refactor: remove temporary API payload logging and enhance session log structure
- Eliminated the `_log_api_payload` method used for temporary debugging, streamlining the codebase. - Updated the `_save_session_log` method to save the full raw session, including all messages and metadata, improving the clarity and completeness of session logs. - Adjusted session log entry to include additional context such as `base_url` and `platform` for better tracking.
This commit is contained in:
teknium1
106
run_agent.py
106
run_agent.py
@@ -2021,66 +2021,6 @@ class AIAgent:
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except Exception as e:
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print(f"⚠️ Failed to save trajectory: {e}")
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def _log_api_payload(self, turn_number: int, api_kwargs: Dict[str, Any], response=None):
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"""
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[TEMPORARY DEBUG] Log the full API payload and response token metrics
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for each agent turn to a per-session JSONL file for inspection.
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Writes one JSON line per turn to logs/payload_<session_id>.jsonl.
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Tool schemas are summarized (just names) to keep logs readable.
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Args:
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turn_number: Which API call this is (1-indexed)
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api_kwargs: The full kwargs dict being passed to chat.completions.create
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response: The API response object (optional, added after the call completes)
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"""
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try:
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payload_log_file = self.logs_dir / f"payload_{self.session_id}.jsonl"
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# Build a serializable copy of the request payload
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payload = {
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"turn": turn_number,
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"timestamp": datetime.now().isoformat(),
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"model": api_kwargs.get("model"),
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"max_tokens": api_kwargs.get("max_tokens"),
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"extra_body": api_kwargs.get("extra_body"),
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"num_tools": len(api_kwargs.get("tools") or []),
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"tool_names": [t["function"]["name"] for t in (api_kwargs.get("tools") or [])],
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"messages": api_kwargs.get("messages", []),
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}
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# Add response token metrics if available
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if response is not None:
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try:
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usage_raw = response.usage.model_dump() if hasattr(response.usage, 'model_dump') else {}
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payload["response"] = {
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# Core token counts
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"prompt_tokens": usage_raw.get("prompt_tokens"),
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"completion_tokens": usage_raw.get("completion_tokens"),
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"total_tokens": usage_raw.get("total_tokens"),
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# Completion breakdown (reasoning tokens, etc.)
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"completion_tokens_details": usage_raw.get("completion_tokens_details"),
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# Prompt breakdown (cached tokens, etc.)
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"prompt_tokens_details": usage_raw.get("prompt_tokens_details"),
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# Cost tracking
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"cost": usage_raw.get("cost"),
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"is_byok": usage_raw.get("is_byok"),
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"cost_details": usage_raw.get("cost_details"),
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# Provider info (top-level field from OpenRouter)
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"provider": getattr(response, 'provider', None),
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"response_model": getattr(response, 'model', None),
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}
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except Exception:
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payload["response"] = {"error": "failed to extract usage"}
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with open(payload_log_file, "a", encoding="utf-8") as f:
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f.write(json.dumps(payload, ensure_ascii=False, default=str) + "\n")
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except Exception as e:
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# Silent fail - don't interrupt the agent for debug logging
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if self.verbose_logging:
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logging.warning(f"Failed to log API payload: {e}")
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def _mask_api_key_for_logs(self, key: Optional[str]) -> Optional[str]:
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if not key:
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return None
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@@ -2172,48 +2112,35 @@ class AIAgent:
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def _save_session_log(self, messages: List[Dict[str, Any]] = None):
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"""
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Save the current session trajectory to the logs directory.
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Automatically called after each conversation turn to maintain
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a complete log of the session for debugging and inspection.
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Args:
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messages: Message history to save (uses self._session_messages if not provided)
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Save the full raw session to a JSON file.
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Stores every message exactly as the agent sees it: user messages,
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assistant messages (with reasoning, finish_reason, tool_calls),
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tool responses (with tool_call_id, tool_name), and injected system
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messages (compression summaries, todo snapshots, etc.).
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Overwritten after each turn so it always reflects the latest state.
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"""
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messages = messages or self._session_messages
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if not messages:
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return
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try:
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# Extract the actual user query for the trajectory format.
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# Skip prefill messages (they're ephemeral and shouldn't appear in trajectories)
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# so the first user message we find is the real task prompt.
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first_user_query = ""
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start_idx = len(self.prefill_messages) if self.prefill_messages else 0
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for msg in messages[start_idx:]:
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if msg.get("role") == "user":
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first_user_query = msg.get("content", "")
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break
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# Convert to trajectory format
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trajectory = self._convert_to_trajectory_format(messages, first_user_query, True)
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# Build the session log entry
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entry = {
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"session_id": self.session_id,
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"model": self.model,
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"base_url": self.base_url,
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"platform": self.platform,
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"session_start": self.session_start.isoformat(),
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"last_updated": datetime.now().isoformat(),
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"message_count": len(messages),
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"conversations": trajectory,
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"messages": messages,
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}
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# Write to session log file (overwrite with latest state)
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with open(self.session_log_file, "w", encoding="utf-8") as f:
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json.dump(entry, f, indent=2, ensure_ascii=False)
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json.dump(entry, f, indent=2, ensure_ascii=False, default=str)
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except Exception as e:
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# Silent fail - don't interrupt the user experience for logging issues
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if self.verbose_logging:
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logging.warning(f"Failed to save session log: {e}")
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@@ -2584,9 +2511,6 @@ class AIAgent:
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resp_model = getattr(response, 'model', 'N/A') if response else 'N/A'
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logging.debug(f"API Response received - Model: {resp_model}, Usage: {response.usage if hasattr(response, 'usage') else 'N/A'}")
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# [DEBUG] Log the full API payload + response token metrics
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self._log_api_payload(api_call_count, api_kwargs, response=response)
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# Validate response has valid choices before proceeding
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if response is None or not hasattr(response, 'choices') or response.choices is None or len(response.choices) == 0:
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# Stop spinner before printing error messages
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