Add documentation explaining the difference between model formats:
- `gemini/model` → Gemini API (simple API key)
- `vertex_ai/model` → Vertex AI (GCP credentials)
- `model` (no prefix) → defaults to Vertex AI
This addresses user confusion when models without prefix require
GCP authentication instead of simple API key auth.
Ref #8424
- Add google-cloud-aiplatform as optional dependency in pyproject.toml
- Add 'google' extra for easy installation: pip install litellm[google]
- Improve error messages when Google SDK is not installed to guide users
Fixes#5483
Replace independent auto-incrementing chart versioning with 1-1 sync
to LiteLLM version. This allows users to easily map Helm chart versions
to LiteLLM versions without needing to inspect appVersion.
Changes:
- Remove auto-increment logic that read from OCI registry
- Chart version now equals LiteLLM tag without 'v' prefix (v1.81.0 -> 1.81.0)
- appVersion equals full Docker tag (v1.81.0)
- Update both ghcr_deploy.yml and ghcr_helm_deploy.yml workflows
Before: helm chart 0.1.837 -> user has to guess LiteLLM version
After: helm chart 1.81.0 -> matches LiteLLM v1.81.0
References:
- https://codefresh.io/docs/docs/ci-cd-guides/helm-best-practices/
* feat: add gemini video metadata and detail support
Implement support for video_metadata and enhanced detail parameter
for Gemini 3.0+ models:
- Add video_metadata field to ChatCompletionFileObjectFile type
- Supports fps, start_offset, and end_offset parameters
- Properly converts snake_case to camelCase for Gemini API
- Extend detail parameter to support medium and ultra_high levels
- Maps to MEDIA_RESOLUTION_MEDIUM and MEDIA_RESOLUTION_ULTRA_HIGH
- Update _process_gemini_image to handle video metadata transformation
- Add version gating to only apply features for Gemini 3+ models
- Add comprehensive test coverage (6 new test cases)
- Test detail parameter with file objects
- Test video_metadata fields (fps, start_offset, end_offset)
- Test combined detail + video_metadata usage
- Test new detail levels (medium, ultra_high)
- Test version gating (Gemini 1.5 vs 3.0)
Note: video_metadata is only supported for video files but error
handling is delegated to Vertex AI for other media types.
* refactor: rename _process_gemini_image to _process_gemini_media
The function handles multiple media types (images, audio, video, PDF),
not just images. Renamed to better reflect its actual purpose.
- Update function name in transformation.py
- Update all function calls and references
- Update test names and imports to match
- Improve docstring to clarify it handles all media types
* docs: add video metadata and media resolution control documentation
Add comprehensive documentation for Gemini 3+ video processing features:
- Document media resolution control (detail parameter) for images and videos
- Add video_metadata field documentation (fps, start_offset, end_offset)
- Include usage examples with tabs for basic, combined, and proxy scenarios
- Update both Gemini and Vertex AI provider documentation
- Clarify snake_case to camelCase field conversion for Gemini API
Signed-off-by: Kris Xia <xiajiayi0506@gmail.com>
* refactor(gemini): extract metadata application into helper function
Extract duplicated Gemini 3+ media_resolution and video_metadata
application logic from _process_gemini_media into a dedicated
_apply_gemini_3_metadata helper function to improve code maintainability.
---------
Signed-off-by: Kris Xia <xiajiayi0506@gmail.com>
