* refactor(passthrough_endpoints-success-handler): refactor llm passthrough logging logic
isolate the llm translation work to enable cost tracking on sdk
* feat: initial implementation of passthrough SDK cost calculation
enables bedrock passthrough cost tracking to work
* feat(cost_calculator.py): working cost calculation for bedrock passthrough
* feat(litellm_logging.py): consider allm_passthrough in cost tracking
allows async calls (e.g. via proxy) to work
* feat(bedrock/passthrough): working event stream decoding for bedrock passthrough calls + logging instrumentation for passthrough sdk calls (log on stream completion)
Enables bedrock streaming cost calculation
* feat(litellm_logging.py): support streaming passthrough cost tracking
* feat(passthrough/main.py): working async streaming cost calculation
Closes https://github.com/BerriAI/litellm/issues/11359
* feat(proxy_server.py): fix passthrough routing when llm router enabled
* feat: further fixes
* feat(bedrock/): working bedrock passthrough cost tracking (non-streaming)
* feat(litellm_logging.py): working usage tracking for bedrock passthrough calls
ensures tokens are logged
* feat(bedrock/passthrough): add converse passthrough cost tracking support
* feat(base_llm/passthrough): remove redundant function
* refactor(litellm_logging.py): refactor function to be below 50 LOC
* test: update test
* test: remove redundant test
- Change verbose_logger.info() to verbose_logger.debug() for cost calculation messages
- Ensures cost calculation details are only shown when DEBUG logging is enabled
- Reduces log noise in production environments
Part 2/2 of fix for #9815
- Initialize verbose_logger, verbose_proxy_logger, and verbose_router_logger with the correct log level
- Ensures loggers respect the LITELLM_LOG environment variable setting
- Fixes part of issue #9815 where logs were shown regardless of log level setting
Part 1/2 of fix for #9815
* [Bug Fix] Anthropic - Token Usage Null Handling in calculate_usage (BerriAI/litellm#11920)
* [Fix] Missed a null check and used a cast instead by error
- Fix type error where _handle_error was called with provider_config=None
- Add proper provider config retrieval logic similar to llm_passthrough_route
- Handle cases where provider config may not be available
- Ensure type safety while maintaining backward compatibility
* fix(docs): Remove unused dotenv dependency from docusaurus config
The dotenv package was being required in docusaurus.config.js but was listed as
a devDependency, causing build failures. Since no environment variables are
actually used in the config, removed the unnecessary import.
* fix(docs): Remove reference to non-existent spending_monitoring doc
The sidebars.js file was referencing proxy/spending_monitoring which was deleted
in commit ba7463b9c. This was causing the documentation build to fail with missing
document errors.
* feat: initial commit adding bedrock support via the new sdk passthrough logic
ensures correct sequencing of tasks (pre call checks etc. can run before signing request)
* fix(route_llm_requests.py): passthrough to allm_passthrough_route if no model found
* feat(bedrock/passthrough): working bedrock passthrough via sdk support
* fix(passthrough/main.py): re-add data and json
* feat(passthrough/main): support async passthrough calls to bedrock
* feat(passthrough/main.py): async streaming + completion support
* feat(llm_passthrough_endpoints.py): migrate bedrock passthrough calls to to new bedrock passthrough sdk
Enables calls to work correctly
* fix: fix linting errors
* test: update test
* fix(llm_http_handler.py): raise clearer error on anthropic unified route
Fixes https://github.com/BerriAI/litellm/issues/12063
* fix(key_management_endpoints.py): add new param `new_key` for setting the regenerated key value
user request
* test: add unit tests
* fix(pass_through_endpoints.py): use data instead of json for passthrough requests
fixes bedrock latency issue
* Revert "fix(pass_through_endpoints.py): use data instead of json for passthrough requests"
This reverts commit 021dfd9165f837d37e6aad247ccbd0d2e8ca6043.
Add reasoning content support when Responses API falls
back to completions API, enabling reasoning content for
all LLM providers (Anthropic, Vertex AI, etc.) since
OpenAI is currently the only native Responses API
provider.
* Add ReasoningSummaryTextDeltaEvent for streaming
reasoning deltas
* Update streaming iterator to detect and transform
reasoning content
* Extract reasoning content as separate output items in
transformations
* Support reasoning content alongside regular message
content
Closes https://github.com/BerriAI/litellm/issues/11302
- Fix date formatting in API calls from ISO format to YYYY-MM-DD
- Update userDailyActivityCall, teamDailyActivityCall, and tagDailyActivityCall
- Prevent date mutation by creating new Date objects before API calls
- Set proper time boundaries (00:00:00 to 23:59:59) for same-day selections
The API expects dates in YYYY-MM-DD format but the UI was sending
full ISO timestamps, causing the Today filter to return empty results.
