* fix(vertex_ai): replace custom model names with actual Vertex AI model names in passthrough URLs (#19948)
When the passthrough URL already contains project and location, the code
was skipping the deployment lookup and forwarding the URL as-is to Vertex AI.
For custom model names like gcp/google/gemini-2.5-flash, Vertex AI returned
404 because it only knows the actual model name (gemini-2.5-flash).
The fix makes the deployment lookup always run, so the custom model name
gets replaced with the actual Vertex AI model name before forwarding.
* add _resolve_vertex_model_from_router
* fix: get_llm_provider
* Potential fix for code scanning alert no. 4020: Clear-text logging of sensitive information
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
---------
Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
The regex in get_vertex_model_id_from_url() was using [^/:]+
which stopped at the first slash, truncating model names like
'gcp/google/gemini-2.5-flash' to just 'gcp'. This caused
access_groups checks to fail for custom model names.
Changed the pattern to [^:]+ to allow slashes in model names,
only stopping at the colon before the action (e.g., :generateContent).
* Cleanup code for user cli auth, and make sure not to prompt user for team multiple times while polling
* Adding tests
* Cleanup normalize teams some more
Fixes issue where tool_result content blocks include explicit
'cache_control': null which breaks some Anthropic API channels.
Changes:
- Only include cache_control field when explicitly set and not None
- Prevents serialization of null values in tool_result text content
- Maintains backward compatibility with existing cache_control usage
Related issue: Anthropic tool_result conversion adds explicit null values
that cause compatibility issues with certain API implementations.
Co-Authored-By: Claude (claude-4.5-sonnet) <noreply@anthropic.com>
When Gemini uses implicit caching, it returns cachedContentTokenCount but
NOT cacheTokensDetails. Previously, text_tokens was not adjusted in this case,
causing costs to be calculated as if all tokens were non-cached.
This fix subtracts cachedContentTokenCount from text_tokens when no
cacheTokensDetails is present (implicit caching), ensuring correct cost
calculation with the reduced cache_read pricing.
The lazy loading implementation for encoding in __getattr__ was calling
tiktoken.get_encoding() directly without first setting TIKTOKEN_CACHE_DIR.
This caused tiktoken to attempt downloading the encoding file from the
internet instead of using the local copy bundled with litellm.
This fix uses _get_default_encoding() from _lazy_imports which properly
sets TIKTOKEN_CACHE_DIR before loading tiktoken, ensuring the local cache
is used.
