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cline-port
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bed05b5191 |
@ -1224,6 +1224,12 @@ def init_agent(
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# targets.
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agent._task_completion_guidance = bool(_agent_section.get("task_completion_guidance", True))
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# Universal parallel-tool-call guidance toggle. Default True. Separate
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# flag from task_completion_guidance because a user may want one but not
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# the other. Steers the model to batch independent tool calls into a
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# single turn; the runtime already executes such batches concurrently.
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agent._parallel_tool_call_guidance = bool(_agent_section.get("parallel_tool_call_guidance", True))
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# Local Python toolchain probe toggle. Default True. When False,
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# the probe is skipped entirely (no subprocess calls, no system-prompt
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# line). Useful for users on exotic setups where the probe heuristics
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@ -305,6 +305,45 @@ TASK_COMPLETION_GUIDANCE = (
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"is always better than inventing a result."
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)
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# Universal parallel-tool-call guidance — applied to ALL models.
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#
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# Why this matters for cost: every assistant turn resends the entire
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# accumulated conversation (and, on cache-friendly providers, re-reads the
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# cached prefix and pays for the newly-appended turn). A model that issues
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# one tool call per turn multiplies the number of round-trips — and therefore
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# the resent context — for any task that needs several independent reads,
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# searches, or safe lookups. Batching independent calls into a single
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# assistant response collapses N turns into one, cutting both latency and the
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# resent-context cost that compounds over a long conversation.
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#
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# The hermes-agent runtime already executes a batch of tool calls
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# concurrently when they are independent (read-only tools always; path-scoped
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# file ops when their targets don't overlap — see
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# run_agent._execute_tool_calls / tool_dispatch_helpers). The missing piece
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# was telling the *model* to emit those calls together in the first place;
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# nothing in the open-source system prompt encouraged batching. This block
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# closes that gap.
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#
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# Short on purpose — shipped in the cached system prompt to every user, every
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# session. Token cost is paid once at install and amortised across all
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# sessions via prefix caching. Keep it tight.
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#
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# Ported from cline/cline#11514 ("encourage parallel tool calls"), adapted
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# from Cline's TypeScript tool-surface guidance to hermes-agent's Python
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# prompt-assembly architecture.
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PARALLEL_TOOL_CALL_GUIDANCE = (
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"# Parallel tool calls\n"
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"When you need several pieces of information that don't depend on each "
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"other, request them together in a single response instead of one tool "
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"call per turn. Independent reads, searches, web fetches, and read-only "
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"commands should be batched into the same assistant turn — the runtime "
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"executes independent calls concurrently, and batching avoids resending "
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"the whole conversation on every extra round-trip.\n"
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"Only serialize calls when a later call genuinely depends on an earlier "
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"call's result (e.g. you must read a file before you can patch it). When "
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"in doubt and the calls are independent, batch them."
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)
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# OpenAI GPT/Codex-specific execution guidance. Addresses known failure modes
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# where GPT models abandon work on partial results, skip prerequisite lookups,
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# hallucinate instead of using tools, and declare "done" without verification.
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@ -33,6 +33,7 @@ from agent.prompt_builder import (
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KANBAN_GUIDANCE,
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MEMORY_GUIDANCE,
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OPENAI_MODEL_EXECUTION_GUIDANCE,
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PARALLEL_TOOL_CALL_GUIDANCE,
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PLATFORM_HINTS,
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SESSION_SEARCH_GUIDANCE,
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SKILLS_GUIDANCE,
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@ -123,6 +124,17 @@ def build_system_prompt_parts(agent: Any, system_message: Optional[str] = None)
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if getattr(agent, "_task_completion_guidance", True) and agent.valid_tool_names:
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stable_parts.append(TASK_COMPLETION_GUIDANCE)
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# Universal parallel-tool-call guidance. Tells the model to batch
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# independent tool calls into one assistant turn rather than emitting one
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# call per turn — the runtime already runs independent calls concurrently
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# (read-only tools always; non-overlapping path-scoped file ops), so the
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# only thing missing was steering the model to produce the batch. Cuts
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# round-trips and the resent-context cost that compounds over a long
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# conversation. Gated by config.yaml ``agent.parallel_tool_call_guidance``
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# (default True) and only injected when tools are actually loaded.
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if getattr(agent, "_parallel_tool_call_guidance", True) and agent.valid_tool_names:
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stable_parts.append(PARALLEL_TOOL_CALL_GUIDANCE)
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# Tool-aware behavioral guidance: only inject when the tools are loaded
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tool_guidance = []
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if "memory" in agent.valid_tool_names:
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@ -853,6 +853,15 @@ DEFAULT_CONFIG = {
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# plausible-looking output when a real path is blocked. Costs ~80
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# tokens in the cached system prompt. Set False to disable globally.
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"task_completion_guidance": True,
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# Universal parallel-tool-call guidance — short prompt block applied to
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# all models that tells the model to batch independent tool calls
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# (reads, searches, web fetches, read-only commands) into one turn
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# instead of one call per turn. The runtime already runs independent
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# calls concurrently, so this just steers the model to produce the
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# batch — cutting round-trips and the resent-context cost that
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# compounds over a long conversation. Costs ~70 tokens in the cached
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# system prompt. Set False to disable globally.
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"parallel_tool_call_guidance": True,
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# Local-environment toolchain probe — surfaces Python/pip/uv/PEP-668
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# state in the system prompt when something non-default is detected
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# (e.g. python3 has no pip module, pip→python version mismatch, PEP
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@ -27,6 +27,7 @@ from agent.prompt_builder import (
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TOOL_USE_ENFORCEMENT_GUIDANCE,
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TOOL_USE_ENFORCEMENT_MODELS,
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OPENAI_MODEL_EXECUTION_GUIDANCE,
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PARALLEL_TOOL_CALL_GUIDANCE,
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MEMORY_GUIDANCE,
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SESSION_SEARCH_GUIDANCE,
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PLATFORM_HINTS,
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@ -1497,6 +1498,43 @@ class TestOpenAIModelExecutionGuidance:
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assert len(OPENAI_MODEL_EXECUTION_GUIDANCE) > 100
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class TestParallelToolCallGuidance:
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"""Behavior contracts for the universal parallel-tool-call guidance block.
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Asserts the invariants the block must satisfy (steer batching, scope to
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independent calls, stay short for the cached prompt) rather than freezing
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its exact wording.
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"""
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def test_is_nonempty_string(self):
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assert isinstance(PARALLEL_TOOL_CALL_GUIDANCE, str)
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assert PARALLEL_TOOL_CALL_GUIDANCE.strip()
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def test_steers_batching_into_one_response(self):
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text = PARALLEL_TOOL_CALL_GUIDANCE.lower()
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# Must tell the model to group independent calls together.
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assert "single response" in text or "same" in text and "turn" in text
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assert "independent" in text
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def test_carves_out_dependent_calls(self):
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# Must NOT tell the model to batch dependent calls — that would break
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# ordering (read-before-patch). The block has to acknowledge the
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# serialize-when-dependent case.
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text = PARALLEL_TOOL_CALL_GUIDANCE.lower()
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assert "depend" in text
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def test_stays_short_for_cached_prompt(self):
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# Shipped in every cached system prompt — keep it tight. The existing
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# task-completion block is ~600 chars; allow generous headroom but
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# guard against accidental essay growth.
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assert len(PARALLEL_TOOL_CALL_GUIDANCE) < 900
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def test_has_a_heading(self):
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# Heading delimits it as its own section in the assembled prompt.
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assert PARALLEL_TOOL_CALL_GUIDANCE.lstrip().startswith("#")
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# =========================================================================
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# Budget warning history stripping
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# =========================================================================
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