""
from gateway.platforms.base import resolve_channel_skills
return resolve_channel_skills(self.config.extra, channel_id, parent_id)
bindings = self.config.extra.get("channel_skill_bindings", [])
if not bindings:
return None
ids_to_check = {channel_id}
if parent_id:
ids_to_check.add(parent_id)
for entry in bindings:
entry_id = str(entry.get("id", ""))
if entry_id in ids_to_check:
skills = entry.get("skills") or entry.get("skill")
if isinstance(skills, str):
return [skills]
if isinstance(skills, list) and skills:
return list(dict.fromkeys(skills)) # dedup, preserve order
return None
def _resolve_channel_prompt(self, channel_id: str, parent_id: str | None = None) -> str | None:
"""Resolve a Discord per-channel prompt, preferring the exact channel over its parent."""
@@ -3243,7 +3261,6 @@ class DiscordAdapter(BasePlatformAdapter):
if auto_thread and not skip_thread and not is_voice_linked_channel and not is_reply_message:
thread = await self._auto_create_thread(message)
if thread:
parent_channel_id = str(message.channel.id)
is_thread = True
thread_id = str(thread.id)
auto_threaded_channel = thread
@@ -3303,9 +3320,6 @@ class DiscordAdapter(BasePlatformAdapter):
thread_id=thread_id,
chat_topic=chat_topic,
is_bot=getattr(message.author, "bot", False),
guild_id=str(message.guild.id) if message.guild else None,
parent_chat_id=parent_channel_id,
message_id=str(message.id),
)
# Build media URLs -- download image attachments to local cache so the
-9
View File
@@ -57,15 +57,6 @@ class MessageDeduplicator:
if len(self._seen) > self._max_size:
cutoff = now - self._ttl
self._seen = {k: v for k, v in self._seen.items() if v > cutoff}
if len(self._seen) > self._max_size:
# TTL pruning alone does not cap the cache when every entry is
# still fresh. Keep the newest entries so the helper's
# max_size bound is enforced under sustained traffic.
newest = sorted(
self._seen.items(),
key=lambda item: item[1],
)[-self._max_size:]
self._seen = dict(newest)
return False
def clear(self):
-14
View File
@@ -532,20 +532,6 @@ class MatrixAdapter(BasePlatformAdapter):
)
await crypto_store.open()
# Bind the store to the runtime device_id before any
# put_account() runs. PgCryptoStore defaults _device_id
# to "" and its crypto_account UPSERT never updates the
# device_id column on conflict — so once put_account
# writes blank, it stays blank forever. That breaks
# every downstream device-scoped olm operation: peer
# to-device ciphertext can't find our identity key and
# no megolm sessions ever land. Setting _device_id here
# (in-memory; the on-disk row may not exist yet) makes
# the first put_account write the correct value.
# DeviceID is a NewType(str) so plain str works at runtime.
if client.device_id:
await crypto_store.put_device_id(client.device_id)
crypto_state = _CryptoStateStore(state_store, self._joined_rooms)
olm = OlmMachine(client, crypto_store, crypto_state)
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+1 -27
View File
@@ -703,6 +703,7 @@ class TelegramAdapter(BasePlatformAdapter):
"write_timeout": _env_float("HERMES_TELEGRAM_HTTP_WRITE_TIMEOUT", 20.0),
}
proxy_url = resolve_proxy_url("TELEGRAM_PROXY")
disable_fallback = (os.getenv("HERMES_TELEGRAM_DISABLE_FALLBACK_IPS", "").strip().lower() in ("1", "true", "yes", "on"))
fallback_ips = self._fallback_ips()
if not fallback_ips:
@@ -713,8 +714,6 @@ class TelegramAdapter(BasePlatformAdapter):
", ".join(fallback_ips),
)
proxy_targets = ["api.telegram.org", *fallback_ips]
proxy_url = resolve_proxy_url("TELEGRAM_PROXY", target_hosts=proxy_targets)
if fallback_ips and not proxy_url and not disable_fallback:
logger.info(
"[%s] Telegram fallback IPs active: %s",
@@ -1209,31 +1208,6 @@ class TelegramAdapter(BasePlatformAdapter):
)
return SendResult(success=False, error=str(e))
async def delete_message(self, chat_id: str, message_id: str) -> bool:
"""Delete a previously sent Telegram message.
Used by the stream consumer's fresh-final cleanup path (ported
from openclaw/openclaw#72038) to remove long-lived preview
messages after sending the completed reply as a fresh message.
Telegram's Bot API ``deleteMessage`` works for bot-posted
messages in the last 48 hours. Failures are non-fatal the
caller leaves the preview in place and logs at debug level.
"""
if not self._bot:
return False
try:
await self._bot.delete_message(
chat_id=int(chat_id),
message_id=int(message_id),
)
return True
except Exception as e:
logger.debug(
"[%s] Failed to delete Telegram message %s: %s",
self.name, message_id, e,
)
return False
async def send_update_prompt(
self, chat_id: str, prompt: str, default: str = "",
session_key: str = "",
+3 -3
View File
@@ -43,10 +43,10 @@ _DOH_PROVIDERS: list[dict] = [
_SEED_FALLBACK_IPS: list[str] = ["149.154.167.220"]
def _resolve_proxy_url(target_hosts=None) -> str | None:
def _resolve_proxy_url() -> str | None:
# Delegate to shared implementation (env vars + macOS system proxy detection)
from gateway.platforms.base import resolve_proxy_url
return resolve_proxy_url("TELEGRAM_PROXY", target_hosts=target_hosts)
return resolve_proxy_url("TELEGRAM_PROXY")
class TelegramFallbackTransport(httpx.AsyncBaseTransport):
@@ -60,7 +60,7 @@ class TelegramFallbackTransport(httpx.AsyncBaseTransport):
def __init__(self, fallback_ips: Iterable[str], **transport_kwargs):
self._fallback_ips = [ip for ip in dict.fromkeys(_normalize_fallback_ips(fallback_ips))]
proxy_url = _resolve_proxy_url(target_hosts=[_TELEGRAM_API_HOST, *self._fallback_ips])
proxy_url = _resolve_proxy_url()
if proxy_url and "proxy" not in transport_kwargs:
transport_kwargs["proxy"] = proxy_url
self._primary = httpx.AsyncHTTPTransport(**transport_kwargs)
File diff suppressed because it is too large Load Diff
-647
View File
@@ -1,647 +0,0 @@
"""
yuanbao_media.py 元宝平台媒体处理模块
提供 COS 上传文件下载TIM 媒体消息构建等功能
移植自 TypeScript media.tsyuanbao-openclaw-plugin
使用 httpx 替代 cos-nodejs-sdk-v5避免引入额外 SDK 依赖
COS 上传流程
1. 调用 genUploadInfo 获取临时凭证tmpSecretId/tmpSecretKey/sessionToken
2. 用临时凭证通过 HMAC-SHA1 签名构建 Authorization
3. HTTP PUT 上传到 COS
TIM 消息体构建
- buildImageMsgBody() TIMImageElem
- buildFileMsgBody() TIMFileElem
"""
from __future__ import annotations
import hashlib
import hmac
import logging
import os
import re
import secrets
import struct
import time
import urllib.parse
from datetime import datetime, timezone, timedelta
from typing import Optional, Any
import httpx
logger = logging.getLogger(__name__)
# ============ 常量 ============
UPLOAD_INFO_PATH = "/api/resource/genUploadInfo"
DEFAULT_API_DOMAIN = "yuanbao.tencent.com"
DEFAULT_MAX_SIZE_MB = 50
# COS 加速域名后缀(优先使用全球加速)
COS_USE_ACCELERATE = True
# ============ 类型映射 ============
# MIME → image_format 数字(TIM 协议字段)
_MIME_TO_IMAGE_FORMAT: dict[str, int] = {
"image/jpeg": 1,
"image/jpg": 1,
"image/gif": 2,
"image/png": 3,
"image/bmp": 4,
"image/webp": 255,
"image/heic": 255,
"image/tiff": 255,
}
# 文件扩展名 → MIME
_EXT_TO_MIME: dict[str, str] = {
".jpg": "image/jpeg",
".jpeg": "image/jpeg",
".png": "image/png",
".gif": "image/gif",
".webp": "image/webp",
".bmp": "image/bmp",
".heic": "image/heic",
".tiff": "image/tiff",
".ico": "image/x-icon",
".pdf": "application/pdf",
".doc": "application/msword",
".docx": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
".xls": "application/vnd.ms-excel",
".xlsx": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
".ppt": "application/vnd.ms-powerpoint",
".pptx": "application/vnd.openxmlformats-officedocument.presentationml.presentation",
".txt": "text/plain",
".zip": "application/zip",
".tar": "application/x-tar",
".gz": "application/gzip",
".mp3": "audio/mpeg",
".mp4": "video/mp4",
".wav": "audio/wav",
".ogg": "audio/ogg",
".webm": "video/webm",
}
# ============ 工具函数 ============
def guess_mime_type(filename: str) -> str:
"""根据文件扩展名猜测 MIME 类型。"""
ext = os.path.splitext(filename)[-1].lower()
return _EXT_TO_MIME.get(ext, "application/octet-stream")
def is_image(filename: str, mime_type: str = "") -> bool:
"""判断是否为图片类型。"""
if mime_type.startswith("image/"):
return True
ext = os.path.splitext(filename)[-1].lower()
return ext in {".jpg", ".jpeg", ".png", ".gif", ".webp", ".bmp", ".heic", ".tiff", ".ico"}
def get_image_format(mime_type: str) -> int:
"""获取 TIM 图片格式编号。"""
return _MIME_TO_IMAGE_FORMAT.get(mime_type.lower(), 255)
def md5_hex(data: bytes) -> str:
"""计算 MD5 十六进制摘要。"""
return hashlib.md5(data).hexdigest()
def generate_file_id() -> str:
"""生成随机文件 ID(32 位 hex)。"""
return secrets.token_hex(16)
# ============ 图片尺寸解析(纯 Python,无需 Pillow ============
def parse_image_size(data: bytes) -> Optional[dict[str, int]]:
"""
解析图片宽高支持 JPEG/PNG/GIF/WebP无需第三方依赖
返回 {"width": w, "height": h} None无法识别
"""
return (
_parse_png_size(data)
or _parse_jpeg_size(data)
or _parse_gif_size(data)
or _parse_webp_size(data)
)
def _parse_png_size(buf: bytes) -> Optional[dict[str, int]]:
if len(buf) < 24:
return None
if buf[:4] != b"\x89PNG":
return None
w = struct.unpack(">I", buf[16:20])[0]
h = struct.unpack(">I", buf[20:24])[0]
return {"width": w, "height": h}
def _parse_jpeg_size(buf: bytes) -> Optional[dict[str, int]]:
if len(buf) < 4 or buf[0] != 0xFF or buf[1] != 0xD8:
return None
i = 2
while i < len(buf) - 9:
if buf[i] != 0xFF:
i += 1
continue
marker = buf[i + 1]
if marker in (0xC0, 0xC2):
h = struct.unpack(">H", buf[i + 5: i + 7])[0]
w = struct.unpack(">H", buf[i + 7: i + 9])[0]
return {"width": w, "height": h}
if i + 3 < len(buf):
i += 2 + struct.unpack(">H", buf[i + 2: i + 4])[0]
else:
break
return None
def _parse_gif_size(buf: bytes) -> Optional[dict[str, int]]:
if len(buf) < 10:
return None
sig = buf[:6].decode("ascii", errors="replace")
if sig not in ("GIF87a", "GIF89a"):
return None
w = struct.unpack("<H", buf[6:8])[0]
h = struct.unpack("<H", buf[8:10])[0]
return {"width": w, "height": h}
def _parse_webp_size(buf: bytes) -> Optional[dict[str, int]]:
if len(buf) < 16:
return None
if buf[:4] != b"RIFF" or buf[8:12] != b"WEBP":
return None
chunk = buf[12:16].decode("ascii", errors="replace")
if chunk == "VP8 ":
if len(buf) >= 30 and buf[23] == 0x9D and buf[24] == 0x01 and buf[25] == 0x2A:
w = struct.unpack("<H", buf[26:28])[0] & 0x3FFF
h = struct.unpack("<H", buf[28:30])[0] & 0x3FFF
return {"width": w, "height": h}
elif chunk == "VP8L":
if len(buf) >= 25 and buf[20] == 0x2F:
bits = struct.unpack("<I", buf[21:25])[0]
w = (bits & 0x3FFF) + 1
h = ((bits >> 14) & 0x3FFF) + 1
return {"width": w, "height": h}
elif chunk == "VP8X":
if len(buf) >= 30:
w = (buf[24] | (buf[25] << 8) | (buf[26] << 16)) + 1
h = (buf[27] | (buf[28] << 8) | (buf[29] << 16)) + 1
return {"width": w, "height": h}
return None
# ============ URL 下载 ============
async def download_url(
url: str,
max_size_mb: int = DEFAULT_MAX_SIZE_MB,
) -> tuple[bytes, str]:
"""
下载 URL 内容返回 (bytes, content_type)
Args:
url: HTTP(S) URL
max_size_mb: 最大允许大小MB超过则抛出异常
Returns:
(data_bytes, content_type_string)
Raises:
ValueError: 内容超过大小限制
httpx.HTTPError: 网络/HTTP 错误
"""
max_bytes = max_size_mb * 1024 * 1024
async with httpx.AsyncClient(timeout=30.0, follow_redirects=True) as client:
# 先 HEAD 检查大小
try:
head = await client.head(url)
content_length = int(head.headers.get("content-length", 0) or 0)
if content_length > 0 and content_length > max_bytes:
raise ValueError(
f"文件过大: {content_length / 1024 / 1024:.1f} MB > {max_size_mb} MB"
)
except httpx.HTTPStatusError:
pass # 部分服务器不支持 HEAD,忽略
# GET 下载(流式读取,防止超限)
async with client.stream("GET", url) as resp:
resp.raise_for_status()
content_type = resp.headers.get("content-type", "").split(";")[0].strip()
chunks: list[bytes] = []
downloaded = 0
async for chunk in resp.aiter_bytes(65536):
downloaded += len(chunk)
if downloaded > max_bytes:
raise ValueError(
f"文件过大: 已超过 {max_size_mb} MB 限制"
)
chunks.append(chunk)
data = b"".join(chunks)
return data, content_type
# ============ COS 鉴权(HMAC-SHA1 ============
def _cos_sign(
method: str,
path: str,
params: dict[str, str],
headers: dict[str, str],
secret_id: str,
secret_key: str,
start_time: Optional[int] = None,
expire_seconds: int = 3600,
) -> str:
"""
构建 COS 请求签名q-sign-algorithm=sha1 方案
参考https://cloud.tencent.com/document/product/436/7778
Args:
method: HTTP 方法小写 "put"
path: URL 路径URL encode 后的小写
params: URL 查询参数 dict用于签名
headers: 参与签名的请求头 dictkey 需小写
secret_id: 临时 SecretIdtmpSecretId
secret_key: 临时 SecretKeytmpSecretKey
start_time: 签名起始 Unix 时间戳默认 now
expire_seconds: 签名有效期默认 3600
Returns:
Authorization header 完整字符串
"""
now = int(time.time())
q_sign_time = f"{start_time or now};{(start_time or now) + expire_seconds}"
# Step 1: SignKey = HMAC-SHA1(SecretKey, q-sign-time)
sign_key = hmac.new(
secret_key.encode("utf-8"),
q_sign_time.encode("utf-8"),
hashlib.sha1,
).hexdigest()
# Step 2: HttpString
# 参数和头部需按字典序排列,key 小写
sorted_params = sorted((k.lower(), urllib.parse.quote(str(v), safe="") ) for k, v in params.items())
sorted_headers = sorted((k.lower(), urllib.parse.quote(str(v), safe="") ) for k, v in headers.items())
url_param_list = ";".join(k for k, _ in sorted_params)
url_params = "&".join(f"{k}={v}" for k, v in sorted_params)
header_list = ";".join(k for k, _ in sorted_headers)
header_str = "&".join(f"{k}={v}" for k, v in sorted_headers)
http_string = "\n".join([
method.lower(),
path,
url_params,
header_str,
"",
])
# Step 3: StringToSign = sha1 hash of HttpString
sha1_of_http = hashlib.sha1(http_string.encode("utf-8")).hexdigest()
string_to_sign = "\n".join([
"sha1",
q_sign_time,
sha1_of_http,
"",
])
# Step 4: Signature = HMAC-SHA1(SignKey, StringToSign)
signature = hmac.new(
sign_key.encode("utf-8"),
string_to_sign.encode("utf-8"),
hashlib.sha1,
).hexdigest()
return (
f"q-sign-algorithm=sha1"
f"&q-ak={secret_id}"
f"&q-sign-time={q_sign_time}"
f"&q-key-time={q_sign_time}"
f"&q-header-list={header_list}"
f"&q-url-param-list={url_param_list}"
f"&q-signature={signature}"
)
# ============ 主要公开 API ============
async def get_cos_credentials(
app_key: str,
api_domain: str,
token: str,
filename: str = "file",
file_id: Optional[str] = None,
bot_id: str = "",
route_env: str = "",
) -> dict:
"""
调用 genUploadInfo 接口获取 COS 临时密钥及上传配置
Args:
app_key: 应用 Key用于 X-ID
api_domain: API 域名 https://bot.yuanbao.tencent.com
token: 当前有效的签票 tokenX-Token
filename: 待上传的文件名含扩展名
file_id: 客户端生成的唯一文件 ID不传则自动生成
bot_id: Bot 账号 ID用于 X-ID
Returns:
COS 上传配置 dict包含以下字段
bucketName (str) COS Bucket 名称
region (str) COS 地域
location (str) 上传 Key对象路径
encryptTmpSecretId (str) 临时 SecretId
encryptTmpSecretKey(str) 临时 SecretKey
encryptToken (str) SessionToken
startTime (int) 凭证起始时间戳Unix
expiredTime (int) 凭证过期时间戳Unix
resourceUrl (str) 上传后的公网访问 URL
resourceID (str) 资源 ID可选
Raises:
RuntimeError: 接口返回非 0 code 或字段缺失
"""
if file_id is None:
file_id = generate_file_id()
upload_url = f"{api_domain.rstrip('/')}{UPLOAD_INFO_PATH}"
headers = {
"Content-Type": "application/json",
"X-Token": token,
"X-ID": bot_id or app_key,
"X-Source": "web",
}
if route_env:
headers["X-Route-Env"] = route_env
body = {
"fileName": filename,
"fileId": file_id,
"docFrom": "localDoc",
"docOpenId": "",
}
async with httpx.AsyncClient(timeout=15.0) as client:
resp = await client.post(upload_url, json=body, headers=headers)
resp.raise_for_status()
result: dict[str, Any] = resp.json()
code = result.get("code")
if code != 0 and code is not None:
raise RuntimeError(
f"genUploadInfo 失败: code={code}, msg={result.get('msg', '')}"
)
data = result.get("data") or result
required_fields = ["bucketName", "location"]
missing = [f for f in required_fields if not data.get(f)]
if missing:
raise RuntimeError(
f"genUploadInfo 返回字段不完整: 缺少字段 {missing}"
)
return data
async def upload_to_cos(
file_bytes: bytes,
filename: str,
content_type: str,
credentials: dict,
bucket: str,
region: str,
) -> dict:
"""
通过 httpx PUT 请求将文件上传到 COS
使用临时凭证tmpSecretId/tmpSecretKey/sessionToken构建 HMAC-SHA1 签名
Args:
file_bytes: 文件二进制内容
filename: 文件名用于辅助计算 MIMEUUID
content_type: MIME 类型 "image/jpeg"
credentials: get_cos_credentials() 返回的 dict包含
encryptTmpSecretId tmpSecretId
encryptTmpSecretKey tmpSecretKey
encryptToken sessionToken
location COS key对象路径
resourceUrl 上传后公网 URL
startTime 凭证起始时间Unix
expiredTime 凭证过期时间Unix
bucket: COS Bucket 名称 chatbot-1234567890
region: COS 地域 ap-guangzhou
Returns:
上传结果 dict包含
url (str) COS 公网访问 URL
uuid (str) 文件内容 MD5
size (int) 文件大小字节
width (int, optional) 图片宽度仅图片
height (int, optional) 图片高度仅图片
Raises:
httpx.HTTPStatusError: COS 返回非 2xx 状态
RuntimeError: credentials 字段缺失
"""
secret_id: str = credentials.get("encryptTmpSecretId", "")
secret_key: str = credentials.get("encryptTmpSecretKey", "")
session_token: str = credentials.get("encryptToken", "")
cos_key: str = credentials.get("location", "")
resource_url: str = credentials.get("resourceUrl", "")
start_time: Optional[int] = credentials.get("startTime")
expired_time: Optional[int] = credentials.get("expiredTime")
if not secret_id or not secret_key or not cos_key:
raise RuntimeError(
f"COS credentials 不完整: secretId={bool(secret_id)}, "
f"secretKey={bool(secret_key)}, location={bool(cos_key)}"
)
# 构建 COS 上传 URL(优先使用全球加速域名)
if COS_USE_ACCELERATE:
cos_host = f"{bucket}.cos.accelerate.myqcloud.com"
else:
cos_host = f"{bucket}.cos.{region}.myqcloud.com"
# URL encode cos_key(保留 /
encoded_key = urllib.parse.quote(cos_key, safe="/")
cos_url = f"https://{cos_host}/{encoded_key.lstrip('/')}"
# 确定 Content-Type
if not content_type or content_type == "application/octet-stream":
if is_image(filename):
content_type = guess_mime_type(filename)
else:
content_type = "application/octet-stream"
# 计算文件 MD5 + size
file_uuid = md5_hex(file_bytes)
file_size = len(file_bytes)
# 参与签名的请求头
sign_headers = {
"host": cos_host,
"content-type": content_type,
"x-cos-security-token": session_token,
}
# 计算签名有效期
now = int(time.time())
sign_start = start_time if start_time else now
sign_expire = (expired_time - now) if expired_time and expired_time > now else 3600
authorization = _cos_sign(
method="put",
path=f"/{encoded_key.lstrip('/')}",
params={},
headers=sign_headers,
secret_id=secret_id,
secret_key=secret_key,
start_time=sign_start,
expire_seconds=sign_expire,
)
put_headers = {
"Authorization": authorization,
"Content-Type": content_type,
"x-cos-security-token": session_token,
}
logger.info(
"COS PUT: bucket=%s region=%s key=%s size=%d mime=%s",
bucket, region, cos_key, file_size, content_type,
)
async with httpx.AsyncClient(timeout=120.0) as client:
resp = await client.put(
cos_url,
content=file_bytes,
headers=put_headers,
)
resp.raise_for_status()
# 解析图片尺寸(仅图片类型)
result: dict[str, Any] = {
"url": resource_url or cos_url,
"uuid": file_uuid,
"size": file_size,
}
if content_type.startswith("image/"):
size_info = parse_image_size(file_bytes)
if size_info:
result["width"] = size_info["width"]
result["height"] = size_info["height"]
logger.info(
"COS 上传成功: url=%s size=%d",
result["url"], file_size,
)
return result
# ============ TIM 媒体消息构建 ============
def build_image_msg_body(
url: str,
uuid: Optional[str] = None,
filename: Optional[str] = None,
size: int = 0,
width: int = 0,
height: int = 0,
mime_type: str = "",
) -> list[dict]:
"""
构建腾讯 IM TIMImageElem 消息体
参考https://cloud.tencent.com/document/product/269/2720
Args:
url: 图片公网访问 URLCOS resourceUrl
uuid: 文件 UUIDMD5 或其他唯一标识
filename: 文件名uuid 为空时作为备用
size: 文件大小字节
width: 图片宽度像素
height: 图片高度像素
mime_type: MIME 类型用于确定 image_format
Returns:
TIMImageElem 消息体列表适合直接放入 msg_body
"""
_uuid = uuid or filename or _basename_from_url(url) or "image"
image_format = get_image_format(mime_type) if mime_type else 255
return [
{
"msg_type": "TIMImageElem",
"msg_content": {
"uuid": _uuid,
"image_format": image_format,
"image_info_array": [
{
"type": 1, # 1 = 原图
"size": size,
"width": width,
"height": height,
"url": url,
}
],
},
}
]
def build_file_msg_body(
url: str,
filename: str,
uuid: Optional[str] = None,
size: int = 0,
) -> list[dict]:
"""
构建腾讯 IM TIMFileElem 消息体
参考https://cloud.tencent.com/document/product/269/2720
Args:
url: 文件公网访问 URLCOS resourceUrl
filename: 文件名含扩展名
uuid: 文件 UUIDMD5 或其他唯一标识不传则使用 filename
size: 文件大小字节
Returns:
TIMFileElem 消息体列表适合直接放入 msg_body
"""
_uuid = uuid or filename
return [
{
"msg_type": "TIMFileElem",
"msg_content": {
"uuid": _uuid,
"file_name": filename,
"file_size": size,
"url": url,
},
}
]
# ============ 内部工具 ============
def _basename_from_url(url: str) -> str:
"""从 URL 提取文件名。"""
try:
parsed = urllib.parse.urlparse(url)
return os.path.basename(parsed.path)
except Exception:
return ""
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"""
Yuanbao sticker (TIMFaceElem) support.
Ported from yuanbao-openclaw-plugin/src/sticker/.
TIMFaceElem wire format:
{
"msg_type": "TIMFaceElem",
"msg_content": {
"index": 0, # always 0 per Yuanbao convention
"data": "<json>", # serialised sticker metadata
}
}
The `data` field carries a JSON string with the sticker's metadata so the
receiver can look up the correct asset in the emoji pack.
"""
from __future__ import annotations
import json
import random
import re
import unicodedata
from typing import Optional
# ---------------------------------------------------------------------------
# Sticker catalogue ported from builtin-stickers.json
# Key : canonical name (Chinese)
# Value : {sticker_id, package_id, name, description, width, height, formats}
# ---------------------------------------------------------------------------
STICKER_MAP: dict[str, dict] = {
"六六六": {
"sticker_id": "278", "package_id": "1003", "name": "六六六",
"description": "666 厉害 牛 棒 绝了 好强 awesome",
"width": 128, "height": 128, "formats": "png",
},
"我想开了": {
"sticker_id": "262", "package_id": "1003", "name": "我想开了",
"description": "想开 佛系 释怀 顿悟 看淡了 无所谓",
"width": 128, "height": 128, "formats": "png",
},
"害羞": {
"sticker_id": "130", "package_id": "1003", "name": "害羞",
"description": "腼腆 不好意思 脸红 娇羞 羞涩 捂脸",
"width": 128, "height": 128, "formats": "png",
},
"比心": {
"sticker_id": "252", "package_id": "1003", "name": "比心",
"description": "笔芯 爱你 爱心手势 love heart 喜欢你",
"width": 128, "height": 128, "formats": "png",
},
"委屈": {
"sticker_id": "125", "package_id": "1003", "name": "委屈",
"description": "难过 想哭 可怜巴巴 瘪嘴 受伤 被欺负",
"width": 128, "height": 128, "formats": "png",
},
"亲亲": {
"sticker_id": "146", "package_id": "1003", "name": "亲亲",
"description": "么么 mua 亲一下 kiss 飞吻 啵",
"width": 128, "height": 128, "formats": "png",
},
"": {
"sticker_id": "131", "package_id": "1003", "name": "",
"description": "帅 墨镜 cool 高冷 有型 swagger",
"width": 128, "height": 128, "formats": "png",
},
"": {
"sticker_id": "145", "package_id": "1003", "name": "",
"description": "睡觉 困 zzZ 打盹 躺平 休眠 sleepy",
"width": 128, "height": 128, "formats": "png",
},
"发呆": {
"sticker_id": "152", "package_id": "1003", "name": "发呆",
"description": "懵 愣住 放空 呆滞 出神 脑子空白",
"width": 128, "height": 128, "formats": "png",
},
"可怜": {
"sticker_id": "157", "package_id": "1003", "name": "可怜",
"description": "卖萌 求饶 委屈巴巴 弱小 拜托 眼巴巴",
"width": 128, "height": 128, "formats": "png",
},
"摊手": {
"sticker_id": "200", "package_id": "1003", "name": "摊手",
"description": "无奈 没办法 耸肩 随便 那咋整 whatever",
"width": 128, "height": 128, "formats": "png",
},
"头大": {
"sticker_id": "213", "package_id": "1003", "name": "头大",
"description": "头疼 烦恼 郁闷 难搞 崩溃 一团乱",
"width": 128, "height": 128, "formats": "png",
},
"": {
"sticker_id": "256", "package_id": "1003", "name": "",
"description": "害怕 惊恐 震惊 吓一跳 恐怖 怂",
"width": 128, "height": 128, "formats": "png",
},
"吐血": {
"sticker_id": "203", "package_id": "1003", "name": "吐血",
"description": "无语 崩溃 被雷 内伤 一口老血 屮",
"width": 128, "height": 128, "formats": "png",
},
"": {
"sticker_id": "185", "package_id": "1003", "name": "",
"description": "傲娇 生气 不满 撇嘴 不理 赌气",
"width": 128, "height": 128, "formats": "png",
},
"嘿嘿": {
"sticker_id": "220", "package_id": "1003", "name": "嘿嘿",
"description": "坏笑 猥琐笑 偷笑 憨笑 得意 你懂的",
"width": 128, "height": 128, "formats": "png",
},
"头秃": {
"sticker_id": "218", "package_id": "1003", "name": "头秃",
"description": "程序员 加班 焦虑 没头发 秃了 肝爆",
"width": 128, "height": 128, "formats": "png",
},
"暗中观察": {
"sticker_id": "221", "package_id": "1003", "name": "暗中观察",
"description": "窥屏 潜水 偷偷看 角落 围观 屏住呼吸",
"width": 128, "height": 128, "formats": "png",
},
"我酸了": {
"sticker_id": "224", "package_id": "1003", "name": "我酸了",
"description": "嫉妒 柠檬精 羡慕 吃柠檬 眼红 恰柠檬",
"width": 128, "height": 128, "formats": "png",
},
"打call": {
"sticker_id": "246", "package_id": "1003", "name": "打call",
"description": "应援 加油 支持 喝彩 助威 call",
"width": 128, "height": 128, "formats": "png",
},
"庆祝": {
"sticker_id": "251", "package_id": "1003", "name": "庆祝",
"description": "祝贺 开心 耶 party 胜利 干杯",
"width": 128, "height": 128, "formats": "png",
},
"奋斗": {
"sticker_id": "151", "package_id": "1003", "name": "奋斗",
"description": "努力 加油 拼搏 冲 干劲 卷起来",
"width": 128, "height": 128, "formats": "png",
},
"惊讶": {
"sticker_id": "143", "package_id": "1003", "name": "惊讶",
"description": "震惊 哇 不敢相信 OMG 居然 这么离谱",
"width": 128, "height": 128, "formats": "png",
},
"疑问": {
"sticker_id": "144", "package_id": "1003", "name": "疑问",
"description": "问号 不懂 啥 为什么 啥情况 懵逼问",
"width": 128, "height": 128, "formats": "png",
},
"仔细分析": {
"sticker_id": "248", "package_id": "1003", "name": "仔细分析",
"description": "思考 推敲 认真 研究 琢磨 让我想想",
"width": 128, "height": 128, "formats": "png",
},
"撅嘴": {
"sticker_id": "184", "package_id": "1003", "name": "撅嘴",
"description": "嘟嘴 卖萌 不高兴 撒娇 嘴翘",
"width": 128, "height": 128, "formats": "png",
},
"泪奔": {
"sticker_id": "199", "package_id": "1003", "name": "泪奔",
"description": "大哭 伤心 破防 感动哭 泪流满面 呜呜",
"width": 128, "height": 128, "formats": "png",
},
"尊嘟假嘟": {
"sticker_id": "276", "package_id": "1003", "name": "尊嘟假嘟",
"description": "真的假的 真假 可爱问 你骗我 是不是",
"width": 128, "height": 128, "formats": "png",
},
"略略略": {
"sticker_id": "113", "package_id": "1003", "name": "略略略",
"description": "调皮 吐舌 不服 略 气死你 鬼脸",
"width": 128, "height": 128, "formats": "png",
},
"": {
"sticker_id": "180", "package_id": "1003", "name": "",
"description": "想睡 倦 打哈欠 睁不开眼 好困啊 sleepy",
"width": 128, "height": 128, "formats": "png",
},
"折磨": {
"sticker_id": "181", "package_id": "1003", "name": "折磨",
"description": "难受 痛苦 煎熬 蚌埠住了 受不了 要命",
"width": 128, "height": 128, "formats": "png",
},
"抠鼻": {
"sticker_id": "182", "package_id": "1003", "name": "抠鼻",
"description": "不屑 无聊 淡定 无所谓 鄙视 挖鼻",
"width": 128, "height": 128, "formats": "png",
},
"鼓掌": {
"sticker_id": "183", "package_id": "1003", "name": "鼓掌",
"description": "拍手 叫好 赞同 666 喝彩 掌声",
"width": 128, "height": 128, "formats": "png",
},
"斜眼笑": {
"sticker_id": "204", "package_id": "1003", "name": "斜眼笑",
"description": "滑稽 坏笑 doge 意味深长 阴阳怪气 嘿嘿嘿",
"width": 128, "height": 128, "formats": "png",
},
"辣眼睛": {
"sticker_id": "216", "package_id": "1003", "name": "辣眼睛",
"description": "看不下去 cringe 毁三观 太丑了 瞎了",
"width": 128, "height": 128, "formats": "png",
},
"哦哟": {
"sticker_id": "217", "package_id": "1003", "name": "哦哟",
"description": "惊讶 起哄 哇哦 有戏 不简单 哟",
"width": 128, "height": 128, "formats": "png",
},
"吃瓜": {
"sticker_id": "222", "package_id": "1003", "name": "吃瓜",
"description": "围观 看戏 八卦 路人 看热闹 板凳",
"width": 128, "height": 128, "formats": "png",
},
"狗头": {
"sticker_id": "225", "package_id": "1003", "name": "狗头",
"description": "doge 保命 开玩笑 滑稽 反讽 懂的都懂",
"width": 128, "height": 128, "formats": "png",
},
"敬礼": {
"sticker_id": "227", "package_id": "1003", "name": "敬礼",
"description": "salute 尊重 收到 遵命 致敬 报告",
"width": 128, "height": 128, "formats": "png",
},
"": {
"sticker_id": "231", "package_id": "1003", "name": "",
"description": "知道了 明白 敷衍 嗯 这样啊 收到",
"width": 128, "height": 128, "formats": "png",
},
"拿到红包": {
"sticker_id": "236", "package_id": "1003", "name": "拿到红包",
"description": "红包 谢谢老板 发财 开心 抢到了 欧气",
"width": 128, "height": 128, "formats": "png",
},
"牛吖": {
"sticker_id": "239", "package_id": "1003", "name": "牛吖",
"description": "牛 厉害 强 666 佩服 大佬",
"width": 128, "height": 128, "formats": "png",
},
"贴贴": {
"sticker_id": "272", "package_id": "1003", "name": "贴贴",
"description": "抱抱 亲昵 蹭蹭 亲密 靠靠 撒娇贴",
"width": 128, "height": 128, "formats": "png",
},
"爱心": {
"sticker_id": "138", "package_id": "1003", "name": "爱心",
"description": "心 love 喜欢你 红心 示爱 么么哒",
"width": 128, "height": 128, "formats": "png",
},
"晚安": {
"sticker_id": "170", "package_id": "1003", "name": "晚安",
"description": "好梦 睡了 night 早点休息 安啦 moon",
"width": 128, "height": 128, "formats": "png",
},
"太阳": {
"sticker_id": "176", "package_id": "1003", "name": "太阳",
"description": "晴天 早上好 阳光 morning 好天气 日",
"width": 128, "height": 128, "formats": "png",
},
"柠檬": {
"sticker_id": "266", "package_id": "1003", "name": "柠檬",
"description": "酸 嫉妒 柠檬精 羡慕 我酸 恰柠檬",
"width": 128, "height": 128, "formats": "png",
},
"大冤种": {
"sticker_id": "267", "package_id": "1003", "name": "大冤种",
"description": "倒霉 吃亏 自嘲 好心没好报 背锅 工具人",
"width": 128, "height": 128, "formats": "png",
},
"吐了": {
"sticker_id": "132", "package_id": "1003", "name": "吐了",
"description": "恶心 yue 受不了 嫌弃 想吐 生理不适",
"width": 128, "height": 128, "formats": "png",
},
"": {
"sticker_id": "134", "package_id": "1003", "name": "",
"description": "生气 愤怒 火大 暴躁 气炸 怼",
"width": 128, "height": 128, "formats": "png",
},
"玫瑰": {
"sticker_id": "165", "package_id": "1003", "name": "玫瑰",
"description": "花 示爱 表白 浪漫 送你花 情人节",
"width": 128, "height": 128, "formats": "png",
},
"凋谢": {
"sticker_id": "119", "package_id": "1003", "name": "凋谢",
"description": "花谢 失恋 难过 枯萎 心碎 凉了",
"width": 128, "height": 128, "formats": "png",
},
"点赞": {
"sticker_id": "159", "package_id": "1003", "name": "点赞",
"description": "赞 认同 好棒 good like 大拇指 顶",
"width": 128, "height": 128, "formats": "png",
},
"握手": {
"sticker_id": "164", "package_id": "1003", "name": "握手",
"description": "合作 你好 商务 hello deal 成交 友好",
"width": 128, "height": 128, "formats": "png",
},
"抱拳": {
"sticker_id": "163", "package_id": "1003", "name": "抱拳",
"description": "谢谢 失敬 江湖 承让 拜托 有礼",
"width": 128, "height": 128, "formats": "png",
},
"ok": {
"sticker_id": "169", "package_id": "1003", "name": "ok",
"description": "好的 收到 没问题 okay 行 可以 懂了",
"width": 128, "height": 128, "formats": "png",
},
"拳头": {
"sticker_id": "174", "package_id": "1003", "name": "拳头",
"description": "加油 干 冲 fight 力量 击拳 硬气",
"width": 128, "height": 128, "formats": "png",
},
"鞭炮": {
"sticker_id": "191", "package_id": "1003", "name": "鞭炮",
"description": "过年 喜庆 爆竹 春节 噼里啪啦 红",
"width": 128, "height": 128, "formats": "png",
},
"烟花": {
"sticker_id": "258", "package_id": "1003", "name": "烟花",
"description": "庆典 漂亮 新年 嘭 绽放 节日快乐",
"width": 128, "height": 128, "formats": "png",
},
}
def get_sticker_by_name(name: str) -> Optional[dict]:
"""
按名称查找贴纸支持模糊匹配
匹配优先级
1. 完全相等name
2. name 包含查询词前缀/子串
3. description 包含查询词同义词搜索
4. 通用模糊评分 sticker-search 同算法命中即返回得分最高的一条
返回 sticker dict找不到返回 None
"""
if not name:
return None
query = name.strip()
if query in STICKER_MAP:
return STICKER_MAP[query]
for key, sticker in STICKER_MAP.items():
if query in key or key in query:
return sticker
for sticker in STICKER_MAP.values():
desc = sticker.get("description", "")
if query in desc:
return sticker
matches = search_stickers(query, limit=1)
return matches[0] if matches else None
def get_random_sticker(category: str = None) -> dict:
"""
随机返回一个贴纸
若指定 category则在 description 中含有该关键词的贴纸里随机选取
category None 时从全表随机
"""
if category:
candidates = [
s for s in STICKER_MAP.values()
if category in s.get("description", "") or category in s.get("name", "")
]
if candidates:
return random.choice(candidates)
return random.choice(list(STICKER_MAP.values()))
def get_sticker_by_id(sticker_id: str) -> Optional[dict]:
"""按 sticker_id 精确查找贴纸。"""
if not sticker_id:
return None
sid = str(sticker_id).strip()
for sticker in STICKER_MAP.values():
if sticker.get("sticker_id") == sid:
return sticker
return None
# ---------------------------------------------------------------------------
# 模糊搜索(对齐 chatbot-web yuanbao-openclaw-plugin/sticker-cache.ts.searchStickers
# ---------------------------------------------------------------------------
_PUNCT_RE = re.compile(r"[\s\u3000\-_·.,,。!?\"“”'‘’、/\\]+")
def _normalize_text(raw: str) -> str:
return unicodedata.normalize("NFKC", str(raw or "")).strip().lower()
def _compact_text(raw: str) -> str:
return _PUNCT_RE.sub("", _normalize_text(raw))
def _multiset_char_hit_ratio(needle: str, haystack: str) -> float:
if not needle:
return 0.0
bag: dict[str, int] = {}
for ch in haystack:
bag[ch] = bag.get(ch, 0) + 1
hits = 0
for ch in needle:
n = bag.get(ch, 0)
if n > 0:
hits += 1
bag[ch] = n - 1
return hits / len(needle)
def _bigram_jaccard(a: str, b: str) -> float:
if len(a) < 2 or len(b) < 2:
return 0.0
A = {a[i:i + 2] for i in range(len(a) - 1)}
B = {b[i:i + 2] for i in range(len(b) - 1)}
inter = len(A & B)
union = len(A) + len(B) - inter
return inter / union if union else 0.0
def _longest_subsequence_ratio(needle: str, haystack: str) -> float:
if not needle:
return 0.0
j = 0
for ch in haystack:
if j >= len(needle):
break
if ch == needle[j]:
j += 1
return j / len(needle)
def _score_field(haystack: str, query: str) -> float:
hay = _normalize_text(haystack)
q = _normalize_text(query)
if not hay or not q:
return 0.0
hay_c = _compact_text(haystack)
q_c = _compact_text(query)
best = 0.0
if hay == q:
best = max(best, 100.0)
if q in hay:
best = max(best, 92 + min(6, len(q)))
if len(q) >= 2 and hay.startswith(q):
best = max(best, 88.0)
if q_c and q_c in hay_c:
best = max(best, 86.0)
best = max(best, _multiset_char_hit_ratio(q_c, hay_c) * 62)
best = max(best, _bigram_jaccard(q_c, hay_c) * 58)
best = max(best, _longest_subsequence_ratio(q_c, hay_c) * 52)
if len(q) == 1 and q in hay:
best = max(best, 68.0)
return best
def search_stickers(query: str, limit: int = 10) -> list[dict]:
"""
在内置贴纸表中按模糊匹配排序返回前 N 条结果
评分综合 name/description 字段的子串字符多重集覆盖bigram Jaccard子序列比例
name 权重略高于 description×0.88 query 时按字典顺序返回前 N
"""
safe_limit = max(1, min(500, int(limit) if limit else 10))
if not query or not _normalize_text(query):
return list(STICKER_MAP.values())[:safe_limit]
scored: list[tuple[float, dict]] = []
for sticker in STICKER_MAP.values():
name_s = _score_field(sticker.get("name", ""), query)
desc_s = _score_field(sticker.get("description", ""), query) * 0.88
sid = str(sticker.get("sticker_id", "")).strip()
q_norm = _normalize_text(query)
id_s = 0.0
if sid and q_norm:
sid_norm = _normalize_text(sid)
if sid_norm == q_norm:
id_s = 100.0
elif q_norm in sid_norm:
id_s = 84.0
scored.append((max(name_s, desc_s, id_s), sticker))
scored.sort(key=lambda x: x[0], reverse=True)
top = scored[0][0] if scored else 0
if top <= 0:
return [s for _, s in scored[:safe_limit]]
if top >= 22:
floor = 18.0
elif top >= 12:
floor = max(10.0, top * 0.5)
else:
floor = max(6.0, top * 0.35)
filtered = [pair for pair in scored if pair[0] >= floor]
out = filtered if filtered else scored
return [s for _, s in out[:safe_limit]]
def build_face_msg_body(
face_index: int,
face_type: int = 1,
data: Optional[str] = None,
) -> list:
"""
构造 TIMFaceElem 消息体
Yuanbao 约定
- index 固定传 0服务端通过 data 字段识别具体表情
- data JSON 字符串包含 sticker_id / package_id 等字段
Args:
face_index: 保留字段暂时不影响 wire formatYuanbao 固定 index=0
face_index > 0 时视为旧版 QQ 表情 ID直接放入 index
face_type: 保留字段兼容旧接口当前未使用
data: 已序列化的 JSON 字符串 None 时仅传 index
Returns:
符合 Yuanbao TIM 协议的 msg_body list::
[{"msg_type": "TIMFaceElem", "msg_content": {"index": 0, "data": "..."}}]
"""
msg_content: dict = {"index": face_index}
if data is not None:
msg_content["data"] = data
return [{"msg_type": "TIMFaceElem", "msg_content": msg_content}]
def build_sticker_msg_body(sticker: dict) -> list:
"""
STICKER_MAP 中的 sticker dict 直接构造 TIMFaceElem 消息体
这是 send_sticker() 的内部辅助确保 data 字段与原始 JS 插件一致
"""
data_payload = json.dumps(
{
"sticker_id": sticker["sticker_id"],
"package_id": sticker["package_id"],
"width": sticker.get("width", 128),
"height": sticker.get("height", 128),
"formats": sticker.get("formats", "png"),
"name": sticker["name"],
},
ensure_ascii=False,
separators=(",", ":"),
)
return build_face_msg_body(face_index=0, data=data_payload)
+503 -739
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File diff suppressed because it is too large Load Diff
+18 -110
View File
@@ -60,10 +60,6 @@ from .config import (
SessionResetPolicy, # noqa: F401 — re-exported via gateway/__init__.py
HomeChannel,
)
from .whatsapp_identity import (
canonical_whatsapp_identifier,
normalize_whatsapp_identifier,
)
@dataclass
@@ -87,9 +83,6 @@ class SessionSource:
user_id_alt: Optional[str] = None # Platform-specific stable alt ID (Signal UUID, Feishu union_id)
chat_id_alt: Optional[str] = None # Signal group internal ID
is_bot: bool = False # True when the message author is a bot/webhook (Discord)
guild_id: Optional[str] = None # Discord guild / Slack workspace / Matrix server scope
parent_chat_id: Optional[str] = None # Parent channel when chat_id refers to a thread
message_id: Optional[str] = None # ID of the triggering message (for pin/reply/react)
@property
def description(self) -> str:
@@ -127,14 +120,8 @@ class SessionSource:
d["user_id_alt"] = self.user_id_alt
if self.chat_id_alt:
d["chat_id_alt"] = self.chat_id_alt
if self.guild_id:
d["guild_id"] = self.guild_id
if self.parent_chat_id:
d["parent_chat_id"] = self.parent_chat_id
if self.message_id:
d["message_id"] = self.message_id
return d
@classmethod
def from_dict(cls, data: Dict[str, Any]) -> "SessionSource":
return cls(
@@ -148,9 +135,6 @@ class SessionSource:
chat_topic=data.get("chat_topic"),
user_id_alt=data.get("user_id_alt"),
chat_id_alt=data.get("chat_id_alt"),
guild_id=data.get("guild_id"),
parent_chat_id=data.get("parent_chat_id"),
message_id=data.get("message_id"),
)
@@ -202,31 +186,6 @@ that requires raw IDs). Discord is excluded because mentions use ``<@user_id>``
and the LLM needs the real ID to tag users."""
def _discord_tools_loaded() -> bool:
"""True iff the agent will actually have Discord tools this session.
Two conditions must hold:
1. The `discord` or `discord_admin` toolset is enabled for the
Discord platform via `hermes tools` (opt-in, default OFF).
2. `DISCORD_BOT_TOKEN` is set the tool's `check_fn` gates on it
at registry time, so the toolset being enabled in config is not
enough if the token isn't configured.
Returns False (safe default keeps the stale-API disclaimer) on any
error so a bad config can't silently promise tools the agent lacks.
"""
if not (os.environ.get("DISCORD_BOT_TOKEN") or "").strip():
return False
try:
from hermes_cli.config import load_config
from hermes_cli.tools_config import _get_platform_tools
cfg = load_config()
enabled = _get_platform_tools(cfg, "discord", include_default_mcp_servers=False)
return "discord" in enabled or "discord_admin" in enabled
except Exception:
return False
def build_session_context_prompt(
context: SessionContext,
*,
@@ -310,57 +269,17 @@ def build_session_context_prompt(
"**Platform notes:** You are running inside Slack. "
"You do NOT have access to Slack-specific APIs — you cannot search "
"channel history, pin/unpin messages, manage channels, or list users. "
"Do not promise to perform these actions. The gateway may inline the "
"current message's Slack block/attachment payload when available, but "
"you still cannot call Slack APIs yourself."
"Do not promise to perform these actions. If the user asks, explain "
"that you can only read messages sent directly to you and respond."
)
elif context.source.platform == Platform.DISCORD:
# Inject the Discord IDs block only when the agent actually has
# Discord tools loaded this session — i.e. the user opted into
# `discord` / `discord_admin` via `hermes tools` AND the bot
# token is configured. Otherwise keep the stale-API disclaimer
# honest so we never promise tools the agent lacks.
if _discord_tools_loaded():
src = context.source
id_lines = ["", "**Discord IDs (for the `discord` / `discord_admin` tools):**"]
if src.guild_id:
id_lines.append(f" - Guild: `{src.guild_id}`")
if src.thread_id and src.parent_chat_id:
id_lines.append(f" - Parent channel: `{src.parent_chat_id}`")
id_lines.append(f" - Thread: `{src.thread_id}` (use as `channel_id` for fetch_messages etc.)")
else:
id_lines.append(f" - Channel: `{src.chat_id}`")
if src.message_id:
id_lines.append(f" - Triggering message: `{src.message_id}`")
lines.extend(id_lines)
else:
lines.append("")
lines.append(
"**Platform notes:** You are running inside Discord. "
"You do NOT have access to Discord-specific APIs — you cannot search "
"channel history, pin messages, manage roles, or list server members. "
"Do not promise to perform these actions. If the user asks, explain "
"that you can only read messages sent directly to you and respond."
)
elif context.source.platform == Platform.BLUEBUBBLES:
lines.append("")
lines.append(
"**Platform notes:** You are responding via iMessage. "
"Keep responses short and conversational — think texts, not essays. "
"Structure longer replies as separate short thoughts, each separated "
"by a blank line (double newline). Each block between blank lines "
"will be delivered as its own iMessage bubble, so write accordingly: "
"one idea per bubble, 13 sentences each. "
"If the user needs a detailed answer, give the short version first "
"and offer to elaborate."
)
elif context.source.platform == Platform.YUANBAO:
lines.append("")
lines.append(
"**Platform notes:** You are running inside Yuanbao. "
"You CAN send private (DM) messages via the send_message tool. "
"Use target='yuanbao:direct:<account_id>' for DM "
"and target='yuanbao:group:<group_code>' for group chat."
"**Platform notes:** You are running inside Discord. "
"You do NOT have access to Discord-specific APIs — you cannot search "
"channel history, pin messages, manage roles, or list server members. "
"Do not promise to perform these actions. If the user asks, explain "
"that you can only read messages sent directly to you and respond."
)
# Connected platforms
@@ -448,11 +367,11 @@ class SessionEntry:
auto_reset_reason: Optional[str] = None # "idle" or "daily"
reset_had_activity: bool = False # whether the expired session had any messages
# Set by the background expiry watcher after it finalizes an expired
# session (invoking on_session_finalize hooks and evicting the cached
# agent). Persisted to sessions.json so the flag survives gateway
# restarts — prevents redundant finalization runs.
expiry_finalized: bool = False
# Set by the background expiry watcher after it successfully flushes
# memories for this session. Persisted to sessions.json so the flag
# survives gateway restarts (the old in-memory _pre_flushed_sessions
# set was lost on restart, causing redundant re-flushes).
memory_flushed: bool = False
# When True the next call to get_or_create_session() will auto-reset
# this session (create a new session_id) so the user starts fresh.
@@ -488,7 +407,7 @@ class SessionEntry:
"last_prompt_tokens": self.last_prompt_tokens,
"estimated_cost_usd": self.estimated_cost_usd,
"cost_status": self.cost_status,
"expiry_finalized": self.expiry_finalized,
"memory_flushed": self.memory_flushed,
"suspended": self.suspended,
"resume_pending": self.resume_pending,
"resume_reason": self.resume_reason,
@@ -540,7 +459,7 @@ class SessionEntry:
last_prompt_tokens=data.get("last_prompt_tokens", 0),
estimated_cost_usd=data.get("estimated_cost_usd", 0.0),
cost_status=data.get("cost_status", "unknown"),
expiry_finalized=data.get("expiry_finalized", data.get("memory_flushed", False)),
memory_flushed=data.get("memory_flushed", False),
suspended=data.get("suspended", False),
resume_pending=data.get("resume_pending", False),
resume_reason=data.get("resume_reason"),
@@ -599,24 +518,15 @@ def build_session_key(
"""
platform = source.platform.value
if source.chat_type == "dm":
dm_chat_id = source.chat_id
if source.platform == Platform.WHATSAPP:
dm_chat_id = canonical_whatsapp_identifier(source.chat_id)
if dm_chat_id:
if source.chat_id:
if source.thread_id:
return f"agent:main:{platform}:dm:{dm_chat_id}:{source.thread_id}"
return f"agent:main:{platform}:dm:{dm_chat_id}"
return f"agent:main:{platform}:dm:{source.chat_id}:{source.thread_id}"
return f"agent:main:{platform}:dm:{source.chat_id}"
if source.thread_id:
return f"agent:main:{platform}:dm:{source.thread_id}"
return f"agent:main:{platform}:dm"
participant_id = source.user_id_alt or source.user_id
if participant_id and source.platform == Platform.WHATSAPP:
# Same JID/LID-flip bug as the DM case: without canonicalisation, a
# single group member gets two isolated per-user sessions when the
# bridge reshuffles alias forms.
participant_id = canonical_whatsapp_identifier(str(participant_id)) or participant_id
key_parts = ["agent:main", platform, source.chat_type]
if source.chat_id:
@@ -1241,7 +1151,6 @@ class SessionStore:
reasoning_content=message.get("reasoning_content") if message.get("role") == "assistant" else None,
reasoning_details=message.get("reasoning_details") if message.get("role") == "assistant" else None,
codex_reasoning_items=message.get("codex_reasoning_items") if message.get("role") == "assistant" else None,
codex_message_items=message.get("codex_message_items") if message.get("role") == "assistant" else None,
)
except Exception as e:
logger.debug("Session DB operation failed: %s", e)
@@ -1274,7 +1183,6 @@ class SessionStore:
reasoning_content=msg.get("reasoning_content") if role == "assistant" else None,
reasoning_details=msg.get("reasoning_details") if role == "assistant" else None,
codex_reasoning_items=msg.get("codex_reasoning_items") if role == "assistant" else None,
codex_message_items=msg.get("codex_message_items") if role == "assistant" else None,
)
except Exception as e:
logger.debug("Failed to rewrite transcript in DB: %s", e)
-110
View File
@@ -44,14 +44,6 @@ class StreamConsumerConfig:
buffer_threshold: int = 40
cursor: str = ""
buffer_only: bool = False
# When >0, the final edit for a streamed response is delivered as a
# fresh message if the original preview has been visible for at least
# this many seconds. This makes the platform's visible timestamp
# reflect completion time instead of first-token time for long-running
# responses (e.g. reasoning models that stream slowly). Ported from
# openclaw/openclaw#72038. Default 0 = always edit in place (legacy
# behavior). The gateway enables this selectively per-platform.
fresh_final_after_seconds: float = 0.0
class GatewayStreamConsumer:
@@ -99,12 +91,6 @@ class GatewayStreamConsumer:
self._queue: queue.Queue = queue.Queue()
self._accumulated = ""
self._message_id: Optional[str] = None
# Wall-clock timestamp (time.monotonic) when ``_message_id`` was
# first assigned from a successful first-send. Used by the
# fresh-final logic to detect long-lived previews whose edit
# timestamps would be stale by completion time. Ported from
# openclaw/openclaw#72038.
self._message_created_ts: Optional[float] = None
self._already_sent = False
self._edit_supported = True # Disabled when progressive edits are no longer usable
self._last_edit_time = 0.0
@@ -150,7 +136,6 @@ class GatewayStreamConsumer:
if preserve_no_edit and self._message_id == "__no_edit__":
return
self._message_id = None
self._message_created_ts = None
self._accumulated = ""
self._last_sent_text = ""
self._fallback_final_send = False
@@ -749,81 +734,6 @@ class GatewayStreamConsumer:
logger.error("Commentary send error: %s", e)
return False
def _should_send_fresh_final(self) -> bool:
"""Return True when a long-lived preview should be replaced with a
fresh final message instead of an edit.
Conditions:
- Fresh-final is enabled (``fresh_final_after_seconds > 0``).
- We have a real preview message id (not the ``__no_edit__`` sentinel
and not ``None``).
- The preview has been visible for at least the configured threshold.
Ported from openclaw/openclaw#72038.
"""
threshold = getattr(self.cfg, "fresh_final_after_seconds", 0.0) or 0.0
if threshold <= 0:
return False
if not self._message_id or self._message_id == "__no_edit__":
return False
if self._message_created_ts is None:
return False
age = time.monotonic() - self._message_created_ts
return age >= threshold
async def _try_fresh_final(self, text: str) -> bool:
"""Send ``text`` as a brand-new message (best-effort delete the old
preview) so the platform's visible timestamp reflects completion
time. Returns True on successful delivery, False on any failure so
the caller falls back to the normal edit path.
Ported from openclaw/openclaw#72038.
"""
old_message_id = self._message_id
try:
result = await self.adapter.send(
chat_id=self.chat_id,
content=text,
metadata=self.metadata,
)
except Exception as e:
logger.debug("Fresh-final send failed, falling back to edit: %s", e)
return False
if not getattr(result, "success", False):
return False
# Successful fresh send — try to delete the stale preview so the
# user doesn't see the old edit-stuck message underneath. Cleanup
# is best-effort; platforms that don't implement ``delete_message``
# just leave the preview behind (still an acceptable outcome —
# the visible final timestamp is the important part).
if old_message_id and old_message_id != "__no_edit__":
delete_fn = getattr(self.adapter, "delete_message", None)
if delete_fn is not None:
try:
await delete_fn(self.chat_id, old_message_id)
except Exception as e:
logger.debug(
"Fresh-final preview cleanup failed (%s): %s",
old_message_id, e,
)
# Adopt the new message id as the current message so subsequent
# callers (e.g. overflow split loops, finalize retries) see a
# consistent state.
new_message_id = getattr(result, "message_id", None)
if new_message_id:
self._message_id = new_message_id
self._message_created_ts = time.monotonic()
else:
# Send succeeded but platform didn't return an id — treat the
# delivery as final-only and fall back to "__no_edit__" so we
# don't try to edit something we can't address.
self._message_id = "__no_edit__"
self._message_created_ts = None
self._already_sent = True
self._last_sent_text = text
self._final_response_sent = True
return True
async def _send_or_edit(self, text: str, *, finalize: bool = False) -> bool:
"""Send or edit the streaming message.
@@ -876,22 +786,6 @@ class GatewayStreamConsumer:
finalize and self._adapter_requires_finalize
):
return True
# Fresh-final for long-lived previews: when finalizing
# the last edit in a streaming sequence, if the
# original preview has been visible for at least
# ``fresh_final_after_seconds``, send the completed
# reply as a fresh message so the platform's visible
# timestamp reflects completion time instead of the
# preview creation time. Best-effort cleanup of the
# old preview follows. Ported from
# openclaw/openclaw#72038. Gated by config so the
# legacy edit-in-place path stays the default.
if (
finalize
and self._should_send_fresh_final()
and await self._try_fresh_final(text)
):
return True
# Edit existing message
result = await self.adapter.edit_message(
chat_id=self.chat_id,
@@ -958,10 +852,6 @@ class GatewayStreamConsumer:
if result.success:
if result.message_id:
self._message_id = result.message_id
# Track when the preview first became visible to
# the user so fresh-final logic can detect stale
# preview timestamps on long-running responses.
self._message_created_ts = time.monotonic()
else:
self._edit_supported = False
self._already_sent = True
-155
View File
@@ -1,155 +0,0 @@
"""Shared helpers for canonicalising WhatsApp sender identity.
WhatsApp's bridge can surface the same human under two different JID shapes
within a single conversation:
- LID form: ``999999999999999@lid``
- Phone form: ``15551234567@s.whatsapp.net``
Both the authorisation path (:mod:`gateway.run`) and the session-key path
(:mod:`gateway.session`) need to collapse these aliases to a single stable
identity. This module is the single source of truth for that resolution so
the two paths can never drift apart.
Public helpers:
- :func:`normalize_whatsapp_identifier` strip JID/LID/device/plus syntax
down to the bare numeric identifier.
- :func:`canonical_whatsapp_identifier` walk the bridge's
``lid-mapping-*.json`` files and return a stable canonical identity
across phone/LID variants.
- :func:`expand_whatsapp_aliases` return the full alias set for an
identifier. Used by authorisation code that needs to match any known
form of a sender against an allow-list.
Plugins that need per-sender behaviour on WhatsApp (role-based routing,
per-contact authorisation, policy gating in a gateway hook) should use
``canonical_whatsapp_identifier`` so their bookkeeping lines up with
Hermes' own session keys.
"""
from __future__ import annotations
import json
import logging
import re
from typing import Set
logger = logging.getLogger(__name__)
# WhatsApp JIDs are numeric (or plus-prefixed numeric) with optional
# ``@``, ``.`` and ``:`` separators. ``\w`` is pinned to ASCII so
# full-width digits / Unicode word chars can't sneak through.
_SAFE_IDENTIFIER_RE = re.compile(r"^[A-Za-z0-9@.+\-]+$")
from hermes_constants import get_hermes_home
def normalize_whatsapp_identifier(value: str) -> str:
"""Strip WhatsApp JID/LID syntax down to its stable numeric identifier.
Accepts any of the identifier shapes the WhatsApp bridge may emit:
``"60123456789@s.whatsapp.net"``, ``"60123456789:47@s.whatsapp.net"``,
``"60123456789@lid"``, or a bare ``"+601****6789"`` / ``"60123456789"``.
Returns just the numeric identifier (``"60123456789"``) suitable for
equality comparisons.
Useful for plugins that want to match sender IDs against
user-supplied config (phone numbers in ``config.yaml``) without
worrying about which variant the bridge happens to deliver.
"""
return (
str(value or "")
.strip()
.replace("+", "", 1)
.split(":", 1)[0]
.split("@", 1)[0]
)
def expand_whatsapp_aliases(identifier: str) -> Set[str]:
"""Resolve WhatsApp phone/LID aliases via bridge session mapping files.
Returns the set of all identifiers transitively reachable through the
bridge's ``$HERMES_HOME/whatsapp/session/lid-mapping-*.json`` files,
starting from ``identifier``. The result always includes the
normalized input itself, so callers can safely ``in`` check against
the return value without a separate fallback branch.
Returns an empty set if ``identifier`` normalizes to empty.
"""
normalized = normalize_whatsapp_identifier(identifier)
if not normalized:
return set()
session_dir = get_hermes_home() / "whatsapp" / "session"
resolved: Set[str] = set()
queue = [normalized]
while queue:
current = queue.pop(0)
if not current or current in resolved:
continue
# Defense-in-depth: reject identifiers that could sneak path
# separators / traversal segments into the ``lid-mapping-{current}``
# filename below. The hardcoded ``lid-mapping-`` prefix already
# prevents escape via pathlib's component split (an attacker can't
# create ``lid-mapping-..`` as a real directory in session_dir), but
# this keeps the identifier space to the characters WhatsApp JIDs
# actually use and avoids depending on that filesystem-layout
# invariant.
if not _SAFE_IDENTIFIER_RE.match(current):
continue
resolved.add(current)
for suffix in ("", "_reverse"):
mapping_path = session_dir / f"lid-mapping-{current}{suffix}.json"
if not mapping_path.exists():
continue
try:
mapped = normalize_whatsapp_identifier(
json.loads(mapping_path.read_text(encoding="utf-8"))
)
except (OSError, json.JSONDecodeError) as exc:
logger.debug("whatsapp_identity: failed to read %s: %s", mapping_path, exc)
continue
if mapped and mapped not in resolved:
queue.append(mapped)
return resolved
def canonical_whatsapp_identifier(identifier: str) -> str:
"""Return a stable WhatsApp sender identity across phone-JID/LID variants.
WhatsApp may surface the same person under either a phone-format JID
(``60123456789@s.whatsapp.net``) or a LID (``1234567890@lid``). This
applies to a DM ``chat_id`` *and* to the ``participant_id`` of a
member inside a group chat both represent a user identity, and the
bridge may flip between the two for the same human.
This helper reads the bridge's ``whatsapp/session/lid-mapping-*.json``
files, walks the mapping transitively, and picks the shortest
(numeric-preferred) alias as the canonical identity.
:func:`gateway.session.build_session_key` uses this for both WhatsApp
DM chat_ids and WhatsApp group participant_ids, so callers get the
same session-key identity Hermes itself uses.
Plugins that need per-sender behaviour (role-based routing,
authorisation, per-contact policy) should use this so their
bookkeeping lines up with Hermes' session bookkeeping even when
the bridge reshuffles aliases.
Returns an empty string if ``identifier`` normalizes to empty. If no
mapping files exist yet (fresh bridge install), returns the
normalized input unchanged.
"""
normalized = normalize_whatsapp_identifier(identifier)
if not normalized:
return ""
# expand_whatsapp_aliases always includes `normalized` itself in the
# returned set, so the min() below degrades gracefully to `normalized`
# when no lid-mapping files are present.
aliases = expand_whatsapp_aliases(normalized)
return min(aliases, key=lambda candidate: (len(candidate), candidate))
+4 -39
View File
@@ -356,14 +356,6 @@ PROVIDER_REGISTRY: Dict[str, ProviderConfig] = {
api_key_env_vars=(),
base_url_env_var="BEDROCK_BASE_URL",
),
"azure-foundry": ProviderConfig(
id="azure-foundry",
name="Azure Foundry",
auth_type="api_key",
inference_base_url="", # User-provided endpoint
api_key_env_vars=("AZURE_FOUNDRY_API_KEY",),
base_url_env_var="AZURE_FOUNDRY_BASE_URL",
),
}
@@ -467,27 +459,11 @@ def _resolve_api_key_provider_secret(
pass
return "", ""
from hermes_cli.config import get_env_value
for env_var in pconfig.api_key_env_vars:
# Check both os.environ and ~/.hermes/.env file
val = (get_env_value(env_var) or "").strip()
val = os.getenv(env_var, "").strip()
if has_usable_secret(val):
return val, env_var
# Fallback: try credential pool (e.g. zai key stored via auth.json)
try:
from agent.credential_pool import load_pool
pool = load_pool(provider_id)
if pool and pool.has_credentials():
entry = pool.peek()
if entry:
key = getattr(entry, "access_token", "") or getattr(entry, "runtime_api_key", "")
key = str(key).strip()
if has_usable_secret(key):
return key, f"credential_pool:{provider_id}"
except Exception:
pass
return "", ""
@@ -767,18 +743,7 @@ def _load_auth_store(auth_file: Optional[Path] = None) -> Dict[str, Any]:
try:
raw = json.loads(auth_file.read_text())
except Exception as exc:
corrupt_path = auth_file.with_suffix(".json.corrupt")
try:
import shutil
shutil.copy2(auth_file, corrupt_path)
except Exception:
pass
logger.warning(
"auth: failed to parse %s (%s) — starting with empty store. "
"Corrupt file preserved at %s",
auth_file, exc, corrupt_path,
)
except Exception:
return {"version": AUTH_STORE_VERSION, "providers": {}}
if isinstance(raw, dict) and (
@@ -4260,10 +4225,10 @@ def _login_nous(args, pconfig: ProviderConfig) -> None:
)
from hermes_cli.models import (
get_curated_nous_model_ids, get_pricing_for_provider,
_PROVIDER_MODELS, get_pricing_for_provider,
check_nous_free_tier, partition_nous_models_by_tier,
)
model_ids = get_curated_nous_model_ids()
model_ids = _PROVIDER_MODELS.get("nous", [])
print()
unavailable_models: list = []
-300
View File
@@ -1,300 +0,0 @@
"""Azure Foundry endpoint auto-detection.
Inspect an Azure AI Foundry / Azure OpenAI endpoint to determine:
- API transport (OpenAI-style ``chat_completions`` vs
Anthropic-style ``anthropic_messages``)
- Available models (best effort Azure does not expose a deployment
listing via the inference API key, but Azure OpenAI v1 endpoints
return the resource's model catalog via ``GET /models``)
- Context length for each discovered/entered model, via the existing
:func:`agent.model_metadata.get_model_context_length` resolver.
Rationale:
Azure has no pure-API-key deployment-listing endpoint per Microsoft,
deployment enumeration requires ARM management-plane auth. Azure
OpenAI v1 endpoints ``{resource}.openai.azure.com/openai/v1`` do return
a ``/models`` list, but it reflects the resource's *available* models
rather than the user's *deployed* deployment names. In practice it is
still a useful hint the user picks a familiar model name and we look
up its context length from the catalog.
The detector never crashes on errors (every HTTP call is wrapped in a
broad try/except). Callers get a :class:`DetectionResult` with whatever
information could be gathered, and fall back to manual entry for the
rest.
"""
from __future__ import annotations
import json
import logging
import re
from dataclasses import dataclass, field
from typing import Optional
from urllib import request as urllib_request
from urllib.error import HTTPError, URLError
from urllib.parse import urlparse, urlunparse
logger = logging.getLogger(__name__)
# Default Azure OpenAI ``api-version`` to probe with. The v1 GA endpoint
# accepts requests without ``api-version`` entirely, so this is only used
# as a fallback for pre-v1 resources that still require it.
_AZURE_OPENAI_PROBE_API_VERSIONS = (
"2025-04-01-preview",
"2024-10-21", # oldest GA that supports /models
)
# Default Azure Anthropic ``api-version``. Matches the value used by
# ``agent/anthropic_adapter.py`` when building the Anthropic client.
_AZURE_ANTHROPIC_API_VERSION = "2025-04-15"
@dataclass
class DetectionResult:
"""Everything auto-detection could gather from a base URL + API key."""
#: Detected API transport: ``"chat_completions"``,
#: ``"anthropic_messages"``, or ``None`` when detection failed.
api_mode: Optional[str] = None
#: Deployment / model IDs returned by ``/models`` (best effort).
#: Empty when the endpoint doesn't expose the list with an API key.
models: list[str] = field(default_factory=list)
#: Lowercased host from the base URL (used for display messages).
hostname: str = ""
#: Human-readable reason the detector chose ``api_mode``. Useful
#: for explaining auto-detection to the user in the wizard.
reason: str = ""
#: ``True`` when ``/models`` returned a valid OpenAI-shaped payload.
models_probe_ok: bool = False
#: ``True`` when the URL was determined to be an Anthropic-style
#: endpoint (from path suffix or live probe).
is_anthropic: bool = False
def _http_get_json(url: str, api_key: str, timeout: float = 6.0) -> tuple[int, Optional[dict]]:
"""GET a URL with ``api-key`` + ``Authorization`` headers. Return
``(status_code, parsed_json_or_None)``. Never raises."""
req = urllib_request.Request(url, method="GET")
# Azure OpenAI uses ``api-key``. Some Azure deployments (and
# Anthropic-style routes) use ``Authorization: Bearer``. Send both
# so we probe once per URL rather than twice.
req.add_header("api-key", api_key)
req.add_header("Authorization", f"Bearer {api_key}")
req.add_header("User-Agent", "hermes-agent/azure-detect")
try:
with urllib_request.urlopen(req, timeout=timeout) as resp:
body = resp.read()
try:
return resp.status, json.loads(body.decode("utf-8", errors="replace"))
except Exception:
return resp.status, None
except HTTPError as exc:
return exc.code, None
except (URLError, TimeoutError, OSError) as exc:
logger.debug("azure_detect: GET %s failed: %s", url, exc)
return 0, None
except Exception as exc: # pragma: no cover — defensive
logger.debug("azure_detect: GET %s unexpected error: %s", url, exc)
return 0, None
def _strip_trailing_v1(url: str) -> str:
"""Strip trailing ``/v1`` or ``/v1/`` so we can construct sub-paths."""
return re.sub(r"/v1/?$", "", url.rstrip("/"))
def _looks_like_anthropic_path(url: str) -> bool:
"""Return True when the URL's path ends in ``/anthropic`` or
contains a ``/anthropic/`` segment. Used by Azure Foundry
resources that route Claude traffic through a dedicated path."""
try:
parsed = urlparse(url)
path = (parsed.path or "").lower().rstrip("/")
return path.endswith("/anthropic") or "/anthropic/" in path + "/"
except Exception:
return False
def _extract_model_ids(payload: dict) -> list[str]:
"""Extract a list of model IDs from an OpenAI-shaped ``/models``
response. Returns ``[]`` on any shape mismatch."""
data = payload.get("data") if isinstance(payload, dict) else None
if not isinstance(data, list):
return []
ids: list[str] = []
for item in data:
if not isinstance(item, dict):
continue
# OpenAI shape: {"id": "gpt-5.4", "object": "model", ...}
mid = item.get("id") or item.get("model") or item.get("name")
if isinstance(mid, str) and mid:
ids.append(mid)
return ids
def _probe_openai_models(base_url: str, api_key: str) -> tuple[bool, list[str]]:
"""Probe ``<base>/models`` for an OpenAI-shaped response.
Returns ``(ok, models)``. ``ok`` is True iff the endpoint accepted
us as an OpenAI-style caller (200 OK + OpenAI-shaped JSON body).
"""
base_url = base_url.rstrip("/")
# Azure OpenAI v1: {resource}.openai.azure.com/openai/v1 — no
# api-version required for GA paths, so probe without first.
candidates = [f"{base_url}/models"]
# Fallback: explicit api-version for pre-v1 resources
for v in _AZURE_OPENAI_PROBE_API_VERSIONS:
candidates.append(f"{base_url}/models?api-version={v}")
for url in candidates:
status, body = _http_get_json(url, api_key)
if status == 200 and body is not None:
ids = _extract_model_ids(body)
if ids:
logger.info(
"azure_detect: /models probe OK at %s (%d models)",
url, len(ids),
)
return True, ids
# 200 + empty list still counts as "OpenAI shape, no models
# listed" — let the user proceed with manual entry.
if isinstance(body, dict) and "data" in body:
return True, []
return False, []
def _probe_anthropic_messages(base_url: str, api_key: str) -> bool:
"""Send a zero-token request to ``<base>/v1/messages`` and check
whether the endpoint at least *recognises* the Anthropic Messages
shape (any 4xx that mentions ``messages`` or ``model``, or a 400
``invalid_request`` with an Anthropic error shape). Never completes
a real chat.
"""
base = _strip_trailing_v1(base_url)
url = f"{base}/v1/messages?api-version={_AZURE_ANTHROPIC_API_VERSION}"
payload = json.dumps({
"model": "probe",
"max_tokens": 1,
"messages": [{"role": "user", "content": "ping"}],
}).encode("utf-8")
req = urllib_request.Request(url, method="POST", data=payload)
req.add_header("api-key", api_key)
req.add_header("Authorization", f"Bearer {api_key}")
req.add_header("anthropic-version", "2023-06-01")
req.add_header("content-type", "application/json")
req.add_header("User-Agent", "hermes-agent/azure-detect")
try:
with urllib_request.urlopen(req, timeout=6.0) as resp:
# Should never 200 — "probe" isn't a real deployment. But
# if it does, the endpoint definitely speaks Anthropic.
return resp.status < 500
except HTTPError as exc:
# 4xx with an Anthropic-shaped error body = Anthropic endpoint.
try:
body = exc.read().decode("utf-8", errors="replace")
lowered = body.lower()
if "anthropic" in lowered or '"type"' in lowered and '"error"' in lowered:
return True
# Pre-Azure-v1 Azure Foundry returns a plain 404 for
# Anthropic-style calls on non-Anthropic deployments. A
# 400 "model not found" IS Anthropic though.
if exc.code == 400 and ("messages" in lowered or "model" in lowered):
return True
return False
except Exception:
return False
except (URLError, TimeoutError, OSError):
return False
except Exception: # pragma: no cover
return False
def detect(base_url: str, api_key: str) -> DetectionResult:
"""Inspect an Azure endpoint and describe its transport + models.
Call this from the wizard before asking the user to pick an API
mode manually. The caller should treat the returned
:class:`DetectionResult` as *advisory* if ``api_mode`` is None,
fall back to asking the user.
"""
result = DetectionResult()
try:
parsed = urlparse(base_url)
result.hostname = (parsed.hostname or "").lower()
except Exception:
result.hostname = ""
# 1. Path sniff. Azure Foundry exposes Anthropic-style deployments
# under a dedicated ``/anthropic`` path.
if _looks_like_anthropic_path(base_url):
result.is_anthropic = True
result.api_mode = "anthropic_messages"
result.reason = "URL path ends in /anthropic → Anthropic Messages API"
return result
# 2. Try the OpenAI-style /models probe. If this works, the
# endpoint definitely speaks OpenAI wire.
ok, models = _probe_openai_models(base_url, api_key)
if ok:
result.models_probe_ok = True
result.models = models
result.api_mode = "chat_completions"
result.reason = (
f"GET /models returned {len(models)} model(s) — OpenAI-style endpoint"
if models
else "GET /models returned an OpenAI-shaped empty list — OpenAI-style endpoint"
)
return result
# 3. Fallback: probe the Anthropic Messages shape. Slower and more
# intrusive than /models, so only run it when the OpenAI probe
# failed.
if _probe_anthropic_messages(base_url, api_key):
result.is_anthropic = True
result.api_mode = "anthropic_messages"
result.reason = "Endpoint accepts Anthropic Messages shape"
return result
# Nothing matched. Caller falls back to manual selection.
result.reason = (
"Could not probe endpoint (private network, missing model list, or "
"non-standard path) — falling back to manual API-mode selection"
)
return result
def lookup_context_length(model: str, base_url: str, api_key: str) -> Optional[int]:
"""Thin wrapper around :func:`agent.model_metadata.get_model_context_length`
that returns ``None`` when only the fallback default (128k) would
fire, so the wizard can distinguish "we actually know this" from
"we guessed."""
try:
from agent.model_metadata import (
DEFAULT_FALLBACK_CONTEXT,
get_model_context_length,
)
except Exception:
return None
try:
n = get_model_context_length(model, base_url=base_url, api_key=api_key)
except Exception as exc:
logger.debug("azure_detect: context length lookup failed: %s", exc)
return None
if isinstance(n, int) and n > 0 and n != DEFAULT_FALLBACK_CONTEXT:
return n
return None
__all__ = ["DetectionResult", "detect", "lookup_context_length"]
+4 -114
View File
@@ -84,7 +84,9 @@ COMMAND_REGISTRY: list[CommandDef] = [
CommandDef("deny", "Deny a pending dangerous command", "Session",
gateway_only=True),
CommandDef("background", "Run a prompt in the background", "Session",
aliases=("bg", "btw"), args_hint="<prompt>"),
aliases=("bg",), args_hint="<prompt>"),
CommandDef("btw", "Ephemeral side question using session context (no tools, not persisted)", "Session",
args_hint="<question>"),
CommandDef("agents", "Show active agents and running tasks", "Session",
aliases=("tasks",)),
CommandDef("queue", "Queue a prompt for the next turn (doesn't interrupt)", "Session",
@@ -101,8 +103,7 @@ COMMAND_REGISTRY: list[CommandDef] = [
# Configuration
CommandDef("config", "Show current configuration", "Configuration",
cli_only=True),
CommandDef("model", "Switch model for this session", "Configuration",
aliases=("provider",), args_hint="[model] [--provider name] [--global]"),
CommandDef("model", "Switch model for this session", "Configuration", args_hint="[model] [--provider name] [--global]"),
CommandDef("gquota", "Show Google Gemini Code Assist quota usage", "Info",
cli_only=True),
@@ -125,9 +126,6 @@ COMMAND_REGISTRY: list[CommandDef] = [
cli_only=True, args_hint="[name]"),
CommandDef("voice", "Toggle voice mode", "Configuration",
args_hint="[on|off|tts|status]", subcommands=("on", "off", "tts", "status")),
CommandDef("busy", "Control what Enter does while Hermes is working", "Configuration",
cli_only=True, args_hint="[queue|steer|interrupt|status]",
subcommands=("queue", "steer", "interrupt", "status")),
# Tools & Skills
CommandDef("tools", "Manage tools: /tools [list|disable|enable] [name...]", "Tools & Skills",
@@ -806,114 +804,6 @@ def discord_skill_commands_by_category(
return trimmed_categories, uncategorized, hidden
# ---------------------------------------------------------------------------
# Slack native slash commands
# ---------------------------------------------------------------------------
# Slack slash command name constraints: lowercase a-z, 0-9, hyphens,
# underscores. Max 32 chars. Slack app manifest accepts up to 50 slash
# commands per app.
_SLACK_MAX_SLASH_COMMANDS = 50
_SLACK_NAME_LIMIT = 32
_SLACK_INVALID_CHARS = re.compile(r"[^a-z0-9_\-]")
def _sanitize_slack_name(raw: str) -> str:
"""Convert a command name to a valid Slack slash command name.
Slack allows lowercase a-z, digits, hyphens, and underscores. Max 32
chars. Uppercase is lowercased; invalid chars are stripped.
"""
name = raw.lower()
name = _SLACK_INVALID_CHARS.sub("", name)
name = name.strip("-_")
return name[:_SLACK_NAME_LIMIT]
def slack_native_slashes() -> list[tuple[str, str, str]]:
"""Return (slash_name, description, usage_hint) triples for Slack.
Every gateway-available command in ``COMMAND_REGISTRY`` is surfaced as
a standalone Slack slash command (e.g. ``/btw``, ``/stop``, ``/model``),
matching Discord's and Telegram's model where every command is a
first-class slash and not a ``/hermes <verb>`` subcommand.
Both canonical names and aliases are included so users can type any
documented form (e.g. ``/background``, ``/bg``, and ``/btw`` all work).
Plugin-registered slash commands are included too.
Results are clamped to Slack's 50-command limit with duplicate-name
avoidance. ``/hermes`` is always reserved as the first entry so the
legacy ``/hermes <subcommand>`` form keeps working for anything that
gets dropped by the clamp or for free-form questions.
"""
overrides = _resolve_config_gates()
entries: list[tuple[str, str, str]] = []
seen: set[str] = set()
# Reserve /hermes as the catch-all top-level command.
entries.append(("hermes", "Talk to Hermes or run a subcommand", "[subcommand] [args]"))
seen.add("hermes")
def _add(name: str, desc: str, hint: str) -> None:
slack_name = _sanitize_slack_name(name)
if not slack_name or slack_name in seen:
return
if len(entries) >= _SLACK_MAX_SLASH_COMMANDS:
return
# Slack description cap is 2000 chars; keep it short.
entries.append((slack_name, desc[:140], hint[:100]))
seen.add(slack_name)
# First pass: canonical names (so they win slots if we hit the cap).
for cmd in COMMAND_REGISTRY:
if not _is_gateway_available(cmd, overrides):
continue
_add(cmd.name, cmd.description, cmd.args_hint or "")
# Second pass: aliases.
for cmd in COMMAND_REGISTRY:
if not _is_gateway_available(cmd, overrides):
continue
for alias in cmd.aliases:
# Skip aliases that only differ from canonical by case/punctuation
# normalization (already covered by _add dedup).
_add(alias, f"Alias for /{cmd.name}{cmd.description}", cmd.args_hint or "")
# Third pass: plugin commands.
for name, description, args_hint in _iter_plugin_command_entries():
_add(name, description, args_hint or "")
return entries
def slack_app_manifest(request_url: str = "https://hermes-agent.local/slack/commands") -> dict[str, Any]:
"""Generate a Slack app manifest with all gateway commands as slashes.
``request_url`` is required by Slack's manifest schema for every slash
command, but in Socket Mode (which we use) Slack ignores it and routes
the command event through the WebSocket. A placeholder URL is fine.
The returned dict is the ``features.slash_commands`` portion only
callers compose it into a full manifest (or merge into an existing
one). Keeping it narrow avoids coupling us to the rest of the manifest
schema (display_information, oauth_config, settings, etc.) which users
set up once in the Slack UI and rarely change.
"""
slashes = []
for name, desc, usage in slack_native_slashes():
entry = {
"command": f"/{name}",
"description": desc or f"Run /{name}",
"should_escape": False,
"url": request_url,
}
if usage:
entry["usage_hint"] = usage
slashes.append(entry)
return {"features": {"slash_commands": slashes}}
def slack_subcommand_map() -> dict[str, str]:
"""Return subcommand -> /command mapping for Slack /hermes handler.
+10 -171
View File
@@ -465,7 +465,6 @@ DEFAULT_CONFIG = {
"command_timeout": 30, # Timeout for browser commands in seconds (screenshot, navigate, etc.)
"record_sessions": False, # Auto-record browser sessions as WebM videos
"allow_private_urls": False, # Allow navigating to private/internal IPs (localhost, 192.168.x.x, etc.)
"auto_local_for_private_urls": True, # When a cloud provider is set, auto-spawn local Chromium for LAN/localhost URLs instead of sending them to the cloud
"cdp_url": "", # Optional persistent CDP endpoint for attaching to an existing Chromium/Chrome
# CDP supervisor — dialog + frame detection via a persistent WebSocket.
# Active only when a CDP-capable backend is attached (Browserbase or
@@ -487,19 +486,6 @@ DEFAULT_CONFIG = {
"checkpoints": {
"enabled": True,
"max_snapshots": 50, # Max checkpoints to keep per directory
# Auto-maintenance: shadow repos accumulate forever under
# ~/.hermes/checkpoints/ (one per cd'd working directory). Field
# reports put the typical offender at 1000+ repos / ~12 GB. When
# auto_prune is on, hermes sweeps at startup (at most once per
# min_interval_hours) and deletes:
# * orphan repos: HERMES_WORKDIR no longer exists on disk
# * stale repos: newest mtime older than retention_days
# Opt-in so users who rely on /rollback against long-ago sessions
# never lose data silently.
"auto_prune": False,
"retention_days": 7,
"delete_orphans": True,
"min_interval_hours": 24,
},
# Maximum characters returned by a single read_file call. Reads that
@@ -626,6 +612,14 @@ DEFAULT_CONFIG = {
"timeout": 30,
"extra_body": {},
},
"flush_memories": {
"provider": "auto",
"model": "",
"base_url": "",
"api_key": "",
"timeout": 30,
"extra_body": {},
},
"title_generation": {
"provider": "auto",
"model": "",
@@ -640,7 +634,7 @@ DEFAULT_CONFIG = {
"compact": False,
"personality": "kawaii",
"resume_display": "full",
"busy_input_mode": "interrupt", # interrupt | queue | steer
"busy_input_mode": "interrupt",
"bell_on_complete": False,
"show_reasoning": False,
"streaming": False,
@@ -789,15 +783,6 @@ DEFAULT_CONFIG = {
# warning log if out of range.
"max_spawn_depth": 1, # depth cap (1 = flat [default], 2 = orchestrator→leaf, 3 = three-level)
"orchestrator_enabled": True, # kill switch for role="orchestrator"
# When a subagent hits a dangerous-command approval prompt, the parent's
# prompt_toolkit TUI owns stdin — a thread-local input() call from the
# subagent worker would deadlock the parent UI. To avoid the deadlock,
# subagent threads ALWAYS resolve approvals non-interactively:
# false (default) → auto-deny with a logger.warning audit line (safe)
# true → auto-approve "once" with a logger.warning audit line
# Flip to true only if you trust delegated work to run dangerous cmds
# without human review (cron pipelines, batch automation, etc.).
"subagent_auto_approve": False,
},
# Ephemeral prefill messages file — JSON list of {role, content} dicts
@@ -854,7 +839,7 @@ DEFAULT_CONFIG = {
"auto_thread": True, # Auto-create threads on @mention in channels (like Slack)
"reactions": True, # Add 👀/✅/❌ reactions to messages during processing
"channel_prompts": {}, # Per-channel ephemeral system prompts (forum parents apply to child threads)
# discord / discord_admin tools: restrict which actions the agent may call.
# discord_server tool: restrict which actions the agent may call.
# Default (empty) = all actions allowed (subject to bot privileged intents).
# Accepts comma-separated string ("list_guilds,list_channels,fetch_messages")
# or YAML list. Unknown names are dropped with a warning at load time.
@@ -973,27 +958,6 @@ DEFAULT_CONFIG = {
"backup_count": 3, # Number of rotated backup files to keep
},
# Remotely-hosted model catalog manifest. When enabled, the CLI fetches
# curated model lists for OpenRouter and Nous Portal from this URL,
# falling back to the in-repo snapshot on network failure. Lets us
# update model picker lists without shipping a hermes-agent release.
# The default URL is served by the docs site GitHub Pages deploy.
"model_catalog": {
"enabled": True,
"url": "https://hermes-agent.nousresearch.com/docs/api/model-catalog.json",
# Disk cache TTL in hours. Beyond this, the CLI refetches on the
# next /model or `hermes model` invocation; network failures
# silently fall back to the stale cache.
"ttl_hours": 24,
# Optional per-provider override URLs for third parties that want
# to self-host their own curation list using the same schema.
# Example:
# providers:
# openrouter:
# url: https://example.com/my-curation.json
"providers": {},
},
# Network settings — workarounds for connectivity issues.
"network": {
# Force IPv4 connections. On servers with broken or unreachable IPv6,
@@ -1030,13 +994,6 @@ DEFAULT_CONFIG = {
"min_interval_hours": 24,
},
# Contextual first-touch onboarding hints (see agent/onboarding.py).
# Each hint is shown once per install and then latched here so it
# never fires again. Users can wipe the section to re-see all hints.
"onboarding": {
"seen": {},
},
# Config schema version - bump this when adding new required fields
"_config_version": 22,
}
@@ -1413,21 +1370,6 @@ OPTIONAL_ENV_VARS = {
"category": "provider",
"advanced": True,
},
"AZURE_FOUNDRY_API_KEY": {
"description": "Azure Foundry API key for custom Azure endpoints",
"prompt": "Azure Foundry API Key",
"url": "https://ai.azure.com/",
"password": True,
"category": "provider",
},
"AZURE_FOUNDRY_BASE_URL": {
"description": "Azure Foundry base URL (set via 'hermes model' for endpoint-specific config)",
"prompt": "Azure Foundry base URL",
"url": None,
"password": False,
"category": "provider",
"advanced": True,
},
# ── Tool API keys ──
"EXA_API_KEY": {
@@ -1595,44 +1537,6 @@ OPTIONAL_ENV_VARS = {
"category": "tool",
},
# ── Bundled skills (opt-in: only needed if the user uses that skill) ──
# These use category="skill" (distinct from "tool") so the sandbox
# env blocklist in tools/environments/local.py does NOT rewrite them —
# skills legitimately need these passed through to curl via
# tools/env_passthrough.py when the user's skill calls out.
"NOTION_API_KEY": {
"description": "Notion integration token (used by the `notion` skill)",
"prompt": "Notion API key",
"url": "https://www.notion.so/my-integrations",
"password": True,
"category": "skill",
"advanced": True,
},
"LINEAR_API_KEY": {
"description": "Linear personal API key (used by the `linear` skill)",
"prompt": "Linear API key",
"url": "https://linear.app/settings/api",
"password": True,
"category": "skill",
"advanced": True,
},
"AIRTABLE_API_KEY": {
"description": "Airtable personal access token (used by the `airtable` skill)",
"prompt": "Airtable API key",
"url": "https://airtable.com/create/tokens",
"password": True,
"category": "skill",
"advanced": True,
},
"TENOR_API_KEY": {
"description": "Tenor API key for GIF search (used by the `gif-search` skill)",
"prompt": "Tenor API key",
"url": "https://developers.google.com/tenor/guides/quickstart",
"password": True,
"category": "skill",
"advanced": True,
},
# ── Honcho ──
"HONCHO_API_KEY": {
"description": "Honcho API key for AI-native persistent memory",
@@ -2301,71 +2205,6 @@ def get_compatible_custom_providers(
return compatible
def get_custom_provider_context_length(
model: str,
base_url: str,
custom_providers: Optional[List[Dict[str, Any]]] = None,
config: Optional[Dict[str, Any]] = None,
) -> Optional[int]:
"""Look up a per-model ``context_length`` override from ``custom_providers``.
Matches any entry whose ``base_url`` equals ``base_url`` (trailing-slash
insensitive) and returns ``custom_providers[i].models.<model>.context_length``
if present and valid. Returns ``None`` when no override applies.
This is the single source of truth for custom-provider context overrides,
used by:
* ``AIAgent.__init__`` (startup resolution)
* ``AIAgent.switch_model`` (mid-session ``/model`` switch)
* ``hermes_cli.model_switch.resolve_display_context_length`` (``/model`` confirmation display)
* ``gateway.run._format_session_info`` (``/info`` display)
* ``agent.model_metadata.get_model_context_length`` (when custom_providers is threaded through)
Before this helper existed, the lookup was duplicated in ``run_agent.py``'s
startup path only; every other path (notably ``/model`` switch) fell back
to the 128K default. See #15779.
"""
if not model or not base_url:
return None
if custom_providers is None:
try:
custom_providers = get_compatible_custom_providers(config)
except Exception:
if config is None:
return None
raw = config.get("custom_providers")
custom_providers = raw if isinstance(raw, list) else []
if not isinstance(custom_providers, list):
return None
target_url = (base_url or "").rstrip("/")
if not target_url:
return None
for entry in custom_providers:
if not isinstance(entry, dict):
continue
entry_url = (entry.get("base_url") or "").rstrip("/")
if not entry_url or entry_url != target_url:
continue
models = entry.get("models")
if not isinstance(models, dict):
continue
model_cfg = models.get(model)
if not isinstance(model_cfg, dict):
continue
raw_ctx = model_cfg.get("context_length")
if raw_ctx is None:
continue
try:
ctx = int(raw_ctx)
except (TypeError, ValueError):
continue
if ctx > 0:
return ctx
return None
def check_config_version() -> Tuple[int, int]:
"""
Check config version.
+1 -5
View File
@@ -320,11 +320,7 @@ def run_doctor(args):
known_providers.add("custom:" + name.lower().replace(" ", "-"))
canonical_provider = provider
if (
provider
and _resolve_provider_full is not None
and provider not in ("auto", "custom")
):
if provider and _resolve_provider_full is not None and provider != "auto":
provider_def = _resolve_provider_full(provider, user_providers, custom_providers)
canonical_provider = provider_def.id if provider_def is not None else None
-361
View File
@@ -1,361 +0,0 @@
"""
hermes fallback manage the fallback provider chain.
Fallback providers are tried in order when the primary model fails with
rate-limit, overload, or connection errors. See:
https://hermes-agent.nousresearch.com/docs/user-guide/features/fallback-providers
Subcommands:
hermes fallback [list] Show the current fallback chain (default when no subcommand)
hermes fallback add Pick provider + model via the same picker as `hermes model`,
then append the selection to the chain
hermes fallback remove Pick an entry to delete from the chain
hermes fallback clear Remove all fallback entries
Storage: ``fallback_providers`` in ``~/.hermes/config.yaml`` (top-level, list of
``{provider, model, base_url?, api_mode?}`` dicts). The legacy single-dict
``fallback_model`` format is migrated to the new list format on first add.
"""
from __future__ import annotations
import copy
from typing import Any, Dict, List, Optional
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _read_chain(config: Dict[str, Any]) -> List[Dict[str, Any]]:
"""Return the normalized fallback chain as a list of dicts.
Accepts both the new list format (``fallback_providers``) and the legacy
single-dict format (``fallback_model``). The returned list is always a
fresh copy callers can mutate without touching the config dict.
"""
chain = config.get("fallback_providers") or []
if isinstance(chain, list):
result = [dict(e) for e in chain if isinstance(e, dict) and e.get("provider") and e.get("model")]
if result:
return result
legacy = config.get("fallback_model")
if isinstance(legacy, dict) and legacy.get("provider") and legacy.get("model"):
return [dict(legacy)]
if isinstance(legacy, list):
return [dict(e) for e in legacy if isinstance(e, dict) and e.get("provider") and e.get("model")]
return []
def _write_chain(config: Dict[str, Any], chain: List[Dict[str, Any]]) -> None:
"""Persist the chain to ``fallback_providers`` and clear legacy key."""
config["fallback_providers"] = chain
# Drop the legacy single-dict key on write so there's only one source of truth.
if "fallback_model" in config:
config.pop("fallback_model", None)
def _format_entry(entry: Dict[str, Any]) -> str:
"""One-line human-readable rendering of a fallback entry."""
provider = entry.get("provider", "?")
model = entry.get("model", "?")
base = entry.get("base_url")
suffix = f" [{base}]" if base else ""
return f"{model} (via {provider}){suffix}"
def _extract_fallback_from_model_cfg(model_cfg: Any) -> Optional[Dict[str, Any]]:
"""Pull the ``{provider, model, base_url?, api_mode?}`` dict from a ``config["model"]`` snapshot."""
if not isinstance(model_cfg, dict):
return None
provider = (model_cfg.get("provider") or "").strip()
# The picker writes the selected model to ``model.default``.
model = (model_cfg.get("default") or model_cfg.get("model") or "").strip()
if not provider or not model:
return None
entry: Dict[str, Any] = {"provider": provider, "model": model}
base_url = (model_cfg.get("base_url") or "").strip()
if base_url:
entry["base_url"] = base_url
api_mode = (model_cfg.get("api_mode") or "").strip()
if api_mode:
entry["api_mode"] = api_mode
return entry
def _snapshot_auth_active_provider() -> Any:
"""Return the current ``active_provider`` in auth.json, or a sentinel if unavailable."""
try:
from hermes_cli.auth import _load_auth_store
store = _load_auth_store()
return store.get("active_provider")
except Exception:
return None
def _restore_auth_active_provider(value: Any) -> None:
"""Write back a previously snapshotted ``active_provider`` value."""
try:
from hermes_cli.auth import _auth_store_lock, _load_auth_store, _save_auth_store
with _auth_store_lock():
store = _load_auth_store()
store["active_provider"] = value
_save_auth_store(store)
except Exception:
# Best-effort — if auth.json can't be restored, the user's primary
# provider may have been deactivated by the picker. They can re-run
# `hermes model` to fix it. Don't fail the fallback add.
pass
# ---------------------------------------------------------------------------
# Subcommand handlers
# ---------------------------------------------------------------------------
def cmd_fallback_list(args) -> None: # noqa: ARG001
"""Print the current fallback chain."""
from hermes_cli.config import load_config
config = load_config()
chain = _read_chain(config)
print()
if not chain:
print(" No fallback providers configured.")
print()
print(" Add one with: hermes fallback add")
print()
return
primary = _describe_primary(config)
if primary:
print(f" Primary: {primary}")
print()
print(f" Fallback chain ({len(chain)} {'entry' if len(chain) == 1 else 'entries'}):")
for i, entry in enumerate(chain, 1):
print(f" {i}. {_format_entry(entry)}")
print()
print(" Tried in order when the primary fails (rate-limit, 5xx, connection errors).")
print(" Docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/fallback-providers")
print()
def _describe_primary(config: Dict[str, Any]) -> Optional[str]:
"""One-line description of the primary model for display purposes."""
model_cfg = config.get("model")
if isinstance(model_cfg, dict):
provider = (model_cfg.get("provider") or "?").strip() or "?"
model = (model_cfg.get("default") or model_cfg.get("model") or "?").strip() or "?"
return f"{model} (via {provider})"
if isinstance(model_cfg, str) and model_cfg.strip():
return model_cfg.strip()
return None
def cmd_fallback_add(args) -> None:
"""Launch the same picker as `hermes model`, then append the selection to the chain."""
from hermes_cli.main import _require_tty, select_provider_and_model
from hermes_cli.config import load_config, save_config
_require_tty("fallback add")
# Snapshot BEFORE the picker runs so we can distinguish "user actually
# picked something" from "user cancelled" by comparing before/after.
before_cfg = load_config()
model_before = copy.deepcopy(before_cfg.get("model"))
active_provider_before = _snapshot_auth_active_provider()
print()
print(" Adding a fallback provider. The picker below is the same one used by")
print(" `hermes model` — select the provider + model you want as a fallback.")
print()
try:
select_provider_and_model(args=args)
except SystemExit:
# Some provider flows exit on auth failure — restore state and re-raise.
_restore_model_cfg(model_before)
_restore_auth_active_provider(active_provider_before)
raise
# Read the post-picker state to see what the user selected.
after_cfg = load_config()
model_after = after_cfg.get("model")
new_entry = _extract_fallback_from_model_cfg(model_after)
if not new_entry:
# Picker didn't complete (user cancelled or flow bailed). Nothing to do.
_restore_model_cfg(model_before)
_restore_auth_active_provider(active_provider_before)
print()
print(" No fallback added.")
return
# Picker picked the same thing that's already the primary → nothing changed,
# and there's nothing useful to add as a fallback to itself.
primary_entry = _extract_fallback_from_model_cfg(model_before)
if primary_entry and primary_entry["provider"] == new_entry["provider"] \
and primary_entry["model"] == new_entry["model"]:
_restore_model_cfg(model_before)
_restore_auth_active_provider(active_provider_before)
print()
print(f" Selected model matches the current primary ({_format_entry(new_entry)}).")
print(" A provider cannot be a fallback for itself — no change.")
return
# Reload the config with the primary restored, then append the new entry
# to ``fallback_providers``. We deliberately re-load (rather than mutating
# ``after_cfg``) because the picker may have touched other top-level keys
# (custom_providers, providers credentials) that we want to keep.
_restore_model_cfg(model_before)
_restore_auth_active_provider(active_provider_before)
final_cfg = load_config()
chain = _read_chain(final_cfg)
# Reject exact-duplicate fallback entries.
for existing in chain:
if existing.get("provider") == new_entry["provider"] \
and existing.get("model") == new_entry["model"]:
print()
print(f" {_format_entry(new_entry)} is already in the fallback chain — skipped.")
return
chain.append(new_entry)
_write_chain(final_cfg, chain)
save_config(final_cfg)
print()
print(f" Added fallback: {_format_entry(new_entry)}")
print(f" Chain is now {len(chain)} {'entry' if len(chain) == 1 else 'entries'} long.")
print()
print(" Run `hermes fallback list` to view, or `hermes fallback remove` to delete.")
def _restore_model_cfg(model_before: Any) -> None:
"""Restore ``config["model"]`` to a previously-captured snapshot."""
from hermes_cli.config import load_config, save_config
cfg = load_config()
if model_before is None:
cfg.pop("model", None)
else:
cfg["model"] = copy.deepcopy(model_before)
save_config(cfg)
def cmd_fallback_remove(args) -> None: # noqa: ARG001
"""Pick an entry from the chain and remove it."""
from hermes_cli.config import load_config, save_config
config = load_config()
chain = _read_chain(config)
if not chain:
print()
print(" No fallback providers configured — nothing to remove.")
print()
return
choices = [_format_entry(e) for e in chain]
choices.append("Cancel")
try:
from hermes_cli.setup import _curses_prompt_choice
idx = _curses_prompt_choice("Select a fallback to remove:", choices, 0)
except Exception:
idx = _numbered_pick("Select a fallback to remove:", choices)
if idx is None or idx < 0 or idx >= len(chain):
print()
print(" Cancelled — no change.")
return
removed = chain.pop(idx)
_write_chain(config, chain)
save_config(config)
print()
print(f" Removed fallback: {_format_entry(removed)}")
if chain:
print(f" Chain is now {len(chain)} {'entry' if len(chain) == 1 else 'entries'} long.")
else:
print(" Fallback chain is now empty.")
print()
def cmd_fallback_clear(args) -> None: # noqa: ARG001
"""Remove all fallback entries (with confirmation)."""
from hermes_cli.config import load_config, save_config
config = load_config()
chain = _read_chain(config)
if not chain:
print()
print(" No fallback providers configured — nothing to clear.")
print()
return
print()
print(f" Current fallback chain ({len(chain)} {'entry' if len(chain) == 1 else 'entries'}):")
for i, entry in enumerate(chain, 1):
print(f" {i}. {_format_entry(entry)}")
print()
try:
resp = input(" Clear all entries? [y/N]: ").strip().lower()
except (KeyboardInterrupt, EOFError):
print()
print(" Cancelled.")
return
if resp not in ("y", "yes"):
print(" Cancelled — no change.")
return
_write_chain(config, [])
save_config(config)
print()
print(" Fallback chain cleared.")
print()
def _numbered_pick(question: str, choices: List[str]) -> Optional[int]:
"""Fallback numbered-list picker when curses is unavailable."""
print(question)
for i, c in enumerate(choices, 1):
print(f" {i}. {c}")
print()
while True:
try:
val = input(f"Choice [1-{len(choices)}]: ").strip()
if not val:
return None
idx = int(val) - 1
if 0 <= idx < len(choices):
return idx
print(f"Please enter 1-{len(choices)}")
except ValueError:
print("Please enter a number")
except (KeyboardInterrupt, EOFError):
print()
return None
# ---------------------------------------------------------------------------
# Dispatch
# ---------------------------------------------------------------------------
def cmd_fallback(args) -> None:
"""Top-level dispatcher for ``hermes fallback [subcommand]``."""
sub = getattr(args, "fallback_command", None)
if sub in (None, "", "list", "ls"):
cmd_fallback_list(args)
elif sub == "add":
cmd_fallback_add(args)
elif sub in ("remove", "rm"):
cmd_fallback_remove(args)
elif sub == "clear":
cmd_fallback_clear(args)
else:
print(f"Unknown fallback subcommand: {sub}")
print("Use one of: list, add, remove, clear")
raise SystemExit(2)
-24
View File
@@ -2724,24 +2724,6 @@ _PLATFORMS = [
"help": "OpenID to deliver cron results and notifications to."},
],
},
{
"key": "yuanbao",
"label": "Yuanbao",
"emoji": "💎",
"token_var": "YUANBAO_APP_ID",
"setup_instructions": [
"1. Download the Yuanbao app from https://yuanbao.tencent.com/",
"2. In the app, go to PAI → My Bot and create a new bot",
"3. After the bot is created, copy the App ID and App Secret",
"4. Enter them below and Hermes will connect automatically over WebSocket",
],
"vars": [
{"name": "YUANBAO_APP_ID", "prompt": "App ID", "password": False,
"help": "The App ID from your Yuanbao IM Bot credentials."},
{"name": "YUANBAO_APP_SECRET", "prompt": "App Secret", "password": True,
"help": "The App Secret (used for HMAC signing) from your Yuanbao IM Bot."},
],
},
]
@@ -3126,12 +3108,6 @@ def _setup_wecom():
print_success("💬 WeCom configured!")
def _setup_yuanbao():
"""Configure Yuanbao via the standard platform setup."""
yuanbao_platform = next(p for p in _PLATFORMS if p["key"] == "yuanbao")
_setup_standard_platform(yuanbao_platform)
def _is_service_installed() -> bool:
"""Check if the gateway is installed as a system service."""
if supports_systemd_services():
-1
View File
@@ -125,7 +125,6 @@ _DEFAULT_PAYLOADS = {
"task_id": "test-task",
"tool_call_id": "test-call",
"result": '{"output": "hello"}',
"duration_ms": 42,
},
"pre_llm_call": {
"session_id": "test-session",
+48 -862
View File
File diff suppressed because it is too large Load Diff
-329
View File
@@ -1,329 +0,0 @@
"""Remote model catalog fetcher.
The Hermes docs site hosts a JSON manifest of curated models for providers
we want to update without shipping a release (currently OpenRouter and
Nous Portal). This module fetches, validates, and caches that manifest,
falling back to the in-repo hardcoded lists when the network is unavailable.
Pipeline
--------
1. ``get_catalog()`` returns a parsed manifest dict.
- Checks in-process cache (invalidated by TTL).
- Reads disk cache at ``~/.hermes/cache/model_catalog.json``.
- Fetches the master URL if disk cache is stale or missing.
- On any fetch failure, keeps using the stale cache (or empty dict).
2. ``get_curated_openrouter_models()`` / ``get_curated_nous_models()``
thin accessors returning the shapes existing callers expect. Each
falls back to the in-repo hardcoded list on any lookup failure.
Schema (version 1)
------------------
::
{
"version": 1,
"updated_at": "2026-04-25T22:00:00Z",
"metadata": {...}, # free-form
"providers": {
"openrouter": {
"metadata": {...}, # free-form
"models": [
{"id": "vendor/model", "description": "recommended",
"metadata": {...}} # free-form, model-level
]
},
"nous": {...}
}
}
Unknown fields are ignored extra metadata can be added at either level
without bumping ``version``. ``version`` bumps are reserved for
breaking changes (renaming ``providers``, changing ``models`` shape).
"""
from __future__ import annotations
import json
import logging
import os
import time
import urllib.error
import urllib.request
from pathlib import Path
from typing import Any
from hermes_cli import __version__ as _HERMES_VERSION
logger = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# Constants
# ---------------------------------------------------------------------------
DEFAULT_CATALOG_URL = (
"https://hermes-agent.nousresearch.com/docs/api/model-catalog.json"
)
DEFAULT_TTL_HOURS = 24
DEFAULT_FETCH_TIMEOUT = 8.0
SUPPORTED_SCHEMA_VERSION = 1
_HERMES_USER_AGENT = f"hermes-cli/{_HERMES_VERSION}"
# In-process cache to avoid repeated disk + parse work across multiple
# calls within the same session. Invalidated by TTL against the disk file's
# mtime, so calling code never has to think about this.
_catalog_cache: dict[str, Any] | None = None
_catalog_cache_source_mtime: float = 0.0
# ---------------------------------------------------------------------------
# Config
# ---------------------------------------------------------------------------
def _load_catalog_config() -> dict[str, Any]:
"""Load the ``model_catalog`` config block with defaults filled in."""
try:
from hermes_cli.config import load_config
cfg = load_config() or {}
except Exception:
cfg = {}
raw = cfg.get("model_catalog")
if not isinstance(raw, dict):
raw = {}
return {
"enabled": bool(raw.get("enabled", True)),
"url": str(raw.get("url") or DEFAULT_CATALOG_URL),
"ttl_hours": float(raw.get("ttl_hours") or DEFAULT_TTL_HOURS),
"providers": raw.get("providers") if isinstance(raw.get("providers"), dict) else {},
}
def _cache_path() -> Path:
"""Return the disk cache path. Import lazily so tests can monkeypatch home."""
from hermes_constants import get_hermes_home
return get_hermes_home() / "cache" / "model_catalog.json"
# ---------------------------------------------------------------------------
# Fetch + validate + cache
# ---------------------------------------------------------------------------
def _fetch_manifest(url: str, timeout: float) -> dict[str, Any] | None:
"""HTTP GET the manifest URL and return a parsed dict, or None on failure."""
try:
req = urllib.request.Request(
url,
headers={
"Accept": "application/json",
"User-Agent": _HERMES_USER_AGENT,
},
)
with urllib.request.urlopen(req, timeout=timeout) as resp:
data = json.loads(resp.read().decode())
except (urllib.error.URLError, TimeoutError, json.JSONDecodeError, OSError) as exc:
logger.info("model catalog fetch failed (%s): %s", url, exc)
return None
except Exception as exc: # pragma: no cover — defensive
logger.info("model catalog fetch errored (%s): %s", url, exc)
return None
if not _validate_manifest(data):
logger.info("model catalog at %s failed schema validation", url)
return None
return data
def _validate_manifest(data: Any) -> bool:
"""Return True when ``data`` matches the minimum manifest shape."""
if not isinstance(data, dict):
return False
version = data.get("version")
if not isinstance(version, int) or version > SUPPORTED_SCHEMA_VERSION:
# Future schema version we don't understand — refuse rather than
# guess. Older schemas (version < 1) aren't supported either.
return False
providers = data.get("providers")
if not isinstance(providers, dict):
return False
for pname, pblock in providers.items():
if not isinstance(pname, str) or not isinstance(pblock, dict):
return False
models = pblock.get("models")
if not isinstance(models, list):
return False
for m in models:
if not isinstance(m, dict):
return False
if not isinstance(m.get("id"), str) or not m["id"].strip():
return False
return True
def _read_disk_cache() -> tuple[dict[str, Any] | None, float]:
"""Return ``(data_or_none, mtime)``. mtime is 0 if file is missing."""
path = _cache_path()
try:
mtime = path.stat().st_mtime
except (OSError, FileNotFoundError):
return (None, 0.0)
try:
with open(path) as fh:
data = json.load(fh)
except (OSError, json.JSONDecodeError):
return (None, 0.0)
if not _validate_manifest(data):
return (None, 0.0)
return (data, mtime)
def _write_disk_cache(data: dict[str, Any]) -> None:
path = _cache_path()
try:
path.parent.mkdir(parents=True, exist_ok=True)
tmp = path.with_suffix(path.suffix + ".tmp")
with open(tmp, "w") as fh:
json.dump(data, fh, indent=2)
fh.write("\n")
os.replace(tmp, path)
except OSError as exc:
logger.info("model catalog cache write failed: %s", exc)
# ---------------------------------------------------------------------------
# Public API
# ---------------------------------------------------------------------------
def get_catalog(*, force_refresh: bool = False) -> dict[str, Any]:
"""Return the parsed model catalog manifest, or an empty dict on failure.
Callers should treat a missing provider/model as "use the in-repo fallback"
never raise from this function so the CLI keeps working offline.
"""
global _catalog_cache, _catalog_cache_source_mtime
cfg = _load_catalog_config()
if not cfg["enabled"]:
return {}
ttl_seconds = max(0.0, cfg["ttl_hours"] * 3600.0)
disk_data, disk_mtime = _read_disk_cache()
now = time.time()
disk_fresh = disk_data is not None and (now - disk_mtime) < ttl_seconds
# In-process cache hit: disk hasn't changed since we loaded it and still fresh.
if (
not force_refresh
and _catalog_cache is not None
and disk_data is not None
and disk_mtime == _catalog_cache_source_mtime
and disk_fresh
):
return _catalog_cache
# Disk is fresh enough — use it without a network hit.
if not force_refresh and disk_fresh and disk_data is not None:
_catalog_cache = disk_data
_catalog_cache_source_mtime = disk_mtime
return disk_data
# Need to (re)fetch. If it fails, fall back to any stale disk copy.
fetched = _fetch_manifest(cfg["url"], DEFAULT_FETCH_TIMEOUT)
if fetched is not None:
_write_disk_cache(fetched)
new_disk_data, new_mtime = _read_disk_cache()
if new_disk_data is not None:
_catalog_cache = new_disk_data
_catalog_cache_source_mtime = new_mtime
return new_disk_data
_catalog_cache = fetched
_catalog_cache_source_mtime = now
return fetched
if disk_data is not None:
_catalog_cache = disk_data
_catalog_cache_source_mtime = disk_mtime
return disk_data
return {}
def _fetch_provider_override(provider: str) -> dict[str, Any] | None:
"""If ``model_catalog.providers.<name>.url`` is set, fetch that instead."""
cfg = _load_catalog_config()
if not cfg["enabled"]:
return None
provider_cfg = cfg["providers"].get(provider)
if not isinstance(provider_cfg, dict):
return None
override_url = provider_cfg.get("url")
if not isinstance(override_url, str) or not override_url.strip():
return None
# Override fetches skip the disk cache because they're usually
# third-party self-hosted. Re-request on every call but with a short
# timeout so they don't block the picker.
return _fetch_manifest(override_url.strip(), DEFAULT_FETCH_TIMEOUT)
def _get_provider_block(provider: str) -> dict[str, Any] | None:
"""Return the provider's manifest block, respecting per-provider overrides."""
override = _fetch_provider_override(provider)
if override is not None:
block = override.get("providers", {}).get(provider)
if isinstance(block, dict):
return block
catalog = get_catalog()
if not catalog:
return None
block = catalog.get("providers", {}).get(provider)
return block if isinstance(block, dict) else None
def get_curated_openrouter_models() -> list[tuple[str, str]] | None:
"""Return OpenRouter's curated ``[(id, description), ...]`` from the manifest.
Returns ``None`` when the manifest is unavailable, so callers can fall
back to their hardcoded list.
"""
block = _get_provider_block("openrouter")
if not block:
return None
out: list[tuple[str, str]] = []
for m in block.get("models", []):
mid = str(m.get("id") or "").strip()
if not mid:
continue
desc = str(m.get("description") or "")
out.append((mid, desc))
return out or None
def get_curated_nous_models() -> list[str] | None:
"""Return Nous Portal's curated list of model ids from the manifest.
Returns ``None`` when the manifest is unavailable.
"""
block = _get_provider_block("nous")
if not block:
return None
out: list[str] = []
for m in block.get("models", []):
mid = str(m.get("id") or "").strip()
if mid:
out.append(mid)
return out or None
def reset_cache() -> None:
"""Clear the in-process cache. Used by tests and ``hermes model --refresh``."""
global _catalog_cache, _catalog_cache_source_mtime
_catalog_cache = None
_catalog_cache_source_mtime = 0.0
+12 -75
View File
@@ -527,49 +527,6 @@ def _resolve_alias_fallback(
return None
def resolve_display_context_length(
model: str,
provider: str,
base_url: str = "",
api_key: str = "",
model_info: Optional[ModelInfo] = None,
custom_providers: list | None = None,
) -> Optional[int]:
"""Resolve the context length to show in /model output.
models.dev reports per-vendor context (e.g. gpt-5.5 = 1.05M on openai)
but provider-enforced limits can be lower (e.g. Codex OAuth caps the
same slug at 272k). The authoritative source is
``agent.model_metadata.get_model_context_length`` which already knows
about Codex OAuth, Copilot, Nous, and falls back to models.dev for the
rest.
When ``custom_providers`` is provided, per-model ``context_length``
overrides from ``custom_providers[].models.<id>.context_length`` are
honored this closes #15779 where ``/model`` switch ignored user-set
overrides.
Prefer the provider-aware value; fall back to ``model_info.context_window``
only if the resolver returns nothing.
"""
try:
from agent.model_metadata import get_model_context_length
ctx = get_model_context_length(
model,
base_url=base_url or "",
api_key=api_key or "",
provider=provider or None,
custom_providers=custom_providers,
)
if ctx:
return int(ctx)
except Exception:
pass
if model_info is not None and model_info.context_window:
return int(model_info.context_window)
return None
# ---------------------------------------------------------------------------
# Core model-switching pipeline
# ---------------------------------------------------------------------------
@@ -838,14 +795,9 @@ def switch_model(
requested=current_provider,
target_model=new_model,
)
# If resolution fell through to "custom" (e.g. named custom provider like
# "ollama-launch" that resolve_runtime_provider doesn't know), keep existing
# credentials. Otherwise use the resolved values (picks up credential rotation,
# base_url adjustments for OpenCode, etc.).
if runtime.get("provider") != "custom":
api_key = runtime.get("api_key", "")
base_url = runtime.get("base_url", "")
api_mode = runtime.get("api_mode", "")
api_key = runtime.get("api_key", "")
base_url = runtime.get("base_url", "")
api_mode = runtime.get("api_mode", "")
except Exception:
pass
@@ -879,31 +831,16 @@ def switch_model(
"message": f"Could not validate `{new_model}`: {e}",
}
# Override rejection if model is in the user's saved provider config.
# API /v1/models may not list cloud/aliased models even though the server supports them.
if not validation.get("accepted"):
override = False
if user_providers:
for up in user_providers:
if isinstance(up, dict) and up.get("provider") == target_provider:
cfg_models = up.get("models", [])
if new_model in cfg_models or any(
m.get("name") == new_model for m in cfg_models if isinstance(m, dict)
):
override = True
break
if override:
validation = {"accepted": True, "persist": True, "recognized": False, "message": validation.get("message", "")}
else:
msg = validation.get("message", "Invalid model")
return ModelSwitchResult(
success=False,
new_model=new_model,
target_provider=target_provider,
provider_label=provider_label,
is_global=is_global,
error_message=msg,
)
msg = validation.get("message", "Invalid model")
return ModelSwitchResult(
success=False,
new_model=new_model,
target_provider=target_provider,
provider_label=provider_label,
is_global=is_global,
error_message=msg,
)
# Apply auto-correction if validation found a closer match
if validation.get("corrected_model"):
+84 -162
View File
@@ -33,6 +33,8 @@ COPILOT_REASONING_EFFORTS_O_SERIES = ["low", "medium", "high"]
# (model_id, display description shown in menus)
OPENROUTER_MODELS: list[tuple[str, str]] = [
("moonshotai/kimi-k2.6", "recommended"),
("deepseek/deepseek-v4-pro", ""),
("deepseek/deepseek-v4-flash", ""),
("anthropic/claude-opus-4.7", ""),
("anthropic/claude-opus-4.6", ""),
("anthropic/claude-sonnet-4.6", ""),
@@ -40,7 +42,7 @@ OPENROUTER_MODELS: list[tuple[str, str]] = [
("anthropic/claude-sonnet-4.5", ""),
("anthropic/claude-haiku-4.5", ""),
("openrouter/elephant-alpha", "free"),
("openai/gpt-5.5", ""),
("openai/gpt-5.4", ""),
("openai/gpt-5.4-mini", ""),
("xiaomi/mimo-v2.5-pro", ""),
("xiaomi/mimo-v2.5", ""),
@@ -63,7 +65,7 @@ OPENROUTER_MODELS: list[tuple[str, str]] = [
("nvidia/nemotron-3-super-120b-a12b:free", "free"),
("arcee-ai/trinity-large-preview:free", "free"),
("arcee-ai/trinity-large-thinking", ""),
("openai/gpt-5.5-pro", ""),
("openai/gpt-5.4-pro", ""),
("openai/gpt-5.4-nano", ""),
]
@@ -109,6 +111,8 @@ def _codex_curated_models() -> list[str]:
_PROVIDER_MODELS: dict[str, list[str]] = {
"nous": [
"moonshotai/kimi-k2.6",
"deepseek/deepseek-v4-pro",
"deepseek/deepseek-v4-flash",
"xiaomi/mimo-v2.5-pro",
"xiaomi/mimo-v2.5",
"anthropic/claude-opus-4.7",
@@ -116,7 +120,7 @@ _PROVIDER_MODELS: dict[str, list[str]] = {
"anthropic/claude-sonnet-4.6",
"anthropic/claude-sonnet-4.5",
"anthropic/claude-haiku-4.5",
"openai/gpt-5.5",
"openai/gpt-5.4",
"openai/gpt-5.4-mini",
"openai/gpt-5.3-codex",
"google/gemini-3-pro-preview",
@@ -135,7 +139,7 @@ _PROVIDER_MODELS: dict[str, list[str]] = {
"x-ai/grok-4.20-beta",
"nvidia/nemotron-3-super-120b-a12b",
"arcee-ai/trinity-large-thinking",
"openai/gpt-5.5-pro",
"openai/gpt-5.4-pro",
"openai/gpt-5.4-nano",
],
# Native OpenAI Chat Completions (api.openai.com). Used by /model counts and
@@ -379,9 +383,6 @@ _PROVIDER_MODELS: dict[str, list[str]] = {
"us.meta.llama4-maverick-17b-instruct-v1:0",
"us.meta.llama4-scout-17b-instruct-v1:0",
],
# Azure Foundry: user-provided endpoint and model.
# Empty list because models depend on the endpoint configuration.
"azure-foundry": [],
}
# Vercel AI Gateway: derive the bare-model-id catalog from the curated
@@ -739,7 +740,6 @@ CANONICAL_PROVIDERS: list[ProviderEntry] = [
ProviderEntry("opencode-zen", "OpenCode Zen", "OpenCode Zen (35+ curated models, pay-as-you-go)"),
ProviderEntry("opencode-go", "OpenCode Go", "OpenCode Go (open models, $10/month subscription)"),
ProviderEntry("bedrock", "AWS Bedrock", "AWS Bedrock (Claude, Nova, Llama, DeepSeek — IAM or API key)"),
ProviderEntry("azure-foundry", "Azure Foundry", "Azure Foundry (OpenAI-style or Anthropic-style endpoint — your Azure AI deployment)"),
]
# Derived dicts — used throughout the codebase
@@ -872,16 +872,7 @@ def fetch_openrouter_models(
if _openrouter_catalog_cache is not None and not force_refresh:
return list(_openrouter_catalog_cache)
# Prefer the remotely-hosted catalog manifest; fall back to the in-repo
# snapshot when the manifest is unreachable. Both are curated lists that
# drive the picker; the OpenRouter live /v1/models filter (tool support,
# free pricing) is applied on top either way.
try:
from hermes_cli.model_catalog import get_curated_openrouter_models
remote = get_curated_openrouter_models()
except Exception:
remote = None
fallback = list(remote) if remote else list(OPENROUTER_MODELS)
fallback = list(OPENROUTER_MODELS)
preferred_ids = [mid for mid, _ in fallback]
try:
@@ -934,24 +925,6 @@ def model_ids(*, force_refresh: bool = False) -> list[str]:
return [mid for mid, _ in fetch_openrouter_models(force_refresh=force_refresh)]
def get_curated_nous_model_ids() -> list[str]:
"""Return the curated Nous Portal model-id list.
Prefers the remotely-hosted catalog manifest (published under
``website/static/api/model-catalog.json``); falls back to the in-repo
snapshot in ``_PROVIDER_MODELS["nous"]`` when the manifest is
unreachable. Always returns a list (never None).
"""
try:
from hermes_cli.model_catalog import get_curated_nous_models
remote = get_curated_nous_models()
except Exception:
remote = None
if remote:
return list(remote)
return list(_PROVIDER_MODELS.get("nous", []))
def _ai_gateway_model_is_free(pricing: Any) -> bool:
"""Return True if an AI Gateway model has $0 input AND output pricing."""
if not isinstance(pricing, dict):
@@ -1406,124 +1379,6 @@ def curated_models_for_provider(
return [(m, "") for m in models]
def _provider_keys(provider: str) -> set[str]:
key = (provider or "").strip().lower()
normalized = normalize_provider(provider)
return {k for k in (key, normalized) if k}
def _model_in_provider_catalog(name_lower: str, providers: set[str]) -> bool:
return any(
name_lower == model.lower()
for provider in providers
for model in _PROVIDER_MODELS.get(provider, [])
)
_AGGREGATOR_PROVIDERS = frozenset(
{"nous", "openrouter", "ai-gateway", "copilot", "kilocode"}
)
def _resolve_static_model_alias(
name_lower: str,
current_keys: set[str],
) -> Optional[tuple[str, str]]:
"""Resolve short aliases (e.g. sonnet/opus) using static catalogs only."""
try:
from hermes_cli.model_switch import MODEL_ALIASES
except Exception:
return None
identity = MODEL_ALIASES.get(name_lower)
if identity is None:
return None
vendor = identity.vendor
family = identity.family
def _match(provider: str) -> Optional[str]:
models = _PROVIDER_MODELS.get(provider, [])
if not models:
return None
prefix = (
f"{vendor}/{family}"
if provider in _AGGREGATOR_PROVIDERS
else family
).lower()
for model in models:
if model.lower().startswith(prefix):
return model
return None
for provider in current_keys:
if matched := _match(provider):
return provider, matched
for provider in _PROVIDER_MODELS:
if provider in current_keys or provider in _AGGREGATOR_PROVIDERS:
continue
if matched := _match(provider):
return provider, matched
for provider in _AGGREGATOR_PROVIDERS:
if provider in current_keys and (matched := _match(provider)):
return provider, matched
return None
def detect_static_provider_for_model(
model_name: str,
current_provider: str,
) -> Optional[tuple[str, str]]:
"""Auto-detect a provider from static catalogs only.
Returns ``(provider_id, model_name)``. The model name may be remapped
when a static alias or bare provider name resolves to a catalog default.
Returns ``None`` when no confident match is found.
"""
name = (model_name or "").strip()
if not name:
return None
name_lower = name.lower()
current_keys = _provider_keys(current_provider)
alias_match = _resolve_static_model_alias(name_lower, current_keys)
if alias_match:
return alias_match
# --- Step 0: bare provider name typed as model ---
# If someone types `/model nous` or `/model anthropic`, treat it as a
# provider switch and pick the first model from that provider's catalog.
# Skip "custom" and "openrouter" — custom has no model catalog, and
# openrouter requires an explicit model name to be useful.
resolved_provider = _PROVIDER_ALIASES.get(name_lower, name_lower)
if resolved_provider not in {"custom", "openrouter"}:
default_models = _PROVIDER_MODELS.get(resolved_provider, [])
if (
resolved_provider in _PROVIDER_LABELS
and default_models
and resolved_provider not in current_keys
):
return (resolved_provider, default_models[0])
# Aggregators list other providers' models — never auto-switch TO them
# If the model belongs to the current provider's catalog, don't suggest switching
if _model_in_provider_catalog(name_lower, current_keys):
return None
# --- Step 1: check static provider catalogs for a direct match ---
for pid, models in _PROVIDER_MODELS.items():
if pid in current_keys or pid in _AGGREGATOR_PROVIDERS:
continue
if any(name_lower == m.lower() for m in models):
return (pid, name)
return None
def detect_provider_for_model(
model_name: str,
current_provider: str,
@@ -1536,19 +1391,86 @@ def detect_provider_for_model(
Priority:
0. Bare provider name switch to that provider's default model
1. Direct provider static catalog match
2. OpenRouter catalog match
1. Direct provider with credentials (highest)
2. Direct provider without credentials remap to OpenRouter slug
3. OpenRouter catalog match
"""
name = (model_name or "").strip()
if not name:
return None
static_match = detect_static_provider_for_model(name, current_provider)
if static_match:
return static_match
if _model_in_provider_catalog(name.lower(), _provider_keys(current_provider)):
name_lower = name.lower()
# --- Step 0: bare provider name typed as model ---
# If someone types `/model nous` or `/model anthropic`, treat it as a
# provider switch and pick the first model from that provider's catalog.
# Skip "custom" and "openrouter" — custom has no model catalog, and
# openrouter requires an explicit model name to be useful.
resolved_provider = _PROVIDER_ALIASES.get(name_lower, name_lower)
if resolved_provider not in {"custom", "openrouter"}:
default_models = _PROVIDER_MODELS.get(resolved_provider, [])
if (
resolved_provider in _PROVIDER_LABELS
and default_models
and resolved_provider != normalize_provider(current_provider)
):
return (resolved_provider, default_models[0])
# Aggregators list other providers' models — never auto-switch TO them
_AGGREGATORS = {"nous", "openrouter", "ai-gateway", "copilot", "kilocode"}
# If the model belongs to the current provider's catalog, don't suggest switching
current_models = _PROVIDER_MODELS.get(current_provider, [])
if any(name_lower == m.lower() for m in current_models):
return None
# --- Step 1: check static provider catalogs for a direct match ---
direct_match: Optional[str] = None
for pid, models in _PROVIDER_MODELS.items():
if pid == current_provider or pid in _AGGREGATORS:
continue
if any(name_lower == m.lower() for m in models):
direct_match = pid
break
if direct_match:
# Check if we have credentials for this provider — env vars,
# credential pool, or auth store entries.
has_creds = False
try:
from hermes_cli.auth import PROVIDER_REGISTRY
pconfig = PROVIDER_REGISTRY.get(direct_match)
if pconfig:
for env_var in pconfig.api_key_env_vars:
if os.getenv(env_var, "").strip():
has_creds = True
break
except Exception:
pass
# Also check credential pool and auth store — covers OAuth,
# Claude Code tokens, and other non-env-var credentials (#10300).
if not has_creds:
try:
from agent.credential_pool import load_pool
pool = load_pool(direct_match)
if pool.has_credentials():
has_creds = True
except Exception:
pass
if not has_creds:
try:
from hermes_cli.auth import _load_auth_store
store = _load_auth_store()
if direct_match in store.get("providers", {}) or direct_match in store.get("credential_pool", {}):
has_creds = True
except Exception:
pass
# Always return the direct provider match. If credentials are
# missing, the client init will give a clear error rather than
# silently routing through the wrong provider (#10300).
return (direct_match, name)
# --- Step 2: check OpenRouter catalog ---
# First try exact match (handles provider/model format)
or_slug = _find_openrouter_slug(name)
@@ -2649,8 +2571,8 @@ def validate_requested_model(
)
return {
"accepted": True,
"persist": True,
"accepted": False,
"persist": False,
"recognized": False,
"message": message,
}
+8 -16
View File
@@ -9,7 +9,6 @@ from typing import Dict, Iterable, Optional, Set
from hermes_cli.auth import get_nous_auth_status
from hermes_cli.config import get_env_value, load_config
from tools.managed_tool_gateway import is_managed_tool_gateway_ready
from utils import is_truthy_value
from tools.tool_backend_helpers import (
fal_key_is_configured,
has_direct_modal_credentials,
@@ -26,13 +25,6 @@ _DEFAULT_PLATFORM_TOOLSETS = {
}
def _uses_gateway(section: object) -> bool:
"""Return True when a config section explicitly opts into the gateway."""
if not isinstance(section, dict):
return False
return is_truthy_value(section.get("use_gateway"), default=False)
@dataclass(frozen=True)
class NousFeatureState:
key: str
@@ -270,11 +262,11 @@ def get_nous_subscription_features(
# use_gateway flags — when True, the user explicitly opted into the
# Tool Gateway via `hermes model`, so direct credentials should NOT
# prevent gateway routing.
web_use_gateway = _uses_gateway(web_cfg)
tts_use_gateway = _uses_gateway(tts_cfg)
browser_use_gateway = _uses_gateway(browser_cfg)
web_use_gateway = bool(web_cfg.get("use_gateway"))
tts_use_gateway = bool(tts_cfg.get("use_gateway"))
browser_use_gateway = bool(browser_cfg.get("use_gateway"))
image_gen_cfg = config.get("image_gen") if isinstance(config.get("image_gen"), dict) else {}
image_use_gateway = _uses_gateway(image_gen_cfg)
image_use_gateway = bool(image_gen_cfg.get("use_gateway"))
direct_exa = bool(get_env_value("EXA_API_KEY"))
direct_firecrawl = bool(get_env_value("FIRECRAWL_API_KEY") or get_env_value("FIRECRAWL_API_URL"))
@@ -609,10 +601,10 @@ def get_gateway_eligible_tools(
# no direct keys exist — we only skip the prompt for tools where
# use_gateway was explicitly set.
opted_in = {
"web": _uses_gateway(config.get("web")),
"image_gen": _uses_gateway(config.get("image_gen")),
"tts": _uses_gateway(config.get("tts")),
"browser": _uses_gateway(config.get("browser")),
"web": bool((config.get("web") if isinstance(config.get("web"), dict) else {}).get("use_gateway")),
"image_gen": bool((config.get("image_gen") if isinstance(config.get("image_gen"), dict) else {}).get("use_gateway")),
"tts": bool((config.get("tts") if isinstance(config.get("tts"), dict) else {}).get("use_gateway")),
"browser": bool((config.get("browser") if isinstance(config.get("browser"), dict) else {}).get("use_gateway")),
}
unconfigured: list[str] = []
-202
View File
@@ -1,202 +0,0 @@
"""Oneshot (-z) mode: send a prompt, get the final content block, exit.
Bypasses cli.py entirely. No banner, no spinner, no session_id line,
no stderr chatter. Just the agent's final text to stdout.
Toolsets = whatever the user has configured for "cli" in `hermes tools`.
Rules / memory / AGENTS.md / preloaded skills = same as a normal chat turn.
Approvals = auto-bypassed (HERMES_YOLO_MODE=1 is set for the call).
Working directory = the user's CWD (AGENTS.md etc. resolve from there as usual).
Model / provider selection mirrors `hermes chat`:
- Both optional. If omitted, use the user's configured default.
- If both given, pair them exactly as given.
- If only --model given, auto-detect the provider that serves it.
- If only --provider given, error out (ambiguous caller must pick a model).
Env var fallbacks (used when the corresponding arg is not passed):
- HERMES_INFERENCE_MODEL
- HERMES_INFERENCE_PROVIDER (already read by resolve_runtime_provider)
"""
from __future__ import annotations
import logging
import os
import sys
from contextlib import redirect_stderr, redirect_stdout
from typing import Optional
def run_oneshot(
prompt: str,
model: Optional[str] = None,
provider: Optional[str] = None,
) -> int:
"""Execute a single prompt and print only the final content block.
Args:
prompt: The user message to send.
model: Optional model override. Falls back to HERMES_INFERENCE_MODEL
env var, then config.yaml's model.default / model.model.
provider: Optional provider override. Falls back to
HERMES_INFERENCE_PROVIDER env var, then config.yaml's model.provider,
then "auto".
Returns the exit code. Caller should sys.exit() with the return.
"""
# Silence every stdlib logger for the duration. AIAgent, tools, and
# provider adapters all log to stderr through the root logger; file
# handlers added by setup_logging() keep working (they're attached to
# the root logger's handler list, not affected by level), but no
# bytes reach the terminal.
logging.disable(logging.CRITICAL)
# --provider without --model is ambiguous: carrying the user's configured
# model across to a different provider is usually wrong (that provider may
# not host it), and silently picking the provider's catalog default hides
# the mismatch. Require the caller to be explicit. Validate BEFORE the
# stderr redirect so the message actually reaches the terminal.
env_model_early = os.getenv("HERMES_INFERENCE_MODEL", "").strip()
if provider and not ((model or "").strip() or env_model_early):
sys.stderr.write(
"hermes -z: --provider requires --model (or HERMES_INFERENCE_MODEL). "
"Pass both explicitly, or neither to use your configured defaults.\n"
)
return 2
# Auto-approve any shell / tool approvals. Non-interactive by
# definition — a prompt would hang forever.
os.environ["HERMES_YOLO_MODE"] = "1"
os.environ["HERMES_ACCEPT_HOOKS"] = "1"
# Redirect stderr AND stdout to devnull for the entire call tree.
# We'll print the final response to the real stdout at the end.
real_stdout = sys.stdout
devnull = open(os.devnull, "w")
try:
with redirect_stdout(devnull), redirect_stderr(devnull):
response = _run_agent(prompt, model=model, provider=provider)
finally:
try:
devnull.close()
except Exception:
pass
if response:
real_stdout.write(response)
if not response.endswith("\n"):
real_stdout.write("\n")
real_stdout.flush()
return 0
def _run_agent(
prompt: str,
model: Optional[str] = None,
provider: Optional[str] = None,
) -> str:
"""Build an AIAgent exactly like a normal CLI chat turn would, then
run a single conversation. Returns the final response string."""
# Imports are local so they don't run when hermes is invoked for
# other commands (keeps top-level CLI startup cheap).
from hermes_cli.config import load_config
from hermes_cli.models import detect_provider_for_model
from hermes_cli.runtime_provider import resolve_runtime_provider
from hermes_cli.tools_config import _get_platform_tools
from run_agent import AIAgent
cfg = load_config()
# Resolve effective model: explicit arg → env var → config.
model_cfg = cfg.get("model") or {}
if isinstance(model_cfg, str):
cfg_model = model_cfg
else:
cfg_model = model_cfg.get("default") or model_cfg.get("model") or ""
env_model = os.getenv("HERMES_INFERENCE_MODEL", "").strip()
effective_model = (model or "").strip() or env_model or cfg_model
# Resolve effective provider: explicit arg → (auto-detect from model if
# model was explicit) → env / config (handled inside resolve_runtime_provider).
#
# When --model is given without --provider, auto-detect the provider that
# serves that model — same semantic as `/model <name>` in an interactive
# session. Without this, resolve_runtime_provider() would fall back to
# the user's configured default provider, which may not host the model
# the caller just asked for.
effective_provider = (provider or "").strip() or None
if effective_provider is None and (model or env_model):
# Only auto-detect when the model was explicitly requested via arg or
# env var (not when it came from config — that's the "use my defaults"
# path and the configured provider is already correct).
explicit_model = (model or "").strip() or env_model
if explicit_model:
cfg_provider = ""
if isinstance(model_cfg, dict):
cfg_provider = str(model_cfg.get("provider") or "").strip().lower()
current_provider = (
cfg_provider
or os.getenv("HERMES_INFERENCE_PROVIDER", "").strip().lower()
or "auto"
)
detected = detect_provider_for_model(explicit_model, current_provider)
if detected:
effective_provider, effective_model = detected
runtime = resolve_runtime_provider(
requested=effective_provider,
target_model=effective_model or None,
)
# Pull in whatever toolsets the user has enabled for "cli".
# sorted() gives stable ordering; set→list for AIAgent's signature.
toolsets_list = sorted(_get_platform_tools(cfg, "cli"))
agent = AIAgent(
api_key=runtime.get("api_key"),
base_url=runtime.get("base_url"),
provider=runtime.get("provider"),
api_mode=runtime.get("api_mode"),
model=effective_model,
enabled_toolsets=toolsets_list,
quiet_mode=True,
platform="cli",
credential_pool=runtime.get("credential_pool"),
# Interactive callbacks are intentionally NOT wired beyond this
# one. In oneshot mode there's no user sitting at a terminal:
# - clarify → returns a synthetic "pick a default" instruction
# so the agent continues instead of stalling on
# the tool's built-in "not available" error
# - sudo password prompt → terminal_tool gates on
# HERMES_INTERACTIVE which we never set
# - shell-hook approval → auto-approved via HERMES_ACCEPT_HOOKS=1
# (set above); also falls back to deny on non-tty
# - dangerous-command approval → bypassed via HERMES_YOLO_MODE=1
# - skill secret capture → returns gracefully when no callback set
clarify_callback=_oneshot_clarify_callback,
)
# Belt-and-braces: make sure AIAgent doesn't invoke any streaming
# display callbacks that would bypass our stdout capture.
agent.suppress_status_output = True
agent.stream_delta_callback = None
agent.tool_gen_callback = None
return agent.chat(prompt) or ""
def _oneshot_clarify_callback(question: str, choices=None) -> str:
"""Clarify is disabled in oneshot mode — tell the agent to pick a
default and proceed instead of stalling or erroring."""
if choices:
return (
f"[oneshot mode: no user available. Pick the best option from "
f"{choices} using your own judgment and continue.]"
)
return (
"[oneshot mode: no user available. Make the most reasonable "
"assumption you can and continue.]"
)
-1
View File
@@ -36,7 +36,6 @@ PLATFORMS: OrderedDict[str, PlatformInfo] = OrderedDict([
("wecom_callback", PlatformInfo(label="💬 WeCom Callback", default_toolset="hermes-wecom-callback")),
("weixin", PlatformInfo(label="💬 Weixin", default_toolset="hermes-weixin")),
("qqbot", PlatformInfo(label="💬 QQBot", default_toolset="hermes-qqbot")),
("yuanbao", PlatformInfo(label="🤖 Yuanbao", default_toolset="hermes-yuanbao")),
("webhook", PlatformInfo(label="🔗 Webhook", default_toolset="hermes-webhook")),
("api_server", PlatformInfo(label="🌐 API Server", default_toolset="hermes-api-server")),
("cron", PlatformInfo(label="⏰ Cron", default_toolset="hermes-cron")),
-6
View File
@@ -167,12 +167,6 @@ HERMES_OVERLAYS: Dict[str, HermesOverlay] = {
transport="openai_chat",
base_url_env_var="OLLAMA_BASE_URL",
),
# Azure Foundry: supports both OpenAI-style and Anthropic-style endpoints.
# The transport is determined at runtime from config.yaml model.api_mode.
"azure-foundry": HermesOverlay(
transport="openai_chat", # default; overridden by api_mode in config
base_url_env_var="AZURE_FOUNDRY_BASE_URL",
),
}
-229
View File
@@ -1,229 +0,0 @@
"""PTY bridge for `hermes dashboard` chat tab.
Wraps a child process behind a pseudo-terminal so its ANSI output can be
streamed to a browser-side terminal emulator (xterm.js) and typed
keystrokes can be fed back in. The only caller today is the
``/api/pty`` WebSocket endpoint in ``hermes_cli.web_server``.
Design constraints:
* **POSIX-only.** Hermes Agent supports Windows exclusively via WSL, which
exposes a native POSIX PTY via ``openpty(3)``. Native Windows Python
has no PTY; :class:`PtyUnavailableError` is raised with a user-readable
install/platform message so the dashboard can render a banner instead of
crashing.
* **Zero Node dependency on the server side.** We use :mod:`ptyprocess`,
which is a pure-Python wrapper around the OS calls. The browser talks
to the same ``hermes --tui`` binary it would launch from the CLI, so
every TUI feature (slash popover, model picker, tool rows, markdown,
skin engine, clarify/sudo/approval prompts) ships automatically.
* **Byte-safe I/O.** Reads and writes go through the PTY master fd
directly we avoid :class:`ptyprocess.PtyProcessUnicode` because
streaming ANSI is inherently byte-oriented and UTF-8 boundaries may land
mid-read.
"""
from __future__ import annotations
import errno
import fcntl
import os
import select
import signal
import struct
import sys
import termios
import time
from typing import Optional, Sequence
try:
import ptyprocess # type: ignore
_PTY_AVAILABLE = not sys.platform.startswith("win")
except ImportError: # pragma: no cover - dev env without ptyprocess
ptyprocess = None # type: ignore
_PTY_AVAILABLE = False
__all__ = ["PtyBridge", "PtyUnavailableError"]
class PtyUnavailableError(RuntimeError):
"""Raised when a PTY cannot be created on this platform.
Today this means native Windows (no ConPTY bindings) or a dev
environment missing the ``ptyprocess`` dependency. The dashboard
surfaces the message to the user as a chat-tab banner.
"""
class PtyBridge:
"""Thin wrapper around ``ptyprocess.PtyProcess`` for byte streaming.
Not thread-safe. A single bridge is owned by the WebSocket handler
that spawned it; the reader runs in an executor thread while writes
happen on the event-loop thread. Both sides are OK because the
kernel PTY is the actual synchronization point we never call
:mod:`ptyprocess` methods concurrently, we only call ``os.read`` and
``os.write`` on the master fd, which is safe.
"""
def __init__(self, proc: "ptyprocess.PtyProcess"): # type: ignore[name-defined]
self._proc = proc
self._fd: int = proc.fd
self._closed = False
# -- lifecycle --------------------------------------------------------
@classmethod
def is_available(cls) -> bool:
"""True if a PTY can be spawned on this platform."""
return bool(_PTY_AVAILABLE)
@classmethod
def spawn(
cls,
argv: Sequence[str],
*,
cwd: Optional[str] = None,
env: Optional[dict] = None,
cols: int = 80,
rows: int = 24,
) -> "PtyBridge":
"""Spawn ``argv`` behind a new PTY and return a bridge.
Raises :class:`PtyUnavailableError` if the platform can't host a
PTY. Raises :class:`FileNotFoundError` or :class:`OSError` for
ordinary exec failures (missing binary, bad cwd, etc.).
"""
if not _PTY_AVAILABLE:
if sys.platform.startswith("win"):
raise PtyUnavailableError(
"Pseudo-terminals are unavailable on this platform. "
"Hermes Agent supports Windows only via WSL."
)
if ptyprocess is None:
raise PtyUnavailableError(
"The `ptyprocess` package is missing. "
"Install with: pip install ptyprocess "
"(or pip install -e '.[pty]')."
)
raise PtyUnavailableError("Pseudo-terminals are unavailable.")
# Let caller-supplied env fully override inheritance; if they pass
# None we inherit the server's env (same semantics as subprocess).
spawn_env = os.environ.copy() if env is None else env
proc = ptyprocess.PtyProcess.spawn( # type: ignore[union-attr]
list(argv),
cwd=cwd,
env=spawn_env,
dimensions=(rows, cols),
)
return cls(proc)
@property
def pid(self) -> int:
return int(self._proc.pid)
def is_alive(self) -> bool:
if self._closed:
return False
try:
return bool(self._proc.isalive())
except Exception:
return False
# -- I/O --------------------------------------------------------------
def read(self, timeout: float = 0.2) -> Optional[bytes]:
"""Read up to 64 KiB of raw bytes from the PTY master.
Returns:
* bytes zero or more bytes of child output
* empty bytes (``b""``) no data available within ``timeout``
* None child has exited and the master fd is at EOF
Never blocks longer than ``timeout`` seconds. Safe to call after
:meth:`close`; returns ``None`` in that case.
"""
if self._closed:
return None
try:
readable, _, _ = select.select([self._fd], [], [], timeout)
except (OSError, ValueError):
return None
if not readable:
return b""
try:
data = os.read(self._fd, 65536)
except OSError as exc:
# EIO on Linux = slave side closed. EBADF = already closed.
if exc.errno in (errno.EIO, errno.EBADF):
return None
raise
if not data:
return None
return data
def write(self, data: bytes) -> None:
"""Write raw bytes to the PTY master (i.e. the child's stdin)."""
if self._closed or not data:
return
# os.write can return a short write under load; loop until drained.
view = memoryview(data)
while view:
try:
n = os.write(self._fd, view)
except OSError as exc:
if exc.errno in (errno.EIO, errno.EBADF, errno.EPIPE):
return
raise
if n <= 0:
return
view = view[n:]
def resize(self, cols: int, rows: int) -> None:
"""Forward a terminal resize to the child via ``TIOCSWINSZ``."""
if self._closed:
return
# struct winsize: rows, cols, xpixel, ypixel (all unsigned short)
winsize = struct.pack("HHHH", max(1, rows), max(1, cols), 0, 0)
try:
fcntl.ioctl(self._fd, termios.TIOCSWINSZ, winsize)
except OSError:
pass
# -- teardown ---------------------------------------------------------
def close(self) -> None:
"""Terminate the child (SIGTERM → 0.5s grace → SIGKILL) and close fds.
Idempotent. Reaping the child is important so we don't leak
zombies across the lifetime of the dashboard process.
"""
if self._closed:
return
self._closed = True
# SIGHUP is the conventional "your terminal went away" signal.
# We escalate if the child ignores it.
for sig in (signal.SIGHUP, signal.SIGTERM, signal.SIGKILL):
if not self._proc.isalive():
break
try:
self._proc.kill(sig)
except Exception:
pass
deadline = time.monotonic() + 0.5
while self._proc.isalive() and time.monotonic() < deadline:
time.sleep(0.02)
try:
self._proc.close(force=True)
except Exception:
pass
# Context-manager sugar — handy in tests and ad-hoc scripts.
def __enter__(self) -> "PtyBridge":
return self
def __exit__(self, *_exc) -> None:
self.close()
+7 -148
View File
@@ -221,19 +221,6 @@ def _resolve_runtime_from_pool_entry(
elif provider == "copilot":
api_mode = _copilot_runtime_api_mode(model_cfg, getattr(entry, "runtime_api_key", ""))
base_url = base_url or PROVIDER_REGISTRY["copilot"].inference_base_url
elif provider == "azure-foundry":
# Azure Foundry: read api_mode and base_url from config
cfg_provider = str(model_cfg.get("provider") or "").strip().lower()
if cfg_provider == "azure-foundry":
cfg_base_url = str(model_cfg.get("base_url") or "").strip().rstrip("/")
if cfg_base_url:
base_url = cfg_base_url
configured_mode = _parse_api_mode(model_cfg.get("api_mode"))
if configured_mode:
api_mode = configured_mode
# For Anthropic-style endpoints, strip /v1 suffix
if api_mode == "anthropic_messages":
base_url = re.sub(r"/v1/?$", "", base_url)
else:
configured_provider = str(model_cfg.get("provider") or "").strip().lower()
# Honour model.base_url from config.yaml when the configured provider
@@ -602,71 +589,6 @@ def _resolve_openrouter_runtime(
}
def _resolve_azure_foundry_runtime(
*,
requested_provider: str,
model_cfg: Dict[str, Any],
explicit_api_key: Optional[str] = None,
explicit_base_url: Optional[str] = None,
) -> Dict[str, Any]:
"""Resolve an Azure Foundry runtime entry.
Reads ``model.base_url`` + ``model.api_mode`` from config.yaml (or
explicit overrides), pulls the API key from ``.env`` / env var, and
strips a trailing ``/v1`` for Anthropic-style endpoints because the
Anthropic SDK appends ``/v1/messages`` internally.
Raises :class:`AuthError` when required values are missing.
"""
explicit_api_key = str(explicit_api_key or "").strip()
explicit_base_url_clean = str(explicit_base_url or "").strip().rstrip("/")
cfg_provider = str(model_cfg.get("provider") or "").strip().lower()
cfg_base_url = ""
cfg_api_mode = "chat_completions"
if cfg_provider == "azure-foundry":
cfg_base_url = str(model_cfg.get("base_url") or "").strip().rstrip("/")
cfg_api_mode = _parse_api_mode(model_cfg.get("api_mode")) or "chat_completions"
env_base_url = os.getenv("AZURE_FOUNDRY_BASE_URL", "").strip().rstrip("/")
base_url = explicit_base_url_clean or cfg_base_url or env_base_url
if not base_url:
raise AuthError(
"Azure Foundry requires a base URL. Set it via 'hermes model' or "
"the AZURE_FOUNDRY_BASE_URL environment variable."
)
api_key = explicit_api_key
if not api_key:
try:
from hermes_cli.config import get_env_value
api_key = get_env_value("AZURE_FOUNDRY_API_KEY") or ""
except Exception:
api_key = ""
if not api_key:
api_key = os.getenv("AZURE_FOUNDRY_API_KEY", "").strip()
if not api_key:
raise AuthError(
"Azure Foundry requires an API key. Set AZURE_FOUNDRY_API_KEY in "
"~/.hermes/.env or run 'hermes model' to configure."
)
# Anthropic SDK appends /v1/messages itself, so strip any trailing /v1
# we inherited from the configured base_url to avoid double-/v1 paths.
if cfg_api_mode == "anthropic_messages":
base_url = re.sub(r"/v1/?$", "", base_url)
source = "explicit" if (explicit_api_key or explicit_base_url) else "config"
return {
"provider": "azure-foundry",
"api_mode": cfg_api_mode,
"base_url": base_url,
"api_key": api_key,
"source": source,
"requested_provider": requested_provider,
}
def _resolve_explicit_runtime(
*,
provider: str,
@@ -756,15 +678,6 @@ def _resolve_explicit_runtime(
"requested_provider": requested_provider,
}
# Azure Foundry: user-configured endpoint with selectable API mode
if provider == "azure-foundry":
return _resolve_azure_foundry_runtime(
requested_provider=requested_provider,
model_cfg=model_cfg,
explicit_api_key=explicit_api_key,
explicit_base_url=explicit_base_url,
)
pconfig = PROVIDER_REGISTRY.get(provider)
if pconfig and pconfig.auth_type == "api_key":
env_url = ""
@@ -833,40 +746,6 @@ def resolve_runtime_provider(
"""
requested_provider = resolve_requested_provider(requested)
# Azure Anthropic short-circuit: when explicitly targeting an Azure endpoint
# with provider="anthropic", bypass _resolve_named_custom_runtime (which would
# return provider="custom" with chat_completions api_mode and no valid key).
# Instead, use the Azure key directly with anthropic_messages api_mode.
_eff_base = (explicit_base_url or "").strip()
if requested_provider == "anthropic" and "azure.com" in _eff_base:
_azure_key = (
(explicit_api_key or "").strip()
or os.getenv("AZURE_ANTHROPIC_KEY", "").strip()
or os.getenv("ANTHROPIC_API_KEY", "").strip()
)
return {
"provider": "anthropic",
"api_mode": "anthropic_messages",
"base_url": _eff_base.rstrip("/"),
"api_key": _azure_key,
"source": "azure-explicit",
"requested_provider": requested_provider,
}
# Azure Foundry: user-configured endpoint with selectable API mode
# (OpenAI-style chat_completions or Anthropic-style anthropic_messages).
# Resolve before the custom-runtime / pool / generic paths so Azure
# config is always picked up from model.base_url + model.api_mode,
# regardless of whether the caller passed explicit_* args.
if requested_provider == "azure-foundry":
azure_runtime = _resolve_azure_foundry_runtime(
requested_provider=requested_provider,
model_cfg=_get_model_config(),
explicit_api_key=explicit_api_key,
explicit_base_url=explicit_base_url,
)
return azure_runtime
custom_runtime = _resolve_named_custom_runtime(
requested_provider=requested_provider,
explicit_api_key=explicit_api_key,
@@ -1045,6 +924,13 @@ def resolve_runtime_provider(
# Anthropic (native Messages API)
if provider == "anthropic":
from agent.anthropic_adapter import resolve_anthropic_token
token = resolve_anthropic_token()
if not token:
raise AuthError(
"No Anthropic credentials found. Set ANTHROPIC_TOKEN or ANTHROPIC_API_KEY, "
"run 'claude setup-token', or authenticate with 'claude /login'."
)
# Allow base URL override from config.yaml model.base_url, but only
# when the configured provider is anthropic — otherwise a non-Anthropic
# base_url (e.g. Codex endpoint) would leak into Anthropic requests.
@@ -1053,33 +939,6 @@ def resolve_runtime_provider(
if cfg_provider == "anthropic":
cfg_base_url = (model_cfg.get("base_url") or "").strip().rstrip("/")
base_url = cfg_base_url or "https://api.anthropic.com"
# For Azure AI Foundry endpoints, use ANTHROPIC_API_KEY directly —
# Claude Code OAuth tokens (sk-ant-oat01) are not accepted by Azure.
# Azure keys don't start with "sk-ant-" so resolve_anthropic_token()
# would find the Claude Code OAuth token first (priority 3) and return
# that instead, causing 401s. Detect Azure endpoints and use the env
# key directly to bypass the OAuth priority chain.
_is_azure_endpoint = "azure.com" in base_url.lower() or (
cfg_base_url and "azure.com" in cfg_base_url.lower()
)
if _is_azure_endpoint:
token = (
os.getenv("AZURE_ANTHROPIC_KEY", "").strip()
or os.getenv("ANTHROPIC_API_KEY", "").strip()
)
if not token:
raise AuthError(
"No Azure Anthropic API key found. Set AZURE_ANTHROPIC_KEY or ANTHROPIC_API_KEY."
)
else:
from agent.anthropic_adapter import resolve_anthropic_token
token = resolve_anthropic_token()
if not token:
raise AuthError(
"No Anthropic credentials found. Set ANTHROPIC_TOKEN or ANTHROPIC_API_KEY, "
"run 'claude setup-token', or authenticate with 'claude /login'."
)
return {
"provider": "anthropic",
"api_mode": "anthropic_messages",
+63 -96
View File
@@ -1856,32 +1856,27 @@ def _setup_slack():
if existing:
print_info("Slack: already configured")
if not prompt_yes_no("Reconfigure Slack?", False):
# Even without reconfiguring, offer to refresh the manifest so
# new commands (e.g. /btw, /stop, ...) get registered in Slack.
if prompt_yes_no(
"Regenerate the Slack app manifest with the latest command "
"list? (recommended after `hermes update`)",
True,
):
_write_slack_manifest_and_instruct()
return
print_info("Steps to create a Slack app:")
print_info(" 1. Go to https://api.slack.com/apps → Create New App")
print_info(" Pick 'From an app manifest' — we'll generate one for you below.")
print_info(" 1. Go to https://api.slack.com/apps → Create New App (from scratch)")
print_info(" 2. Enable Socket Mode: Settings → Socket Mode → Enable")
print_info(" • Create an App-Level Token with 'connections:write' scope")
print_info(" 3. Install to Workspace: Settings → Install App")
print_info(" 4. After installing, invite the bot to channels: /invite @YourBot")
print_info(" 3. Add Bot Token Scopes: Features → OAuth & Permissions")
print_info(" Required scopes: chat:write, app_mentions:read,")
print_info(" channels:history, channels:read, im:history,")
print_info(" im:read, im:write, users:read, files:read, files:write")
print_info(" Optional for private channels: groups:history")
print_info(" 4. Subscribe to Events: Features → Event Subscriptions → Enable")
print_info(" Required events: message.im, message.channels, app_mention")
print_info(" Optional for private channels: message.groups")
print_warning(" ⚠ Without message.channels the bot will ONLY work in DMs,")
print_warning(" not public channels.")
print_info(" 5. Install to Workspace: Settings → Install App")
print_info(" 6. Reinstall the app after any scope or event changes")
print_info(" 7. After installing, invite the bot to channels: /invite @YourBot")
print()
print_info(" Full guide: https://hermes-agent.nousresearch.com/docs/user-guide/messaging/slack/")
print()
# Generate and write manifest up-front so the user can paste it into
# the "Create from manifest" flow instead of clicking through scopes /
# events / slash commands one at a time.
_write_slack_manifest_and_instruct()
print()
bot_token = prompt("Slack Bot Token (xoxb-...)", password=True)
if not bot_token:
@@ -1907,49 +1902,6 @@ def _setup_slack():
print_info(" Set SLACK_ALLOW_ALL_USERS=true or GATEWAY_ALLOW_ALL_USERS=true only if you intentionally want open workspace access.")
def _write_slack_manifest_and_instruct():
"""Generate the Slack manifest, write it under HERMES_HOME, and print
paste-into-Slack instructions.
Exposed as its own helper so both the initial setup flow and the
"reconfigure? → no" branch can refresh the manifest without the user
re-entering tokens. Failures are non-fatal if the manifest write
fails for any reason, we print a warning and skip rather than abort
the whole Slack setup.
"""
try:
from hermes_cli.slack_cli import _build_full_manifest
from hermes_constants import get_hermes_home
manifest = _build_full_manifest(
bot_name="Hermes",
bot_description="Your Hermes agent on Slack",
)
target = Path(get_hermes_home()) / "slack-manifest.json"
target.parent.mkdir(parents=True, exist_ok=True)
import json as _json
target.write_text(
_json.dumps(manifest, indent=2, ensure_ascii=False) + "\n",
encoding="utf-8",
)
print_success(f"Slack app manifest written to: {target}")
print_info(
" Paste it into https://api.slack.com/apps → your app → Features "
"→ App Manifest → Edit, then Save. Slack will prompt to "
"reinstall if scopes or slash commands changed."
)
print_info(
" Re-run `hermes slack manifest --write` anytime to refresh after "
"Hermes adds new commands."
)
except Exception as exc: # pragma: no cover - best-effort UX helper
print_warning(f"Couldn't write Slack manifest: {exc}")
print_info(
" You can generate it manually later with: "
"hermes slack manifest --write"
)
def _setup_matrix():
"""Configure Matrix credentials."""
print_header("Matrix")
@@ -2133,12 +2085,6 @@ def _setup_feishu():
_gateway_setup_feishu()
def _setup_yuanbao():
"""Configure Yuanbao via gateway setup."""
from hermes_cli.gateway import _setup_yuanbao as _gateway_setup_yuanbao
_gateway_setup_yuanbao()
def _setup_wecom():
"""Configure WeCom (Enterprise WeChat) via gateway setup."""
from hermes_cli.gateway import _setup_wecom as _gateway_setup_wecom
@@ -2283,7 +2229,6 @@ _GATEWAY_PLATFORMS = [
("WhatsApp", "WHATSAPP_ENABLED", _setup_whatsapp),
("DingTalk", "DINGTALK_CLIENT_ID", _setup_dingtalk),
("Feishu / Lark", "FEISHU_APP_ID", _setup_feishu),
("Yuanbao", "YUANBAO_APP_ID", _setup_yuanbao),
("WeCom (Enterprise WeChat)", "WECOM_BOT_ID", _setup_wecom),
("WeCom Callback (Self-Built App)", "WECOM_CALLBACK_CORP_ID", _setup_wecom_callback),
("Weixin (WeChat)", "WEIXIN_ACCOUNT_ID", _setup_weixin),
@@ -2918,6 +2863,17 @@ SETUP_SECTIONS = [
("agent", "Agent Settings", setup_agent_settings),
]
# The returning-user menu intentionally omits standalone TTS because model setup
# already includes TTS selection and tools setup covers the rest of the provider
# configuration. Keep this list in the same order as the visible menu entries.
RETURNING_USER_MENU_SECTION_KEYS = [
"model",
"terminal",
"gateway",
"tools",
"agent",
]
def run_setup_wizard(args):
"""Run the interactive setup wizard.
@@ -2942,9 +2898,6 @@ def run_setup_wizard(args):
save_config(copy.deepcopy(DEFAULT_CONFIG))
print_success("Configuration reset to defaults.")
reconfigure_requested = bool(getattr(args, "reconfigure", False))
quick_requested = bool(getattr(args, "quick", False))
config = load_config()
hermes_home = get_hermes_home()
@@ -3036,36 +2989,50 @@ def run_setup_wizard(args):
migration_ran = False
if is_existing:
# Existing install — default is the full-wizard reconfigure flow.
# Every prompt shows the current value as its default, so pressing
# Enter keeps it. Opt into `--quick` for the narrow "just fill in
# missing items" flow (useful after a partial OpenClaw migration
# or when a required API key got cleared).
if quick_requested:
# ── Returning User Menu ──
print()
print_header("Welcome Back!")
print_success("You already have Hermes configured.")
print()
menu_choices = [
"Quick Setup - configure missing items only",
"Full Setup - reconfigure everything",
"Model & Provider",
"Terminal Backend",
"Messaging Platforms (Gateway)",
"Tools",
"Agent Settings",
"Exit",
]
choice = prompt_choice("What would you like to do?", menu_choices, 0)
if choice == 0:
# Quick setup
_run_quick_setup(config, hermes_home)
return
print()
print_header("Reconfigure")
print_success("You already have Hermes configured.")
print_info("Running the full wizard — each prompt shows your current value.")
print_info("Press Enter to keep it, or type a new value to change it.")
print_info("")
print_info("Tip: jump straight to a section with 'hermes setup model|terminal|")
print_info(" gateway|tools|agent', or fill only missing items with --quick.")
# Fall through to the "Full Setup — run all sections" block below.
# --reconfigure is now the default on existing installs; the flag
# is preserved for backwards compatibility but is a no-op here.
elif choice == 1:
# Full setup — fall through to run all sections
pass
elif choice == 7:
print_info("Exiting. Run 'hermes setup' again when ready.")
return
elif 2 <= choice <= 6:
# Individual section — map by key, not by position.
# SETUP_SECTIONS includes TTS but the returning-user menu skips it,
# so positional indexing (choice - 2) would dispatch the wrong section.
section_key = RETURNING_USER_MENU_SECTION_KEYS[choice - 2]
section = next((s for s in SETUP_SECTIONS if s[0] == section_key), None)
if section:
_, label, func = section
func(config)
save_config(config)
_print_setup_summary(config, hermes_home)
return
else:
# ── First-Time Setup ──
print()
# --reconfigure / --quick on a fresh install are meaningless — fall
# through to the normal first-time flow.
if reconfigure_requested or quick_requested:
print_info("No existing configuration found — running first-time setup.")
print()
# Offer OpenClaw migration before configuration begins
migration_ran = _offer_openclaw_migration(hermes_home)
if migration_ran:
+20 -230
View File
@@ -11,10 +11,9 @@ handler are thin wrappers that parse args and delegate.
"""
import json
import re
import shutil
from pathlib import Path
from typing import Any, Dict, List, Optional
from typing import Any, Dict, Optional
from rich.console import Console
from rich.panel import Panel
@@ -142,103 +141,6 @@ def _derive_category_from_install_path(install_path: str) -> str:
return "" if parent == "." else parent
# ---------------------------------------------------------------------------
# Interactive name/category resolution for URL-installed skills
# ---------------------------------------------------------------------------
_VALID_NAME_RE = re.compile(r"^[a-z][a-z0-9_-]*$")
_VALID_CATEGORY_RE = re.compile(r"^[a-z][a-z0-9_/-]*$")
def _is_valid_installed_skill_name(name: str) -> bool:
"""Accept identifier-shaped names, reject empty / sentinel-y values."""
if not isinstance(name, str):
return False
candidate = name.strip().lower()
if not candidate or candidate in {"skill", "readme", "index", "unnamed-skill"}:
return False
return bool(_VALID_NAME_RE.match(candidate))
def _existing_categories() -> List[str]:
"""Return sorted subdirectory names under ``~/.hermes/skills/`` that look
like category buckets (contain at least one ``SKILL.md`` somewhere below).
Used to suggest reusable categories when interactively installing from a
URL. Hidden dirs (``.hub``, ``.trash``) are skipped.
"""
from tools.skills_hub import SKILLS_DIR
out: List[str] = []
try:
for entry in SKILLS_DIR.iterdir():
if not entry.is_dir() or entry.name.startswith("."):
continue
# Only count as a category if it contains skills, not if it IS a skill.
# Heuristic: if ``<entry>/SKILL.md`` exists, it's a skill at the
# top level (no category); otherwise treat as a category bucket.
if (entry / "SKILL.md").exists():
continue
# Has at least one nested SKILL.md?
try:
if any(entry.rglob("SKILL.md")):
out.append(entry.name)
except OSError:
continue
except (FileNotFoundError, OSError):
return []
return sorted(set(out))
def _prompt_for_skill_name(c: Console, url: str, default: str = "") -> Optional[str]:
"""Prompt interactively for a skill name. Returns None on cancel/EOF."""
c.print()
c.print(
f"[yellow]The SKILL.md at {url} doesn't declare a `name:` in its "
f"frontmatter,[/]\n[yellow]and the URL path doesn't produce a valid "
f"identifier either.[/]"
)
default_hint = f" [{default}]" if default else ""
c.print(
f"[bold]Enter a skill name{default_hint}:[/] "
f"[dim](lowercase letters, digits, hyphens, underscores; starts with a letter)[/]"
)
try:
answer = input("Name: ").strip()
except (EOFError, KeyboardInterrupt):
return None
if not answer and default:
answer = default
if not _is_valid_installed_skill_name(answer):
c.print(f"[bold red]Invalid name:[/] {answer!r}. Aborting install.\n")
return None
return answer
def _prompt_for_category(c: Console, existing: List[str]) -> str:
"""Prompt interactively for a category. Empty/None input means flat install."""
c.print()
if existing:
c.print(
"[bold]Pick a category[/] "
"[dim](reuse an existing bucket, type a new one, or press Enter to install flat)[/]"
)
c.print(f"[dim]Existing: {', '.join(existing)}[/]")
else:
c.print(
"[bold]Category[/] [dim](optional — press Enter to install flat at ~/.hermes/skills/<name>/)[/]"
)
try:
answer = input("Category: ").strip()
except (EOFError, KeyboardInterrupt):
return ""
if not answer:
return ""
if not _VALID_CATEGORY_RE.match(answer):
c.print(f"[dim]Invalid category {answer!r} — installing flat.[/]")
return ""
return answer
def do_search(query: str, source: str = "all", limit: int = 10,
console: Optional[Console] = None) -> None:
"""Search registries and display results as a Rich table."""
@@ -407,17 +309,8 @@ def do_browse(page: int = 1, page_size: int = 20, source: str = "all",
def do_install(identifier: str, category: str = "", force: bool = False,
console: Optional[Console] = None, skip_confirm: bool = False,
invalidate_cache: bool = True,
name_override: str = "") -> None:
"""Fetch, quarantine, scan, confirm, and install a skill.
``name_override`` lets non-interactive callers (slash commands, gateway,
scripts) supply a skill name when the upstream SKILL.md lacks a valid
``name:`` frontmatter field. On interactive TTY surfaces, a missing name
triggers a prompt instead; ``skip_confirm=True`` means "non-interactive"
(so pair it with ``name_override`` when installing from a URL that has
no frontmatter).
"""
invalidate_cache: bool = True) -> None:
"""Fetch, quarantine, scan, confirm, and install a skill."""
from tools.skills_hub import (
GitHubAuth, create_source_router, ensure_hub_dirs,
quarantine_bundle, install_from_quarantine, HubLockFile,
@@ -461,58 +354,6 @@ def do_install(identifier: str, category: str = "", force: bool = False,
c.print()
return
# URL-sourced skills may arrive with an empty name when SKILL.md has no
# ``name:`` in frontmatter AND the URL path doesn't yield a valid
# identifier. Resolve by (1) --name override, (2) interactive prompt on
# a TTY, (3) refuse with an actionable error on non-interactive surfaces.
bundle_meta = getattr(bundle, "metadata", {}) or {}
if bundle.source == "url" and (not bundle.name or bundle_meta.get("awaiting_name")):
if name_override and _is_valid_installed_skill_name(name_override):
bundle.name = name_override.strip()
bundle_meta["awaiting_name"] = False
elif name_override:
c.print(
f"[bold red]Invalid --name:[/] {name_override!r}. "
"Must be a lowercase identifier (letters, digits, hyphens, "
"underscores; starts with a letter).\n"
)
return
elif skip_confirm:
# Non-interactive surface (slash command / TUI / gateway). Can't
# prompt — emit an actionable error.
url = bundle_meta.get("url") or identifier
c.print(
f"[bold red]Cannot install from URL:[/] {url}\n"
"[yellow]The SKILL.md has no `name:` in its frontmatter, "
"and the URL path doesn't produce a valid identifier.[/]\n\n"
"Retry with an explicit name:\n"
f" [bold]/skills install {url} --name <your-name>[/]\n"
f" [bold]hermes skills install {url} --name <your-name>[/]\n\n"
"[dim]Or ask the SKILL.md's author to add a `name:` field to "
"its YAML frontmatter.[/]\n"
)
return
else:
# Interactive TTY — prompt.
url = bundle_meta.get("url") or identifier
chosen = _prompt_for_skill_name(c, url)
if not chosen:
c.print("[dim]Installation cancelled.[/]\n")
return
bundle.name = chosen
bundle_meta["awaiting_name"] = False
# Keep SkillMeta in sync so downstream "already installed" checks,
# audit logs, and display all see the final name.
if meta is not None:
meta.name = bundle.name
meta.path = bundle.name
# URL-sourced skills: offer to pick a category interactively when the
# caller didn't specify one (TTY only — non-interactive installs fall
# through to flat install, matching all other sources).
if bundle.source == "url" and not category and not skip_confirm:
category = _prompt_for_category(c, _existing_categories())
# Auto-detect category for official skills (e.g. "official/autonomous-ai-agents/blackbox")
if bundle.source == "official" and not category:
id_parts = bundle.identifier.split("/") # ["official", "category", "skill"]
@@ -758,24 +599,11 @@ def inspect_skill(identifier: str) -> Optional[dict]:
return out
def do_list(source_filter: str = "all",
enabled_only: bool = False,
console: Optional[Console] = None) -> None:
"""List installed skills, distinguishing hub, builtin, and local skills.
Args:
source_filter: ``all`` | ``hub`` | ``builtin`` | ``local``.
enabled_only: If True, hide disabled skills from the output.
Enabled/disabled state is resolved against the currently active profile's
config ``hermes -p <profile> skills list`` reads that profile's
``skills.disabled`` list because ``-p`` swaps ``HERMES_HOME`` at process
start. No explicit profile flag needed here.
"""
def do_list(source_filter: str = "all", console: Optional[Console] = None) -> None:
"""List installed skills, distinguishing hub, builtin, and local skills."""
from tools.skills_hub import HubLockFile, ensure_hub_dirs
from tools.skills_sync import _read_manifest
from tools.skills_tool import _find_all_skills
from agent.skill_utils import get_disabled_skill_names
c = console or _console
ensure_hub_dirs()
@@ -783,26 +611,17 @@ def do_list(source_filter: str = "all",
hub_installed = {e["name"]: e for e in lock.list_installed()}
builtin_names = set(_read_manifest())
# Pull ALL skills (including disabled ones) so we can annotate status.
all_skills = _find_all_skills(skip_disabled=True)
disabled_names = get_disabled_skill_names()
all_skills = _find_all_skills()
title = "Installed Skills"
if enabled_only:
title += " (enabled only)"
table = Table(title=title)
table = Table(title="Installed Skills")
table.add_column("Name", style="bold cyan")
table.add_column("Category", style="dim")
table.add_column("Source", style="dim")
table.add_column("Trust", style="dim")
table.add_column("Status", style="dim")
hub_count = 0
builtin_count = 0
local_count = 0
enabled_count = 0
disabled_count = 0
for skill in sorted(all_skills, key=lambda s: (s.get("category") or "", s["name"])):
name = skill["name"]
@@ -813,48 +632,29 @@ def do_list(source_filter: str = "all",
source_type = "hub"
source_display = hub_entry.get("source", "hub")
trust = hub_entry.get("trust_level", "community")
hub_count += 1
elif name in builtin_names:
source_type = "builtin"
source_display = "builtin"
trust = "builtin"
builtin_count += 1
else:
source_type = "local"
source_display = "local"
trust = "local"
local_count += 1
if source_filter != "all" and source_filter != source_type:
continue
is_enabled = name not in disabled_names
if enabled_only and not is_enabled:
continue
if source_type == "hub":
hub_count += 1
elif source_type == "builtin":
builtin_count += 1
else:
local_count += 1
if is_enabled:
enabled_count += 1
status_cell = "[bold green]enabled[/]"
else:
disabled_count += 1
status_cell = "[dim red]disabled[/]"
trust_style = {"builtin": "bright_cyan", "trusted": "green", "community": "yellow", "local": "dim"}.get(trust, "dim")
trust_label = "official" if source_display == "official" else trust
table.add_row(name, category, source_display, f"[{trust_style}]{trust_label}[/]", status_cell)
table.add_row(name, category, source_display, f"[{trust_style}]{trust_label}[/]")
c.print(table)
summary = f"[dim]{hub_count} hub-installed, {builtin_count} builtin, {local_count} local"
if enabled_only:
summary += f"{enabled_count} enabled shown"
else:
summary += f"{enabled_count} enabled, {disabled_count} disabled"
summary += "[/]\n"
c.print(summary)
c.print(
f"[dim]{hub_count} hub-installed, {builtin_count} builtin, {local_count} local[/]\n"
)
def do_check(name: Optional[str] = None, console: Optional[Console] = None) -> None:
@@ -1323,15 +1123,11 @@ def skills_command(args) -> None:
do_search(args.query, source=args.source, limit=args.limit)
elif action == "install":
do_install(args.identifier, category=args.category, force=args.force,
skip_confirm=getattr(args, "yes", False),
name_override=getattr(args, "name", "") or "")
skip_confirm=getattr(args, "yes", False))
elif action == "inspect":
do_inspect(args.identifier)
elif action == "list":
do_list(
source_filter=args.source,
enabled_only=getattr(args, "enabled_only", False),
)
do_list(source_filter=args.source)
elif action == "check":
do_check(name=getattr(args, "name", None))
elif action == "update":
@@ -1381,7 +1177,6 @@ def handle_skills_slash(cmd: str, console: Optional[Console] = None) -> None:
/skills search kubernetes
/skills install openai/skills/skill-creator
/skills install openai/skills/skill-creator --force
/skills install https://example.com/path/SKILL.md
/skills inspect openai/skills/skill-creator
/skills list
/skills list --source hub
@@ -1458,11 +1253,10 @@ def handle_skills_slash(cmd: str, console: Optional[Console] = None) -> None:
elif action == "install":
if not args:
c.print("[bold red]Usage:[/] /skills install <identifier-or-url> [--name <name>] [--category <cat>] [--force] [--now]\n")
c.print("[bold red]Usage:[/] /skills install <identifier> [--category <cat>] [--force] [--now]\n")
return
identifier = args[0]
category = ""
name_override = ""
# Slash commands run inside prompt_toolkit where input() hangs.
# Always skip confirmation — the user typing the command is implicit consent.
skip_confirm = True
@@ -1473,11 +1267,9 @@ def handle_skills_slash(cmd: str, console: Optional[Console] = None) -> None:
for i, a in enumerate(args):
if a == "--category" and i + 1 < len(args):
category = args[i + 1]
elif a == "--name" and i + 1 < len(args):
name_override = args[i + 1]
do_install(identifier, category=category, force=force,
skip_confirm=skip_confirm, invalidate_cache=invalidate_cache,
name_override=name_override, console=c)
console=c)
elif action == "inspect":
if not args:
@@ -1487,12 +1279,11 @@ def handle_skills_slash(cmd: str, console: Optional[Console] = None) -> None:
elif action == "list":
source_filter = "all"
enabled_only = "--enabled-only" in args or "--enabled" in args
if "--source" in args:
idx = args.index("--source")
if idx + 1 < len(args):
source_filter = args[idx + 1]
do_list(source_filter=source_filter, enabled_only=enabled_only, console=c)
do_list(source_filter=source_filter, console=c)
elif action == "check":
name = args[0] if args else None
@@ -1580,8 +1371,7 @@ def _print_skills_help(console: Console) -> None:
" [cyan]search[/] <query> Search registries for skills\n"
" [cyan]install[/] <identifier> Install a skill (with security scan)\n"
" [cyan]inspect[/] <identifier> Preview a skill without installing\n"
" [cyan]list[/] [--source hub|builtin|local] [--enabled-only]\n"
" List installed skills; --enabled-only filters to the active profile's live set\n"
" [cyan]list[/] [--source hub|builtin|local] List installed skills\n"
" [cyan]check[/] [name] Check hub skills for upstream updates\n"
" [cyan]update[/] [name] Update hub skills with upstream changes\n"
" [cyan]audit[/] [name] Re-scan hub skills for security\n"
-152
View File
@@ -1,152 +0,0 @@
"""``hermes slack ...`` CLI subcommands.
Today only ``hermes slack manifest`` is implemented it generates the
Slack app manifest JSON for registering every gateway command as a native
Slack slash (``/btw``, ``/stop``, ``/model``, ) so users get the same
first-class slash UX Discord and Telegram already have.
Typical workflow::
$ hermes slack manifest > slack-manifest.json
# or:
$ hermes slack manifest --write
Then paste the printed JSON into the Slack app config (Features App
Manifest Edit) and click Save. Slack diffs the manifest and prompts
for reinstall when scopes/commands change.
"""
from __future__ import annotations
import json
import sys
from pathlib import Path
def _build_full_manifest(bot_name: str, bot_description: str) -> dict:
"""Build a full Slack manifest merging display info + our slash list.
The slash-command list is always generated from ``COMMAND_REGISTRY`` so
it stays in sync with the rest of Hermes. Other manifest sections
(display info, OAuth scopes, socket mode) are set to sensible defaults
for a Hermes deployment users can tweak them in the Slack UI after
pasting.
"""
from hermes_cli.commands import slack_app_manifest
partial = slack_app_manifest()
slashes = partial["features"]["slash_commands"]
return {
"_metadata": {
"major_version": 1,
"minor_version": 1,
},
"display_information": {
"name": bot_name[:35],
"description": (bot_description or "Your Hermes agent on Slack")[:140],
"background_color": "#1a1a2e",
},
"features": {
"bot_user": {
"display_name": bot_name[:80],
"always_online": True,
},
"slash_commands": slashes,
"assistant_view": {
"assistant_description": "Chat with Hermes in threads and DMs.",
},
},
"oauth_config": {
"scopes": {
"bot": [
"app_mentions:read",
"assistant:write",
"channels:history",
"channels:read",
"chat:write",
"commands",
"files:read",
"files:write",
"groups:history",
"im:history",
"im:read",
"im:write",
"users:read",
],
},
},
"settings": {
"event_subscriptions": {
"bot_events": [
"app_mention",
"assistant_thread_context_changed",
"assistant_thread_started",
"message.channels",
"message.groups",
"message.im",
],
},
"interactivity": {
"is_enabled": True,
},
"org_deploy_enabled": False,
"socket_mode_enabled": True,
"token_rotation_enabled": False,
},
}
def slack_manifest_command(args) -> int:
"""Print or write a Slack app manifest JSON.
Flags (all parsed in ``hermes_cli/main.py``):
--write [PATH] Write to file instead of stdout (default path:
``$HERMES_HOME/slack-manifest.json``)
--name NAME Override the bot display name (default: "Hermes")
--description DESC Override the bot description
--slashes-only Emit only the ``features.slash_commands`` array (for
merging into an existing manifest manually)
"""
name = getattr(args, "name", None) or "Hermes"
description = getattr(args, "description", None) or "Your Hermes agent on Slack"
if getattr(args, "slashes_only", False):
from hermes_cli.commands import slack_app_manifest
manifest = slack_app_manifest()["features"]["slash_commands"]
else:
manifest = _build_full_manifest(name, description)
payload = json.dumps(manifest, indent=2, ensure_ascii=False) + "\n"
write_target = getattr(args, "write", None)
if write_target is not None:
if isinstance(write_target, bool) and write_target:
# --write with no value → default location
try:
from hermes_constants import get_hermes_home
target = Path(get_hermes_home()) / "slack-manifest.json"
except Exception:
target = Path.home() / ".hermes" / "slack-manifest.json"
else:
target = Path(write_target).expanduser()
target.parent.mkdir(parents=True, exist_ok=True)
target.write_text(payload, encoding="utf-8")
print(f"Slack manifest written to: {target}", file=sys.stderr)
print(
"\nNext steps:\n"
" 1. Open https://api.slack.com/apps and pick your Hermes app\n"
" (or create a new one: Create New App → From an app manifest).\n"
f" 2. Features → App Manifest → paste the contents of\n"
f" {target}\n"
" 3. Save; Slack will prompt to reinstall the app if scopes or\n"
" slash commands changed.\n"
" 4. Make sure Socket Mode is enabled and you have a bot token\n"
" (xoxb-...) and app token (xapp-...) configured via\n"
" `hermes setup`.\n",
file=sys.stderr,
)
else:
sys.stdout.write(payload)
return 0
+1 -2
View File
@@ -326,8 +326,7 @@ def show_status(args):
"WeCom Callback": ("WECOM_CALLBACK_CORP_ID", None),
"Weixin": ("WEIXIN_ACCOUNT_ID", "WEIXIN_HOME_CHANNEL"),
"BlueBubbles": ("BLUEBUBBLES_SERVER_URL", "BLUEBUBBLES_HOME_CHANNEL"),
"QQBot": ("QQ_APP_ID", "QQ_HOME_CHANNEL"),
"Yuanbao": ("YUANBAO_APP_ID", "YUANBAO_HOME_CHANNEL"),
"QQBot": ("QQ_APP_ID", "QQBOT_HOME_CHANNEL"),
}
for name, (token_var, home_var) in platforms.items():
+4 -4
View File
@@ -20,10 +20,10 @@ def get_provider_request_timeout(
try:
from hermes_cli.config import load_config
config = load_config()
except Exception:
except ImportError:
return None
config = load_config()
providers = config.get("providers", {}) if isinstance(config, dict) else {}
provider_config = (
providers.get(provider_id, {}) if isinstance(providers, dict) else {}
@@ -49,10 +49,10 @@ def get_provider_stale_timeout(
try:
from hermes_cli.config import load_config
config = load_config()
except Exception:
except ImportError:
return None
config = load_config()
providers = config.get("providers", {}) if isinstance(config, dict) else {}
provider_config = (
providers.get(provider_id, {}) if isinstance(providers, dict) else {}
+3 -2
View File
@@ -10,7 +10,8 @@ import random
TIPS = [
# --- Slash Commands ---
"/background <prompt> (alias /bg or /btw) runs a task in a separate session while your current one stays free.",
"/btw <question> asks a quick side question without tools or history — great for clarifications.",
"/background <prompt> runs a task in a separate session while your current one stays free.",
"/branch forks the current session so you can explore a different direction without losing progress.",
"/compress manually compresses conversation context when things get long.",
"/rollback lists filesystem checkpoints — restore files the agent modified to any prior state.",
@@ -106,7 +107,7 @@ TIPS = [
"Set display.streaming: true to see tokens appear in real time as the model generates.",
"Set display.show_reasoning: true to watch the model's chain-of-thought reasoning.",
"Set display.compact: true to reduce whitespace in output for denser information.",
"Set display.busy_input_mode: queue to queue messages instead of interrupting the agent, or steer to inject them mid-run via /steer.",
"Set display.busy_input_mode: queue to queue messages instead of interrupting the agent.",
"Set display.resume_display: minimal to skip the full conversation recap on session resume.",
"Set compression.threshold: 0.50 to control when auto-compression fires (default: 50% of context).",
"Set agent.max_turns: 200 to let the agent take more tool-calling steps per turn.",
+22 -169
View File
@@ -11,7 +11,6 @@ the `platform_toolsets` key.
import json as _json
import logging
import os
import sys
from pathlib import Path
from typing import Dict, List, Optional, Set
@@ -26,7 +25,7 @@ from hermes_cli.nous_subscription import (
get_nous_subscription_features,
)
from tools.tool_backend_helpers import fal_key_is_configured, managed_nous_tools_enabled
from utils import base_url_hostname, is_truthy_value
from utils import base_url_hostname
logger = logging.getLogger(__name__)
@@ -69,59 +68,25 @@ CONFIGURABLE_TOOLSETS = [
("rl", "🧪 RL Training", "Tinker-Atropos training tools"),
("homeassistant", "🏠 Home Assistant", "smart home device control"),
("spotify", "🎵 Spotify", "playback, search, playlists, library"),
("discord", "💬 Discord (read/participate)", "fetch messages, search members, create thread"),
("discord_admin", "🛡️ Discord Server Admin", "list channels/roles, pin, assign roles"),
("yuanbao", "🤖 Yuanbao", "group info, member queries, DM"),
]
# Toolsets that are OFF by default for new installs.
# They're still in _HERMES_CORE_TOOLS (available at runtime if enabled),
# but the setup checklist won't pre-select them for first-time users.
_DEFAULT_OFF_TOOLSETS = {"moa", "homeassistant", "rl", "spotify", "discord", "discord_admin"}
# Platform-scoped toolsets: only appear in the `hermes tools` checklist for
# these platforms, and only resolve/save for these platforms. A toolset
# absent from this map is available on every platform (current behaviour).
#
# Use this for tools whose APIs only make sense on one platform (Discord
# server admin, Slack workspace admin, etc.). Keeps every other platform's
# checklist from filling up with irrelevant toggles.
_TOOLSET_PLATFORM_RESTRICTIONS: Dict[str, Set[str]] = {
"discord": {"discord"},
"discord_admin": {"discord"},
}
def _toolset_allowed_for_platform(ts_key: str, platform: str) -> bool:
"""Return True if ``ts_key`` is configurable on ``platform``.
Toolsets without a restriction entry are allowed everywhere (the default).
"""
allowed = _TOOLSET_PLATFORM_RESTRICTIONS.get(ts_key)
return allowed is None or platform in allowed
_DEFAULT_OFF_TOOLSETS = {"moa", "homeassistant", "rl", "spotify"}
def _get_effective_configurable_toolsets():
"""Return CONFIGURABLE_TOOLSETS + any plugin-provided toolsets.
Plugin toolsets are appended at the end so they appear after the
built-in toolsets in the TUI checklist. A plugin whose toolset key
already appears in ``CONFIGURABLE_TOOLSETS`` is skipped bundled
plugins (e.g. ``plugins/spotify``) share their toolset key with the
built-in entry, and we want the built-in label/description to win.
Without the dedupe, ``hermes tools`` "reconfigure existing" would
list the same toolset twice.
built-in toolsets in the TUI checklist.
"""
result = list(CONFIGURABLE_TOOLSETS)
seen = {ts_key for ts_key, _, _ in result}
try:
from hermes_cli.plugins import discover_plugins, get_plugin_toolsets
discover_plugins() # idempotent — ensures plugins are loaded
for entry in get_plugin_toolsets():
if entry[0] in seen:
continue
seen.add(entry[0])
result.append(entry)
result.extend(get_plugin_toolsets())
except Exception:
pass
return result
@@ -403,9 +368,13 @@ TOOL_CATEGORIES = {
"providers": [
{
"name": "Spotify Web API",
"tag": "PKCE OAuth — opens the setup wizard",
"env_vars": [],
"post_setup": "spotify",
"tag": "PKCE OAuth — run `hermes auth spotify` after this",
"env_vars": [
{"key": "HERMES_SPOTIFY_CLIENT_ID", "prompt": "Spotify app client_id",
"url": "https://developer.spotify.com/dashboard"},
{"key": "HERMES_SPOTIFY_REDIRECT_URI", "prompt": "Redirect URI (must be allow-listed in your Spotify app)",
"default": "http://127.0.0.1:43827/spotify/callback"},
],
},
],
},
@@ -509,35 +478,6 @@ def _run_post_setup(post_setup_key: str):
_print_warning(" kittentts install timed out (>5min)")
_print_info(f" Run manually: python -m pip install -U '{wheel_url}' soundfile")
elif post_setup_key == "spotify":
# Run the full `hermes auth spotify` flow — if the user has no
# client_id yet, this drops them into the interactive wizard
# (opens the Spotify dashboard, prompts for client_id, persists
# to ~/.hermes/.env), then continues straight into PKCE. If they
# already have an app, it skips the wizard and just does OAuth.
from types import SimpleNamespace
try:
from hermes_cli.auth import login_spotify_command
except Exception as exc:
_print_warning(f" Could not load Spotify auth: {exc}")
_print_info(" Run manually: hermes auth spotify")
return
_print_info(" Starting Spotify login...")
try:
login_spotify_command(SimpleNamespace(
client_id=None, redirect_uri=None, scope=None,
no_browser=False, timeout=None,
))
_print_success(" Spotify authenticated")
except SystemExit as exc:
# User aborted the wizard, or OAuth failed — don't fail the
# toolset enable; they can retry with `hermes auth spotify`.
_print_warning(f" Spotify login did not complete: {exc}")
_print_info(" Run later: hermes auth spotify")
except Exception as exc:
_print_warning(f" Spotify login failed: {exc}")
_print_info(" Run manually: hermes auth spotify")
elif post_setup_key == "rl_training":
try:
__import__("tinker_atropos")
@@ -626,7 +566,7 @@ def _get_platform_tools(
include_default_mcp_servers: bool = True,
) -> Set[str]:
"""Resolve which individual toolset names are enabled for a platform."""
from toolsets import resolve_toolset, TOOLSETS
from toolsets import resolve_toolset
platform_toolsets = config.get("platform_toolsets") or {}
toolset_names = platform_toolsets.get(platform)
@@ -640,8 +580,6 @@ def _get_platform_tools(
toolset_names = [str(ts) for ts in toolset_names]
configurable_keys = {ts_key for ts_key, _, _ in CONFIGURABLE_TOOLSETS}
plugin_ts_keys = _get_plugin_toolset_keys()
platform_default_keys = {p["default_toolset"] for p in PLATFORMS.values()}
# If the saved list contains any configurable keys directly, the user
# has explicitly configured this platform — use direct membership.
@@ -651,10 +589,7 @@ def _get_platform_tools(
has_explicit_config = any(ts in configurable_keys for ts in toolset_names)
if has_explicit_config:
enabled_toolsets = {
ts for ts in toolset_names
if ts in configurable_keys and _toolset_allowed_for_platform(ts, platform)
}
enabled_toolsets = {ts for ts in toolset_names if ts in configurable_keys}
else:
# No explicit config — fall back to resolving composite toolset names
# (e.g. "hermes-cli") to individual tool names and reverse-mapping.
@@ -664,61 +599,14 @@ def _get_platform_tools(
enabled_toolsets = set()
for ts_key, _, _ in CONFIGURABLE_TOOLSETS:
if not _toolset_allowed_for_platform(ts_key, platform):
continue
ts_tools = set(resolve_toolset(ts_key))
if ts_tools and ts_tools.issubset(all_tool_names):
enabled_toolsets.add(ts_key)
default_off = set(_DEFAULT_OFF_TOOLSETS)
# Legacy safety: if the platform's own name matches a default-off
# toolset (e.g. `homeassistant` platform + `homeassistant` toolset),
# keep that toolset enabled on first install. Skip this dodge for
# platform-restricted toolsets — those are always opt-in even on
# their own platform (e.g. `discord` + `discord` should stay OFF).
if platform in default_off and platform not in _TOOLSET_PLATFORM_RESTRICTIONS:
if platform in default_off:
default_off.remove(platform)
# Home Assistant is already runtime-gated by its check_fn (requires
# HASS_TOKEN to register any tools). When a user has configured
# HASS_TOKEN, they've explicitly opted in — don't also strip it via
# _DEFAULT_OFF_TOOLSETS, which would silently drop HA from platforms
# (e.g. cron) that run through _get_platform_tools without an
# explicit saved toolset list. Without this, Norbert's HA cron jobs
# regressed after #14798 made cron honor per-platform tool config.
if "homeassistant" in default_off and os.getenv("HASS_TOKEN"):
default_off.remove("homeassistant")
enabled_toolsets -= default_off
# Recover non-configurable platform toolsets (e.g. discord, feishu_doc,
# feishu_drive). These are part of the platform's default composite but
# absent from CONFIGURABLE_TOOLSETS, so they can't appear in the TUI
# checklist or in a user-saved config. Must run in BOTH branches —
# otherwise saving via `hermes tools` (which flips has_explicit_config
# to True) silently drops them.
platform_tool_universe = set(resolve_toolset(PLATFORMS[platform]["default_toolset"]))
configurable_tool_universe = set()
for ck in configurable_keys:
configurable_tool_universe.update(resolve_toolset(ck))
claimed = set()
for ts_key in enabled_toolsets:
claimed.update(resolve_toolset(ts_key))
skip = configurable_keys | plugin_ts_keys | platform_default_keys
skip |= {k for k in TOOLSETS if k.startswith("hermes-")}
skip |= set(_DEFAULT_OFF_TOOLSETS) - {platform}
for ts_key, ts_def in TOOLSETS.items():
if ts_key in skip:
continue
if ts_def.get("includes"):
continue
ts_tools = set(resolve_toolset(ts_key))
if not ts_tools or not ts_tools.issubset(platform_tool_universe):
continue
if ts_tools.issubset(configurable_tool_universe):
continue
if not ts_tools.issubset(claimed):
enabled_toolsets.add(ts_key)
claimed.update(ts_tools)
# Plugin toolsets: enabled by default unless explicitly disabled, or
# unless the toolset is in _DEFAULT_OFF_TOOLSETS (e.g. spotify —
# shipped as a bundled plugin but user must opt in via `hermes tools`
@@ -726,6 +614,7 @@ def _get_platform_tools(
# A plugin toolset is "known" for a platform once `hermes tools`
# has been saved for that platform (tracked via known_plugin_toolsets).
# Unknown plugins default to enabled; known-but-absent = disabled.
plugin_ts_keys = _get_plugin_toolset_keys()
if plugin_ts_keys:
known_map = config.get("known_plugin_toolsets", {})
known_for_platform = set(known_map.get(platform, []))
@@ -743,6 +632,7 @@ def _get_platform_tools(
# Preserve any explicit non-configurable toolset entries (for example,
# custom toolsets or MCP server names saved in platform_toolsets).
platform_default_keys = {p["default_toolset"] for p in PLATFORMS.values()}
explicit_passthrough = {
ts
for ts in toolset_names
@@ -788,14 +678,6 @@ def _save_platform_tools(config: dict, platform: str, enabled_toolset_keys: Set[
"""
config.setdefault("platform_toolsets", {})
# Drop platform-scoped toolsets that don't apply here. Prevents the
# "Configure all platforms" checklist (or a hand-edited config.yaml)
# from turning on, say, the `discord` toolset for Telegram.
enabled_toolset_keys = {
ts for ts in enabled_toolset_keys
if _toolset_allowed_for_platform(ts, platform)
}
# Get the set of all configurable toolset keys (built-in + plugin)
configurable_keys = {ts_key for ts_key, _, _ in CONFIGURABLE_TOOLSETS}
plugin_keys = _get_plugin_toolset_keys()
@@ -810,7 +692,6 @@ def _save_platform_tools(config: dict, platform: str, enabled_toolset_keys: Set[
existing_toolsets = config.get("platform_toolsets", {}).get(platform, [])
if not isinstance(existing_toolsets, list):
existing_toolsets = []
existing_toolsets = [str(ts) for ts in existing_toolsets]
# Preserve any entries that are NOT configurable toolsets and NOT platform
# defaults (i.e. only MCP server names should be preserved)
@@ -818,11 +699,6 @@ def _save_platform_tools(config: dict, platform: str, enabled_toolset_keys: Set[
entry for entry in existing_toolsets
if entry not in configurable_keys and entry not in platform_default_keys
}
# Opening `hermes tools` is the user's opt-in to reconfigure tools, so treat
# saving from the picker as consent to clear the "no_mcp" sentinel. The
# picker has no checkbox for no_mcp, so without this users who once set it
# by hand could never re-enable MCP servers through the UI.
preserved_entries.discard("no_mcp")
# Merge preserved entries with new enabled toolsets
config["platform_toolsets"][platform] = sorted(enabled_toolset_keys | preserved_entries)
@@ -930,7 +806,7 @@ def _estimate_tool_tokens() -> Dict[str, int]:
return _tool_token_cache
def _prompt_toolset_checklist(platform_label: str, enabled: Set[str], platform: str = "cli") -> Set[str]:
def _prompt_toolset_checklist(platform_label: str, enabled: Set[str]) -> Set[str]:
"""Multi-select checklist of toolsets. Returns set of selected toolset keys."""
from hermes_cli.curses_ui import curses_checklist
from toolsets import resolve_toolset
@@ -938,12 +814,7 @@ def _prompt_toolset_checklist(platform_label: str, enabled: Set[str], platform:
# Pre-compute per-tool token counts (cached after first call).
tool_tokens = _estimate_tool_tokens()
effective_all = _get_effective_configurable_toolsets()
# Drop platform-scoped toolsets that don't apply to this platform.
effective = [
(k, l, d) for (k, l, d) in effective_all
if _toolset_allowed_for_platform(k, platform)
]
effective = _get_effective_configurable_toolsets()
labels = []
for ts_key, ts_label, ts_desc in effective:
@@ -1188,7 +1059,7 @@ def _is_provider_active(provider: dict, config: dict) -> bool:
configured_provider = image_cfg.get("provider")
if configured_provider not in (None, "", "fal"):
return False
if image_cfg.get("use_gateway") is not None and not is_truthy_value(image_cfg.get("use_gateway"), default=False):
if image_cfg.get("use_gateway") is False:
return False
return feature.managed_by_nous
if provider.get("tts_provider"):
@@ -1220,7 +1091,7 @@ def _is_provider_active(provider: dict, config: dict) -> bool:
return (
provider["imagegen_backend"] == "fal"
and configured_provider in (None, "", "fal")
and not is_truthy_value(image_cfg.get("use_gateway"), default=False)
and not image_cfg.get("use_gateway")
)
return False
@@ -1857,7 +1728,7 @@ def tools_command(args=None, first_install: bool = False, config: dict = None):
checklist_preselected = current_enabled - _DEFAULT_OFF_TOOLSETS
# Show checklist
new_enabled = _prompt_toolset_checklist(pinfo["label"], checklist_preselected, pkey)
new_enabled = _prompt_toolset_checklist(pinfo["label"], checklist_preselected)
added = new_enabled - current_enabled
removed = current_enabled - new_enabled
@@ -2213,11 +2084,7 @@ def _apply_mcp_change(config: dict, targets: List[str], action: str) -> Set[str]
def _print_tools_list(enabled_toolsets: set, mcp_servers: dict, platform: str = "cli"):
"""Print a summary of enabled/disabled toolsets and MCP tool filters."""
effective_all = _get_effective_configurable_toolsets()
effective = [
(k, l, d) for (k, l, d) in effective_all
if _toolset_allowed_for_platform(k, platform)
]
effective = _get_effective_configurable_toolsets()
builtin_keys = {ts_key for ts_key, _, _ in CONFIGURABLE_TOOLSETS}
print(f"Built-in toolsets ({platform}):")
@@ -2283,20 +2150,6 @@ def tools_disable_enable_command(args):
_print_error(f"Unknown toolset '{name}'")
toolset_targets = [t for t in toolset_targets if t in valid_toolsets]
# Reject platform-scoped toolsets on platforms that don't allow them.
restricted_targets = [
t for t in toolset_targets
if not _toolset_allowed_for_platform(t, platform)
]
if restricted_targets:
for name in restricted_targets:
allowed = sorted(_TOOLSET_PLATFORM_RESTRICTIONS.get(name) or set())
_print_error(
f"Toolset '{name}' is not available on platform '{platform}' "
f"(only: {', '.join(allowed)})"
)
toolset_targets = [t for t in toolset_targets if t not in restricted_targets]
if toolset_targets:
_apply_toolset_change(config, platform, toolset_targets, action)
+10 -349
View File
@@ -49,7 +49,7 @@ from hermes_cli.config import (
from gateway.status import get_running_pid, read_runtime_status
try:
from fastapi import FastAPI, HTTPException, Request, WebSocket, WebSocketDisconnect
from fastapi import FastAPI, HTTPException, Request
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import FileResponse, HTMLResponse, JSONResponse
from fastapi.staticfiles import StaticFiles
@@ -73,10 +73,6 @@ app = FastAPI(title="Hermes Agent", version=__version__)
_SESSION_TOKEN = secrets.token_urlsafe(32)
_SESSION_HEADER_NAME = "X-Hermes-Session-Token"
# In-browser Chat tab (/chat, /api/pty, …). Off unless ``hermes dashboard --tui``
# or HERMES_DASHBOARD_TUI=1. Set from :func:`start_server`.
_DASHBOARD_EMBEDDED_CHAT_ENABLED = False
# Simple rate limiter for the reveal endpoint
_reveal_timestamps: List[float] = []
_REVEAL_MAX_PER_WINDOW = 5
@@ -287,7 +283,7 @@ _SCHEMA_OVERRIDES: Dict[str, Dict[str, Any]] = {
"display.busy_input_mode": {
"type": "select",
"description": "Input behavior while agent is running",
"options": ["interrupt", "queue", "steer"],
"options": ["queue", "interrupt", "block"],
},
"memory.provider": {
"type": "select",
@@ -1533,30 +1529,26 @@ def _submit_anthropic_pkce(session_id: str, code_input: str) -> Dict[str, Any]:
with urllib.request.urlopen(req, timeout=20) as resp:
result = json.loads(resp.read().decode())
except Exception as e:
with _oauth_sessions_lock:
sess["status"] = "error"
sess["error_message"] = f"Token exchange failed: {e}"
sess["status"] = "error"
sess["error_message"] = f"Token exchange failed: {e}"
return {"ok": False, "status": "error", "message": sess["error_message"]}
access_token = result.get("access_token", "")
refresh_token = result.get("refresh_token", "")
expires_in = int(result.get("expires_in") or 3600)
if not access_token:
with _oauth_sessions_lock:
sess["status"] = "error"
sess["error_message"] = "No access token returned"
sess["status"] = "error"
sess["error_message"] = "No access token returned"
return {"ok": False, "status": "error", "message": sess["error_message"]}
expires_at_ms = int(time.time() * 1000) + (expires_in * 1000)
try:
_save_anthropic_oauth_creds(access_token, refresh_token, expires_at_ms)
except Exception as e:
with _oauth_sessions_lock:
sess["status"] = "error"
sess["error_message"] = f"Save failed: {e}"
sess["status"] = "error"
sess["error_message"] = f"Save failed: {e}"
return {"ok": False, "status": "error", "message": sess["error_message"]}
with _oauth_sessions_lock:
sess["status"] = "approved"
sess["status"] = "approved"
_log.info("oauth/pkce: anthropic login completed (session=%s)", session_id)
return {"ok": True, "status": "approved"}
@@ -2271,327 +2263,6 @@ async def get_usage_analytics(days: int = 30):
db.close()
# ---------------------------------------------------------------------------
# /api/pty — PTY-over-WebSocket bridge for the dashboard "Chat" tab.
#
# The endpoint spawns the same ``hermes --tui`` binary the CLI uses, behind
# a POSIX pseudo-terminal, and forwards bytes + resize escapes across a
# WebSocket. The browser renders the ANSI through xterm.js (see
# web/src/pages/ChatPage.tsx).
#
# Auth: ``?token=<session_token>`` query param (browsers can't set
# Authorization on the WS upgrade). Same ephemeral ``_SESSION_TOKEN`` as
# REST. Localhost-only — we defensively reject non-loopback clients even
# though uvicorn binds to 127.0.0.1.
# ---------------------------------------------------------------------------
import re
import asyncio
from hermes_cli.pty_bridge import PtyBridge, PtyUnavailableError
_RESIZE_RE = re.compile(rb"\x1b\[RESIZE:(\d+);(\d+)\]")
_PTY_READ_CHUNK_TIMEOUT = 0.2
_VALID_CHANNEL_RE = re.compile(r"^[A-Za-z0-9._-]{1,128}$")
# Starlette's TestClient reports the peer as "testclient"; treat it as
# loopback so tests don't need to rewrite request scope.
_LOOPBACK_HOSTS = frozenset({"127.0.0.1", "::1", "localhost", "testclient"})
# Per-channel subscriber registry used by /api/pub (PTY-side gateway → dashboard)
# and /api/events (dashboard → browser sidebar). Keyed by an opaque channel id
# the chat tab generates on mount; entries auto-evict when the last subscriber
# drops AND the publisher has disconnected.
_event_channels: dict[str, set] = {}
_event_lock = asyncio.Lock()
def _resolve_chat_argv(
resume: Optional[str] = None,
sidecar_url: Optional[str] = None,
) -> tuple[list[str], Optional[str], Optional[dict]]:
"""Resolve the argv + cwd + env for the chat PTY.
Default: whatever ``hermes --tui`` would run. Tests monkeypatch this
function to inject a tiny fake command (``cat``, ``sh -c 'printf …'``)
so nothing has to build Node or the TUI bundle.
Session resume is propagated via the ``HERMES_TUI_RESUME`` env var
matching what ``hermes_cli.main._launch_tui`` does for the CLI path.
Appending ``--resume <id>`` to argv doesn't work because ``ui-tui`` does
not parse its argv.
`sidecar_url` (when set) is forwarded as ``HERMES_TUI_SIDECAR_URL`` so
the spawned ``tui_gateway.entry`` can mirror dispatcher emits to the
dashboard's ``/api/pub`` endpoint (see :func:`pub_ws`).
"""
from hermes_cli.main import PROJECT_ROOT, _make_tui_argv
argv, cwd = _make_tui_argv(PROJECT_ROOT / "ui-tui", tui_dev=False)
env = os.environ.copy()
env.setdefault("NODE_ENV", "production")
if resume:
env["HERMES_TUI_RESUME"] = resume
if sidecar_url:
env["HERMES_TUI_SIDECAR_URL"] = sidecar_url
return list(argv), str(cwd) if cwd else None, env
def _build_sidecar_url(channel: str) -> Optional[str]:
"""ws:// URL the PTY child should publish events to, or None when unbound."""
host = getattr(app.state, "bound_host", None)
port = getattr(app.state, "bound_port", None)
if not host or not port:
return None
netloc = f"[{host}]:{port}" if ":" in host and not host.startswith("[") else f"{host}:{port}"
qs = urllib.parse.urlencode({"token": _SESSION_TOKEN, "channel": channel})
return f"ws://{netloc}/api/pub?{qs}"
async def _broadcast_event(channel: str, payload: str) -> None:
"""Fan out one publisher frame to every subscriber on `channel`."""
async with _event_lock:
subs = list(_event_channels.get(channel, ()))
for sub in subs:
try:
await sub.send_text(payload)
except Exception:
# Subscriber went away mid-send; the /api/events finally clause
# will remove it from the registry on its next iteration.
pass
def _channel_or_close_code(ws: WebSocket) -> Optional[str]:
"""Return the channel id from the query string or None if invalid."""
channel = ws.query_params.get("channel", "")
return channel if _VALID_CHANNEL_RE.match(channel) else None
@app.websocket("/api/pty")
async def pty_ws(ws: WebSocket) -> None:
if not _DASHBOARD_EMBEDDED_CHAT_ENABLED:
await ws.close(code=4403)
return
# --- auth + loopback check (before accept so we can close cleanly) ---
token = ws.query_params.get("token", "")
expected = _SESSION_TOKEN
if not hmac.compare_digest(token.encode(), expected.encode()):
await ws.close(code=4401)
return
client_host = ws.client.host if ws.client else ""
if client_host and client_host not in _LOOPBACK_HOSTS:
await ws.close(code=4403)
return
await ws.accept()
# --- spawn PTY ------------------------------------------------------
resume = ws.query_params.get("resume") or None
channel = _channel_or_close_code(ws)
sidecar_url = _build_sidecar_url(channel) if channel else None
try:
argv, cwd, env = _resolve_chat_argv(resume=resume, sidecar_url=sidecar_url)
except SystemExit as exc:
# _make_tui_argv calls sys.exit(1) when node/npm is missing.
await ws.send_text(f"\r\n\x1b[31mChat unavailable: {exc}\x1b[0m\r\n")
await ws.close(code=1011)
return
try:
bridge = PtyBridge.spawn(argv, cwd=cwd, env=env)
except PtyUnavailableError as exc:
await ws.send_text(f"\r\n\x1b[31mChat unavailable: {exc}\x1b[0m\r\n")
await ws.close(code=1011)
return
except (FileNotFoundError, OSError) as exc:
await ws.send_text(f"\r\n\x1b[31mChat failed to start: {exc}\x1b[0m\r\n")
await ws.close(code=1011)
return
loop = asyncio.get_running_loop()
# --- reader task: PTY master → WebSocket ----------------------------
async def pump_pty_to_ws() -> None:
while True:
chunk = await loop.run_in_executor(
None, bridge.read, _PTY_READ_CHUNK_TIMEOUT
)
if chunk is None: # EOF
return
if not chunk: # no data this tick; yield control and retry
await asyncio.sleep(0)
continue
try:
await ws.send_bytes(chunk)
except Exception:
return
reader_task = asyncio.create_task(pump_pty_to_ws())
# --- writer loop: WebSocket → PTY master ----------------------------
try:
while True:
msg = await ws.receive()
msg_type = msg.get("type")
if msg_type == "websocket.disconnect":
break
raw = msg.get("bytes")
if raw is None:
text = msg.get("text")
raw = text.encode("utf-8") if isinstance(text, str) else b""
if not raw:
continue
# Resize escape is consumed locally, never written to the PTY.
match = _RESIZE_RE.match(raw)
if match and match.end() == len(raw):
cols = int(match.group(1))
rows = int(match.group(2))
bridge.resize(cols=cols, rows=rows)
continue
bridge.write(raw)
except WebSocketDisconnect:
pass
finally:
reader_task.cancel()
try:
await reader_task
except (asyncio.CancelledError, Exception):
pass
bridge.close()
# ---------------------------------------------------------------------------
# /api/ws — JSON-RPC WebSocket sidecar for the dashboard "Chat" tab.
#
# Drives the same `tui_gateway.dispatch` surface Ink uses over stdio, so the
# dashboard can render structured metadata (model badge, tool-call sidebar,
# slash launcher, session info) alongside the xterm.js terminal that PTY
# already paints. Both transports bind to the same session id when one is
# active, so a tool.start emitted by the agent fans out to both sinks.
# ---------------------------------------------------------------------------
@app.websocket("/api/ws")
async def gateway_ws(ws: WebSocket) -> None:
if not _DASHBOARD_EMBEDDED_CHAT_ENABLED:
await ws.close(code=4403)
return
token = ws.query_params.get("token", "")
if not hmac.compare_digest(token.encode(), _SESSION_TOKEN.encode()):
await ws.close(code=4401)
return
client_host = ws.client.host if ws.client else ""
if client_host and client_host not in _LOOPBACK_HOSTS:
await ws.close(code=4403)
return
from tui_gateway.ws import handle_ws
await handle_ws(ws)
# ---------------------------------------------------------------------------
# /api/pub + /api/events — chat-tab event broadcast.
#
# The PTY-side ``tui_gateway.entry`` opens /api/pub at startup (driven by
# HERMES_TUI_SIDECAR_URL set in /api/pty's PTY env) and writes every
# dispatcher emit through it. The dashboard fans those frames out to any
# subscriber that opened /api/events on the same channel id. This is what
# gives the React sidebar its tool-call feed without breaking the PTY
# child's stdio handshake with Ink.
# ---------------------------------------------------------------------------
@app.websocket("/api/pub")
async def pub_ws(ws: WebSocket) -> None:
if not _DASHBOARD_EMBEDDED_CHAT_ENABLED:
await ws.close(code=4403)
return
token = ws.query_params.get("token", "")
if not hmac.compare_digest(token.encode(), _SESSION_TOKEN.encode()):
await ws.close(code=4401)
return
client_host = ws.client.host if ws.client else ""
if client_host and client_host not in _LOOPBACK_HOSTS:
await ws.close(code=4403)
return
channel = _channel_or_close_code(ws)
if not channel:
await ws.close(code=4400)
return
await ws.accept()
try:
while True:
await _broadcast_event(channel, await ws.receive_text())
except WebSocketDisconnect:
pass
@app.websocket("/api/events")
async def events_ws(ws: WebSocket) -> None:
if not _DASHBOARD_EMBEDDED_CHAT_ENABLED:
await ws.close(code=4403)
return
token = ws.query_params.get("token", "")
if not hmac.compare_digest(token.encode(), _SESSION_TOKEN.encode()):
await ws.close(code=4401)
return
client_host = ws.client.host if ws.client else ""
if client_host and client_host not in _LOOPBACK_HOSTS:
await ws.close(code=4403)
return
channel = _channel_or_close_code(ws)
if not channel:
await ws.close(code=4400)
return
await ws.accept()
async with _event_lock:
_event_channels.setdefault(channel, set()).add(ws)
try:
while True:
# Subscribers don't speak — the receive() just blocks until
# disconnect so the connection stays open as long as the
# browser holds it.
await ws.receive_text()
except WebSocketDisconnect:
pass
finally:
async with _event_lock:
subs = _event_channels.get(channel)
if subs is not None:
subs.discard(ws)
if not subs:
_event_channels.pop(channel, None)
def mount_spa(application: FastAPI):
"""Mount the built SPA. Falls back to index.html for client-side routing.
@@ -2613,10 +2284,8 @@ def mount_spa(application: FastAPI):
def _serve_index():
"""Return index.html with the session token injected."""
html = _index_path.read_text()
chat_js = "true" if _DASHBOARD_EMBEDDED_CHAT_ENABLED else "false"
token_script = (
f'<script>window.__HERMES_SESSION_TOKEN__="{_SESSION_TOKEN}";'
f"window.__HERMES_DASHBOARD_EMBEDDED_CHAT__={chat_js};</script>"
f'<script>window.__HERMES_SESSION_TOKEN__="{_SESSION_TOKEN}";</script>'
)
html = html.replace("</head>", f"{token_script}</head>", 1)
return HTMLResponse(
@@ -3129,15 +2798,10 @@ def start_server(
port: int = 9119,
open_browser: bool = True,
allow_public: bool = False,
*,
embedded_chat: bool = False,
):
"""Start the web UI server."""
import uvicorn
global _DASHBOARD_EMBEDDED_CHAT_ENABLED
_DASHBOARD_EMBEDDED_CHAT_ENABLED = embedded_chat
_LOCALHOST = ("127.0.0.1", "localhost", "::1")
if host not in _LOCALHOST and not allow_public:
raise SystemExit(
@@ -3153,10 +2817,7 @@ def start_server(
# Record the bound host so host_header_middleware can validate incoming
# Host headers against it. Defends against DNS rebinding (GHSA-ppp5-vxwm-4cf7).
# bound_port is also stashed so /api/pty can build the back-WS URL the
# PTY child uses to publish events to the dashboard sidebar.
app.state.bound_host = host
app.state.bound_port = port
if open_browser:
import webbrowser
+4 -3
View File
@@ -195,6 +195,10 @@ def setup_logging(
The ``logs/`` directory where files are written.
"""
global _logging_initialized
if _logging_initialized and not force:
home = hermes_home or get_hermes_home()
return home / "logs"
home = hermes_home or get_hermes_home()
log_dir = home / "logs"
log_dir.mkdir(parents=True, exist_ok=True)
@@ -244,9 +248,6 @@ def setup_logging(
log_filter=_ComponentFilter(COMPONENT_PREFIXES["gateway"]),
)
if _logging_initialized and not force:
return log_dir
# Ensure root logger level is low enough for the handlers to fire.
if root.level == logging.NOTSET or root.level > level:
root.setLevel(level)
+19 -158
View File
@@ -31,7 +31,7 @@ T = TypeVar("T")
DEFAULT_DB_PATH = get_hermes_home() / "state.db"
SCHEMA_VERSION = 9
SCHEMA_VERSION = 8
SCHEMA_SQL = """
CREATE TABLE IF NOT EXISTS schema_version (
@@ -83,8 +83,7 @@ CREATE TABLE IF NOT EXISTS messages (
reasoning TEXT,
reasoning_content TEXT,
reasoning_details TEXT,
codex_reasoning_items TEXT,
codex_message_items TEXT
codex_reasoning_items TEXT
);
CREATE TABLE IF NOT EXISTS state_meta (
@@ -357,15 +356,6 @@ class SessionDB:
except sqlite3.OperationalError:
pass # Column already exists
cursor.execute("UPDATE schema_version SET version = 8")
if current_version < 9:
# v9: preserve replayable Codex assistant message ids/phases so
# follow-up turns can rebuild Responses API message items instead
# of flattening everything to plain assistant text.
try:
cursor.execute('ALTER TABLE messages ADD COLUMN "codex_message_items" TEXT')
except sqlite3.OperationalError:
pass # Column already exists
cursor.execute("UPDATE schema_version SET version = 9")
# Unique title index — always ensure it exists (safe to run after migrations
# since the title column is guaranteed to exist at this point)
@@ -832,18 +822,7 @@ class SessionDB:
params = []
if not include_children:
# Show root sessions and branch sessions (whose parent ended with
# end_reason='branched' before the child was created), while still
# hiding sub-agent runs and compression continuations (which also
# carry a parent_session_id but were spawned while the parent was
# still live — i.e., started_at < parent.ended_at).
where_clauses.append(
"(s.parent_session_id IS NULL"
" OR EXISTS (SELECT 1 FROM sessions p"
" WHERE p.id = s.parent_session_id"
" AND p.end_reason = 'branched'"
" AND s.started_at >= p.ended_at))"
)
where_clauses.append("s.parent_session_id IS NULL")
if source:
where_clauses.append("s.source = ?")
@@ -977,7 +956,6 @@ class SessionDB:
reasoning_content: str = None,
reasoning_details: Any = None,
codex_reasoning_items: Any = None,
codex_message_items: Any = None,
) -> int:
"""
Append a message to a session. Returns the message row ID.
@@ -994,10 +972,6 @@ class SessionDB:
json.dumps(codex_reasoning_items)
if codex_reasoning_items else None
)
codex_message_items_json = (
json.dumps(codex_message_items)
if codex_message_items else None
)
tool_calls_json = json.dumps(tool_calls) if tool_calls else None
# Pre-compute tool call count
@@ -1009,9 +983,8 @@ class SessionDB:
cursor = conn.execute(
"""INSERT INTO messages (session_id, role, content, tool_call_id,
tool_calls, tool_name, timestamp, token_count, finish_reason,
reasoning, reasoning_content, reasoning_details, codex_reasoning_items,
codex_message_items)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
reasoning, reasoning_content, reasoning_details, codex_reasoning_items)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
(
session_id,
role,
@@ -1026,7 +999,6 @@ class SessionDB:
reasoning_content,
reasoning_details_json,
codex_items_json,
codex_message_items_json,
),
)
msg_id = cursor.lastrowid
@@ -1132,27 +1104,19 @@ class SessionDB:
current = child_id
return session_id
def get_messages_as_conversation(
self, session_id: str, include_ancestors: bool = False
) -> List[Dict[str, Any]]:
def get_messages_as_conversation(self, session_id: str) -> List[Dict[str, Any]]:
"""
Load messages in the OpenAI conversation format (role + content dicts).
Used by the gateway to restore conversation history.
"""
session_ids = [session_id]
if include_ancestors:
session_ids = self._session_lineage_root_to_tip(session_id)
with self._lock:
placeholders = ",".join("?" for _ in session_ids)
rows = self._conn.execute(
cursor = self._conn.execute(
"SELECT role, content, tool_call_id, tool_calls, tool_name, "
"reasoning, reasoning_content, reasoning_details, codex_reasoning_items, "
"codex_message_items "
f"FROM messages WHERE session_id IN ({placeholders}) ORDER BY timestamp, id",
tuple(session_ids),
).fetchall()
"reasoning, reasoning_content, reasoning_details, codex_reasoning_items "
"FROM messages WHERE session_id = ? ORDER BY timestamp, id",
(session_id,),
)
rows = cursor.fetchall()
messages = []
for row in rows:
msg = {"role": row["role"], "content": row["content"]}
@@ -1186,53 +1150,9 @@ class SessionDB:
except (json.JSONDecodeError, TypeError):
logger.warning("Failed to deserialize codex_reasoning_items, falling back to None")
msg["codex_reasoning_items"] = None
if row["codex_message_items"]:
try:
msg["codex_message_items"] = json.loads(row["codex_message_items"])
except (json.JSONDecodeError, TypeError):
logger.warning("Failed to deserialize codex_message_items, falling back to None")
msg["codex_message_items"] = None
if include_ancestors and self._is_duplicate_replayed_user_message(messages, msg):
continue
messages.append(msg)
return messages
def _session_lineage_root_to_tip(self, session_id: str) -> List[str]:
if not session_id:
return [session_id]
chain = []
current = session_id
seen = set()
with self._lock:
for _ in range(100):
if not current or current in seen:
break
seen.add(current)
chain.append(current)
row = self._conn.execute(
"SELECT parent_session_id FROM sessions WHERE id = ?",
(current,),
).fetchone()
if row is None:
break
current = row["parent_session_id"] if hasattr(row, "keys") else row[0]
return list(reversed(chain)) or [session_id]
@staticmethod
def _is_duplicate_replayed_user_message(messages: List[Dict[str, Any]], msg: Dict[str, Any]) -> bool:
if msg.get("role") != "user":
return False
content = msg.get("content")
if not isinstance(content, str) or not content:
return False
for prev in reversed(messages):
if prev.get("role") == "user" and prev.get("content") == content:
return True
if prev.get("role") == "assistant" and (prev.get("content") or prev.get("tool_calls")):
return False
return False
# =========================================================================
# Search
# =========================================================================
@@ -1557,45 +1477,12 @@ class SessionDB:
)
self._execute_write(_do)
@staticmethod
def _remove_session_files(sessions_dir: Optional[Path], session_id: str) -> None:
"""Remove on-disk transcript files for a session.
Cleans up ``{session_id}.json``, ``{session_id}.jsonl``, and any
``request_dump_{session_id}_*.json`` files left by the gateway.
Silently skips files that don't exist and swallows OSError so a
filesystem hiccup never blocks a DB operation.
"""
if sessions_dir is None:
return
for suffix in (".json", ".jsonl"):
p = sessions_dir / f"{session_id}{suffix}"
try:
p.unlink(missing_ok=True)
except OSError:
pass
# request_dump files use session_id as a prefix component
try:
for p in sessions_dir.glob(f"request_dump_{session_id}_*.json"):
try:
p.unlink(missing_ok=True)
except OSError:
pass
except OSError:
pass
def delete_session(
self,
session_id: str,
sessions_dir: Optional[Path] = None,
) -> bool:
def delete_session(self, session_id: str) -> bool:
"""Delete a session and all its messages.
Child sessions are orphaned (parent_session_id set to NULL) rather
than cascade-deleted, so they remain accessible independently.
When *sessions_dir* is provided, also removes on-disk transcript
files (``.json`` / ``.jsonl`` / ``request_dump_*``) for the deleted
session. Returns True if the session was found and deleted.
Returns True if the session was found and deleted.
"""
def _do(conn):
cursor = conn.execute(
@@ -1612,29 +1499,16 @@ class SessionDB:
conn.execute("DELETE FROM messages WHERE session_id = ?", (session_id,))
conn.execute("DELETE FROM sessions WHERE id = ?", (session_id,))
return True
return self._execute_write(_do)
deleted = self._execute_write(_do)
if deleted:
self._remove_session_files(sessions_dir, session_id)
return deleted
def prune_sessions(
self,
older_than_days: int = 90,
source: str = None,
sessions_dir: Optional[Path] = None,
) -> int:
def prune_sessions(self, older_than_days: int = 90, source: str = None) -> int:
"""Delete sessions older than N days. Returns count of deleted sessions.
Only prunes ended sessions (not active ones). Child sessions outside
the prune window are orphaned (parent_session_id set to NULL) rather
than cascade-deleted. When *sessions_dir* is provided, also removes
on-disk transcript files (``.json`` / ``.jsonl`` /
``request_dump_*``) for every pruned session, outside the DB
transaction.
than cascade-deleted.
"""
cutoff = time.time() - (older_than_days * 86400)
removed_ids: list[str] = []
def _do(conn):
if source:
@@ -1664,14 +1538,9 @@ class SessionDB:
for sid in session_ids:
conn.execute("DELETE FROM messages WHERE session_id = ?", (sid,))
conn.execute("DELETE FROM sessions WHERE id = ?", (sid,))
removed_ids.append(sid)
return len(session_ids)
count = self._execute_write(_do)
# Clean up on-disk files outside the DB transaction
for sid in removed_ids:
self._remove_session_files(sessions_dir, sid)
return count
return self._execute_write(_do)
# ── Meta key/value (for scheduler bookkeeping) ──
@@ -1725,7 +1594,6 @@ class SessionDB:
retention_days: int = 90,
min_interval_hours: int = 24,
vacuum: bool = True,
sessions_dir: Optional[Path] = None,
) -> Dict[str, Any]:
"""Idempotent auto-maintenance: prune old sessions + optional VACUUM.
@@ -1733,10 +1601,6 @@ class SessionDB:
within ``min_interval_hours`` no-op. Designed to be called once at
startup from long-lived entrypoints (CLI, gateway, cron scheduler).
When *sessions_dir* is provided, on-disk transcript files
(``.json`` / ``.jsonl`` / ``request_dump_*``) for pruned sessions
are removed as part of the same sweep (issue #3015).
Never raises. On any failure, logs a warning and returns a dict
with ``"error"`` set.
@@ -1760,10 +1624,7 @@ class SessionDB:
except (TypeError, ValueError):
pass # corrupt meta; treat as no prior run
pruned = self.prune_sessions(
older_than_days=retention_days,
sessions_dir=sessions_dir,
)
pruned = self.prune_sessions(older_than_days=retention_days)
result["pruned"] = pruned
# Only VACUUM if we actually freed rows — VACUUM on a tight DB
+25 -41
View File
@@ -24,7 +24,6 @@ import json
import asyncio
import logging
import threading
import time
from typing import Dict, Any, List, Optional, Tuple
from tools.registry import discover_builtin_tools, registry
@@ -289,34 +288,30 @@ def get_tool_definitions(
filtered_tools[i] = {"type": "function", "function": dynamic_schema}
break
# Rebuild discord / discord_admin schemas based on the bot's privileged
# intents (detected from GET /applications/@me) and the user's action
# allowlist in config. Hides actions the bot's intents don't support so
# the model never attempts them, and annotates fetch_messages when the
# Rebuild discord_server schema based on the bot's privileged intents
# (detected from GET /applications/@me) and the user's action allowlist
# in config. Hides actions the bot's intents don't support so the
# model never attempts them, and annotates fetch_messages when the
# MESSAGE_CONTENT intent is missing.
_discord_schema_fns = {
"discord": "get_dynamic_schema_core",
"discord_admin": "get_dynamic_schema_admin",
}
for discord_tool_name in _discord_schema_fns:
if discord_tool_name in available_tool_names:
try:
from tools import discord_tool as _dt
schema_fn = getattr(_dt, _discord_schema_fns[discord_tool_name])
dynamic = schema_fn()
except Exception:
dynamic = None
if dynamic is None:
filtered_tools = [
t for t in filtered_tools
if t.get("function", {}).get("name") != discord_tool_name
]
available_tool_names.discard(discord_tool_name)
else:
for i, td in enumerate(filtered_tools):
if td.get("function", {}).get("name") == discord_tool_name:
filtered_tools[i] = {"type": "function", "function": dynamic}
break
if "discord_server" in available_tool_names:
try:
from tools.discord_tool import get_dynamic_schema
dynamic = get_dynamic_schema()
except Exception: # pragma: no cover — defensive, fall back to static
dynamic = None
if dynamic is None:
# Tool filtered out entirely (empty allowlist or detection disabled
# the only remaining actions). Drop it from the schema list.
filtered_tools = [
t for t in filtered_tools
if t.get("function", {}).get("name") != "discord_server"
]
available_tool_names.discard("discord_server")
else:
for i, td in enumerate(filtered_tools):
if td.get("function", {}).get("name") == "discord_server":
filtered_tools[i] = {"type": "function", "function": dynamic}
break
# Strip web tool cross-references from browser_navigate description when
# web_search / web_extract are not available. The static schema says
@@ -469,9 +464,9 @@ def _coerce_number(value: str, integer_only: bool = False):
f = float(value)
except (ValueError, OverflowError):
return value
# Guard against inf/nan — not JSON-serializable, keep original string
# Guard against inf/nan before int() conversion
if f != f or f == float("inf") or f == float("-inf"):
return value
return f
# If it looks like an integer (no fractional part), return int
if f == int(f):
return int(f)
@@ -568,14 +563,6 @@ def handle_function_call(
except Exception:
pass # file_tools may not be loaded yet
# Measure tool dispatch latency so post_tool_call and
# transform_tool_result hooks can observe per-tool duration.
# Inspired by Claude Code 2.1.119, which added ``duration_ms`` to
# PostToolUse hook inputs so plugin authors can build latency
# dashboards, budget alerts, and regression canaries without having
# to wrap every tool manually. We use monotonic() so the value is
# unaffected by wall-clock adjustments during the call.
_dispatch_start = time.monotonic()
if function_name == "execute_code":
# Prefer the caller-provided list so subagents can't overwrite
# the parent's tool set via the process-global.
@@ -591,7 +578,6 @@ def handle_function_call(
task_id=task_id,
user_task=user_task,
)
duration_ms = int((time.monotonic() - _dispatch_start) * 1000)
try:
from hermes_cli.plugins import invoke_hook
@@ -603,7 +589,6 @@ def handle_function_call(
task_id=task_id or "",
session_id=session_id or "",
tool_call_id=tool_call_id or "",
duration_ms=duration_ms,
)
except Exception:
pass
@@ -624,7 +609,6 @@ def handle_function_call(
task_id=task_id or "",
session_id=session_id or "",
tool_call_id=tool_call_id or "",
duration_ms=duration_ms,
)
for hook_result in hook_results:
if isinstance(hook_result, str):
+1 -1
View File
@@ -156,7 +156,7 @@
for entry in "''${ENTRIES[@]}"; do
IFS=":" read -r ATTR FOLDER NIX_FILE <<< "$entry"
echo "==> .#$ATTR ($FOLDER -> $NIX_FILE)"
OUTPUT=$(nix build ".#$ATTR.npmDeps" --no-link --rebuild --print-build-logs 2>&1)
OUTPUT=$(nix build ".#$ATTR.npmDeps" --no-link --print-build-logs 2>&1)
STATUS=$?
if [ "$STATUS" -eq 0 ]; then
echo " ok"
+1 -1
View File
@@ -4,7 +4,7 @@ let
src = ../ui-tui;
npmDeps = pkgs.fetchNpmDeps {
inherit src;
hash = "sha256-Chz+NW9NXqboXHOa6PKwf5bhAkkcFtKNhvKWwg2XSPc=";
hash = "sha256-RU4qSHgJPMyfRSEJDzkG4+MReDZDc6QbTD2wisa5QE0=";
};
npm = hermesNpmLib.mkNpmPassthru { folder = "ui-tui"; attr = "tui"; pname = "hermes-tui"; };
+1 -1
View File
@@ -4,7 +4,7 @@ let
src = ../web;
npmDeps = pkgs.fetchNpmDeps {
inherit src;
hash = "sha256-4Z8KQ69QhO83X6zff+5urWBv6MME686MhTTMdwSl65o=";
hash = "sha256-TS/vrCHbdvXkPcAPxImKzAd2pdDCrKlgYZkXBMQ+TEg=";
};
npm = hermesNpmLib.mkNpmPassthru { folder = "web"; attr = "web"; pname = "hermes-web"; };
@@ -380,10 +380,6 @@ def backup_existing(path: Path, backup_root: Path) -> Optional[Path]:
# Replace OpenClaw brand names with Hermes in migrated text so that
# memory entries, user profiles, SOUL.md, and workspace instructions
# read as self-referential to the new agent identity.
#
# Case-preserving: ``OpenClaw`` → ``Hermes`` (prose), but lowercase matches
# like ``openclaw`` → ``hermes`` (so filesystem paths like ``~/.openclaw``
# become ``~/.hermes`` — the real Hermes home — not the broken ``~/.Hermes``).
_REBRAND_PATTERNS: List[Tuple[re.Pattern, str]] = [
(re.compile(r'\bOpen[\s-]?Claw\b', re.IGNORECASE), 'Hermes'),
(re.compile(r'\bClawdBot\b', re.IGNORECASE), 'Hermes'),
@@ -391,31 +387,10 @@ _REBRAND_PATTERNS: List[Tuple[re.Pattern, str]] = [
]
def _case_preserving_replacement(replacement: str):
"""Return a re.sub replacement fn that lowercases the result when the
matched text was all-lowercase.
Keeps ``OpenClaw`` ``Hermes`` but maps ``openclaw`` ``hermes`` so a
filesystem path like ``~/.openclaw/config.yaml`` rewrites to
``~/.hermes/config.yaml`` (the real Hermes home) instead of the broken
``~/.Hermes/config.yaml``.
"""
def _sub(match: "re.Match[str]") -> str:
matched = match.group(0)
if matched and matched.islower():
return replacement.lower()
return replacement
return _sub
def rebrand_text(text: str) -> str:
"""Replace OpenClaw / ClawdBot / MoltBot brand names with Hermes.
Preserves case so filesystem-path matches (lowercase) don't become
capitalized directory names that don't exist.
"""
"""Replace OpenClaw / ClawdBot / MoltBot brand names with Hermes."""
for pattern, replacement in _REBRAND_PATTERNS:
text = pattern.sub(_case_preserving_replacement(replacement), text)
text = pattern.sub(replacement, text)
return text
-25
View File
@@ -91,29 +91,4 @@
// Register this plugin — the dashboard picks it up automatically.
window.__HERMES_PLUGINS__.register("example", ExamplePage);
// ─────────────────────────────────────────────────────────────────────
// Page-scoped slot demo: inject a small banner at the top of /sessions.
//
// Built-in pages expose named slots (<page>:top, <page>:bottom) that
// plugins can populate without overriding the whole route. The
// manifest lists the slots we use in its `slots` array so the shell
// knows to render <PluginSlot name="sessions:top" /> there.
// ─────────────────────────────────────────────────────────────────────
function SessionsTopBanner() {
return React.createElement(Card, {
className: "border-dashed",
},
React.createElement(CardContent, { className: "flex items-center gap-3 py-2" },
React.createElement(Badge, { variant: "outline" }, "Example"),
React.createElement("span", {
className: "text-xs text-muted-foreground",
}, "This banner was injected into the Sessions page by the example plugin via the ",
React.createElement("code", { className: "font-courier" }, "sessions:top"),
" slot."),
),
);
}
window.__HERMES_PLUGINS__.registerSlot("example", "sessions:top", SessionsTopBanner);
})();
@@ -8,7 +8,6 @@
"path": "/example",
"position": "after:skills"
},
"slots": ["sessions:top"],
"entry": "dist/index.js",
"api": "plugin_api.py"
}
+29 -124
View File
@@ -3,9 +3,7 @@
Long-term memory with knowledge graph, entity resolution, and multi-strategy
retrieval. Supports cloud (API key) and local modes.
Configurable request timeout via HINDSIGHT_TIMEOUT env var or config.json.
Configurable embedded daemon idle timeout via HINDSIGHT_IDLE_TIMEOUT env var
or config.json idle_timeout.
Configurable timeout via HINDSIGHT_TIMEOUT env var or config.json.
Original PR #1811 by benfrank241, adapted to MemoryProvider ABC.
@@ -16,7 +14,6 @@ Config via environment variables:
HINDSIGHT_API_URL API endpoint
HINDSIGHT_MODE cloud or local (default: cloud)
HINDSIGHT_TIMEOUT API request timeout in seconds (default: 120)
HINDSIGHT_IDLE_TIMEOUT embedded daemon idle timeout seconds; 0 disables shutdown (default: 300)
HINDSIGHT_RETAIN_TAGS comma-separated tags attached to retained memories
HINDSIGHT_RETAIN_SOURCE metadata source value attached to retained memories
HINDSIGHT_RETAIN_USER_PREFIX label used before user turns in retained transcripts
@@ -48,7 +45,6 @@ _DEFAULT_API_URL = "https://api.hindsight.vectorize.io"
_DEFAULT_LOCAL_URL = "http://localhost:8888"
_MIN_CLIENT_VERSION = "0.4.22"
_DEFAULT_TIMEOUT = 120 # seconds — cloud API can take 30-40s per request
_DEFAULT_IDLE_TIMEOUT = 300 # seconds — Hindsight embedded daemon default
_VALID_BUDGETS = {"low", "mid", "high"}
_PROVIDER_DEFAULT_MODELS = {
"openai": "gpt-4o-mini",
@@ -63,17 +59,6 @@ _PROVIDER_DEFAULT_MODELS = {
}
def _parse_int_setting(value: Any, default: int) -> int:
"""Parse an integer config/env value, falling back on invalid input."""
if value is None or value == "":
return default
try:
return int(value)
except (TypeError, ValueError):
logger.warning("Invalid integer Hindsight setting %r; using default %s", value, default)
return default
def _check_local_runtime() -> tuple[bool, str | None]:
"""Return whether local embedded Hindsight imports cleanly.
@@ -218,8 +203,6 @@ def _load_config() -> dict:
return {
"mode": os.environ.get("HINDSIGHT_MODE", "cloud"),
"apiKey": os.environ.get("HINDSIGHT_API_KEY", ""),
"timeout": _parse_int_setting(os.environ.get("HINDSIGHT_TIMEOUT"), _DEFAULT_TIMEOUT),
"idle_timeout": _parse_int_setting(os.environ.get("HINDSIGHT_IDLE_TIMEOUT"), _DEFAULT_IDLE_TIMEOUT),
"retain_tags": os.environ.get("HINDSIGHT_RETAIN_TAGS", ""),
"retain_source": os.environ.get("HINDSIGHT_RETAIN_SOURCE", ""),
"retain_user_prefix": os.environ.get("HINDSIGHT_RETAIN_USER_PREFIX", "User"),
@@ -321,16 +304,6 @@ def _build_embedded_profile_env(config: dict[str, Any], *, llm_api_key: str | No
}
if current_base_url:
env_values["HINDSIGHT_API_LLM_BASE_URL"] = str(current_base_url)
idle_timeout = (
config.get("idle_timeout")
if config.get("idle_timeout") is not None
else os.environ.get("HINDSIGHT_IDLE_TIMEOUT")
)
if idle_timeout is not None and idle_timeout != "":
env_values["HINDSIGHT_EMBED_DAEMON_IDLE_TIMEOUT"] = str(
_parse_int_setting(idle_timeout, _DEFAULT_IDLE_TIMEOUT)
)
return env_values
@@ -439,7 +412,6 @@ class HindsightMemoryProvider(MemoryProvider):
self._turn_index = 0
self._client = None
self._timeout = _DEFAULT_TIMEOUT
self._idle_timeout = _DEFAULT_IDLE_TIMEOUT
self._prefetch_result = ""
self._prefetch_lock = threading.Lock()
self._prefetch_thread = None
@@ -620,17 +592,10 @@ class HindsightMemoryProvider(MemoryProvider):
sys.stdout.write(" LLM API key: ")
sys.stdout.flush()
llm_key = getpass.getpass(prompt="") if sys.stdin.isatty() else sys.stdin.readline().strip()
if llm_key:
env_writes["HINDSIGHT_LLM_API_KEY"] = llm_key
else:
env_path = Path(hermes_home) / ".env"
existing_llm_key = ""
if env_path.exists():
for line in env_path.read_text().splitlines():
if line.startswith("HINDSIGHT_LLM_API_KEY="):
existing_llm_key = line.split("=", 1)[1]
break
env_writes["HINDSIGHT_LLM_API_KEY"] = existing_llm_key
# Always write explicitly (including empty) so the provider sees ""
# rather than a missing variable. The daemon reads from .env at
# startup and fails when HINDSIGHT_LLM_API_KEY is unset.
env_writes["HINDSIGHT_LLM_API_KEY"] = llm_key
# Step 4: Save everything
provider_config["bank_id"] = "hermes"
@@ -640,11 +605,6 @@ class HindsightMemoryProvider(MemoryProvider):
timeout_val = existing_timeout if existing_timeout else _DEFAULT_TIMEOUT
provider_config["timeout"] = timeout_val
env_writes["HINDSIGHT_TIMEOUT"] = str(timeout_val)
if mode == "local_embedded":
existing_idle_timeout = self._config.get("idle_timeout") if self._config else None
idle_timeout_val = existing_idle_timeout if existing_idle_timeout is not None else _DEFAULT_IDLE_TIMEOUT
provider_config["idle_timeout"] = idle_timeout_val
env_writes["HINDSIGHT_IDLE_TIMEOUT"] = str(idle_timeout_val)
config["memory"]["provider"] = "hindsight"
save_config(config)
@@ -733,7 +693,6 @@ class HindsightMemoryProvider(MemoryProvider):
{"key": "recall_max_input_chars", "description": "Maximum input query length for auto-recall", "default": 800},
{"key": "recall_prompt_preamble", "description": "Custom preamble for recalled memories in context"},
{"key": "timeout", "description": "API request timeout in seconds", "default": _DEFAULT_TIMEOUT},
{"key": "idle_timeout", "description": "Embedded daemon idle timeout in seconds (0 disables auto-shutdown)", "default": _DEFAULT_IDLE_TIMEOUT, "when": {"mode": "local_embedded"}},
]
def _get_client(self):
@@ -761,14 +720,6 @@ class HindsightMemoryProvider(MemoryProvider):
)
if self._llm_base_url:
kwargs["llm_base_url"] = self._llm_base_url
idle_timeout = _parse_int_setting(
self._config.get("idle_timeout")
if self._config.get("idle_timeout") is not None
else os.environ.get("HINDSIGHT_IDLE_TIMEOUT", self._idle_timeout),
_DEFAULT_IDLE_TIMEOUT,
)
self._idle_timeout = idle_timeout
kwargs["idle_timeout"] = idle_timeout
self._client = HindsightEmbedded(**kwargs)
else:
from hindsight_client import Hindsight
@@ -785,38 +736,6 @@ class HindsightMemoryProvider(MemoryProvider):
"""Schedule *coro* on the shared loop using the configured timeout."""
return _run_sync(coro, timeout=self._timeout)
def _is_retriable_embedded_connection_error(self, exc: Exception) -> bool:
"""Return True for stale embedded-daemon connection failures."""
if self._mode != "local_embedded":
return False
text = f"{type(exc).__name__}: {exc}".lower()
return any(
marker in text
for marker in (
"cannot connect to host",
"connection refused",
"connect call failed",
"clientconnectorerror",
)
)
def _run_hindsight_operation(self, operation):
"""Run an async Hindsight client operation, retrying once after idle shutdown."""
client = self._get_client()
try:
return self._run_sync(operation(client))
except Exception as exc:
if not self._is_retriable_embedded_connection_error(exc):
raise
logger.info(
"Hindsight embedded daemon appears unreachable; recreating client and retrying once: %s",
exc,
)
self._client = None
client = self._get_client()
self._client = client
return self._run_sync(operation(client))
def initialize(self, session_id: str, **kwargs) -> None:
self._session_id = str(session_id or "").strip()
self._parent_session_id = str(kwargs.get("parent_session_id", "") or "").strip()
@@ -871,14 +790,7 @@ class HindsightMemoryProvider(MemoryProvider):
self._session_turns = []
self._mode = self._config.get("mode", "cloud")
# Read timeout from config or env var, fall back to default
self._timeout = _parse_int_setting(
self._config.get("timeout") if self._config.get("timeout") is not None else os.environ.get("HINDSIGHT_TIMEOUT"),
_DEFAULT_TIMEOUT,
)
self._idle_timeout = _parse_int_setting(
self._config.get("idle_timeout") if self._config.get("idle_timeout") is not None else os.environ.get("HINDSIGHT_IDLE_TIMEOUT"),
_DEFAULT_IDLE_TIMEOUT,
)
self._timeout = self._config.get("timeout") or int(os.environ.get("HINDSIGHT_TIMEOUT", str(_DEFAULT_TIMEOUT)))
# "local" is a legacy alias for "local_embedded"
if self._mode == "local":
self._mode = "local_embedded"
@@ -1069,9 +981,10 @@ class HindsightMemoryProvider(MemoryProvider):
def _run():
try:
client = self._get_client()
if self._prefetch_method == "reflect":
logger.debug("Prefetch: calling reflect (bank=%s, query_len=%d)", self._bank_id, len(query))
resp = self._run_hindsight_operation(lambda client: client.areflect(bank_id=self._bank_id, query=query, budget=self._budget))
resp = self._run_sync(client.areflect(bank_id=self._bank_id, query=query, budget=self._budget))
text = resp.text or ""
else:
recall_kwargs: dict = {
@@ -1085,7 +998,7 @@ class HindsightMemoryProvider(MemoryProvider):
recall_kwargs["types"] = self._recall_types
logger.debug("Prefetch: calling recall (bank=%s, query_len=%d, budget=%s)",
self._bank_id, len(query), self._budget)
resp = self._run_hindsight_operation(lambda client: client.arecall(**recall_kwargs))
resp = self._run_sync(client.arecall(**recall_kwargs))
num_results = len(resp.results) if resp.results else 0
logger.debug("Prefetch: recall returned %d results", num_results)
text = "\n".join(f"- {r.text}" for r in resp.results if r.text) if resp.results else ""
@@ -1218,14 +1131,12 @@ class HindsightMemoryProvider(MemoryProvider):
item.pop("retain_async", None)
logger.debug("Hindsight retain: bank=%s, doc=%s, async=%s, content_len=%d, num_turns=%d",
self._bank_id, self._document_id, self._retain_async, len(content), len(self._session_turns))
self._run_hindsight_operation(
lambda client: client.aretain_batch(
bank_id=self._bank_id,
items=[item],
document_id=self._document_id,
retain_async=self._retain_async,
)
)
self._run_sync(client.aretain_batch(
bank_id=self._bank_id,
items=[item],
document_id=self._document_id,
retain_async=self._retain_async,
))
logger.debug("Hindsight retain succeeded")
except Exception as e:
logger.warning("Hindsight sync failed: %s", e, exc_info=True)
@@ -1241,6 +1152,12 @@ class HindsightMemoryProvider(MemoryProvider):
return [RETAIN_SCHEMA, RECALL_SCHEMA, REFLECT_SCHEMA]
def handle_tool_call(self, tool_name: str, args: dict, **kwargs) -> str:
try:
client = self._get_client()
except Exception as e:
logger.warning("Hindsight client init failed: %s", e)
return tool_error(f"Hindsight client unavailable: {e}")
if tool_name == "hindsight_retain":
content = args.get("content", "")
if not content:
@@ -1254,7 +1171,7 @@ class HindsightMemoryProvider(MemoryProvider):
)
logger.debug("Tool hindsight_retain: bank=%s, content_len=%d, context=%s",
self._bank_id, len(content), context)
self._run_hindsight_operation(lambda client: client.aretain(**retain_kwargs))
self._run_sync(client.aretain(**retain_kwargs))
logger.debug("Tool hindsight_retain: success")
return json.dumps({"result": "Memory stored successfully."})
except Exception as e:
@@ -1277,7 +1194,7 @@ class HindsightMemoryProvider(MemoryProvider):
recall_kwargs["types"] = self._recall_types
logger.debug("Tool hindsight_recall: bank=%s, query_len=%d, budget=%s",
self._bank_id, len(query), self._budget)
resp = self._run_hindsight_operation(lambda client: client.arecall(**recall_kwargs))
resp = self._run_sync(client.arecall(**recall_kwargs))
num_results = len(resp.results) if resp.results else 0
logger.debug("Tool hindsight_recall: %d results", num_results)
if not resp.results:
@@ -1295,11 +1212,9 @@ class HindsightMemoryProvider(MemoryProvider):
try:
logger.debug("Tool hindsight_reflect: bank=%s, query_len=%d, budget=%s",
self._bank_id, len(query), self._budget)
resp = self._run_hindsight_operation(
lambda client: client.areflect(
bank_id=self._bank_id, query=query, budget=self._budget
)
)
resp = self._run_sync(client.areflect(
bank_id=self._bank_id, query=query, budget=self._budget
))
logger.debug("Tool hindsight_reflect: response_len=%d", len(resp.text or ""))
return json.dumps({"result": resp.text or "No relevant memories found."})
except Exception as e:
@@ -1316,19 +1231,9 @@ class HindsightMemoryProvider(MemoryProvider):
if self._client is not None:
try:
if self._mode == "local_embedded":
# HindsightEmbedded.close() delegates to its sync client.close().
# When Hermes created/used that client on the shared async loop,
# closing it from this thread can raise "attached to a different
# loop" before aiohttp releases the session. Close the embedded
# inner async client on the shared loop first, then let the
# wrapper clean up daemon/UI bookkeeping.
inner_client = getattr(self._client, "_client", None)
if inner_client is not None and hasattr(inner_client, "aclose"):
_run_sync(inner_client.aclose())
try:
self._client._client = None
except Exception:
pass
# Use the public close() API. The RuntimeError from
# aiohttp's "attached to a different loop" is expected
# and harmless — the daemon keeps running independently.
try:
self._client.close()
except RuntimeError:
+1 -1
View File
@@ -43,7 +43,7 @@ _TIMEOUT = 30.0
# ---------------------------------------------------------------------------
# Process-level atexit safety net — ensures pending sessions are committed
# even if shutdown_memory_provider is never called (e.g. gateway crash,
# SIGKILL, or exception in the session expiry watcher preventing shutdown).
# SIGKILL, or exception in _async_flush_memories preventing shutdown).
# ---------------------------------------------------------------------------
_last_active_provider: Optional["OpenVikingMemoryProvider"] = None
-11
View File
@@ -78,16 +78,6 @@ termux = [
]
dingtalk = ["dingtalk-stream>=0.20,<1", "alibabacloud-dingtalk>=2.0.0", "qrcode>=7.0,<8"]
feishu = ["lark-oapi>=1.5.3,<2", "qrcode>=7.0,<8"]
google = [
# Required by the google-workspace skill (Gmail, Calendar, Drive, Contacts,
# Sheets, Docs). Declared here so packagers (Nix, Homebrew) ship them with
# the [all] extra and users don't hit runtime `pip install` paths that fail
# in environments without pip (e.g. Nix-managed Python).
"google-api-python-client>=2.100,<3",
"google-auth-oauthlib>=1.0,<2",
"google-auth-httplib2>=0.2,<1",
]
# `hermes dashboard` (localhost SPA + API). Not in core to keep the default install lean.
web = ["fastapi>=0.104.0,<1", "uvicorn[standard]>=0.24.0,<1"]
rl = [
"atroposlib @ git+https://github.com/NousResearch/atropos.git@c20c85256e5a45ad31edf8b7276e9c5ee1995a30",
@@ -119,7 +109,6 @@ all = [
"hermes-agent[voice]",
"hermes-agent[dingtalk]",
"hermes-agent[feishu]",
"hermes-agent[google]",
"hermes-agent[mistral]",
"hermes-agent[bedrock]",
"hermes-agent[web]",
+315 -737
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File diff suppressed because it is too large Load Diff
-95
View File
@@ -1,95 +0,0 @@
#!/usr/bin/env python3
"""Build the Hermes Model Catalog — a centralized JSON manifest of curated models.
This script reads the in-repo hardcoded curated lists (``OPENROUTER_MODELS``,
``_PROVIDER_MODELS["nous"]``) and writes them to a JSON manifest that the
Hermes CLI fetches at runtime. Publishing the catalog through the docs site
lets maintainers update model lists without shipping a Hermes release.
The runtime fetcher falls back to the same in-repo hardcoded lists if the
manifest is unreachable, so this script is a convenience for keeping the
manifest in sync not a source of truth.
Usage::
python scripts/build_model_catalog.py
Output: ``website/static/api/model-catalog.json``
Live URL (after ``deploy-site.yml`` runs on merge to main):
``https://hermes-agent.nousresearch.com/docs/api/model-catalog.json``
"""
from __future__ import annotations
import json
import os
import sys
from datetime import datetime, timezone
REPO_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0, REPO_ROOT)
# Ensure HERMES_HOME is set for imports that touch it at module level.
os.environ.setdefault("HERMES_HOME", os.path.join(os.path.expanduser("~"), ".hermes"))
from hermes_cli.models import OPENROUTER_MODELS, _PROVIDER_MODELS # noqa: E402
OUTPUT_PATH = os.path.join(REPO_ROOT, "website", "static", "api", "model-catalog.json")
CATALOG_VERSION = 1
def build_catalog() -> dict:
return {
"version": CATALOG_VERSION,
"updated_at": datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ"),
"metadata": {
"source": "hermes-agent repo",
"docs": "https://hermes-agent.nousresearch.com/docs/reference/model-catalog",
},
"providers": {
"openrouter": {
"metadata": {
"display_name": "OpenRouter",
"note": (
"Descriptions drive picker badges. Live /api/v1/models "
"filters curated ids by tool-calling support and free pricing."
),
},
"models": [
{"id": mid, "description": desc}
for mid, desc in OPENROUTER_MODELS
],
},
"nous": {
"metadata": {
"display_name": "Nous Portal",
"note": (
"Free-tier gating is determined live via Portal pricing "
"(partition_nous_models_by_tier), not this manifest."
),
},
"models": [
{"id": mid}
for mid in _PROVIDER_MODELS.get("nous", [])
],
},
},
}
def main() -> int:
catalog = build_catalog()
os.makedirs(os.path.dirname(OUTPUT_PATH), exist_ok=True)
with open(OUTPUT_PATH, "w") as fh:
json.dump(catalog, fh, indent=2)
fh.write("\n")
print(f"Wrote {OUTPUT_PATH}")
for provider, block in catalog["providers"].items():
print(f" {provider}: {len(block['models'])} models")
return 0
if __name__ == "__main__":
sys.exit(main())
+377
View File
@@ -0,0 +1,377 @@
# Compression Eval — Design
Status: proposal. Nothing under `scripts/compression_eval/` runs in CI.
This is an offline tool authors run before merging prompt or algorithm
changes to `agent/context_compressor.py`.
## Why
We tune the compressor prompt and the `_template_sections` checklist by
hand, ship, and wait for the next real session to notice regressions.
There is no automated check that a prompt edit still preserves file
paths, error messages, or the active task across a compression.
Factory.ai's December 2025 write-up
(https://factory.ai/news/evaluating-compression) describes a
probe-based eval that scores compressed state on six dimensions. The
methodology is the valuable part — the benchmarks in the post are a
marketing piece. We adopt the methodology and discard the scoreboard.
## Goal
Given a real session transcript and a bank of probe questions that
exercise what the transcript contained, answer:
1. After `ContextCompressor.compress()` runs, can the agent still
answer each probe correctly from the compressed state?
2. Which of the six dimensions (accuracy, context awareness, artifact
trail, completeness, continuity, instruction following) is the
prompt weakest on?
3. Does a prompt change improve or regress any dimension vs. the
previous run?
That is the full scope. No "compare against OpenAI and Anthropic"
benchmarking, no public scoreboard, no marketing claims.
## Non-goals
- Not a pytest. Requires API credentials, costs money, takes minutes
per fixture, and output is LLM-graded and non-deterministic.
- Not part of `scripts/run_tests.sh`. Not invoked by CI.
- Not a replacement for the existing compressor unit tests in
`tests/agent/test_context_compressor.py` — those stay as the
structural / boundary / tool-pair-sanitization guard.
- Not a general trajectory eval. Scoped to context compaction only.
## Where it lives
```
scripts/compression_eval/
├── DESIGN.md # this file
├── README.md # how to run, cost expectations, caveats
├── run_eval.py # entry point (fire CLI, like sample_and_compress.py)
├── scrub_fixtures.py # regenerate fixtures from ~/.hermes/sessions/*.jsonl
├── fixtures/ # checked-in scrubbed session snapshots
│ ├── feature-impl-context-priority.json
│ ├── debug-session-feishu-id-model.json
│ └── config-build-competitive-scouts.json
├── probes/ # probe banks paired with fixtures
│ └── <fixture>.probes.json
├── rubric.py # grading prompt + dimension definitions
├── grader.py # judge-model call + score parsing
├── compressor_driver.py # thin wrapper over ContextCompressor
└── results/ # gitignored; timestamped output per run
└── .gitkeep
```
`scripts/` is the right home: offline tooling, no CI involvement,
precedent already set by `sample_and_compress.py`,
`contributor_audit.py`, `discord-voice-doctor.py`.
`environments/` is for Atropos RL training environments — wrong shape.
`tests/` is hermetic and credential-free — incompatible with a
probe-based eval that needs a judge model.
## Fixture format
A fixture is a single compressed-enough conversation captured from a
real session. Stored as JSON (pretty-printed, reviewable in PRs):
```json
{
"name": "401-debug",
"description": "178-turn session debugging a 401 on /api/auth/login",
"model": "anthropic/claude-sonnet-4.6",
"context_length": 200000,
"messages": [
{"role": "system", "content": "..."},
{"role": "user", "content": "..."},
{"role": "assistant", "content": "...", "tool_calls": [...]},
{"role": "tool", "tool_call_id": "...", "content": "..."}
],
"notes": "Captured 2026-04-24 from session 20260424_*.jsonl; \
PII scrubbed; secrets redacted via redact_sensitive_text."
}
```
### Sourcing fixtures
Fixtures are scrubbed snapshots of real sessions from the
maintainer's `~/.hermes/sessions/*.jsonl` store, generated
reproducibly by `scrub_fixtures.py` in this directory. Re-run the
scrubber with `python3 scripts/compression_eval/scrub_fixtures.py`
to regenerate them after a scrubber change.
Three shipped fixtures cover three different session shapes:
| Fixture | Source shape | Messages | Tokens (rough) | Tests |
|---|---|---|---|---|
| `feature-impl-context-priority` | investigate → patch → test → PR → merge | 75 | ~45k | continuation, artifact trail (2 files modified, 1 PR, ~16k skill_view in head) |
| `debug-session-feishu-id-model` | PR triage + upstream docs + decision | 59 | ~28k | recall (PR #, error shape), decision (outcome + reason), large PR diff blocks |
| `config-build-competitive-scouts` | iterative config: 11 cron jobs across 7 weekdays | 61 | ~26k | artifact trail (which jobs, which days), iterative-merge |
The `~26k-45k` token range is below the default 50%-of-200k
compression threshold, so the eval will always **force** a
`compress()` call rather than wait for the natural trigger. That is
the intended shape — we want a controlled single-shot compression so
score deltas are attributable to the prompt change, not to whether
the threshold happened to fire at the same boundary twice.
### Scrubber pipeline
`scrub_fixtures.py` applies, per message:
1. `agent.redact.redact_sensitive_text` — API keys, tokens,
connection strings
2. Username paths: `/home/teknium``/home/user`
3. Personal handles: all case variants of the maintainer name → `user`
4. Email addresses → `contributor@example.com`; git
`Author: Name <addr>` header lines normalised
5. `<REASONING_SCRATCHPAD>...</REASONING_SCRATCHPAD>` and
`<think>...</think>` stripped from assistant content
6. Messaging-platform user mentions (`<@123456>`, `<@***>`) →
`<@user>`
7. First user message paraphrased to remove personal voice;
subsequent user turns kept verbatim after the redactions above
8. System prompt replaced with a generic public-safe placeholder so
we don't check in the maintainer's tuned soul/skills/memory system
block
9. Orphan empty-assistant messages (artifact of scratchpad-only
turns) and trailing tool messages with no matching assistant are
dropped
10. Tool outputs preserved verbatim. An earlier iteration truncated
> 2KB tool bodies to keep fixture JSON small, but that defeats
the purpose: real sessions have 30KB `skill_view` dumps, 10KB
`read_file` outputs, 5KB `web_extract` bodies — compression has
to handle them. Truncation is now a no-op; the pipeline note
remains in `scrubbing_passes` for audit trail clarity.
Before every fixture PR: grep the fixture for PII patterns. An
audit is embedded at the bottom of the scrubber as comments.
**Fixtures must stay small.** Target <200 KB per fixture, <500 KB
total for the directory. Current total: ~410 KB across three
fixtures. Larger sessions are truncated with a
`truncated_to: <index>` field in the fixture header so the cut is
reviewable.
## Probe format
One probe file per fixture, so reviewers can see the question bank
evolve alongside the fixture:
```json
{
"fixture": "401-debug",
"probes": [
{
"id": "recall-error-code",
"type": "recall",
"question": "What was the original error code and endpoint?",
"expected_facts": ["401", "/api/auth/login"]
},
{
"id": "artifact-files-modified",
"type": "artifact",
"question": "Which files have been modified in this session?",
"expected_facts": ["session_store.py", "redis_client.py"]
},
{
"id": "continuation-next-step",
"type": "continuation",
"question": "What should we do next?",
"expected_facts": ["re-run the integration tests", "restart the worker"]
},
{
"id": "decision-redis-approach",
"type": "decision",
"question": "What did we decide about the Redis issue?",
"expected_facts": ["switch to redis-py 5.x", "pooled connection"]
}
]
}
```
The four probe types come directly from Factory's methodology:
**recall, artifact, continuation, decision**. `expected_facts` gives
the grader concrete anchors instead of relying purely on LLM taste.
Authoring a probe bank is a one-time cost per fixture. 8-12 probes per
fixture is the target — enough to cover all four types, few enough to
grade in under a minute at reasonable cost.
## Grading
Each probe gets scored 0-5 on **six dimensions** (Factory's six):
| Dimension | What it measures |
|-----------------------|-----------------------------------------------------|
| accuracy | File paths, function names, error codes are correct |
| context_awareness | Reflects current state, not a mid-session snapshot |
| artifact_trail | Knows which files were read / modified / created |
| completeness | Addresses all parts of the probe |
| continuity | Agent can continue without re-fetching |
| instruction_following | Probe answered in the requested form |
Grading is done by a single judge-model call per probe with a
deterministic rubric prompt (see `rubric.py`). The rubric includes the
`expected_facts` list so the judge has a concrete anchor. Default
judge model: whatever the user has configured as their main model at
run time (same resolution path as `auxiliary_client.call_llm`). A
`--judge-model` flag allows overriding for consistency across runs.
Non-determinism caveat: two runs of the same fixture will produce
different scores. A single run means nothing. Report medians over
N=3 runs by default, and require an improvement of >=0.3 on any
dimension before claiming a prompt change is a win.
## Run flow
```
python scripts/compression_eval/run_eval.py [OPTIONS]
```
Options (fire-style, mirroring `sample_and_compress.py`):
| Flag | Default | Purpose |
|------------------------|------------|-------------------------------------------|
| `--fixtures` | all | Comma-separated fixture names |
| `--runs` | 3 | Runs per fixture (for median) |
| `--judge-model` | auto | Override judge model |
| `--compressor-model` | auto | Override model used *inside* the compressor |
| `--label` | timestamp | Subdirectory under `results/` |
| `--focus-topic` | none | Pass-through to `compress(focus_topic=)` |
| `--compare-to` | none | Path to a previous run for diff output |
Steps per fixture per run:
1. Load fixture JSON and probe bank.
2. Construct a `ContextCompressor` against the fixture's model.
3. Call `compressor.compress(messages)` — capture the compressed
message list.
4. For each probe: ask the judge model to role-play as the continuing
agent with only the compressed state, then grade the answer on the
six dimensions using `rubric.py`.
5. Write a per-run JSON to `results/<label>/<fixture>-run-N.json`.
6. After all runs, emit a markdown summary to
`results/<label>/report.md`.
## Report format
Pasted verbatim into PR descriptions that touch the compressor:
```
## Compression eval — label 2026-04-25_13-40-02
Main model: anthropic/claude-sonnet-4.6 Judge: same
3 runs per fixture, medians reported.
| Fixture | Accuracy | Context | Artifact | Complete | Continuity | Instruction | Overall |
|----------------|----------|---------|----------|----------|------------|-------------|---------|
| 401-debug | 4.1 | 4.0 | 2.5 | 4.3 | 3.8 | 5.0 | 3.95 |
| pr-review | 3.9 | 3.8 | 3.1 | 4.2 | 3.9 | 5.0 | 3.98 |
| feature-impl | 4.0 | 3.9 | 2.9 | 4.1 | 4.0 | 5.0 | 3.98 |
Per-probe misses (score < 3.0):
- 401-debug / artifact-files-modified: 1.7 — summary dropped redis_client.py
- pr-review / decision-auth-rewrite: 2.3 — outcome captured, reasoning dropped
```
## Cost expectations
Dominated by the judge calls. For 3 fixtures × 10 probes × 3 runs =
90 judge calls per eval run. On Claude Sonnet 4.6 that is roughly
$0.50-$1.50 per full eval depending on probe length. The compressor
itself makes 1 call per fixture × 3 runs = 9 additional calls.
**This is not a check to run after every commit.** It is a
before-merge check for PRs that touch:
- `agent/context_compressor.py` — any change to `_template_sections`,
`_generate_summary`, or `compress()`.
- `agent/auxiliary_client.py` — when changing how compression tasks
are routed.
- `agent/prompt_builder.py` — when the compression-note phrasing
changes.
## Open questions (to resolve before implementing)
1. **Fixture scrubbing: manual or scripted?** A scripted scrub that
also replaces project names / hostnames would lower the cost of
contributing a new fixture. Risk: over-aggressive replacement
destroys the signal the probe depends on. Propose: start manual,
add scripted helpers once we have 3 fixtures and know the common
PII shapes.
2. **Judge model selection.** Factory uses GPT-5.2. We can't pin one
— user's main model changes. Options: (a) grade with main model
(cheap, inconsistent across users), (b) require a specific judge
model (e.g. `claude-sonnet-4.6`), inconsistent for users without
access. Propose (a) with a `--judge-model` override, and make the
model name prominent in the report so comparisons across machines
are legible.
3. **Noise floor.** Before landing prompt changes, run the current
prompt N=10 times to measure per-dimension stddev. That tells us
the minimum delta to call a change significant. Suspect 0.2-0.3 on
a 0-5 scale. Decision deferred until after the first fixture is
landed.
4. **Iterative-merge coverage.** The real Factory-vs-Anthropic
difference is incremental merge vs. regenerate. A fixture that
only compresses once doesn't exercise our iterative path. Add a
fourth fixture that forces two compressions (manually chained),
with probes that test whether information from the first
compression survives the second. Deferred to a follow-up PR.
## Implementation status
This PR ships the full eval end-to-end:
- `scrub_fixtures.py` — reproducible scrubber
- `fixtures/` — three scrubbed session fixtures
- `probes/` — three probe banks (10-11 probes each, all four types)
- `rubric.py` — six-dimension grading rubric + judge-prompt builder + response parser
- `compressor_driver.py` — thin wrapper around `ContextCompressor` for forced single-shot compression
- `grader.py` — two-phase continuation + grading calls via OpenAI SDK
- `report.py` — markdown report renderer + `--compare-to` delta mode + per-run JSON dumper
- `run_eval.py` — entry point (`fire`-style CLI)
- `tests/scripts/test_compression_eval.py` — 33 unit tests covering rubric parsing, report rendering, fixture/probe loading, and a PII smoke test on the fixtures (LLM paths not tested — they require credentials and are exercised by the eval itself)
### Noise floor — one empirical data point
A single same-inputs re-run of `debug-session-feishu-id-model`
(compressor + judge = `openai/gpt-5.4-mini` via Nous Portal,
runs=1) produced:
- Run A overall: 3.25
- Run B overall: 3.17 (delta -0.08)
Individual dimensions varied by up to ±0.5 between the two runs on
single-run medians. This confirms DESIGN.md's "< 0.3 is noise"
guidance is the right order of magnitude for a single-run
comparison. With `runs=3` default, per-dimension variance should
tighten; noise-floor measurement at N=10 is still a useful
follow-up to calibrate precisely.
## Open follow-ups (not blocking this PR)
1. **Iterative-merge fixture** — our actual compression win over
"regenerate from scratch" approaches is only exercised when
`_previous_summary` is re-used on a second compression. None of
the three shipped fixtures force two compressions. The natural
basis is `config-build-competitive-scouts` (already iterative by
shape); splitting it at the Monday/Tuesday boundary would force
the second compression to merge rather than regenerate.
2. **Noise-floor precision** — run the current prompt N=10 times
against one fixture to pin down per-dimension stddev and publish
the numbers in README.
3. **Scripted scrubber helpers** — the current scrubber is manual
per-fixture. A helper that identifies candidate sessions to
scrub (by shape or by keyword) would lower the cost of adding
fixture #4+.
4. **Judge model selection policy** — current code uses whatever
the user passes as `--judge-model` (default: same as compressor).
Pinning the judge across users would stabilise cross-machine
comparisons, at the cost of blocking users without access to
the pinned model.
+110
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@@ -0,0 +1,110 @@
# compression_eval
Offline eval harness for `agent/context_compressor.py`. Runs a real
conversation transcript through the compressor, then probes the
compressed state with targeted questions graded on six dimensions.
## When to run
Before merging changes to:
- `agent/context_compressor.py` — any change to `_template_sections`,
`_generate_summary`, `compress()`, or its boundary logic
- `agent/auxiliary_client.py` — when changing how compression tasks
are routed
- `agent/prompt_builder.py` — when the compression-note phrasing
changes
## Not for CI
This harness makes real model calls (compressor + continuation +
judge = ~3 calls per probe × probes per fixture × runs). Costs ~$0.50
to ~$1.50 per full run depending on models, takes minutes, is
LLM-graded (non-deterministic). It lives in `scripts/` and is
invoked by hand. `tests/` and `scripts/run_tests.sh` do not touch it.
`tests/scripts/test_compression_eval.py` covers the non-LLM code
paths (rubric parsing, report rendering, fixture/probe loading, PII
smoke check on the checked-in fixtures) and DOES run in CI.
## Usage
```bash
# Run all three fixtures, 3 runs each, with your configured provider
python3 scripts/compression_eval/run_eval.py
# Faster iteration — one fixture, one run
python3 scripts/compression_eval/run_eval.py \
--fixtures=debug-session-feishu-id-model --runs=1
# Pin a cheap model for both compression + judge (recommended)
python3 scripts/compression_eval/run_eval.py \
--compressor-provider=nous --compressor-model=openai/gpt-5.4-mini \
--judge-provider=nous --judge-model=openai/gpt-5.4-mini \
--runs=3 --label=baseline
# After editing context_compressor.py, rerun with a new label and diff
python3 scripts/compression_eval/run_eval.py \
--compressor-provider=nous --compressor-model=openai/gpt-5.4-mini \
--judge-provider=nous --judge-model=openai/gpt-5.4-mini \
--runs=3 --label=my-prompt-tweak \
--compare-to=results/baseline
```
Results land in `results/<label>/report.md` and are intended to be
pasted verbatim into PR descriptions. `--compare-to` renders a delta
column per dimension so reviewers can see "did this actually help?"
at a glance.
Rule of thumb: dimension deltas below ±0.3 are within run-to-run
noise on `runs=3`. Publish a bigger N if you want tighter bounds.
## Fixtures
Three scrubbed session snapshots live under `fixtures/`:
- `feature-impl-context-priority.json` — 75 msgs, investigate →
patch → test → PR → merge
- `debug-session-feishu-id-model.json` — 59 msgs, PR triage +
upstream docs + decision
- `config-build-competitive-scouts.json` — 61 msgs, iterative
config accumulation (11 cron jobs)
Regenerate them from the maintainer's `~/.hermes/sessions/*.jsonl`
with `python3 scripts/compression_eval/scrub_fixtures.py`. The
scrubber pipeline and PII-audit checklist are documented in
`DESIGN.md` under **Scrubber pipeline**.
## Probes
One probe bank per fixture under `probes/`, 10-11 probes each,
covering all four types: **recall**, **artifact**, **continuation**,
**decision**. Each probe carries an `expected_facts` list of concrete
anchors (PR numbers, file paths, error codes, commands run) that the
judge sees alongside the assistant's answer.
## How it scores
Six dimensions, 0-5 per probe:
| Dimension | What it measures |
|-----------------------|------------------------------------------------------|
| accuracy | File paths, function names, PR/issue numbers correct |
| context_awareness | Reflects current session state, not a snapshot |
| artifact_trail | Correctly enumerates files / commands / PRs |
| completeness | Addresses ALL parts of the probe |
| continuity | Next assistant could continue without re-fetching |
| instruction_following | Answer in the requested form |
Report renders medians across N runs; probes scoring below 3.0
overall surface in a separate section with the judge's specific
complaint noted inline.
## Related
- `agent/context_compressor.py` — the thing under test
- `tests/agent/test_context_compressor.py` — structural unit tests
that do run in CI
- `scripts/sample_and_compress.py` — the closest existing script in
shape (offline, credential-requiring, not in CI)
- `DESIGN.md` — full architecture + methodology + open follow-ups
@@ -0,0 +1,114 @@
"""Wraps ContextCompressor to run a single forced compression on a fixture.
The real agent loop checks ``should_compress()`` before calling ``compress()``.
Fixtures are intentionally sized below the 100k threshold so ``compress()``
runs in a controlled, single-shot mode score deltas attribute to the
prompt change, not to whether the threshold happened to fire at the same
boundary twice.
Resolves the provider for the compression call via the same path the real
agent uses (``hermes_cli.runtime_provider.resolve_runtime_provider``) so
behaviour matches production aside from being a single call.
"""
from __future__ import annotations
import sys
from pathlib import Path
from typing import Any, Dict, List, Optional
# Make sibling imports work whether invoked as a script or as a module.
_REPO_ROOT = Path(__file__).resolve().parents[2]
if str(_REPO_ROOT) not in sys.path:
sys.path.insert(0, str(_REPO_ROOT))
from agent.context_compressor import ( # noqa: E402
ContextCompressor,
estimate_messages_tokens_rough,
)
def run_compression(
*,
messages: List[Dict[str, Any]],
compressor_model: str,
compressor_provider: str,
compressor_base_url: str,
compressor_api_key: str,
compressor_api_mode: str,
context_length: int,
focus_topic: Optional[str] = None,
summary_model_override: Optional[str] = None,
) -> Dict[str, Any]:
"""Run a single forced compression pass over the fixture messages.
Returns a dict with:
- compressed_messages: the post-compression message list
- summary_text: the summary produced (extracted from the compressed head)
- pre_tokens, post_tokens: rough token counts before/after
- compression_ratio: 1 - (post/pre)
- pre_message_count, post_message_count
"""
compressor = ContextCompressor(
model=compressor_model,
threshold_percent=0.50,
protect_first_n=3,
protect_last_n=20,
summary_target_ratio=0.20,
quiet_mode=True,
summary_model_override=summary_model_override or "",
base_url=compressor_base_url,
api_key=compressor_api_key,
config_context_length=context_length,
provider=compressor_provider,
api_mode=compressor_api_mode,
)
pre_tokens = estimate_messages_tokens_rough(messages)
compressed = compressor.compress(
messages,
current_tokens=pre_tokens,
focus_topic=focus_topic,
)
post_tokens = estimate_messages_tokens_rough(compressed)
summary_text = _extract_summary_from_messages(compressed)
ratio = (1.0 - (post_tokens / pre_tokens)) if pre_tokens > 0 else 0.0
return {
"compressed_messages": compressed,
"summary_text": summary_text,
"pre_tokens": pre_tokens,
"post_tokens": post_tokens,
"compression_ratio": ratio,
"pre_message_count": len(messages),
"post_message_count": len(compressed),
}
_SUMMARY_MARKERS = (
"## Active Task",
"## Goal",
"## Completed Actions",
)
def _extract_summary_from_messages(messages: List[Dict[str, Any]]) -> str:
"""Find the structured summary block inside the compressed message list.
The compressor injects the summary as a user (or system-appended) message
near the head. We look for the section-header markers from
``_template_sections`` in ``agent/context_compressor.py``.
"""
for msg in messages:
content = msg.get("content")
if not isinstance(content, str):
if isinstance(content, list):
content = "\n".join(
p.get("text", "") for p in content if isinstance(p, dict)
)
else:
continue
if any(marker in content for marker in _SUMMARY_MARKERS):
return content
return ""
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
+181
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@@ -0,0 +1,181 @@
"""Two-phase probe grading.
Phase 1 **Continuation**: simulate the next assistant turn. Feed the
compressed message list plus the probe question and ask the continuing
model to answer using only the compressed context. This is exactly what
a real next-turn call would look like.
Phase 2 **Grading**: a separate judge-model call scores the answer on
the six rubric dimensions using ``rubric.build_judge_prompt``.
Both phases use the OpenAI SDK directly against the resolved provider
endpoint, so the explicit api_key + base_url we pass always reaches the
wire. (``agent.auxiliary_client.call_llm`` is designed for task-tagged
auxiliary calls backed by config lookups; for eval we need the explicit
credentials to win unconditionally.)
"""
from __future__ import annotations
import logging
import sys
from pathlib import Path
from typing import Any, Dict, List, Optional
_REPO_ROOT = Path(__file__).resolve().parents[2]
if str(_REPO_ROOT) not in sys.path:
sys.path.insert(0, str(_REPO_ROOT))
from openai import OpenAI # noqa: E402
from rubric import build_judge_prompt, parse_judge_response # noqa: E402
logger = logging.getLogger(__name__)
_CONTINUATION_SYSTEM = (
"You are the continuing assistant in a long session. Earlier turns have "
"been compacted into a handoff summary that is now part of the "
"conversation history. The user has just asked you a question. "
"Answer using ONLY what you can determine from the conversation history "
"you see (including the handoff summary). Do NOT invent details. If the "
"summary does not contain a specific fact, say so explicitly rather "
"than guessing. Be direct and concrete — cite file paths, PR numbers, "
"error codes, and exact values when they are present in the summary."
)
def answer_probe(
*,
compressed_messages: List[Dict[str, Any]],
probe_question: str,
model: str,
provider: str,
base_url: str,
api_key: str,
max_tokens: int = 1024,
timeout: Optional[float] = 120.0,
) -> str:
"""Run the continuation call: what does the next assistant answer?
Builds a messages list of [system_continuation, *compressed, probe_user]
and asks the configured model. Returns the answer content as a string.
"""
# Strip any pre-existing system message from the compressed list and
# replace with our continuation system prompt. The fixture's generic
# system is not the right frame for the continuation simulation.
history = [m for m in compressed_messages if m.get("role") != "system"]
messages = (
[{"role": "system", "content": _CONTINUATION_SYSTEM}]
+ _sanitize_for_chat_api(history)
+ [{"role": "user", "content": probe_question}]
)
client = OpenAI(api_key=api_key, base_url=base_url, timeout=timeout)
response = client.chat.completions.create(
model=model,
messages=messages,
max_tokens=max_tokens,
)
content = response.choices[0].message.content
if not isinstance(content, str):
content = "" if content is None else str(content)
return content.strip()
def grade_probe(
*,
probe_question: str,
probe_type: str,
expected_facts: List[str],
assistant_answer: str,
judge_model: str,
judge_provider: str,
judge_base_url: str,
judge_api_key: str,
max_tokens: int = 512,
timeout: Optional[float] = 120.0,
) -> Dict[str, Any]:
"""Run the judge call and parse the six dimension scores.
Returns dict {scores: {dim: int}, notes: str, overall: float,
raw: str, parse_error: str|None}. On parse failure, scores are zeros
and parse_error is populated the caller decides whether to retry
or accept.
"""
prompt = build_judge_prompt(
probe_question=probe_question,
probe_type=probe_type,
expected_facts=expected_facts,
assistant_answer=assistant_answer,
)
client = OpenAI(api_key=judge_api_key, base_url=judge_base_url, timeout=timeout)
response = client.chat.completions.create(
model=judge_model,
messages=[{"role": "user", "content": prompt}],
max_tokens=max_tokens,
)
raw = response.choices[0].message.content or ""
if not isinstance(raw, str):
raw = str(raw)
try:
parsed = parse_judge_response(raw)
parsed["raw"] = raw
parsed["parse_error"] = None
return parsed
except ValueError as exc:
logger.warning("Judge response parse failed: %s | raw=%r", exc, raw[:200])
from rubric import DIMENSIONS
return {
"scores": {d: 0 for d in DIMENSIONS},
"notes": "",
"overall": 0.0,
"raw": raw,
"parse_error": str(exc),
}
def _sanitize_for_chat_api(
messages: List[Dict[str, Any]],
) -> List[Dict[str, Any]]:
"""Drop tool_calls/tool pairs that are incomplete.
A compressed message list may contain tool_call references whose matching
``tool`` result was summarized away, which breaks strict-validator
providers (Anthropic, OpenAI). Easiest correct behaviour for the eval:
strip tool_calls entirely and drop ``tool`` role messages the
continuation model only needs the summary + recent turns to answer the
probe, not the precise tool-call bookkeeping.
"""
clean: List[Dict[str, Any]] = []
for m in messages:
role = m.get("role")
if role == "tool":
# Convert tool result to a plain user note so the continuation
# model still sees the content without needing the structured
# tool_call_id pairing.
content = m.get("content")
if isinstance(content, list):
content = "\n".join(
p.get("text", "") for p in content if isinstance(p, dict)
)
clean.append({
"role": "user",
"content": f"[earlier tool result]\n{content or ''}",
})
continue
new = {"role": role, "content": m.get("content", "")}
# Drop tool_calls — the downstream assistant message's content
# still describes what the agent was doing.
clean.append(new)
# Collapse consecutive same-role turns into one (alternation rule)
merged: List[Dict[str, Any]] = []
for m in clean:
if merged and merged[-1]["role"] == m["role"]:
prev = merged[-1]
prev_c = prev.get("content") or ""
new_c = m.get("content") or ""
prev["content"] = f"{prev_c}\n\n{new_c}" if prev_c else new_c
else:
merged.append(m)
return merged
@@ -0,0 +1,96 @@
{
"fixture": "config-build-competitive-scouts",
"description": "Probes for the competitive-scout cron-job setup session. Anchors are which agents were configured, which day of the week each runs, and the full final schedule. This fixture most directly tests artifact-trail and iterative-merge because the job list grows by one per user turn.",
"probes": [
{
"id": "recall-first-repo",
"type": "recall",
"question": "What was the first repository the user asked to create a scout cron for, and on what day of the week?",
"expected_facts": ["openclaw", "Sunday"]
},
{
"id": "recall-closed-source-target",
"type": "recall",
"question": "One of the scout targets does not have an open-source repository and had to be configured as a web scan instead. Which one, and on what day?",
"expected_facts": ["claude code", "Friday", "web scan"]
},
{
"id": "artifact-all-jobs",
"type": "artifact",
"question": "List every scout cron job created in this session.",
"expected_facts": [
"openclaw-pr-scout",
"nanoclaw-pr-scout",
"ironclaw-pr-scout",
"kilocode-pr-scout",
"codex-pr-scout",
"gemini-cli-pr-scout",
"cline-pr-scout",
"opencode-pr-scout",
"claude-code-scout",
"aider-pr-scout",
"roocode-pr-scout"
]
},
{
"id": "artifact-final-schedule",
"type": "artifact",
"question": "What is the final weekly schedule? Give the day and the agents scanned on each day.",
"expected_facts": [
"Sun: openclaw, nanoclaw, ironclaw",
"Mon: kilo code",
"Tue: codex",
"Wed: gemini cli, cline",
"Thu: opencode",
"Fri: claude code",
"Sat: aider, roo"
]
},
{
"id": "artifact-sunday-count",
"type": "artifact",
"question": "How many cron jobs run on Sunday?",
"expected_facts": ["3", "three", "openclaw, nanoclaw, ironclaw"]
},
{
"id": "artifact-total-count",
"type": "artifact",
"question": "How many scout cron jobs were created in total by the end of the session?",
"expected_facts": ["11", "eleven"]
},
{
"id": "decision-kilo-open-source",
"type": "decision",
"question": "The user asked whether Kilo Code is open source. What was the answer, and what did the user decide to do with it?",
"expected_facts": [
"yes, open source",
"Kilo-Org/kilocode",
"added as Monday scout"
]
},
{
"id": "decision-saturday-fill",
"type": "decision",
"question": "Saturday was the last open day at one point. Which scout(s) were placed on Saturday, and why were those chosen?",
"expected_facts": ["aider", "roo", "filled in last based on openrouter popularity / cli comparison rankings"]
},
{
"id": "continuation-execution-time",
"type": "continuation",
"question": "At what local time of day do these scout cron jobs run?",
"expected_facts": ["10 AM Pacific", "17:00 UTC", "0 17 * * *"]
},
{
"id": "continuation-skill-used",
"type": "continuation",
"question": "Each scout job runs with a specific skill preloaded. Which one?",
"expected_facts": ["hermes-agent-dev"]
},
{
"id": "continuation-weekday-coverage",
"type": "continuation",
"question": "After the session ended, are there any weekdays still uncovered by a scout job?",
"expected_facts": ["no", "all 7 days covered", "full week loaded"]
}
]
}
@@ -0,0 +1,72 @@
{
"fixture": "debug-session-feishu-id-model",
"description": "Probes for the Feishu identity-model PR #8388 triage session. Anchors are the PR number, what the PR actually contained, what upstream docs confirmed, and the final decision + reasoning.",
"probes": [
{
"id": "recall-pr-number",
"type": "recall",
"question": "What is the PR number under review in this session, and what repository is it against?",
"expected_facts": ["PR #8388", "NousResearch/hermes-agent", "hermes-agent"]
},
{
"id": "recall-bug-claim",
"type": "recall",
"question": "What is the core bug the PR claims to fix? Be specific about the identifier involved.",
"expected_facts": ["open_id", "app-scoped", "not canonical", "Feishu identity model"]
},
{
"id": "recall-upstream-confirmation",
"type": "recall",
"question": "Do upstream Feishu/Lark docs confirm that open_id is app-scoped rather than a canonical cross-app identity?",
"expected_facts": ["yes", "confirmed", "open.feishu.cn", "same user has different Open IDs in different apps"]
},
{
"id": "artifact-pr-scope",
"type": "artifact",
"question": "Roughly how large is PR #8388, and which gateway subsystems does it touch beyond the Feishu adapter?",
"expected_facts": ["4647 lines", "gateway/run.py", "cron/scheduler.py", "gateway/config.py", "multi-account", "bind"]
},
{
"id": "artifact-new-tool",
"type": "artifact",
"question": "Does the PR add a new tool file? If so, what is its path?",
"expected_facts": ["tools/feishu_id_tool.py", "new file"]
},
{
"id": "decision-pr-assessment",
"type": "decision",
"question": "What is the reviewer's overall assessment of PR #8388 — approve, reject, or something more nuanced? Explain in one sentence.",
"expected_facts": [
"core claim is correct",
"scope is wrong",
"bait-and-switch",
"overbuilt",
"implement cleaner ourselves"
]
},
{
"id": "decision-core-claim-validity",
"type": "decision",
"question": "Setting aside the PR's size, is the underlying identity-model concern technically valid or not?",
"expected_facts": ["technically valid", "correct", "open_id is app-scoped"]
},
{
"id": "continuation-next-action",
"type": "continuation",
"question": "Based on the review outcome, what is the next action the agent has been asked to take regarding this PR?",
"expected_facts": ["close the PR", "implement ourselves", "cleaner", "less complex"]
},
{
"id": "continuation-implementation-scope",
"type": "continuation",
"question": "If implementing the Feishu fix cleanly ourselves, which specific behaviour needs to change — what should replace the current use of open_id?",
"expected_facts": ["use union_id", "or user_id", "canonical identity", "cross-app stable ID"]
},
{
"id": "continuation-sources-to-reference",
"type": "continuation",
"question": "Which upstream documentation sources were fetched during review that should be referenced when writing the clean implementation?",
"expected_facts": ["open.feishu.cn", "open.larkoffice.com", "user-identity-introduction"]
}
]
}
@@ -0,0 +1,74 @@
{
"fixture": "feature-impl-context-priority",
"description": "Probes for the .hermes.md / AGENTS.md / CLAUDE.md / .cursorrules priority feature session. Anchors are the concrete facts the next assistant would need to continue: user's priority order, files modified, helper-function structure, live-test scenarios, and PR number.",
"probes": [
{
"id": "recall-priority-order",
"type": "recall",
"question": "What is the priority order the user asked for when multiple project-context files are present? List them from highest to lowest priority.",
"expected_facts": [".hermes.md", "AGENTS.md", "CLAUDE.md", ".cursorrules", "highest to lowest"]
},
{
"id": "recall-selection-mode",
"type": "recall",
"question": "When multiple context files exist in the same directory, does the agent now load all of them or pick only one?",
"expected_facts": ["only one", "priority-based selection", "highest-priority winner"]
},
{
"id": "artifact-files-modified",
"type": "artifact",
"question": "Which files in the hermes-agent repository were modified during this session? List them.",
"expected_facts": [
"agent/prompt_builder.py",
"tests/agent/test_prompt_builder.py"
]
},
{
"id": "artifact-helper-functions",
"type": "artifact",
"question": "The session introduced separate helper functions for each context-file type. What are their names?",
"expected_facts": [
"_load_hermes_md",
"_load_agents_md",
"_load_claude_md",
"_load_cursorrules"
]
},
{
"id": "artifact-test-scenarios",
"type": "artifact",
"question": "A scratch directory was created with scenario subdirectories to live-test the priority chain. Roughly how many scenarios, and what directory was it created under?",
"expected_facts": ["10 scenarios", "/tmp/context-priority-test"]
},
{
"id": "decision-claude-md-was-unsupported",
"type": "decision",
"question": "What was the finding about CLAUDE.md support in the existing loader before this session's changes?",
"expected_facts": ["CLAUDE.md was not handled", "not supported", "new handler added"]
},
{
"id": "decision-load-all-or-one",
"type": "decision",
"question": "Was the decision to load multiple context files when present, or to load only the highest-priority one? Explain the reasoning in one sentence.",
"expected_facts": ["load only one", "highest priority", "user preference", "do not want to load multiple"]
},
{
"id": "continuation-pr-number-and-status",
"type": "continuation",
"question": "A pull request was opened for this feature. What is the PR number and what is its merge status?",
"expected_facts": ["PR #2301", "merged", "squash"]
},
{
"id": "continuation-test-suite-result",
"type": "continuation",
"question": "What was the result of the full test suite run after the implementation changes?",
"expected_facts": ["5680 passed", "0 failures", "clean"]
},
{
"id": "continuation-next-step",
"type": "continuation",
"question": "If asked to pick up this session, what is the current state of main? Anything left to do?",
"expected_facts": ["merged to main", "main is current", "nothing outstanding", "pulled"]
}
]
}
+235
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@@ -0,0 +1,235 @@
"""Markdown report rendering + diff-against-baseline for compression-eval runs.
Report format is optimised for pasting directly into a PR description.
Top-of-report table is the per-fixture medians; below that is the
probe-by-probe miss list (scores < 3.0 on overall).
Diff mode (``compare_to``) emits a second table with deltas per fixture
per dimension against a previous run directory.
"""
from __future__ import annotations
import json
import statistics
from pathlib import Path
from typing import Any, Dict, List, Optional
from rubric import DIMENSIONS
def write_run_json(
*,
results_dir: Path,
fixture_name: str,
run_index: int,
payload: Dict[str, Any],
) -> Path:
"""Dump one fixture's per-run results as JSON for later diffing."""
results_dir.mkdir(parents=True, exist_ok=True)
path = results_dir / f"{fixture_name}-run-{run_index}.json"
with path.open("w") as fh:
json.dump(payload, fh, indent=2, ensure_ascii=False)
return path
def _median(values: List[float]) -> float:
return statistics.median(values) if values else 0.0
def _format_score(value: float) -> str:
return f"{value:.2f}"
def _format_delta(baseline: float, current: float) -> str:
delta = current - baseline
if abs(delta) < 0.01:
return f"{current:.2f} (±0)"
sign = "+" if delta > 0 else ""
return f"{current:.2f} ({sign}{delta:.2f})"
def summarize_fixture_runs(
fixture_runs: List[Dict[str, Any]],
) -> Dict[str, Any]:
"""Collapse N runs of one fixture into per-dimension medians + metadata.
Each run payload is {probes: [{id, type, scores: {...}, overall, ...}]}.
Returns {fixture_name, runs, dimension_medians, overall_median, misses}.
"""
if not fixture_runs:
return {}
fixture_name = fixture_runs[0]["fixture_name"]
n_runs = len(fixture_runs)
# Per-probe-per-dimension aggregation across runs
probe_ids = [p["id"] for p in fixture_runs[0]["probes"]]
per_probe: Dict[str, Dict[str, List[float]]] = {
pid: {d: [] for d in DIMENSIONS} for pid in probe_ids
}
per_probe_overall: Dict[str, List[float]] = {pid: [] for pid in probe_ids}
for run in fixture_runs:
for p in run["probes"]:
pid = p["id"]
for d in DIMENSIONS:
per_probe[pid][d].append(p["scores"].get(d, 0))
per_probe_overall[pid].append(p["overall"])
# Median each probe across runs, then median those medians across probes
dim_medians: Dict[str, float] = {}
for d in DIMENSIONS:
per_probe_med = [_median(per_probe[pid][d]) for pid in probe_ids]
dim_medians[d] = _median(per_probe_med)
overall_median = _median([_median(per_probe_overall[pid]) for pid in probe_ids])
# Misses = probes whose median overall < 3.0
misses: List[Dict[str, Any]] = []
for pid in probe_ids:
med = _median(per_probe_overall[pid])
if med < 3.0:
# Pull the notes from the last run to give the reader a
# concrete clue. (Taking the most recent run is fine —
# notes vary across runs and any one is illustrative.)
notes = ""
probe_type = ""
for p in fixture_runs[-1]["probes"]:
if p["id"] == pid:
notes = p.get("notes", "")
probe_type = p.get("type", "")
break
misses.append({
"id": pid,
"type": probe_type,
"overall_median": med,
"notes": notes,
})
return {
"fixture_name": fixture_name,
"runs": n_runs,
"dimension_medians": dim_medians,
"overall_median": overall_median,
"misses": misses,
"compression": fixture_runs[0].get("compression", {}),
}
def render_report(
*,
label: str,
compressor_model: str,
judge_model: str,
runs_per_fixture: int,
summaries: List[Dict[str, Any]],
baseline_summaries: Optional[List[Dict[str, Any]]] = None,
) -> str:
"""Render the full markdown report.
baseline_summaries is the same shape as summaries, sourced from a
previous run (via --compare-to). When present, dimension scores in
the main table render with deltas.
"""
lines: List[str] = []
lines.append(f"## Compression eval — label `{label}`")
lines.append("")
lines.append(f"- Compressor model: `{compressor_model}`")
lines.append(f"- Judge model: `{judge_model}`")
lines.append(f"- Runs per fixture: {runs_per_fixture}")
lines.append("- Medians over runs reported")
if baseline_summaries:
lines.append("- Deltas shown against baseline run")
lines.append("")
baseline_by_name: Dict[str, Dict[str, Any]] = {}
if baseline_summaries:
baseline_by_name = {s["fixture_name"]: s for s in baseline_summaries}
# Main table
header = ["Fixture"] + DIMENSIONS + ["overall"]
lines.append("| " + " | ".join(header) + " |")
lines.append("|" + "|".join(["---"] * len(header)) + "|")
for s in summaries:
row = [s["fixture_name"]]
baseline = baseline_by_name.get(s["fixture_name"])
for d in DIMENSIONS:
cur = s["dimension_medians"][d]
if baseline and d in baseline.get("dimension_medians", {}):
row.append(_format_delta(baseline["dimension_medians"][d], cur))
else:
row.append(_format_score(cur))
if baseline:
row.append(_format_delta(baseline["overall_median"], s["overall_median"]))
else:
row.append(_format_score(s["overall_median"]))
lines.append("| " + " | ".join(row) + " |")
lines.append("")
# Compression metadata
lines.append("### Compression summary")
lines.append("")
lines.append("| Fixture | Pre tokens | Post tokens | Ratio | Pre msgs | Post msgs |")
lines.append("|---|---|---|---|---|---|")
for s in summaries:
c = s.get("compression", {})
lines.append(
"| {name} | {pre} | {post} | {ratio:.1%} | {pm} | {pom} |".format(
name=s["fixture_name"],
pre=c.get("pre_tokens", 0),
post=c.get("post_tokens", 0),
ratio=c.get("compression_ratio", 0.0),
pm=c.get("pre_message_count", 0),
pom=c.get("post_message_count", 0),
)
)
lines.append("")
# Per-probe misses
any_misses = any(s["misses"] for s in summaries)
if any_misses:
lines.append("### Probes scoring below 3.0 overall (median)")
lines.append("")
for s in summaries:
if not s["misses"]:
continue
lines.append(f"**{s['fixture_name']}**")
for m in s["misses"]:
note_part = f"{m['notes']}" if m["notes"] else ""
lines.append(
f"- `{m['id']}` ({m['type']}): "
f"{m['overall_median']:.2f}{note_part}"
)
lines.append("")
lines.append("### Methodology")
lines.append("")
lines.append(
"Probe-based eval adapted from "
"https://factory.ai/news/evaluating-compression. Each fixture is "
"compressed in a single forced `ContextCompressor.compress()` call, "
"then a continuation call asks the compressor model to answer each "
"probe from the compressed state, then the judge model scores the "
"answer 0-5 on six dimensions. A single run is noisy; medians "
"across multiple runs are the meaningful signal. Changes below "
"~0.3 on any dimension are likely within run-to-run noise."
)
return "\n".join(lines) + "\n"
def load_baseline_summaries(baseline_dir: Path) -> List[Dict[str, Any]]:
"""Load summaries from a previous eval run for --compare-to.
Reads the dumped per-run JSONs and re-summarises them so the
aggregation matches whatever summariser was current at the time of
the new run (forward-compatible with schema additions).
"""
if not baseline_dir.exists():
raise FileNotFoundError(f"baseline dir not found: {baseline_dir}")
by_fixture: Dict[str, List[Dict[str, Any]]] = {}
for path in sorted(baseline_dir.glob("*-run-*.json")):
with path.open() as fh:
payload = json.load(fh)
by_fixture.setdefault(payload["fixture_name"], []).append(payload)
return [summarize_fixture_runs(runs) for runs in by_fixture.values()]

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