* fix(pattern_match_deployments.py): default to user input if unable to map based on wildcards
* test: fix test
* test: reset test name
* test: update conftest to reload proxy server module between tests
* ci(config.yml): move langfuse out of local_testing
reduce ci/cd time
* ci(config.yml): cleanup langfuse ci/cd tests
* fix: update test to not use global proxy_server app module
* ci: move caching to a separate test pipeline
speed up ci pipeline
* test: update conftest to check if proxy_server attr exists before reloading
* build(conftest.py): don't block on inability to reload proxy_server
* ci(config.yml): update caching unit test filter to work on 'cache' keyword as well
* fix(encrypt_decrypt_utils.py): use function to get salt key
* test: mark flaky test
* test: handle anthropic overloaded errors
* refactor: create separate ci/cd pipeline for proxy unit tests
make ci/cd faster
* ci(config.yml): add litellm_proxy_unit_testing to build_and_test jobs
* ci(config.yml): generate prisma binaries for proxy unit tests
* test: readd vertex_key.json
* ci(config.yml): remove `-s` from proxy_unit_test cmd
speed up test
* ci: remove any 'debug' logging flag
speed up ci pipeline
* test: fix test
* test(test_braintrust.py): rerun
* test: add delay for braintrust test
* fix(dual_cache.py): update in-memory check for redis batch get cache
Fixes latency delay for async_batch_redis_cache
* fix(service_logger.py): fix race condition causing otel service logging to be overwritten if service_callbacks set
* feat(user_api_key_auth.py): add parent otel component for auth
allows us to isolate how much latency is added by auth checks
* perf(parallel_request_limiter.py): move async_set_cache_pipeline (from max parallel request limiter) out of execution path (background task)
reduces latency by 200ms
* feat(user_api_key_auth.py): have user api key auth object return user tpm/rpm limits - reduces redis calls in downstream task (parallel_request_limiter)
Reduces latency by 400-800ms
* fix(parallel_request_limiter.py): use batch get cache to reduce user/key/team usage object calls
reduces latency by 50-100ms
* fix: fix linting error
* fix(_service_logger.py): fix import
* fix(user_api_key_auth.py): fix service logging
* fix(dual_cache.py): don't pass 'self'
* fix: fix python3.8 error
* fix: fix init]
* refactor: move gemini translation logic inside the transformation.py file
easier to isolate the gemini translation logic
* fix(gemini-transformation): support multiple tool calls in message body
Merges https://github.com/BerriAI/litellm/pull/6487/files
* test(test_vertex.py): add remaining tests from https://github.com/BerriAI/litellm/pull/6487
* fix(gemini-transformation): return tool calls for multiple tool calls
* fix: support passing logprobs param for vertex + gemini
* feat(vertex_ai): add logprobs support for gemini calls
* fix(anthropic/chat/transformation.py): fix disable parallel tool use flag
* fix: fix linting error
* fix(_logging.py): log stacktrace information in json logs
Closes https://github.com/BerriAI/litellm/issues/6497
* fix(utils.py): fix mem leak for async stream + completion
Uses a global executor pool instead of creating a new thread on each request
Fixes https://github.com/BerriAI/litellm/issues/6404
* fix(factory.py): handle tool call + content in assistant message for bedrock
* fix: fix import
* fix(factory.py): maintain support for content as a str in assistant response
* fix: fix import
* test: cleanup test
* fix(vertex_and_google_ai_studio/): return none for content if no str value
* test: retry flaky tests
* (UI) Fix viewing members, keys in a team + added testing (#6514)
* fix listing teams on ui
* LiteLLM Minor Fixes & Improvements (10/28/2024) (#6475)
* fix(anthropic/chat/transformation.py): support anthropic disable_parallel_tool_use param
Fixes https://github.com/BerriAI/litellm/issues/6456
* feat(anthropic/chat/transformation.py): support anthropic computer tool use
Closes https://github.com/BerriAI/litellm/issues/6427
* fix(vertex_ai/common_utils.py): parse out '$schema' when calling vertex ai
Fixes issue when trying to call vertex from vercel sdk
* fix(main.py): add 'extra_headers' support for azure on all translation endpoints
Fixes https://github.com/BerriAI/litellm/issues/6465
* fix: fix linting errors
* fix(transformation.py): handle no beta headers for anthropic
* test: cleanup test
* fix: fix linting error
* fix: fix linting errors
* fix: fix linting errors
* fix(transformation.py): handle dummy tool call
* fix(main.py): fix linting error
* fix(azure.py): pass required param
* LiteLLM Minor Fixes & Improvements (10/24/2024) (#6441)
* fix(azure.py): handle /openai/deployment in azure api base
* fix(factory.py): fix faulty anthropic tool result translation check
Fixes https://github.com/BerriAI/litellm/issues/6422
* fix(gpt_transformation.py): add support for parallel_tool_calls to azure
Fixes https://github.com/BerriAI/litellm/issues/6440
* fix(factory.py): support anthropic prompt caching for tool results
* fix(vertex_ai/common_utils): don't pop non-null required field
Fixes https://github.com/BerriAI/litellm/issues/6426
* feat(vertex_ai.py): support code_execution tool call for vertex ai + gemini
Closes https://github.com/BerriAI/litellm/issues/6434
* build(model_prices_and_context_window.json): Add 'supports_assistant_prefill' for bedrock claude-3-5-sonnet v2 models
Closes https://github.com/BerriAI/litellm/issues/6437
* fix(types/utils.py): fix linting
* test: update test to include required fields
* test: fix test
* test: handle flaky test
* test: remove e2e test - hitting gemini rate limits
* Litellm dev 10 26 2024 (#6472)
* docs(exception_mapping.md): add missing exception types
Fixes https://github.com/Aider-AI/aider/issues/2120#issuecomment-2438971183
* fix(main.py): register custom model pricing with specific key
Ensure custom model pricing is registered to the specific model+provider key combination
* test: make testing more robust for custom pricing
* fix(redis_cache.py): instrument otel logging for sync redis calls
ensures complete coverage for all redis cache calls
* (Testing) Add unit testing for DualCache - ensure in memory cache is used when expected (#6471)
* test test_dual_cache_get_set
* unit testing for dual cache
* fix async_set_cache_sadd
* test_dual_cache_local_only
* redis otel tracing + async support for latency routing (#6452)
* docs(exception_mapping.md): add missing exception types
Fixes https://github.com/Aider-AI/aider/issues/2120#issuecomment-2438971183
* fix(main.py): register custom model pricing with specific key
Ensure custom model pricing is registered to the specific model+provider key combination
* test: make testing more robust for custom pricing
* fix(redis_cache.py): instrument otel logging for sync redis calls
ensures complete coverage for all redis cache calls
* refactor: pass parent_otel_span for redis caching calls in router
allows for more observability into what calls are causing latency issues
* test: update tests with new params
* refactor: ensure e2e otel tracing for router
* refactor(router.py): add more otel tracing acrosss router
catch all latency issues for router requests
* fix: fix linting error
* fix(router.py): fix linting error
* fix: fix test
* test: fix tests
* fix(dual_cache.py): pass ttl to redis cache
* fix: fix param
* fix(dual_cache.py): set default value for parent_otel_span
* fix(transformation.py): support 'response_format' for anthropic calls
* fix(transformation.py): check for cache_control inside 'function' block
* fix: fix linting error
* fix: fix linting errors
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
---------
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
* ui new build
* Add retry strat (#6520)
Signed-off-by: dbczumar <corey.zumar@databricks.com>
* (fix) slack alerting - don't spam the failed cost tracking alert for the same model (#6543)
* fix use failing_model as cache key for failed_tracking_alert
* fix use standard logging payload for getting response cost
* fix kwargs.get("response_cost")
* fix getting response cost
* (feat) add XAI ChatCompletion Support (#6373)
* init commit for XAI
* add full logic for xai chat completion
* test_completion_xai
* docs xAI
* add xai/grok-beta
* test_xai_chat_config_get_openai_compatible_provider_info
* test_xai_chat_config_map_openai_params
* add xai streaming test
---------
Signed-off-by: dbczumar <corey.zumar@databricks.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Corey Zumar <39497902+dbczumar@users.noreply.github.com>
* feat(custom_logger.py): expose new `async_dataset_hook` for modifying/rejecting argilla items before logging
Allows user more control on what gets logged to argilla for annotations
* feat(google_ai_studio_endpoints.py): add new `/azure/*` pass through route
enables pass-through for azure provider
* feat(utils.py): support checking ollama `/api/show` endpoint for retrieving ollama model info
Fixes https://github.com/BerriAI/litellm/issues/6322
* fix(user_api_key_auth.py): add `/key/delete` to an allowed_ui_routes
Fixes https://github.com/BerriAI/litellm/issues/6236
* fix(user_api_key_auth.py): remove type ignore
* fix(user_api_key_auth.py): route ui vs. api token checks differently
Fixes https://github.com/BerriAI/litellm/issues/6238
* feat(internal_user_endpoints.py): support setting models as a default internal user param
Closes https://github.com/BerriAI/litellm/issues/6239
* fix(user_api_key_auth.py): fix exception string
* fix(user_api_key_auth.py): fix error string
* fix: fix test
