* test: initial test to enforce all functions in user_api_key_auth.py have direct testing
* test(test_user_api_key_auth.py): add is_allowed_route unit test
* test(test_user_api_key_auth.py): add more tests
* test(test_user_api_key_auth.py): add complete testing coverage for all functions in `user_api_key_auth.py`
* test(test_db_schema_changes.py): add a unit test to ensure all db schema changes are backwards compatible
gives user an easy rollback path
* test: fix schema compatibility test filepath
* test: fix test
* feat(pass_through_endpoints.py): fix anthropic end user cost tracking
* fix(anthropic/chat/transformation.py): use returned provider model for anthropic
handles anthropic `-latest` tag in request body throwing cost calculation errors
ensures we can be accurate in our model cost tracking
* feat(model_prices_and_context_window.json): add gemini-2.0-flash-thinking-exp pricing
* test: update test to use assumption that user_api_key_dict can get anthropic user id
* test: fix test
* fix: fix test
* fix(anthropic_pass_through.py): uncomment previous anthropic end-user cost tracking code block
can't guarantee user api key dict always has end user id - too many code paths
* fix(user_api_key_auth.py): this allows end user id from request body to always be read and set in auth object
* fix(auth_check.py): fix linting error
* test: fix auth check
* fix(auth_utils.py): fix get end user id to handle metadata = None
* fix(gpt_transformation.py): fix response_format translation check for 4o models
Fixes https://github.com/BerriAI/litellm/issues/7616
* feat(key_management_endpoints.py): support 'temp_budget_increase' and 'temp_budget_expiry' fields
Allow proxy admin to grant temporary budget increases to keys
* fix(proxy/_types.py): enforce temp_budget_increase and temp_budget_expiry are always passed together
* feat(user_api_key_auth.py): initial working temp budget increase logic
ensures key budget exceeded error checks for temp budget in key metadata
* feat(proxy_server.py): return the key max budget and key spend in the response headers
Allows clientside user to know their remaining limits
* test: add unit testing for new proxy utils
Ensures new key budget is correctly handled
* docs(temporary_budget_increase.md): add doc on temporary budget increase
* fix(utils.py): remove 3.5 from response_format check for now
not all azure 3.5 models support response_format
* fix(user_api_key_auth.py): return valid user api key auth object on all paths
* feat(ui_sso.py): support reading team ids from sso token
* feat(ui_sso.py): working upsert sso user teams membership in litellm - if team exists
Adds user to relevant teams, if user is part of teams and team exists on litellm
* fix(ui_sso.py): safely handle add team member task
* build(ui/): support setting team id when creating team on UI
* build(ui/): teams.tsx
allow setting team id on ui
* build(circle_ci/requirements.txt): add fastapi-sso to ci/cd testing
* fix: fix linting errors
* feat(main.py): mock_response() - support 'litellm.ContextWindowExceededError' in mock response
enabled quicker router/fallback/proxy debug on context window errors
* feat(exception_mapping_utils.py): extract special litellm errors from error str if calling `litellm_proxy/` as provider
Closes https://github.com/BerriAI/litellm/issues/7259
* fix(user_api_key_auth.py): specify 'Received Proxy Server Request' is span kind server
Closes https://github.com/BerriAI/litellm/issues/7298
* feat(proxy/utils.py): get associated litellm budget from db in combined_view for key
allows user to create rate limit tiers and associate those to keys
* feat(proxy/_types.py): update the value of key-level tpm/rpm/model max budget metrics with the associated budget table values if set
allows rate limit tiers to be easily applied to keys
* docs(rate_limit_tiers.md): add doc on setting rate limit / budget tiers
make feature discoverable
* feat(key_management_endpoints.py): return litellm_budget_table value in key generate
make it easy for user to know associated budget on key creation
* fix(key_management_endpoints.py): document 'budget_id' param in `/key/generate`
* docs(key_management_endpoints.py): document budget_id usage
* refactor(budget_management_endpoints.py): refactor budget endpoints into separate file - makes it easier to run documentation testing against it
* docs(test_api_docs.py): add budget endpoints to ci/cd doc test + add missing param info to docs
* fix(customer_endpoints.py): use new pydantic obj name
* docs(user_management_heirarchy.md): add simple doc explaining teams/keys/org/users on litellm
* Litellm dev 12 26 2024 p2 (#7432)
* (Feat) Add logging for `POST v1/fine_tuning/jobs` (#7426)
* init commit ft jobs logging
* add ft logging
* add logging for FineTuningJob
* simple FT Job create test
* (docs) - show all supported Azure OpenAI endpoints in overview (#7428)
* azure batches
* update doc
* docs azure endpoints
* docs endpoints on azure
* docs azure batches api
* docs azure batches api
* fix(key_management_endpoints.py): fix key update to actually work
* test(test_key_management.py): add e2e test asserting ui key update call works
* fix: proxy/_types - fix linting erros
* test: update test
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
* fix: test
* fix(parallel_request_limiter.py): enforce tpm/rpm limits on key from tiers
* fix: fix linting errors
* test: fix test
* fix: remove unused import
* test: update test
* docs(customer_endpoints.py): document new model_max_budget param
* test: specify unique key alias
* docs(budget_management_endpoints.py): document new model_max_budget param
* test: fix test
* test: fix tests
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
* fix(proxy_server.py): enforce team id based model add only works if enterprise user
* fix(auth_checks.py): enforce common_checks can only be imported by user_api_key_auth.py
* fix(auth_checks.py): insert not premium user error message on failed common checks run
* ui fix - allow searching model list + fix bug on filtering
* qa fix - use correct provider name for azure_text
* ui wrap content onto next line
* ui fix - allow selecting current UI session when logging in
* ui session budgets
* ui show provider models on wildcard models
* test provider name appears in model list
* ui fix auto scroll on chat ui tab
* fix(proxy_track_cost_callback.py): log to db if only end user param given
* fix: allows for jwt-auth based end user id spend tracking to work
* fix(utils.py): fix 'get_end_user_id_for_cost_tracking' to use 'user_api_key_end_user_id'
more stable - works with jwt-auth based end user tracking as well
* test(test_jwt.py): add e2e unit test to confirm end user cost tracking works for spend logs
* test: update test to use end_user api key hash param
* fix(langfuse.py): support end user cost tracking via jwt auth + langfuse
logs end user to langfuse if decoded from jwt token
* fix: fix linting errors
* test: fix test
* test: fix test
* fix: fix end user id extraction
* fix: run test earlier
* fix(proxy_server.py): pass model access groups to get_key/get_team models
allows end user to see actual models they have access to, instead of default models
* fix(auth_checks.py): fix linting errors
* fix: fix linting errors
* fix(azure/): support passing headers to azure openai endpoints
Fixes https://github.com/BerriAI/litellm/issues/6217
* fix(utils.py): move default tokenizer to just openai
hf tokenizer makes network calls when trying to get the tokenizer - this slows down execution time calls
* fix(router.py): fix pattern matching router - add generic "*" to it as well
Fixes issue where generic "*" model access group wouldn't show up
* fix(pattern_match_deployments.py): match to more specific pattern
match to more specific pattern
allows setting generic wildcard model access group and excluding specific models more easily
* fix(proxy_server.py): fix _delete_deployment to handle base case where db_model list is empty
don't delete all router models b/c of empty list
Fixes https://github.com/BerriAI/litellm/issues/7196
* fix(anthropic/): fix handling response_format for anthropic messages with anthropic api
* fix(fireworks_ai/): support passing response_format + tool call in same message
Addresses https://github.com/BerriAI/litellm/issues/7135
* Revert "fix(fireworks_ai/): support passing response_format + tool call in same message"
This reverts commit 6a30dc6929.
* test: fix test
* fix(replicate/): fix replicate default retry/polling logic
* test: add unit testing for router pattern matching
* test: update test to use default oai tokenizer
* test: mark flaky test
* test: skip flaky test
* catch DB_CONNECTION_ERROR_TYPES
* fix DB retry mechanism for SpendLog updates
* use DB_CONNECTION_ERROR_TYPES in auth checks
* fix exp back off for writing SpendLogs
* use _raise_failed_update_spend_exception to ensure errors print as NON blocking
* test_update_spend_logs_multiple_batches_with_failure
* fix(edit_budget_modal.tsx): call `/budget/update` endpoint instead of `/budget/new`
allows updating existing budget on ui
* fix(user_api_key_auth.py): support cost tracking for end user via jwt field
* fix(presidio.py): support pii masking on sync logging callbacks
enables masking before logging to langfuse
* feat(utils.py): support retry policy logic inside '.completion()'
Fixes https://github.com/BerriAI/litellm/issues/6623
* fix(utils.py): support retry by retry policy on async logic as well
* fix(handle_jwt.py): set leeway default leeway value
* test: fix test to handle jwt audience claim
* get_api_key_from_custom_header
* add test_get_api_key_from_custom_header
* fix testing use 1 file for test user api key auth
* fix test user api key auth
* test_custom_api_key_header_name
* fix(key_management_endpoints.py): override metadata field value on update
allow user to override tags
* feat(__init__.py): expose new disable_end_user_cost_tracking_prometheus_only metric
allow disabling end user cost tracking on prometheus - fixes cardinality issue
* fix(litellm_pre_call_utils.py): add key/team level enforced params
Fixes https://github.com/BerriAI/litellm/issues/6652
* fix(key_management_endpoints.py): allow user to pass in `enforced_params` as a top level param on /key/generate and /key/update
* docs(enterprise.md): add docs on enforcing required params for llm requests
* Add support of Galadriel API (#7005)
* fix(router.py): robust retry after handling
set retry after time to 0 if >0 healthy deployments. handle base case = 1 deployment
* test(test_router.py): fix test
* feat(bedrock/): add support for 'nova' models
also adds explicit 'converse/' route for simpler routing
* fix: fix 'supports_pdf_input'
return if model supports pdf input on get_model_info
* feat(converse_transformation.py): support bedrock pdf input
* docs(document_understanding.md): add document understanding to docs
* fix(litellm_pre_call_utils.py): fix linting error
* fix(init.py): fix passing of bedrock converse models
* feat(bedrock/converse): support 'response_format={"type": "json_object"}'
* fix(converse_handler.py): fix linting error
* fix(base_llm_unit_tests.py): fix test
* fix: fix test
* test: fix test
* test: fix test
* test: remove duplicate test
---------
Co-authored-by: h4n0 <4738254+h4n0@users.noreply.github.com>
* fix get_standard_logging_object_payload
* fix async_post_call_failure_hook
* fix post_call_failure_hook
* fix change
* fix _is_proxy_only_error
* fix async_post_call_failure_hook
* fix getting request body
* remove redundant code
* use a well named original function name for auth errors
* fix logging auth fails on DD
* fix using request body
* use helper for _handle_logging_proxy_only_error
* fix(factory.py): ensure tool call converts image url
Fixes https://github.com/BerriAI/litellm/issues/6953
* fix(transformation.py): support mp4 + pdf url's for vertex ai
Fixes https://github.com/BerriAI/litellm/issues/6936
* fix(http_handler.py): mask gemini api key in error logs
Fixes https://github.com/BerriAI/litellm/issues/6963
* docs(prometheus.md): update prometheus FAQs
* feat(auth_checks.py): ensure specific model access > wildcard model access
if wildcard model is in access group, but specific model is not - deny access
* fix(auth_checks.py): handle auth checks for team based model access groups
handles scenario where model access group used for wildcard models
* fix(internal_user_endpoints.py): support adding guardrails on `/user/update`
Fixes https://github.com/BerriAI/litellm/issues/6942
* fix(key_management_endpoints.py): fix prepare_metadata_fields helper
* fix: fix tests
* build(requirements.txt): bump openai dep version
fixes proxies argument
* test: fix tests
* fix(http_handler.py): fix error message masking
* fix(bedrock_guardrails.py): pass in prepped data
* test: fix test
* test: fix nvidia nim test
* fix(http_handler.py): return original response headers
* fix: revert maskedhttpstatuserror
* test: update tests
* test: cleanup test
* fix(key_management_endpoints.py): fix metadata field update logic
* fix(key_management_endpoints.py): maintain initial order of guardrails in key update
* fix(key_management_endpoints.py): handle prepare metadata
* fix: fix linting errors
* fix: fix linting errors
* fix: fix linting errors
* fix: fix key management errors
* fix(key_management_endpoints.py): update metadata
* test: update test
* refactor: add more debug statements
* test: skip flaky test
* test: fix test
* fix: fix test
* fix: fix update metadata logic
* fix: fix test
* ci(config.yml): change db url for e2e ui testing
* fix(key_management_endpoints.py): fix user-membership check when creating team key
* docs: add deprecation notice on original `/v1/messages` endpoint + add better swagger tags on pass-through endpoints
* fix(gemini/): fix image_url handling for gemini
Fixes https://github.com/BerriAI/litellm/issues/6897
* fix(teams.tsx): fix member add when role is 'user'
* fix(team_endpoints.py): /team/member_add
fix adding several new members to team
* test(test_vertex.py): remove redundant test
* test(test_proxy_server.py): fix team member add tests
* feat - allow using gemini js SDK with LiteLLM
* add auth for gemini_proxy_route
* basic local test for js
* test cost tagging gemini js requests
* add js sdk test for gemini with litellm
* add docs on gemini JS SDK
* run node.js tests
* fix google ai studio tests
* fix vertex js spend test
* fix(ollama.py): fix get model info request
Fixes https://github.com/BerriAI/litellm/issues/6703
* feat(anthropic/chat/transformation.py): support passing user id to anthropic via openai 'user' param
* docs(anthropic.md): document all supported openai params for anthropic
* test: fix tests
* fix: fix tests
* feat(jina_ai/): add rerank support
Closes https://github.com/BerriAI/litellm/issues/6691
* test: handle service unavailable error
* fix(handler.py): refactor together ai rerank call
* test: update test to handle overloaded error
* test: fix test
* Litellm router trace (#6742)
* feat(router.py): add trace_id to parent functions - allows tracking retry/fallbacks
* feat(router.py): log trace id across retry/fallback logic
allows grouping llm logs for the same request
* test: fix tests
* fix: fix test
* fix(transformation.py): only set non-none stop_sequences
* Litellm router disable fallbacks (#6743)
* bump: version 1.52.6 → 1.52.7
* feat(router.py): enable dynamically disabling fallbacks
Allows for enabling/disabling fallbacks per key
* feat(litellm_pre_call_utils.py): support setting 'disable_fallbacks' on litellm key
* test: fix test
* fix(exception_mapping_utils.py): map 'model is overloaded' to internal server error
* test: handle gemini error
* test: fix test
* fix: new run
* fix raise correct error on /key/info
* add not_found_error error
* fix key not found in DB error
* use 1 helper for checking token hash
* fix error code on key info
* fix test key gen prisma
* test_generate_and_call_key_info
* test fix test_call_with_valid_model_using_all_models
* fix key info tests
* fix(__init__.py): add 'watsonx_text' as mapped llm api route
Fixes https://github.com/BerriAI/litellm/issues/6663
* fix(opentelemetry.py): fix passing parallel tool calls to otel
Fixes https://github.com/BerriAI/litellm/issues/6677
* refactor(test_opentelemetry_unit_tests.py): create a base set of unit tests for all logging integrations - test for parallel tool call handling
reduces bugs in repo
* fix(__init__.py): update provider-model mapping to include all known provider-model mappings
Fixes https://github.com/BerriAI/litellm/issues/6669
* feat(anthropic): support passing document in llm api call
* docs(anthropic.md): add pdf anthropic call to docs + expose new 'supports_pdf_input' function
* fix(factory.py): fix linting error
* fix(deepseek/chat): convert content list to str
Fixes https://github.com/BerriAI/litellm/issues/6642
* test(test_deepseek_completion.py): implement base llm unit tests
increase robustness across providers
* fix(router.py): support content policy violation fallbacks with default fallbacks
* fix(opentelemetry.py): refactor to move otel imports behing flag
Fixes https://github.com/BerriAI/litellm/issues/6636
* fix(opentelemtry.py): close span on success completion
* fix(user_api_key_auth.py): allow user_role to default to none
* fix: mark flaky test
* fix(opentelemetry.py): move otelconfig.from_env to inside the init
prevent otel errors raised just by importing the litellm class
* fix(user_api_key_auth.py): fix auth error
* log error on prometheus service failure hook
* use a more accurate function name for wrapper that handles logging db metrics
* fix log_db_metrics
* test_log_db_metrics_failure_error_types
* fix linting
* fix auth checks
* fix use helper for _handle_failed_db_connection_for_get_key_object
* track ALLOW_FAILED_DB_REQUESTS on prometheus
* fix allow_failed_db_requests check
* fix allow_requests_on_db_unavailable
* fix allow_requests_on_db_unavailable
* docs allow_requests_on_db_unavailable
* identify user_id as litellm_proxy_admin_name when DB is failing
* test_handle_failed_db_connection
* fix test_user_api_key_auth_db_unavailable
* update best practices for prod doc
* update best practices for prod
* fix handle db failure
* refactor(proxy_server.py): add debug logging around license check event (refactor position in startup_event logic)
* fix(proxy/_types.py): allow admin_allowed_routes to be any str
* fix(router.py): raise 400-status code error for no 'model_name' error on router
Fixes issue with status code when unknown model name passed with pattern matching enabled
* fix(converse_handler.py): add claude 3-5 haiku to bedrock converse models
* test: update testing to replace claude-instant-1.2
* fix(router.py): fix router.moderation calls
* test: update test to remove claude-instant-1
* fix(router.py): support model_list values in router.moderation
* test: fix test
* test: fix test
* perf: move writing key to cache, to background task
* perf(litellm_pre_call_utils.py): add otel tracing for pre-call utils
adds 200ms on calls with pgdb connected
* fix(litellm_pre_call_utils.py'): rename call_type to actual call used
* perf(proxy_server.py): remove db logic from _get_config_from_file
was causing db calls to occur on every llm request, if team_id was set on key
* fix(auth_checks.py): add check for reducing db calls if user/team id does not exist in db
reduces latency/call by ~100ms
* fix(proxy_server.py): minor fix on existing_settings not incl alerting
* fix(exception_mapping_utils.py): map databricks exception string
* fix(auth_checks.py): fix auth check logic
* test: correctly mark flaky test
* fix(utils.py): handle auth token error for tokenizers.from_pretrained
* 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]
* feat(router.py): add check for max fallback depth
Prevent infinite loop for fallbacks
Closes https://github.com/BerriAI/litellm/issues/6498
* test: update test
* (fix) Prometheus - Log Postgres DB latency, status on prometheus (#6484)
* fix logging DB fails on prometheus
* unit testing log to otel wrapper
* unit testing for service logger + prometheus
* use LATENCY buckets for service logging
* fix service logging
* docs clarify vertex vs gemini
* (router_strategy/) ensure all async functions use async cache methods (#6489)
* fix router strat
* use async set / get cache in router_strategy
* add coverage for router strategy
* fix imports
* fix batch_get_cache
* use async methods for least busy
* fix least busy use async methods
* fix test_dual_cache_increment
* test async_get_available_deployment when routing_strategy="least-busy"
* (fix) proxy - fix when `STORE_MODEL_IN_DB` should be set (#6492)
* set store_model_in_db at the top
* correctly use store_model_in_db global
* (fix) `PrometheusServicesLogger` `_get_metric` should return metric in Registry (#6486)
* fix logging DB fails on prometheus
* unit testing log to otel wrapper
* unit testing for service logger + prometheus
* use LATENCY buckets for service logging
* fix service logging
* fix _get_metric in prom services logger
* add clear doc string
* unit testing for prom service logger
* bump: version 1.51.0 → 1.51.1
* Add `azure/gpt-4o-mini-2024-07-18` to model_prices_and_context_window.json (#6477)
* Update utils.py (#6468)
Fixed missing keys
* (perf) Litellm redis router fix - ~100ms improvement (#6483)
* 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
* perf(cooldown_cache.py): improve cooldown cache, to store cache results in memory for 5s, prevents redis call from being made on each request
reduces 100ms latency per call with caching enabled on router
* fix: fix test
* fix(cooldown_cache.py): handle if a result is None
* fix(cooldown_cache.py): add debug statements
* refactor(dual_cache.py): move to using an in-memory check for batch get cache, to prevent redis from being hit for every call
* fix(cooldown_cache.py): fix linting erropr
* build: merge main
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Xingyao Wang <xingyao@all-hands.dev>
Co-authored-by: vibhanshu-ob <115142120+vibhanshu-ob@users.noreply.github.com>
* 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
