refactor: tighten MoA traceback logging scope (#1307)

* improve: add exc_info to MoA error logging

* refactor: tighten MoA traceback logging scope

Follow up on salvaged PR #998 by limiting exc_info logging to terminal
failure paths, avoiding duplicate aggregator errors, and refreshing the
MoA default OpenRouter model lineup to current frontier options.

---------

Co-authored-by: aydnOktay <xaydinoktay@gmail.com>

tests/tools/test_mixture_of_agents_tool.py

@@ -0,0 +1,82 @@
+import importlib
+import json
+from types import SimpleNamespace
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+
+moa = importlib.import_module("tools.mixture_of_agents_tool")
+
+
+def test_moa_defaults_track_current_openrouter_frontier_models():
+    assert moa.REFERENCE_MODELS == [
+        "anthropic/claude-opus-4.6",
+        "google/gemini-3-pro-preview",
+        "openai/gpt-5.4-pro",
+        "deepseek/deepseek-v3.2",
+    ]
+    assert moa.AGGREGATOR_MODEL == "anthropic/claude-opus-4.6"
+
+
+@pytest.mark.asyncio
+async def test_reference_model_retry_warnings_avoid_exc_info_until_terminal_failure(monkeypatch):
+    fake_client = SimpleNamespace(
+        chat=SimpleNamespace(
+            completions=SimpleNamespace(
+                create=AsyncMock(side_effect=RuntimeError("rate limited"))
+            )
+        )
+    )
+    warn = MagicMock()
+    err = MagicMock()
+
+    monkeypatch.setattr(moa, "_get_openrouter_client", lambda: fake_client)
+    monkeypatch.setattr(moa.logger, "warning", warn)
+    monkeypatch.setattr(moa.logger, "error", err)
+
+    model, message, success = await moa._run_reference_model_safe(
+        "openai/gpt-5.4-pro", "hello", max_retries=2
+    )
+
+    assert model == "openai/gpt-5.4-pro"
+    assert success is False
+    assert "failed after 2 attempts" in message
+    assert warn.call_count == 2
+    assert all(call.kwargs.get("exc_info") is None for call in warn.call_args_list)
+    err.assert_called_once()
+    assert err.call_args.kwargs.get("exc_info") is True
+
+
+@pytest.mark.asyncio
+async def test_moa_top_level_error_logs_single_traceback_on_aggregator_failure(monkeypatch):
+    monkeypatch.setenv("OPENROUTER_API_KEY", "test-key")
+    monkeypatch.setattr(
+        moa,
+        "_run_reference_model_safe",
+        AsyncMock(return_value=("anthropic/claude-opus-4.6", "ok", True)),
+    )
+    monkeypatch.setattr(
+        moa,
+        "_run_aggregator_model",
+        AsyncMock(side_effect=RuntimeError("aggregator boom")),
+    )
+    monkeypatch.setattr(
+        moa,
+        "_debug",
+        SimpleNamespace(log_call=MagicMock(), save=MagicMock(), active=False),
+    )
+
+    err = MagicMock()
+    monkeypatch.setattr(moa.logger, "error", err)
+
+    result = json.loads(
+        await moa.mixture_of_agents_tool(
+            "solve this",
+            reference_models=["anthropic/claude-opus-4.6"],
+        )
+    )
+
+    assert result["success"] is False
+    assert "Error in MoA processing" in result["error"]
+    err.assert_called_once()
+    assert err.call_args.kwargs.get("exc_info") is True

tools/mixture_of_agents_tool.py

@@ -25,8 +25,8 @@ Architecture:
 3. Multiple layers can be used for iterative refinement (future enhancement)
 
 Models Used (via OpenRouter):
-- Reference Models: claude-opus-4, gemini-2.5-pro, gpt-4.1, deepseek-r1
-- Aggregator Model: claude-opus-4 (highest capability for synthesis)
+- Reference Models: claude-opus-4.6, gemini-3-pro-preview, gpt-5.4-pro, deepseek-v3.2
+- Aggregator Model: claude-opus-4.6 (highest capability for synthesis)
 
 Configuration:
     To customize the MoA setup, modify the configuration constants at the top of this file:
@@ -57,16 +57,18 @@ from tools.debug_helpers import DebugSession
 logger = logging.getLogger(__name__)
 
 # Configuration for MoA processing
-# Reference models - these generate diverse initial responses in parallel (OpenRouter slugs)
+# Reference models - these generate diverse initial responses in parallel.
+# Keep this list aligned with current top-tier OpenRouter frontier options.
 REFERENCE_MODELS = [
-    "anthropic/claude-opus-4.5",
-    "google/gemini-3-pro-preview", 
-    "openai/gpt-5.2-pro",
-    "deepseek/deepseek-v3.2"
+    "anthropic/claude-opus-4.6",
+    "google/gemini-3-pro-preview",
+    "openai/gpt-5.4-pro",
+    "deepseek/deepseek-v3.2",
 ]
 
-# Aggregator model - synthesizes reference responses into final output
-AGGREGATOR_MODEL = "anthropic/claude-opus-4.5"  # Use highest capability model for aggregation
+# Aggregator model - synthesizes reference responses into final output.
+# Prefer the strongest synthesis model in the current OpenRouter lineup.
+AGGREGATOR_MODEL = "anthropic/claude-opus-4.6"
 
 # Temperature settings optimized for MoA performance
 REFERENCE_TEMPERATURE = 0.6  # Balanced creativity for diverse perspectives
@@ -147,14 +149,15 @@ async def _run_reference_model_safe(
             
         except Exception as e:
             error_str = str(e)
-            # Log more detailed error information for debugging
+            # Keep retry-path logging concise; full tracebacks are reserved for
+            # terminal failure paths so long-running MoA retries don't flood logs.
             if "invalid" in error_str.lower():
                 logger.warning("%s invalid request error (attempt %s): %s", model, attempt + 1, error_str)
             elif "rate" in error_str.lower() or "limit" in error_str.lower():
                 logger.warning("%s rate limit error (attempt %s): %s", model, attempt + 1, error_str)
             else:
                 logger.warning("%s unknown error (attempt %s): %s", model, attempt + 1, error_str)
-                
+
             if attempt < max_retries - 1:
                 # Exponential backoff for rate limiting: 2s, 4s, 8s, 16s, 32s, 60s
                 sleep_time = min(2 ** (attempt + 1), 60)
@@ -162,7 +165,7 @@ async def _run_reference_model_safe(
                 await asyncio.sleep(sleep_time)
             else:
                 error_msg = f"{model} failed after {max_retries} attempts: {error_str}"
-                logger.error("%s", error_msg)
+                logger.error("%s", error_msg, exc_info=True)
                 return model, error_msg, False
 
 
@@ -185,7 +188,7 @@ async def _run_aggregator_model(
         str: Synthesized final response
     """
     logger.info("Running aggregator model: %s", AGGREGATOR_MODEL)
-    
+
     # Build parameters for the API call
     api_params = {
         "model": AGGREGATOR_MODEL,
@@ -200,14 +203,14 @@ async def _run_aggregator_model(
             }
         }
     }
-    
+
     # GPT models (especially gpt-4o-mini) don't support custom temperature values
     # Only include temperature for non-GPT models
     if not AGGREGATOR_MODEL.lower().startswith('gpt-'):
         api_params["temperature"] = temperature
-    
+
     response = await _get_openrouter_client().chat.completions.create(**api_params)
-    
+
     content = response.choices[0].message.content.strip()
     logger.info("Aggregation complete (%s characters)", len(content))
     return content
@@ -364,7 +367,7 @@ async def mixture_of_agents_tool(
         
     except Exception as e:
         error_msg = f"Error in MoA processing: {str(e)}"
-        logger.error("%s", error_msg)
+        logger.error("%s", error_msg, exc_info=True)
         
         # Calculate processing time even for errors
         end_time = datetime.datetime.now()