fix(merge): restore contracts caught by main-target CI
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@@ -259,6 +259,114 @@ def _truncate_tool_call_args_json(args: str, head_chars: int = 200) -> str:
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return json.dumps(shrunken, ensure_ascii=False)
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_IMAGE_PART_TYPES = frozenset({"image_url", "input_image", "image"})
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def _is_image_part(part: Any) -> bool:
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"""True if ``part`` is a multimodal image content block.
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Recognizes all three shapes the agent handles:
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- OpenAI chat.completions: ``{"type": "image_url", "image_url": ...}``
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- OpenAI Responses API: ``{"type": "input_image", "image_url": "..."}``
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- Anthropic native: ``{"type": "image", "source": {...}}``
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"""
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if not isinstance(part, dict):
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return False
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return part.get("type") in _IMAGE_PART_TYPES
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def _content_has_images(content: Any) -> bool:
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"""True if a message's ``content`` is a multimodal list with image parts."""
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if not isinstance(content, list):
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return False
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return any(_is_image_part(p) for p in content)
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def _strip_images_from_content(content: Any) -> Any:
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"""Return a copy of ``content`` with every image part replaced by a
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short text placeholder.
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- String content is returned unchanged.
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- Non-list, non-string content is returned unchanged.
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- List content: image parts become ``{"type": "text", "text": "[Attached
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image — stripped after compression]"}``; other parts are preserved as-is.
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Input is never mutated.
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"""
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if not isinstance(content, list):
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return content
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if not any(_is_image_part(p) for p in content):
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return content
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new_parts: List[Any] = []
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for p in content:
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if _is_image_part(p):
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new_parts.append({
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"type": "text",
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"text": "[Attached image — stripped after compression]",
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})
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else:
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new_parts.append(p)
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return new_parts
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def _strip_historical_media(messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
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"""Replace image parts in older messages with placeholder text.
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The anchor is the *last* user message that has any image content. Every
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message before that anchor gets its image parts replaced with a short
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placeholder so the outgoing request stops re-shipping the same multi-MB
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base-64 image blobs on every turn.
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If no user message carries images, the list is returned unchanged.
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If the only user message with images is the very first one (nothing
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earlier to strip), the list is returned unchanged.
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Shallow copies of touched messages only; input is never mutated.
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Port of Kilo-Org/kilocode#9434 (adapted for the OpenAI-style message
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shape the hermes compressor emits).
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"""
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if not messages:
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return messages
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# Find the newest user message that carries at least one image part.
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# We anchor on image-bearing user messages (not all user messages) so
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# a plain text follow-up after a big-image turn still strips the old
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# image — matching the problem kilocode#9434 set out to solve.
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anchor = -1
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for i in range(len(messages) - 1, -1, -1):
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msg = messages[i]
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if not isinstance(msg, dict):
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continue
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if msg.get("role") != "user":
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continue
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if _content_has_images(msg.get("content")):
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anchor = i
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break
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if anchor <= 0:
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# No image-bearing user message, or it's the very first message —
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# nothing before it to strip.
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return messages
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changed = False
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result: List[Dict[str, Any]] = []
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for i, msg in enumerate(messages):
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if i >= anchor or not isinstance(msg, dict):
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result.append(msg)
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continue
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content = msg.get("content")
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if not _content_has_images(content):
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result.append(msg)
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continue
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new_msg = msg.copy()
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new_msg["content"] = _strip_images_from_content(content)
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result.append(new_msg)
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changed = True
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return result if changed else messages
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def _summarize_tool_result(tool_name: str, tool_args: str, tool_content: str) -> str:
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"""Create an informative 1-line summary of a tool call + result.
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@@ -410,6 +518,10 @@ class ContextCompressor(ContextEngine):
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self._last_compression_savings_pct = 100.0
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self._ineffective_compression_count = 0
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self._summary_failure_cooldown_until = 0.0 # transient errors must not block a fresh session
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self.last_real_prompt_tokens = 0
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self.last_compression_rough_tokens = 0
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self.last_rough_tokens_when_real_prompt_fit = 0
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self.awaiting_real_usage_after_compression = False
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def update_model(
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self,
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@@ -507,6 +619,10 @@ class ContextCompressor(ContextEngine):
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self.last_prompt_tokens = 0
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self.last_completion_tokens = 0
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self.last_real_prompt_tokens = 0
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self.last_compression_rough_tokens = 0
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self.last_rough_tokens_when_real_prompt_fit = 0
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self.awaiting_real_usage_after_compression = False
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self.summary_model = summary_model_override or ""
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@@ -540,6 +656,44 @@ class ContextCompressor(ContextEngine):
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self.last_prompt_tokens = usage.get("prompt_tokens", 0)
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self.last_completion_tokens = usage.get("completion_tokens", 0)
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self.last_total_tokens = usage.get("total_tokens", self.last_prompt_tokens + self.last_completion_tokens)
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if self.last_prompt_tokens > 0:
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self.last_real_prompt_tokens = self.last_prompt_tokens
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if self.last_prompt_tokens < self.threshold_tokens:
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if self.awaiting_real_usage_after_compression and self.last_compression_rough_tokens > 0:
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self.last_rough_tokens_when_real_prompt_fit = self.last_compression_rough_tokens
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else:
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self.last_rough_tokens_when_real_prompt_fit = 0
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self.awaiting_real_usage_after_compression = False
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def should_defer_preflight_to_real_usage(self, rough_tokens: int) -> bool:
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"""Return True when a high rough preflight estimate is known-noisy.
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``estimate_request_tokens_rough(..., tools=...)`` intentionally
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overestimates schema-heavy requests so Hermes compresses before a
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provider rejects the payload. After a successful compressed API call,
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though, provider ``prompt_tokens`` are a better signal than repeating
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compaction from the same rough schema overhead. Defer only while the
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rough estimate has grown modestly since a request the provider proved
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fit under the threshold.
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"""
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if rough_tokens < self.threshold_tokens:
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return False
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if self.last_real_prompt_tokens <= 0:
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return False
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if self.last_real_prompt_tokens >= self.threshold_tokens:
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return False
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baseline = self.last_rough_tokens_when_real_prompt_fit or self.last_compression_rough_tokens
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if baseline <= 0:
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return False
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growth = max(0, rough_tokens - baseline)
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tolerated_growth = max(4096, int(self.threshold_tokens * 0.05))
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if growth > tolerated_growth:
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return False
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self.last_rough_tokens_when_real_prompt_fit = max(baseline, rough_tokens)
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return True
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def should_compress(self, prompt_tokens: int = None) -> bool:
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"""Check if context exceeds the compression threshold.
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@@ -1837,6 +1991,14 @@ The user has requested that this compaction PRIORITISE preserving all informatio
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compressed = self._sanitize_tool_pairs(compressed)
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# Replace image parts in all compressed messages before the newest
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# image-bearing user turn with a short text placeholder. Without
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# this, tail messages keep their original multi-MB base-64 image
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# payloads forever, which can push every subsequent API request
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# past the provider's body-size limit and wedge the session.
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# Port of Kilo-Org/kilocode#9434.
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compressed = _strip_historical_media(compressed)
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new_estimate = estimate_messages_tokens_rough(compressed)
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saved_estimate = display_tokens - new_estimate
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