mirror of
https://github.com/tiennm99/litellm.git
synced 2026-07-11 17:05:43 +00:00
0e601d0bfe
* Fix: Map Gemini cached_tokens to Langfuse cache_read_input_tokens Fixes #18520 ## Problem Langfuse integration was not capturing cached tokens from Gemini models. Gemini returns cached tokens in `usage.prompt_tokens_details.cached_tokens`, but Langfuse only read from top-level `usage.cache_read_input_tokens` (which only Anthropic populates). ## Solution Updated langfuse.py to check both locations: 1. First check top-level cache_read_input_tokens (for Anthropic) 2. Then check prompt_tokens_details.cached_tokens (for Gemini, OpenAI, others) This ensures all providers' cached tokens are properly reported to Langfuse. ## Changes - Modified litellm/integrations/langfuse/langfuse.py (lines 742-761) - Added 3 unit tests in tests/test_litellm/integrations/langfuse/test_gemini_cached_tokens.py - All existing Langfuse tests still pass (11/11) ## Testing - test_cached_tokens_extraction: Verifies Gemini cached_tokens extraction - test_cached_tokens_not_present: Backward compatibility (no cached_tokens) - test_cached_tokens_is_zero: Edge case when cached_tokens = 0 * Refactor: Extract cache token logic into helper function Address review feedback from @officer47p - Created _extract_cache_read_input_tokens() helper function - Reduces code bloat in _log_langfuse_v2 method - Improves testability and reusability - All tests still passing (11/11)