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https://github.com/NousResearch/hermes-agent.git
synced 2026-04-25 00:51:20 +00:00
refactor: implement structured logging across multiple modules
- Introduced logging functionality in cli.py, run_agent.py, scheduler.py, and various tool modules to replace print statements with structured logging. - Enhanced error handling and informational messages to improve debugging and monitoring capabilities. - Ensured consistent logging practices across the codebase, facilitating better traceability and maintenance.
This commit is contained in:
teknium1
parent
b6247b71b5
commit
a885d2f240
14 changed files with 303 additions and 303 deletions
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@ -46,6 +46,7 @@ Usage:
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"""
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import json
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import logging
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import os
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import asyncio
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import uuid
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@ -55,6 +56,8 @@ from typing import Dict, Any, List, Optional
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from openai import AsyncOpenAI
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from hermes_constants import OPENROUTER_BASE_URL
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logger = logging.getLogger(__name__)
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_openrouter_client = None
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def _get_openrouter_client():
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@ -108,7 +111,7 @@ DEBUG_DATA = {
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# Create logs directory if debug mode is enabled
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if DEBUG_MODE:
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DEBUG_LOG_PATH.mkdir(exist_ok=True)
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print(f"🐛 MoA debug mode enabled - Session ID: {DEBUG_SESSION_ID}")
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logger.debug("MoA debug mode enabled - Session ID: %s", DEBUG_SESSION_ID)
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def _log_debug_call(tool_name: str, call_data: Dict[str, Any]) -> None:
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@ -149,10 +152,10 @@ def _save_debug_log() -> None:
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with open(debug_filepath, 'w', encoding='utf-8') as f:
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json.dump(DEBUG_DATA, f, indent=2, ensure_ascii=False)
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print(f"🐛 MoA debug log saved: {debug_filepath}")
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logger.debug("MoA debug log saved: %s", debug_filepath)
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except Exception as e:
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print(f"❌ Error saving MoA debug log: {str(e)}")
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logger.error("Error saving MoA debug log: %s", e)
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def _construct_aggregator_prompt(system_prompt: str, responses: List[str]) -> str:
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@ -192,7 +195,7 @@ async def _run_reference_model_safe(
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"""
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for attempt in range(max_retries):
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try:
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print(f"🤖 Querying {model} (attempt {attempt + 1}/{max_retries})")
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logger.info("Querying %s (attempt %s/%s)", model, attempt + 1, max_retries)
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# Build parameters for the API call
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api_params = {
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@ -214,27 +217,27 @@ async def _run_reference_model_safe(
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response = await _get_openrouter_client().chat.completions.create(**api_params)
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content = response.choices[0].message.content.strip()
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print(f"✅ {model} responded ({len(content)} characters)")
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logger.info("%s responded (%s characters)", model, len(content))
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return model, content, True
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except Exception as e:
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error_str = str(e)
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# Log more detailed error information for debugging
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if "invalid" in error_str.lower():
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print(f"⚠️ {model} invalid request error (attempt {attempt + 1}): {error_str}")
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logger.warning("%s invalid request error (attempt %s): %s", model, attempt + 1, error_str)
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elif "rate" in error_str.lower() or "limit" in error_str.lower():
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print(f"⚠️ {model} rate limit error (attempt {attempt + 1}): {error_str}")
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logger.warning("%s rate limit error (attempt %s): %s", model, attempt + 1, error_str)
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else:
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print(f"⚠️ {model} unknown error (attempt {attempt + 1}): {error_str}")
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logger.warning("%s unknown error (attempt %s): %s", model, attempt + 1, error_str)
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if attempt < max_retries - 1:
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# Exponential backoff for rate limiting: 2s, 4s, 8s, 16s, 32s, 60s
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sleep_time = min(2 ** (attempt + 1), 60)
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print(f" Retrying in {sleep_time}s...")
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logger.info("Retrying in %ss...", sleep_time)
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await asyncio.sleep(sleep_time)
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else:
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error_msg = f"{model} failed after {max_retries} attempts: {error_str}"
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print(f"❌ {error_msg}")
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logger.error("%s", error_msg)
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return model, error_msg, False
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@ -256,7 +259,7 @@ async def _run_aggregator_model(
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Returns:
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str: Synthesized final response
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"""
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print(f"🧠 Running aggregator model: {AGGREGATOR_MODEL}")
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logger.info("Running aggregator model: %s", AGGREGATOR_MODEL)
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# Build parameters for the API call
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api_params = {
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@ -281,7 +284,7 @@ async def _run_aggregator_model(
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response = await _get_openrouter_client().chat.completions.create(**api_params)
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content = response.choices[0].message.content.strip()
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print(f"✅ Aggregation complete ({len(content)} characters)")
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logger.info("Aggregation complete (%s characters)", len(content))
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return content
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@ -348,8 +351,8 @@ async def mixture_of_agents_tool(
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}
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try:
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print(f"🚀 Starting Mixture-of-Agents processing...")
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print(f"📝 Query: {user_prompt[:100]}{'...' if len(user_prompt) > 100 else ''}")
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logger.info("Starting Mixture-of-Agents processing...")
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logger.info("Query: %s", user_prompt[:100])
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# Validate API key availability
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if not os.getenv("OPENROUTER_API_KEY"):
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@ -359,10 +362,10 @@ async def mixture_of_agents_tool(
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ref_models = reference_models or REFERENCE_MODELS
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agg_model = aggregator_model or AGGREGATOR_MODEL
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print(f"🔄 Using {len(ref_models)} reference models in 2-layer MoA architecture")
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logger.info("Using %s reference models in 2-layer MoA architecture", len(ref_models))
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# Layer 1: Generate diverse responses from reference models (with failure handling)
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print("📡 Layer 1: Generating reference responses...")
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logger.info("Layer 1: Generating reference responses...")
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model_results = await asyncio.gather(*[
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_run_reference_model_safe(model, user_prompt, REFERENCE_TEMPERATURE)
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for model in ref_models
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@ -381,10 +384,10 @@ async def mixture_of_agents_tool(
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successful_count = len(successful_responses)
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failed_count = len(failed_models)
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print(f"📊 Reference model results: {successful_count} successful, {failed_count} failed")
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logger.info("Reference model results: %s successful, %s failed", successful_count, failed_count)
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if failed_models:
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print(f"⚠️ Failed models: {', '.join(failed_models)}")
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logger.warning("Failed models: %s", ', '.join(failed_models))
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# Check if we have enough successful responses to proceed
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if successful_count < MIN_SUCCESSFUL_REFERENCES:
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@ -395,7 +398,7 @@ async def mixture_of_agents_tool(
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debug_call_data["failed_models"] = failed_models
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# Layer 2: Aggregate responses using the aggregator model
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print("🧠 Layer 2: Synthesizing final response...")
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logger.info("Layer 2: Synthesizing final response...")
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aggregator_system_prompt = _construct_aggregator_prompt(
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AGGREGATOR_SYSTEM_PROMPT,
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successful_responses
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@ -411,7 +414,7 @@ async def mixture_of_agents_tool(
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end_time = datetime.datetime.now()
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processing_time = (end_time - start_time).total_seconds()
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print(f"✅ MoA processing completed in {processing_time:.2f} seconds")
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logger.info("MoA processing completed in %.2f seconds", processing_time)
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# Prepare successful response (only final aggregated result, minimal fields)
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result = {
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@ -436,7 +439,7 @@ async def mixture_of_agents_tool(
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except Exception as e:
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error_msg = f"Error in MoA processing: {str(e)}"
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print(f"❌ {error_msg}")
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logger.error("%s", error_msg)
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# Calculate processing time even for errors
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end_time = datetime.datetime.now()
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