Preserve Gemini thought signatures through streamed tool calls - #206
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ALMGeminiClient hits Gemini's raw OpenAI-compatible endpoint directly, where multi-turn thought signatures ride under extra_content.google on each tool_call. litellm.stream_chunk_builder's tool-call merge (used by _assemble_stream_chunks for the streaming path) only knows how to carry over id/type/function/provider_specific_fields, so it silently dropped extra_content when reassembling streamed chunks -- causing Gemini 3.x audio-native models to fail on the next turn with "Function call is missing a thought_signature". Add _merge_streamed_tool_call_extras to alm_base.py: rebuilds tool_calls from the raw stream chunks, preserving any key litellm's merge doesn't recognize, and is a no-op when no such extra keys are present (e.g. for vLLM-hosted models). Also update system.py's thought-signature log check to recognize extra_content alongside CASCADE's provider_specific_fields.
fanny-riols
marked this pull request as ready for review
August 13, 2026 14:56
katstankiewicz
approved these changes
Aug 17, 2026
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ALMGeminiClient hits Gemini's raw OpenAI-compatible endpoint directly, where multi-turn thought signatures ride under
extra_content.googleon each tool_call.litellm.stream_chunk_builder's tool-call merge (used by_assemble_stream_chunkswhen streaming the LLM response) only knows how to carry over id/type/function/provider_specific_fields, so it silently dropped extra_content when reassembling streamed chunks -- causing Gemini 3.x audio-native models to fail on the next turn with "Function call is missing a thought_signature".Add
_merge_streamed_tool_call_extrasto alm_base.py: rebuilds tool_calls from the raw stream chunks, preserving any key litellm's merge doesn't recognize, and is a no-op when no such extra keys are present (e.g. for vLLM-hosted models). Also update system.py's thought-signature log check to recognize extra_content alongside CASCADE's provider_specific_fields.