* feat(router.py): add retry headers to response
makes it easy to add testing to ensure model-specific retries are respected
* fix(add_retry_headers.py): clarify attempted retries vs. max retries
* test(test_fallbacks.py): add test for checking if max retries set for model is respected
* test(test_fallbacks.py): assert values for attempted retries and max retries are as expected
* fix(utils.py): return timeout in litellm proxy response headers
* test(test_fallbacks.py): add test to assert model specific timeout used on timeout error
* test: add bad model with timeout to proxy
* fix: fix linting error
* fix(router.py): fix get model list from model alias
* test: loosen test restriction - account for other events on proxy
* docs(sidebar.js): docs for support model access groups for wildcard routes
* feat(key_management_endpoints.py): add check if user is premium_user when adding model access group for wildcard route
* refactor(docs/): make control model access a root-level doc in proxy sidebar
easier to discover how to control model access on litellm
* docs: more cleanup
* feat(fireworks_ai/): add document inlining support
Enables user to call non-vision models with images/pdfs/etc.
* test(test_fireworks_ai_translation.py): add unit testing for fireworks ai transform inline helper util
* docs(docs/): add document inlining details to fireworks ai docs
* feat(fireworks_ai/): allow user to dynamically disable auto add transform inline
allows client-side disabling of this feature for proxy users
* feat(fireworks_ai/): return 'supports_vision' and 'supports_pdf_input' true on all fireworks ai models
now true as fireworks ai supports document inlining
* test: fix tests
* fix(router.py): add unit testing for _is_model_access_group_for_wildcard_route
* feat(router.py): support passing model-specific messages in fallbacks
* docs(routing.md): separate router timeouts into separate doc
allow for 1 fallbacks doc (across proxy/router)
* docs(routing.md): cleanup router docs
* docs(reliability.md): cleanup docs
* docs(reliability.md): cleaned up fallback doc
just have 1 doc across sdk/proxy
simplifies docs
* docs(reliability.md): add setting model-specific fallback prompts
* fix: fix linting errors
* test: skip test causing openai rate limit errros
* test: fix test
* test: run vertex test first to catch error
* feat(bedrock/): add bedrock converse top k param
Closes https://github.com/BerriAI/litellm/issues/7087
* Fix bedrock empty content error (#7177)
* add resolver
* handle empty content on bedrock with default content
* use existing default message, tests
* Update tests/llm_translation/test_bedrock_completion.py
* fix tests
* Revert "add resolver"
This reverts commit c717e376ee.
* fallback to empty
---------
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
* fix(factory.py): handle empty content blocks in messages
Fixes https://github.com/BerriAI/litellm/issues/7169
* feat(router.py): add stripped model check to model fallback search
if model_name="openai/gpt-3.5-turbo" and fallback=[{"gpt-3.5-turbo"..}] the fallback should just work as expected
* fix: fix linting error
* fix(factory.py): fix linting error
* fix(factory.py): in base case still support skip empty text blocks
---------
Co-authored-by: Engel Nyst <enyst@users.noreply.github.com>
* 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
* fix(main.py): support passing max retries to azure/openai embedding integrations
Fixes https://github.com/BerriAI/litellm/issues/7003
* feat(team_endpoints.py): allow updating team model aliases
Closes https://github.com/BerriAI/litellm/issues/6956
* feat(router.py): allow specifying model id as fallback - skips any cooldown check
Allows a default model to be checked if all models in cooldown
s/o @micahjsmith
* docs(reliability.md): add fallback to specific model to docs
* fix(utils.py): new 'is_prompt_caching_valid_prompt' helper util
Allows user to identify if messages/tools have prompt caching
Related issue: https://github.com/BerriAI/litellm/issues/6784
* feat(router.py): store model id for prompt caching valid prompt
Allows routing to that model id on subsequent requests
* fix(router.py): only cache if prompt is valid prompt caching prompt
prevents storing unnecessary items in cache
* feat(router.py): support routing prompt caching enabled models to previous deployments
Closes https://github.com/BerriAI/litellm/issues/6784
* test: fix linting errors
* feat(databricks/): convert basemodel to dict and exclude none values
allow passing pydantic message to databricks
* fix(utils.py): ensure all chat completion messages are dict
* (feat) Track `custom_llm_provider` in LiteLLMSpendLogs (#7081)
* add custom_llm_provider to SpendLogsPayload
* add custom_llm_provider to SpendLogs
* add custom llm provider to SpendLogs payload
* test_spend_logs_payload
* Add MLflow to the side bar (#7031)
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
* (bug fix) SpendLogs update DB catch all possible DB errors for retrying (#7082)
* 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
* (Feat) Add StructuredOutputs support for Fireworks.AI (#7085)
* fix model cost map fireworks ai "supports_response_schema": true,
* fix supports_response_schema
* fix map openai params fireworks ai
* test_map_response_format
* test_map_response_format
* added deepinfra/Meta-Llama-3.1-405B-Instruct (#7084)
* bump: version 1.53.9 → 1.54.0
* fix deepinfra
* litellm db fixes LiteLLM_UserTable (#7089)
* ci/cd queue new release
* fix llama-3.3-70b-versatile
* refactor - use consistent file naming convention `AI21/` -> `ai21` (#7090)
* fix refactor - use consistent file naming convention
* ci/cd run again
* fix naming structure
* fix use consistent naming (#7092)
---------
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Yuki Watanabe <31463517+B-Step62@users.noreply.github.com>
Co-authored-by: ali sayyah <ali.sayyah2@gmail.com>
* 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
* 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
* docs(config_settings.md): document all router_settings
* ci(config.yml): add router_settings doc test to ci/cd
* test: debug test on ci/cd
* test: debug ci/cd test
* test: fix test
* fix(team_endpoints.py): skip invalid team object. don't fail `/team/list` call
Causes downstream errors if ui just fails to load team list
* test(base_llm_unit_tests.py): add 'response_format={"type": "text"}' test to base_llm_unit_tests
adds complete coverage for all 'response_format' values to ci/cd
* feat(router.py): support wildcard routes in `get_router_model_info()`
Addresses https://github.com/BerriAI/litellm/issues/6914
* build(model_prices_and_context_window.json): add tpm/rpm limits for all gemini models
Allows for ratelimit tracking for gemini models even with wildcard routing enabled
Addresses https://github.com/BerriAI/litellm/issues/6914
* feat(router.py): add tpm/rpm tracking on success/failure to global_router
Addresses https://github.com/BerriAI/litellm/issues/6914
* feat(router.py): support wildcard routes on router.get_model_group_usage()
* fix(router.py): fix linting error
* fix(router.py): implement get_remaining_tokens_and_requests
Addresses https://github.com/BerriAI/litellm/issues/6914
* fix(router.py): fix linting errors
* test: fix test
* test: fix tests
* docs(config_settings.md): add missing dd env vars to docs
* fix(router.py): check if hidden params is dict
* 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>
* 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>
* fix(core_helpers.py): return None, instead of raising kwargs is None error
Closes https://github.com/BerriAI/litellm/issues/6500
* docs(cost_tracking.md): cleanup doc
* fix(vertex_and_google_ai_studio.py): handle function call with no params passed in
Closes https://github.com/BerriAI/litellm/issues/6495
* test(test_router_timeout.py): add test for router timeout + retry logic
* test: update test to use module level values
* (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
* refactor(prometheus.py): move to using standard logging payload for reading the remaining request / tokens
Ensures prometheus token tracking works for anthropic as well
* fix: fix linting error
* fix(redis_cache.py): make sure ttl is always int (handle float values)
Fixes issue where redis_client.ex was not working correctly due to float ttl
* fix: fix linting error
* test: update test
* fix: fix linting error
---------
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>
* 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>
* 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
* 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
* docs(bedrock.md): clarify bedrock auth in litellm docs
* fix(convert_dict_to_response.py): Fixes https://github.com/BerriAI/litellm/issues/6387
* feat(pattern_match_deployments.py): more robust handling for wildcard routes (model_name: custom_route/* -> openai/*)
Enables user to expose custom routes to users with dynamic handling
* test: add more testing
* docs(custom_pricing.md): add debug tutorial for custom pricing
* test: skip codestral test - unreachable backend
* test: fix test
* fix(pattern_matching_deployments.py): fix typing
* test: cleanup codestral tests - backend api unavailable
* (refactor) prometheus async_log_success_event to be under 100 LOC (#6416)
* unit testig for prometheus
* unit testing for success metrics
* use 1 helper for _increment_token_metrics
* use helper for _increment_remaining_budget_metrics
* use _increment_remaining_budget_metrics
* use _increment_top_level_request_and_spend_metrics
* use helper for _set_latency_metrics
* remove noqa violation
* fix test prometheus
* test prometheus
* unit testing for all prometheus helper functions
* fix prom unit tests
* fix unit tests prometheus
* fix unit test prom
* (refactor) router - use static methods for client init utils (#6420)
* use InitalizeOpenAISDKClient
* use InitalizeOpenAISDKClient static method
* fix # noqa: PLR0915
* (code cleanup) remove unused and undocumented logging integrations - litedebugger, berrispend (#6406)
* code cleanup remove unused and undocumented code files
* fix unused logging integrations cleanup
* bump: version 1.50.3 → 1.50.4
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
* refactor(router.py): move assistants api endpoints to using 1 pass-through factory function
Reduces code, increases testing coverage
* refactor(router.py): reduce _common_check_available_deployment function size
make code more maintainable - reduce possible errors
* test(router_code_coverage.py): include batch_utils + pattern matching in enforced 100% code coverage
Improves reliability
* fix(router.py): fix model id match model dump
* add testing coverage for pattern match router
* fix add_pattern
* fix typo on router_cooldown_event_callback
* add testing for pattern match router
* fix add explanation for pattern match router
* add flake 8 check
* split up litellm _acompletion
* fix get model client
* refactor use commong func to add metadata to kwargs
* use common func to get timeout
* re-use helper to _get_async_model_client
* use _handle_mock_testing_rate_limit_error
* fix docstring for _handle_mock_testing_rate_limit_error
* fix function_with_retries
* use helper for mock testing fallbacks
* router - use 1 func for simple_shuffle
* add doc string for simple_shuffle
* use 1 function for filtering cooldown deployments
* fix use common helper to _get_fallback_model_group_from_fallbacks
* track api key and team in prom latency metric
* add test for latency metric
* test prometheus success metrics for latency
* track team and key labels for deployment failures
* add test for litellm_deployment_failure_responses_total
* fix checks for premium user on prometheus
* log_success_fallback_event and log_failure_fallback_event
* log original_exception in log_success_fallback_event
* track key, team and exception status and class on fallback metrics
* use get_standard_logging_metadata
* fix import error
* track litellm_deployment_successful_fallbacks
* add test test_proxy_fallback_metrics
* add log log_success_fallback_event
* fix test prometheus
* feat(router.py): initial commit for loadbalancing azure batch api endpoints
Closes https://github.com/BerriAI/litellm/issues/5396
* fix(router.py): working `router.acreate_file()`
* feat(router.py): working router.acreate_batch endpoint
* feat(router.py): expose router.aretrieve_batch function
Make it easy for user to retrieve the batch information
* feat(router.py): support 'router.alist_batches' endpoint
Adds support for getting all batches across all endpoints
* feat(router.py): working loadbalancing on `/v1/files`
* feat(proxy_server.py): working loadbalancing on `/v1/batches`
* feat(proxy_server.py): working loadbalancing on Retrieve + List batch
