* attempt to implement the passthrough feature
* Formatting and small change
* Fix formatting
* Format test file
---------
Co-authored-by: Xiaohan Fu <xiaohan@grayswan.ai>
* fix(router): use cacheable prefix for prompt caching cache keys
Fix issue where requests with same cacheable prefix but different user
messages were routing to different deployments, preventing cached token
reuse. The cache key now correctly includes only the cacheable prefix
(up to and including the last cache_control block) instead of the
entire messages array.
## New Functions
### extract_cacheable_prefix()
Static method that extracts the cacheable prefix from messages for
prompt caching. The cacheable prefix is defined as everything UP TO
AND INCLUDING the LAST content block (across all messages) that has
cache_control with type "ephemeral". This includes ALL blocks
before the last cacheable block (even if they don't have cache_control
themselves).
- Finds the last content block with cache_control across all messages
- Returns all messages and content blocks up to and including that
last cacheable block
- Excludes everything after the last cacheable block (including user
messages that come after)
- Returns empty list if no cacheable blocks are found
## Changed Functions
### get_prompt_caching_cache_key()
Modified to use the cacheable prefix instead of the full messages array
when generating cache keys. This ensures that requests with the same
cacheable prefix but different user messages generate the same cache
key, enabling proper routing to the same deployment.
- Now calls extract_cacheable_prefix() to get only cacheable content
- Returns None if no cacheable prefix is found (can't generate key)
- Cache key is now based on cacheable prefix only, not full messages
### async_get_model_id()
Completely refactored to use the cacheable prefix directly instead of
the previous workaround that checked progressively shorter message
slices. The previous implementation was inefficient and unreliable.
- Removed progressive message slicing logic (messages[:-1], messages[:-2], etc.)
- Now uses single direct cache lookup with cacheable prefix-based key
- More efficient (1 lookup instead of up to 4)
- More reliable (uses correct cache key based on cacheable prefix)
- Returns None if no cacheable prefix found
### add_model_id()
Added None check for cache_key to prevent caching when no cacheable
prefix is found. This ensures we don't attempt to cache when there's
no meaningful cache key to use.
- Added guard: returns early if cache_key is None
- Prevents attempting to cache when no cacheable prefix exists
### async_add_model_id()
Added None check for cache_key to prevent caching when no cacheable
prefix is found. Matches the behavior of add_model_id() for consistency.
- Added guard: returns early if cache_key is None
- Prevents attempting to cache when no cacheable prefix exists
### get_model_id()
Added None check for cache_key to handle cases where no cacheable
prefix is found. Ensures consistent behavior across all cache methods.
- Added guard: returns None if cache_key is None
- Prevents calling get_cache() with None key
## Test
### test_router_prompt_caching_same_cacheable_prefix_routes_to_same_deployment()
New end-to-end test that validates the fix. Tests that requests with
the same cacheable prefix (system blocks with cache_control) but
different user messages:
1. Generate the same cache key
2. Successfully perform cache lookup
3. Route to the same deployment
This test reproduces the exact scenario from the user's bug report
where three requests with different user messages should route to the
same deployment but were previously routing to different ones.
Fixes issue where cached tokens couldn't be reused because requests
were routed to different providers due to different cache keys.
* fix(router): use cast() for proper type handling in extract_cacheable_prefix
Replace type annotation with type: ignore comment with proper cast()
from typing module, matching the pattern used throughout the
codebase for creating modified AllMessageValues dictionaries.
This fix addresses the same issue that was resolved for OpenAI video in PR #16708.
The GeminiVideoConfig class was importing BaseVideoConfig only within TYPE_CHECKING,
causing it to be 'Any' at runtime. This prevented the async_transform_video_content_response
method from being available during video content downloads.
Changes:
- Moved BaseVideoConfig import from TYPE_CHECKING to top-level imports
- Added test_gemini_video_config_has_async_transform() to verify the fix
- Ensures GeminiVideoConfig properly inherits BaseVideoConfig at runtime
Fixes video generation errors for Gemini Veo models:
'GeminiVideoConfig' object has no attribute 'async_transform_video_content_response'
* Attempt CI/CD Fix
* Adding test for coverage
* Adding max depth to copilot and vertex
* Fixing mypy lint and docker database
* Fixing UI build issues
* Update playwright test
* though signature tool call id
* [stripe] refactor and tests
* [stripe] remove md and move to factory
* [stripe] remove redudant test
* [stripe] ran black formatting
* [stripe] add thought signature docs
* [stripe] remove unused import
* add AWS fields for KeyManagementSettings
* docs IAM roles
* use aws iam auth on secret manager v2
* fix: load_aws_secret_manager
* test_secret_manager_with_iam_role_settings
* Add thought signature support to v1/messages api
* update the thinking level handling logic
* update the thinking level handling logic
* Add streaming support
* fix intalling litellm error
Gemini 3 models require 'includeThoughts: True' in the thinkingConfig to return the actual thought text. Previously, using reasoning_effort set the 'thinkingLevel' but missed the boolean flag, resulting in empty reasoning_content.
This fix:
1. Updates `_map_reasoning_effort_to_thinking_level` to include `includeThoughts: True` for low/medium/high.
2. Adds unit tests to verify the config mapping.
Fixes#16805
When using Gemini models (2.5/3.0) with streaming + tools enabled,
the reasoning_content field was missing from stream chunks, even though
thinking_blocks were present in non-streaming responses.
Changes:
- Convert thinking_blocks to reasoning_content for streaming responses
- Extract "thinking" field from each thinking_block
- Concatenate multiple thinking parts with newlines
- Assign to reasoning_content in chat_completion_message for streaming
Testing:
- Added test_streaming_chunk_with_tool_calls_includes_reasoning_content
- Test verifies reasoning_content appears with tool calls in streaming
- All 39 existing Gemini tests pass
- Fix blank function name in completions response when using native function calling
- Fix Enum name being used instead of Enum value for comparison in chunk conversion
- Added additional tests to cover changes
Thanks to @mcowger for the invaluable assitance with figuring this issue out!
Fixed#16863
* Use auth key name if there are no app id in in headers or in extra_data
* use key alias instead of key name
* Fix
* last priority key alias
* Fix
* Add tests
- Implement GithubCopilotResponsesAPIConfig for /responses endpoint
- Add support for models requiring responses API (e.g., gpt-5.1-codex)
- Auto-detect vision requests and set X-Initiator header
- Follow OpenAI Responses API compatibility pattern
- Add comprehensive unit tests (16 tests passing)
Fixes#16820
* fix(spend-logs): trim logged response strings
- route spend-log responses through the existing string sanitizer so oversized base64/text fields are truncated before persistence
- add unit tests covering the truncation path and the feature flag
Note: embeddings-specific truncation (numeric vectors) is still pending and will be handled separately.
* remove unnecessary comment
* add: sanitization unit test for embeddings
* fix: simplify sanatization logic
I overcomplicated a simple change for lack of understanding, fixed.
Cost tracking was failing for Responses API when using custom deployment names
with base_model configuration. The issue occurred because:
- Chat Completions API stores model_info in 'metadata'
- Responses API stores model_info in 'litellm_metadata'
- Cost calculator only checked 'metadata', missing Responses API costs
Changes:
- Updated _get_base_model_from_metadata() to check both metadata locations
- Added comprehensive unit tests covering all scenarios
- Maintains backward compatibility (metadata takes precedence)
Fixes#16772
Derek Duenas