Fix false context overflow errors in large sessions

Fixes on record

Merged to main. A stamp counts the issues a fix is linked to.

• #19723 fix(error_classifier): avoid large-context false overflow heuristics

  merged to main

  files: agent/error_classifier.py, tests/agent/test_error_classifier.py

  Show the diff

  • agent/error_classifier.py

    @@ -520,7 +520,12 @@ def _result(reason: FailoverReason, **overrides) -> ClassifiedError:
     
         is_disconnect = any(p in error_msg for p in _SERVER_DISCONNECT_PATTERNS)
         if is_disconnect and not status_code:
    -        is_large = approx_tokens > context_length * 0.6 or approx_tokens > 120000 or num_messages > 200
    +        # Absolute token/message-count thresholds are only a proxy for smaller
    +        # context windows.  Large-context sessions can have hundreds of
    +        # messages while still being far below their actual token budget.
    +        is_large = approx_tokens > context_length * 0.6 or (
    +            context_length <= 256000 and (approx_tokens > 120000 or num_messages > 200)
    +        )
             if is_large:
                 return _result(
                     FailoverReason.context_overflow,
    @@ -766,7 +771,12 @@ def _classify_400(
             if not err_body_msg:
                 err_body_msg = str(body.get("message") or "").strip().lower()
         is_generic = len(err_body_msg) < 30 or err_body_msg in ("error", "")
    -    is_large = approx_tokens > context_length * 0.4 or approx_tokens > 80000 or num_messages > 80
    +    # Absolute token/message-count thresholds are only a proxy for smaller
    +    # context windows.  Large-context sessions can have many messages while
    +    # still being far below their actual token budget.
    +    is_large = approx_tokens > context_length * 0.4 or (
    +        context_length <= 256000 and (approx_tokens > 80000 or num_messages > 80)
    +    )
     
         if is_generic and is_large:
             return result_fn(

  • tests/agent/test_error_classifier.py

    @@ -410,6 +410,24 @@ def test_400_generic_small_session_is_format_error(self):
             result = classify_api_error(e, approx_tokens=1000, context_length=200000)
             assert result.reason == FailoverReason.format_error
     
    +    def test_400_generic_many_messages_below_large_context_pressure_is_format_error(self):
    +        """Large-context sessions should not overflow solely due to message count."""
    +        e = MockAPIError(
    +            "Error",
    +            status_code=400,
    +            body={"error": {"message": "Error"}},
    +        )
    +        result = classify_api_error(
    +            e,
    +            provider="openai-codex",
    +            model="gpt-5.5",
    +            approx_tokens=[redacted:secret-assignment]
    +            context_length=1_000_000,
    +            num_messages=432,
    +        )
    +        assert result.reason == FailoverReason.format_error
    +        assert result.should_compress is False
    +
         # ── Server disconnect + large session ──
     
         def test_disconnect_large_session_context_overflow(self):
    @@ -425,6 +443,20 @@ def test_disconnect_small_session_timeout(self):
             result = classify_api_error(e, approx_tokens=5000, context_length=200000)
             assert result.reason == FailoverReason.timeout
     
    +    def test_disconnect_many_messages_below_large_context_pressure_is_timeout(self):
    +        """Large-context disconnects should not overflow solely due to message count."""
    +        e = Exception("server disconnected without sending complete message")
    +        result = classify_api_error(
    +            e,
    +            provider="openai-codex",
    +            model="gpt-5.5",
    +            approx_tokens=[redacted:secret-assignment]
    +            context_length=1_000_000,
    +            num_messages=432,
    +        )
    +        assert result.reason == FailoverReason.timeout
    +        assert result.should_compress is False
    +
         # ── Provider-specific: Anthropic thinking signature ──
     
         def test_anthropic_thinking_signature(self):