- Add Prometheus metrics for managed batch and file operations
- Track batch creation, file size, duration, and deletion events
- Add CheckBatchCost polling metrics (jobs polled/processed, errors)
- Record metrics in managed_files hook and check_batch_cost utility
- Metrics include labels for model, provider, user, and status
Made-with: Cursor
The retrieve_batch endpoint sets batch status to "complete" but never set
batch_processed=True, permanently blocking file deletion. CheckBatchCost
(the safety net) also excluded completed batches from its primary query,
so batch_processed was never set by either path.
Three fixes:
1. update_batch_in_database sets batch_processed=True when status reaches
"complete", with old-schema fallback retry
2. CheckBatchCost primary query no longer excludes complete/completed
(batch_processed=False filter prevents reprocessing)
3. retrieve_batch early-return now includes "complete" (DB-normalized
spelling) to avoid unnecessary provider re-polls
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(proxy): cap managed-object poll size + expire stale rows + kill-switch flag to prevent OOM/Prisma connection loss
* fix(constants): simplify PROXY_BATCH_POLLING_ENABLED readability
* docs+test: document new polling env vars, add pagination+stale-cleanup tests
* fix: exclude stale_expired from batch poll queries; fix update_many assertions in tests
* fix: scope stale cleanup to file_purpose, fix file_object mocks, add CheckBatchCost tests
* fix: avoid duplicate cost logging in fallback path; guard integer constants against zero/negative values
* fix: cache _has_batch_processed_column; guard cleanup from aborting poll; narrow fallback except
* fix: add complete/completed to primary query not_in; fix vacuous test assertion
- Primary find_many was missing "complete" and "completed" in its not_in
filter, creating asymmetry with the fallback query. A job whose status
was set to "complete" but whose batch_processed flag update failed would
be silently re-fetched and re-processed every cycle, emitting duplicate
cost logs.
- test_fallback_completion_update_omits_batch_processed patched
_is_base64_encoded_unified_file_id to return None, causing an immediate
continue — so update() was never called and the assertion looped over an
empty list (vacuously true). Rewrote the test to mock the full
completion pipeline, verify update() is called exactly once, and assert
batch_processed is absent from the update data.
- Added symmetric test (primary path) proving batch_processed IS included
when the column exists.
Made-with: Cursor
- Remove unused `completed_jobs` list (dead code after per-job update refactor)
- Wrap DB update in try/except to prevent one failed update from aborting remaining jobs
- Add test assertions verifying batch_processed, status, and file_object are written to DB
CheckBatchCost poller updated the status column but not the file_object
JSON column. The list_batches endpoint reads status from file_object,
so batches appeared stuck in "validating" even after Azure reported
them as completed. Now update file_object alongside status in the
per-job DB write.
batch_cost_calculator only checked the global cost map, ignoring
deployment-level custom pricing (input_cost_per_token_batches etc.).
Add optional model_info param through the batch cost chain and pass
it from CheckBatchCost.
* Addd v2/chat support for cohere
* fix streaming
* Use v2_transformation for logging passthrough:
* Use v2_transformation for logging passthrough:
* Add test for checking if document and citation_options is getting passed
* Update the cohere model
* Add cost tracking for vertex ai passthrough batch jobs
* Add full passthrough support
* refactor code according to the comments
* Add passthrough handler
* remove invalid params
* Updated documentation
* Updated documentation
* Updated documentation
* Correct the import
* Add openai videos generation and retrieval support
* add retrieval endpoint
* Add docs
* Add imports
* remove orjson
* remove double import
* fix openai videos format
* remove mock code
* remove not required comments
* Add tests
* Add tests
* Add other video endpoints
* Fix cost calculation and transformation
* Fixed mypy tests
* remove not used imports
* fix documentation for get batch req (#15742)
* Add grounding info to responses API (#15737)
* Add grounding info to responses API
* fix lint errors
* Use typed objects for annotations
* Use typed objects for annotations
* fix mypy error
* Litellm fix json serialize alreting 2 (#15741)
* fix json serializable error for alerts
* Add test
* fix mypt errors
* fix mypt errors
* Add Qwen3 imported model support for AWS Bedrock (#15783)
* Add qwen imported model support
* fix mypy errors
* fix empty user message error (#15784)
* fix typed dict for list
* Add azure supported videos endpoint
* fix mapped tests
* add azure sora models to model map
* Add OpenAI video generation and content retrieval support (#15745)
* Add openai videos generation and retrieval support
* add retrieval endpoint
* Add docs
* Add imports
* remove orjson
* remove double import
* fix openai videos format
* remove mock code
* remove not required comments
* Add tests
* Add tests
* Add other video endpoints
* Fix cost calculation and transformation
* Fixed mypy tests
* remove not used imports
* fix typed dict for list
* fix mypy errors
* move directory
* make v2 chat default
* Fix mypy tests
* Fix mypy tests
* Fix mypy tests
* Fix mypy tests
* Revert "Add Azure Video Generation Support with Sora Integration"
* refactor videos repo
* add test
* Add azure openai videos support
* Add azure openai videos support
* Add router endpoint support for videos
* fix mypy error
* add azure models
* fix mapped test
* fix mypy error
* Add proxy router test
* Add proxy router test
* remove deprecated model name from tests
* fix import error
* fix import error
* Add gaurdrail integration in videos endpoint
* Add logging support for videos endpoint
* Add final documentation supporting videos integration
* fix model name and document input
* Update literals to avoid mypy errors
* Remove unused imports and print statements
* revert guardrail support for video generation and video remix
* revert guardrail support for video generation and video remix
* Fix failing mapped and llm translation tests
* fix: use fastuuid helper across the codebase
First batch of changes, simple drop in replacement.
* second batch of changes
* fixed: script mistake on helper file
* fix(main.py): fix async retryer
Fixes https://github.com/BerriAI/litellm/issues/12830
* fix(forward_clientside_headers_by_model_group.py): filter out 'content-type' from forwardable headers
clientside content-type != proxy content type, can cause requests to hang
* test(tests/): update tests
* feat(proxy_server.py): support batch polling interval
allows admin to control batch polling interval (default is 3600s)
easier debugging
* fix(proxy_settings_endpoint.py): ensure value is actually set before updating env var
* feat(check_batch_cost.py): emit spend log on successful request
ensures cost tracked for batch requests
* feat(proxy_server.py): add background job to poll completed batch jobs
used for calculating cost for batch jobs
* fix(proxy_server.py): run batch cost tracking job every hour
batch jobs take time to complete, no need to run every few seconds
* feat(proxy_server.py): run batch cost tracking job every hour