* 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(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>
* 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>
* 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
