* Add v1 cut of container api
* fix lint errors
* Add proxy support to container apis & logging support (#16049)
* Add proxy support to container apis
* Add logging support
* Add cost tracking support for containers and documentation
* Add new constant documentation
* Add container cost in model map
* fix failing azure tests
* Update tests based on model map changes
* fix model map tests
* fix model map tests
* Container modeshould be container
* Container tests fix
* Merge branch 'main' into litellm_sameer_oct_staging_2
* Add Prometheus metric to track callback logging failures in S3 (#16102)
* Add proxy support to container apis
* Add logging support
* prometheus metric measures how often s3_v2 is failing
* remove not needed files
* remove not needed files
* remove not needed files
* fix mypy errors
* Use logging_callback_manager to get all the callbacks
---------
Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
* fix(apscheduler): prevent memory leaks from jitter and frequent job intervals
Fixes critical memory leak in APScheduler that causes 35GB+ memory allocations
during proxy startup and operation. The leak was identified through Memray
analysis showing massive allocations in normalize() and _apply_jitter()
functions.
Key changes:
1. Remove jitter parameters from all scheduled jobs - jitter was causing
expensive normalize() calculations leading to memory explosion
2. Configure AsyncIOScheduler with optimized job_defaults:
- misfire_grace_time: 3600s (increased from 120s) to prevent backlog
calculations that trigger memory leaks
- coalesce: true to collapse missed runs
- max_instances: 1 to prevent concurrent job execution
- replace_existing: true to avoid duplicate jobs on restart
3. Increase minimum job intervals:
- PROXY_BATCH_WRITE_AT: 30s (was 10s)
- add_deployment/get_credentials jobs: 30s (was 10s)
4. Use fixed intervals with small random offsets instead of jitter for
job distribution across workers
5. Explicitly configure jobstores and executors to minimize overhead
6. Disable timezone awareness to reduce computation
Memory impact:
- Before: 35GB with 483M allocations during startup
- After: <1GB with normal allocation patterns
Performance notes:
- Minimum job intervals increased from 10s to 30s (configurable via env vars)
- Jobs can still be distributed across workers using random start offsets
- No functional changes to job behavior, only timing and memory optimization
Testing:
- Added comprehensive test suite for scheduler configuration
- Verified no job execution backlog on startup
- Tested duplicate job prevention with replace_existing
Related issue: Memory leak in production proxy servers with APScheduler
\ud83e\udd16 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* docs: update PROXY_BATCH_WRITE_AT default value from 10s to 30s
Update documentation to reflect the new default value for PROXY_BATCH_WRITE_AT
changed in PR #15846. The default was increased from 10 seconds to 30 seconds
to prevent memory leaks in APScheduler.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
* refactor: Move APScheduler config to constants.py
Address code review feedback from ishaan-jaff:
- Move scheduler configuration variables (coalesce, misfire_grace_time,
max_instances, replace_existing) to litellm/constants.py
- Update all references in proxy_server.py to use the constants
- Improves maintainability and makes configuration values centralized
Requested-by: @ishaan-jaff
Related: #15846🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
---------
Co-authored-by: Claude <noreply@anthropic.com>
* Implement fix for thinking_blocks and converse API calls
This fixes Claude's models via the Converse API, which should also fix
Claude Code.
* Add thinking literal
* Fix mypy issues
* Type fix for redacted thinking
* Add voyage model integration in sagemaker
* Add config file logic
* Use already exiting voyage transformation
* refactor code as per comments
* fix merge error
* refactor code as per comments
* refactor code as per comments
* UI new build
* [Fix] router - regression when adding/removing models (#15451)
* fix(router): update model_name_to_deployment_indices on deployment removal
When a deployment is deleted, the model_name_to_deployment_indices map
was not being updated, causing stale index references. This could lead
to incorrect routing behavior when deployments with the same model_name
were dynamically removed.
Changes:
- Update _update_deployment_indices_after_removal to maintain
model_name_to_deployment_indices mapping
- Remove deleted indices and decrement indices greater than removed index
- Clean up empty entries when no deployments remain for a model name
- Update test to verify proper index shifting and cleanup behavior
* fix(router): remove redundant index building during initialization
Remove duplicate index building operations that were causing unnecessary
work during router initialization:
1. Removed redundant `_build_model_id_to_deployment_index_map` call in
__init__ - `set_model_list` already builds all indices from scratch
2. Removed redundant `_build_model_name_index` call at end of
`set_model_list` - the index is already built incrementally via
`_create_deployment` -> `_add_model_to_list_and_index_map`
Both indices (model_id_to_deployment_index_map and
model_name_to_deployment_indices) are properly maintained as lookup
indexes through existing helper methods. This change eliminates O(N)
duplicate work during initialization without any behavioral changes.
The indices continue to be correctly synchronized with model_list on
all operations (add/remove/upsert).
* fix(prometheus): Fix Prometheus metric collection in a multi-workers environment (#14929)
Co-authored-by: sotazhang <sotazhang@tencent.com>
* Add tiered pricing and cost calculation for xai
* Use generic cost calculator
* Resolve conflicts in generated HTML files
* Remove penalty params as supported params for gemini preview model (#15503)
* fix conversion of thinking block
* add application level encryption in SQS (#15512)
* docs: fix doc
* docs(index.md): bump rc
* [Fix] GEMINI - CLI - add google_routes to llm_api_routes (#15500)
* fix: add google_routes to llm_api_routes
* test: test_virtual_key_llm_api_routes_allows_google_routes
* build: bump version
* bump: version 1.78.0 → 1.78.1
* add application level encryption in SQS
* add application level encryption in SQS
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: deepanshu <deepanshu.lulla@hq.bill.com>
* [Feat] Bedrock Knowledgebase - return search_response when using /chat/completions API with LiteLLM (#15509)
* docs: fix doc
* docs(index.md): bump rc
* [Fix] GEMINI - CLI - add google_routes to llm_api_routes (#15500)
* fix: add google_routes to llm_api_routes
* test: test_virtual_key_llm_api_routes_allows_google_routes
* add AnthropicCitation
* fix async_post_call_success_deployment_hook
* fix add vector_store_custom_logger to global callbacks
* test_e2e_bedrock_knowledgebase_retrieval_with_llm_api_call
* async_post_call_success_deployment_hook
* add async_post_call_streaming_deployment_hook
* async def test_e2e_bedrock_knowledgebase_retrieval_with_llm_api_call_streaming(setup_vector_store_registry):
* fix _call_post_streaming_deployment_hook
* fix async_post_call_streaming_deployment_hook
* test update
* docs: Accessing Search Results
* docs KB
* fix chatUI
* fix searchResults
* fix onSearchResults
* fix kb
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
* [Feat] Add dynamic rate limits on LiteLLM Gateway (#15518)
* docs: fix doc
* docs(index.md): bump rc
* [Fix] GEMINI - CLI - add google_routes to llm_api_routes (#15500)
* fix: add google_routes to llm_api_routes
* test: test_virtual_key_llm_api_routes_allows_google_routes
* build: bump version
* bump: version 1.78.0 → 1.78.1
* fix: KeyRequestBase
* fix rpm_limit_type
* fix dynamic rate limits
* fix use dynamic limits here
* fix _should_enforce_rate_limit
* fix _should_enforce_rate_limit
* fix counter
* test_dynamic_rate_limiting_v3
* use _create_rate_limit_descriptors
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
* Add google rerank endpoint
* Add docs
* fix mypy error
* fix mypy and lint errors
* Add haiku 4.5 integration
* Add haiku 4.5 integration for other regions as well
* Handle citation field correctly
* Fix filtering headers for signature calcs
* Add haiku 4.5 integration (#15650)
---------
Co-authored-by: Leslie Cheng <leslie.cheng5@gmail.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: Alexsander Hamir <alexsanderhamirgomesbaptista@gmail.com>
Co-authored-by: Lucas <10226902+LoadingZhang@users.noreply.github.com>
Co-authored-by: sotazhang <sotazhang@tencent.com>
Co-authored-by: Deepanshu Lulla <deepanshu.lulla@gmail.com>
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
Co-authored-by: deepanshu <deepanshu.lulla@hq.bill.com>
* fix: cli auth with SSO okta
* fix: add LITTELM_CLI_SERVICE_ACCOUNT_NAME
* fix: get_litellm_cli_user_api_key_auth
* use existing_key CLI
* fix: use existing key
* test auth commands
* test_cli_sso_callback_regenerate_vs_create_flow
* feat: add CLI Token Utilities
* fix: get_stored_api_key
* move file
* fix: get_valid_models
* fix config.yaml
* TestCLITokenUtils
* TestGetValidModelsWithCLI
* fix: tie user id to keys created through CLI
* fix: add teams interface to CLI
* add /keys/update to the list client commands
* fix /sso/cli/poll to return the user_id
* fix: working TeamsManagementClient
* fix CLI Login command
* fixes for auth
* Potential fix for code scanning alert no. 3400: Clear-text logging of sensitive information
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
* ruff fix
---------
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
* fix(prometheus.py): sanitize tag-based labels to handle colons (:) and spaces ( )
* fix(prometheus.py): working tag based metrics
* fix(prometheus.py): emit request tags on post call success hook
* fix(prometheus.py): add user agent tags on request failure
* fix(prometheus.py): add request tags to deployment failure metric
s
* feat(custom_guardrail.py): allow admin to run guardrails on specific modes based on request tags
Enables pre-call checks for openwebui but logging for claude code guardrails
* refactor(custom_guardrail.py): move tag based mode to enterprise
* test(test_custom_guardrail.py): update test
* feat(quick_start.md): add doc on tag-based guardrail mode
* docs(quick_start.md): cleanup doc
* docs: cleanup
* docs(openweb_ui.md): add tutorial to doc
* fix(custom_guardrail.py): ensure user is premium user
* test: update test
