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fac43df9b9
* fix(complexity_router): return empty dict from _classifier_call_metadata when metadata is absent
The LLM classifier reads request_kwargs.get("litellm_metadata"), but the proxy stores request metadata under "metadata", so this returned None. _classifier_call_metadata then passed None straight through to the classifier acompletion call, which assumes a dict and blows up with 'NoneType' object has no attribute 'update'; the router swallowed it and silently fell back to heuristic scoring, so the configured LLM classifier never ran. Returning an empty dict keeps the classifier call well-formed.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(e2e): cover complexity-router LLM classifier routes over the proxy
Add a live e2e regression for the complexity auto-router: a lexically simple but hard prompt ("Is P equal to NP?") is routed by the LLM classifier to the higher-tier anthropic backend, read back from the spend log's model. Before the metadata fix the classifier silently crashed and the router fell back to heuristic SIMPLE scoring on the openai backend, so this test fails pre-fix and passes post-fix.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
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Co-authored-by: Krrish Dholakia <krrishdholakia@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
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| .. | ||
| complexity_router_client.py | ||
| conftest.py | ||
| test_complexity_router_e2e.py | ||