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cleanup

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Teknium 2025-08-21 08:12:01 -07:00
parent 58d5fa1e4c
commit 96cff78335
1 changed files with 14 additions and 7 deletions
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21
mixture_of_agents_tool.py
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@ -196,13 +196,22 @@ async def _run_reference_model_safe(
return model, content, True
except Exception as e:
error_str = str(e)
# Log more detailed error information for debugging
if "invalid" in error_str.lower():
print(f"⚠️ {model} invalid request error (attempt {attempt + 1}): {error_str}")
elif "rate" in error_str.lower() or "limit" in error_str.lower():
print(f"⚠️ {model} rate limit error (attempt {attempt + 1}): {error_str}")
else:
print(f"⚠️ {model} unknown error (attempt {attempt + 1}): {error_str}")
if attempt < max_retries - 1:
# Exponential backoff for rate limiting
sleep_time = 2 ** attempt
print(f"⚠️ {model} failed (attempt {attempt + 1}), retrying in {sleep_time}s: {str(e)}")
print(f" Retrying in {sleep_time}s...")
await asyncio.sleep(sleep_time)
else:
error_msg = f"{model} failed after {max_retries} attempts: {str(e)}"
error_msg = f"{model} failed after {max_retries} attempts: {error_str}"
print(f"❌ {error_msg}")
return model, error_msg, False
@ -370,15 +379,14 @@ async def mixture_of_agents_tool(
print(f"✅ MoA processing completed in {processing_time:.2f} seconds")
# Prepare successful response (only final aggregated result)
# Prepare successful response (only final aggregated result, minimal fields)
result = {
"success": True,
"response": final_response,
"models_used": {
"reference_models": ref_models,
"aggregator_model": agg_model
},
"processing_time": processing_time
}
}
debug_call_data["success"] = True
@ -400,7 +408,7 @@ async def mixture_of_agents_tool(
end_time = datetime.datetime.now()
processing_time = (end_time - start_time).total_seconds()
# Prepare error response
# Prepare error response (minimal fields)
result = {
"success": False,
"response": "MoA processing failed. Please try again or use a single model for this query.",
@ -408,7 +416,6 @@ async def mixture_of_agents_tool(
"reference_models": reference_models or REFERENCE_MODELS,
"aggregator_model": aggregator_model or AGGREGATOR_MODEL
},
"processing_time": processing_time,
"error": error_msg
}