* test: fix import for test
* fix: fix bad error string
* docs: cleanup files docs
* fix(files/main.py): cleanup error string
* style: initial commit with a provider/config pattern for files api
google ai studio files api onboarding
* fix: test
* feat(gemini/files/transformation.py): support gemini files api response transformation
* fix(gemini/files/transformation.py): return file id as gemini uri
allows id to be passed in to chat completion request, just like openai
* feat(llm_http_handler.py): support async route for files api on llm_http_handler
* fix: fix linting errors
* fix: fix model info check
* fix: fix ruff errors
* fix: fix linting errors
* Revert "fix: fix linting errors"
This reverts commit 926a5a527f.
* fix: fix linting errors
* test: fix test
* test: fix tests
* build(pyproject.toml): add new dev dependencies - for type checking
* build: reformat files to fit black
* ci: reformat to fit black
* ci(test-litellm.yml): make tests run clear
* build(pyproject.toml): add ruff
* fix: fix ruff checks
* build(mypy/): fix mypy linting errors
* fix(hashicorp_secret_manager.py): fix passing cert for tls auth
* build(mypy/): resolve all mypy errors
* test: update test
* fix: fix black formatting
* build(pre-commit-config.yaml): use poetry run black
* fix(proxy_server.py): fix linting error
* fix: fix ruff safe representation error
* feat(bedrock/rerank): infer model region if model given as arn
* test: add unit testing to ensure bedrock region name inferred from arn on rerank
* feat(bedrock/rerank/transformation.py): include search units for bedrock rerank result
Resolves https://github.com/BerriAI/litellm/issues/7258#issuecomment-2671557137
* test(test_bedrock_completion.py): add testing for bedrock cohere rerank
* feat(cost_calculator.py): refactor rerank cost tracking to support bedrock cost tracking
* build(model_prices_and_context_window.json): add amazon.rerank model to model cost map
* fix(cost_calculator.py): bedrock/common_utils.py
get base model from model w/ arn -> handles rerank model
* build(model_prices_and_context_window.json): add bedrock cohere rerank pricing
* feat(bedrock/rerank): migrate bedrock config to basererank config
* Revert "feat(bedrock/rerank): migrate bedrock config to basererank config"
This reverts commit 84fae1f167.
* test: add testing to ensure large doc / queries are correctly counted
* Revert "test: add testing to ensure large doc / queries are correctly counted"
This reverts commit 4337f1657e.
* fix(migrate-jina-ai-to-rerank-config): enables cost tracking
* refactor(jina_ai/): finish migrating jina ai to base rerank config
enables cost tracking
* fix(jina_ai/rerank): e2e jina ai rerank cost tracking
* fix: cleanup dead code
* fix: fix python3.8 compatibility error
* test: fix test
* test: add e2e testing for azure ai rerank
* fix: fix linting error
* test: mark cohere as flaky
* test(azure_openai_o1.py): initial commit with testing for azure openai o1 preview model
* fix(base_llm_unit_tests.py): handle azure o1 preview response format tests
skip as o1 on azure doesn't support tool calling yet
* fix: initial commit of azure o1 handler using openai caller
simplifies calling + allows fake streaming logic alr. implemented for openai to just work
* feat(azure/o1_handler.py): fake o1 streaming for azure o1 models
azure does not currently support streaming for o1
* feat(o1_transformation.py): support overriding 'should_fake_stream' on azure/o1 via 'supports_native_streaming' param on model info
enables user to toggle on when azure allows o1 streaming without needing to bump versions
* style(router.py): remove 'give feedback/get help' messaging when router is used
Prevents noisy messaging
Closes https://github.com/BerriAI/litellm/issues/5942
* fix(types/utils.py): handle none logprobs
Fixes https://github.com/BerriAI/litellm/issues/328
* fix(exception_mapping_utils.py): fix error str unbound error
* refactor(azure_ai/): move to openai_like chat completion handler
allows for easy swapping of api base url's (e.g. ai.services.com)
Fixes https://github.com/BerriAI/litellm/issues/7275
* refactor(azure_ai/): move to base llm http handler
* fix(azure_ai/): handle differing api endpoints
* fix(azure_ai/): make sure all unit tests are passing
* fix: fix linting errors
* fix: fix linting errors
* fix: fix linting error
* fix: fix linting errors
* fix(azure_ai/transformation.py): handle extra body param
* fix(azure_ai/transformation.py): fix max retries param handling
* fix: fix test
* test(test_azure_o1.py): fix test
* fix(llm_http_handler.py): support handling azure ai unprocessable entity error
* fix(llm_http_handler.py): handle sync invalid param error for azure ai
* fix(azure_ai/): streaming support with base_llm_http_handler
* fix(llm_http_handler.py): working sync stream calls with unprocessable entity handling for azure ai
* fix: fix linting errors
* fix(llm_http_handler.py): fix linting error
* fix(azure_ai/): handle cohere tool call invalid index param error
* fix(azure_ai/transformation.py): route ai.services.azure calls to the azure provider route
requires token to be passed in as 'api-key'
Closes https://github.com/BerriAI/litellm/issues/7275
* fix(key_management_endpoints.py): enforce user is member of team, if team_id set and team_id exists in team table
* fix(key_management_endpoints.py): handle assigned_user_id = none
* feat(create_key_button.tsx): allow assigning keys to other users
allows proxy admin to easily assign other people keys
* build(create_key_button.tsx): fix error message display
don't swallow the error message for key creation failure
* build(create_key_button.tsx): allow proxy admin to edit team id
* build(create_key_button.tsx): allow proxy admin to assign keys to other users
* build(edit_user.tsx): clarify how 'user budgets' are applied
* test: remove dup test
* fix(key_management_endpoints.py): don't raise error if team not in db
'
* test: fix test
* fix(health.md): add rerank model health check information
* build(model_prices_and_context_window.json): add gemini 2.0 for google ai studio - pricing + commercial rate limits
* build(model_prices_and_context_window.json): add gemini-2.0 supports audio output = true
* docs(team_model_add.md): clarify allowing teams to add models is an enterprise feature
* fix(o1_transformation.py): add support for 'n', 'response_format' and 'stop' params for o1 and 'stream_options' param for o1-mini
* build(model_prices_and_context_window.json): add 'supports_system_message' to supporting openai models
needed as o1-preview, and o1-mini models don't support 'system message
* fix(o1_transformation.py): translate system message based on if o1 model supports it
* fix(o1_transformation.py): return 'stream' param support if o1-mini/o1-preview
o1 currently doesn't support streaming, but the other model versions do
Fixes https://github.com/BerriAI/litellm/issues/7292
* fix(o1_transformation.py): return tool calling/response_format in supported params if model map says so
Fixes https://github.com/BerriAI/litellm/issues/7292
* fix: fix linting errors
* fix: update '_transform_messages'
* fix(o1_transformation.py): fix provider passed for supported param checks
* test(base_llm_unit_tests.py): skip test if api takes >5s to respond
* fix(utils.py): return false in 'supports_factory' if can't find value
* fix(o1_transformation.py): always return stream + stream_options as supported params + handle stream options being passed in for azure o1
* feat(openai.py): support stream faking natively in openai handler
Allows o1 calls to be faked for just the "o1" model, allows native streaming for o1-mini, o1-preview
Fixes https://github.com/BerriAI/litellm/issues/7292
* fix(openai.py): use inference param instead of original optional param
* 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(pass_through_endpoints/): support logging anthropic/gemini pass through calls to langfuse/s3/etc.
* fix(utils.py): allow disabling end user cost tracking with new param
Allows proxy admin to disable cost tracking for end user - keeps prometheus metrics small
* docs(configs.md): add disable_end_user_cost_tracking reference to docs
* feat(key_management_endpoints.py): add support for restricting access to `/key/generate` by team/proxy level role
Enables admin to restrict key creation, and assign team admins to handle distributing keys
* test(test_key_management.py): add unit testing for personal / team key restriction checks
* docs: add docs on restricting key creation
* docs(finetuned_models.md): add new guide on calling finetuned models
* docs(input.md): cleanup anthropic supported params
Closes https://github.com/BerriAI/litellm/issues/6856
* test(test_embedding.py): add test for passing extra headers via embedding
* feat(cohere/embed): pass client to async embedding
* feat(rerank.py): add `/v1/rerank` if missing for cohere base url
Closes https://github.com/BerriAI/litellm/issues/6844
* fix(main.py): pass extra_headers param to openai
Fixes https://github.com/BerriAI/litellm/issues/6836
* fix(litellm_logging.py): don't disable global callbacks when dynamic callbacks are set
Fixes issue where global callbacks - e.g. prometheus were overriden when langfuse was set dynamically
* fix(handler.py): fix linting error
* fix: fix typing
* build: add conftest to proxy_admin_ui_tests/
* test: fix test
* fix: fix linting errors
* test: fix test
* fix: fix pass through testing
* fix(utils.py): support passing dynamic api base to validate_environment
Returns True if just api base is required and api base is passed
* fix(litellm_pre_call_utils.py): feature flag sending client headers to llm api
Fixes https://github.com/BerriAI/litellm/issues/6410
* fix(anthropic/chat/transformation.py): return correct error message
* fix(http_handler.py): add error response text in places where we expect it
* fix(factory.py): handle base case of no non-system messages to bedrock
Fixes https://github.com/BerriAI/litellm/issues/6411
* feat(cohere/embed): Support cohere image embeddings
Closes https://github.com/BerriAI/litellm/issues/6413
* fix(__init__.py): fix linting error
* docs(supported_embedding.md): add image embedding example to docs
* feat(cohere/embed): use cohere embedding returned usage for cost calc
* build(model_prices_and_context_window.json): add embed-english-v3.0 details (image cost + 'supports_image_input' flag)
* fix(cohere_transformation.py): fix linting error
* test(test_proxy_server.py): cleanup test
* test: cleanup test
* fix: fix linting errors
* feat(proxy_cli.py): add new 'log_config' cli param
Allows passing logging.conf to uvicorn on startup
* docs(cli.md): add logging conf to uvicorn cli docs
* fix(get_llm_provider_logic.py): fix default api base for litellm_proxy
Fixes https://github.com/BerriAI/litellm/issues/6332
* feat(openai_like/embedding): Add support for jina ai embeddings
Closes https://github.com/BerriAI/litellm/issues/6337
* docs(deploy.md): update entrypoint.sh filepath post-refactor
Fixes outdated docs
* feat(prometheus.py): emit time_to_first_token metric on prometheus
Closes https://github.com/BerriAI/litellm/issues/6334
* fix(prometheus.py): only emit time to first token metric if stream is True
enables more accurate ttft usage
* test: handle vertex api instability
* fix(get_llm_provider_logic.py): fix import
* fix(openai.py): fix deepinfra default api base
* fix(anthropic/transformation.py): remove anthropic beta header (#6361)
* feat(together_ai/completion): handle together ai completion calls
* fix: handle list of int / list of list of int for text completion calls
* fix(utils.py): check if base model in bedrock converse model list
Fixes https://github.com/BerriAI/litellm/issues/6003
* test(test_optional_params.py): add unit tests for bedrock optional param mapping
Fixes https://github.com/BerriAI/litellm/issues/6003
* feat(utils.py): enable passing dummy tool call for anthropic/bedrock calls if tool_use blocks exist
Fixes https://github.com/BerriAI/litellm/issues/5388
* fixed an issue with tool use of claude models with anthropic and bedrock (#6013)
* fix(utils.py): handle empty schema for anthropic/bedrock
Fixes https://github.com/BerriAI/litellm/issues/6012
* fix: fix linting errors
* fix: fix linting errors
* fix: fix linting errors
* fix(proxy_cli.py): fix import route for app + health checks path (#6026)
* (testing): Enable testing us.anthropic.claude-3-haiku-20240307-v1:0. (#6018)
* fix(proxy_cli.py): fix import route for app + health checks gettsburg.wav
Fixes https://github.com/BerriAI/litellm/issues/5999
---------
Co-authored-by: David Manouchehri <david.manouchehri@ai.moda>
---------
Co-authored-by: Ved Patwardhan <54766411+vedpatwardhan@users.noreply.github.com>
Co-authored-by: David Manouchehri <david.manouchehri@ai.moda>
* LiteLLM Minor Fixes & Improvements (09/26/2024) (#5925)
* fix(litellm_logging.py): don't initialize prometheus_logger if non premium user
Prevents bad error messages in logs
Fixes https://github.com/BerriAI/litellm/issues/5897
* Add Support for Custom Providers in Vision and Function Call Utils (#5688)
* Add Support for Custom Providers in Vision and Function Call Utils Lookup
* Remove parallel function call due to missing model info param
* Add Unit Tests for Vision and Function Call Changes
* fix-#5920: set header value to string to fix "'int' object has no att… (#5922)
* LiteLLM Minor Fixes & Improvements (09/24/2024) (#5880)
* LiteLLM Minor Fixes & Improvements (09/23/2024) (#5842)
* feat(auth_utils.py): enable admin to allow client-side credentials to be passed
Makes it easier for devs to experiment with finetuned fireworks ai models
* feat(router.py): allow setting configurable_clientside_auth_params for a model
Closes https://github.com/BerriAI/litellm/issues/5843
* build(model_prices_and_context_window.json): fix anthropic claude-3-5-sonnet max output token limit
Fixes https://github.com/BerriAI/litellm/issues/5850
* fix(azure_ai/): support content list for azure ai
Fixes https://github.com/BerriAI/litellm/issues/4237
* fix(litellm_logging.py): always set saved_cache_cost
Set to 0 by default
* fix(fireworks_ai/cost_calculator.py): add fireworks ai default pricing
handles calling 405b+ size models
* fix(slack_alerting.py): fix error alerting for failed spend tracking
Fixes regression with slack alerting error monitoring
* fix(vertex_and_google_ai_studio_gemini.py): handle gemini no candidates in streaming chunk error
* docs(bedrock.md): add llama3-1 models
* test: fix tests
* fix(azure_ai/chat): fix transformation for azure ai calls
* feat(azure_ai/embed): Add azure ai embeddings support
Closes https://github.com/BerriAI/litellm/issues/5861
* fix(azure_ai/embed): enable async embedding
* feat(azure_ai/embed): support azure ai multimodal embeddings
* fix(azure_ai/embed): support async multi modal embeddings
* feat(together_ai/embed): support together ai embedding calls
* feat(rerank/main.py): log source documents for rerank endpoints to langfuse
improves rerank endpoint logging
* fix(langfuse.py): support logging `/audio/speech` input to langfuse
* test(test_embedding.py): fix test
* test(test_completion_cost.py): fix helper util
* fix-#5920: set header value to string to fix "'int' object has no attribute 'encode'"
---------
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
* Revert "fix-#5920: set header value to string to fix "'int' object has no att…" (#5926)
This reverts commit a554ae2695.
* build(model_prices_and_context_window.json): add azure ai cohere rerank model pricing
Enables cost tracking for azure ai cohere rerank models
* fix(litellm_logging.py): fix debug log to be clearer
Closes https://github.com/BerriAI/litellm/issues/5909
* test(test_utils.py): fix test name
* fix(azure_ai/cost_calculator.py): support cost tracking for azure ai rerank models
* fix(azure_ai): fix azure ai base model cost tracking for rerank endpoints
* fix(converse_handler.py): support new llama 3-2 models
Fixes https://github.com/BerriAI/litellm/issues/5901
* fix(litellm_logging.py): ensure response is redacted for standard message logging
Fixes https://github.com/BerriAI/litellm/issues/5890#issuecomment-2378242360
* fix(cost_calculator.py): use 'get_model_info' for cohere rerank cost calculation
allows user to set custom cost for model
* fix(config.yml): fix docker hub auht
* build(config.yml): add docker auth to all tests
* fix(db/create_views.py): fix linting error
* fix(main.py): fix circular import
* fix(azure_ai/__init__.py): fix circular import
* fix(main.py): fix import
* fix: fix linting errors
* test: fix test
* fix(proxy_server.py): pass premium user value on startup
used for prometheus init
---------
Co-authored-by: Cole Murray <colemurray.cs@gmail.com>
Co-authored-by: bravomark <62681807+bravomark@users.noreply.github.com>
* handle streaming for azure ai studio error
* [Perf Proxy] parallel request limiter - use one cache update call (#5932)
* fix parallel request limiter - use one cache update call
* ci/cd run again
* run ci/cd again
* use docker username password
* fix config.yml
* fix config
* fix config
* fix config.yml
* ci/cd run again
* use correct typing for batch set cache
* fix async_set_cache_pipeline
* fix only check user id tpm / rpm limits when limits set
* fix test_openai_azure_embedding_with_oidc_and_cf
* test: fix test
* test(test_rerank.py): fix test
---------
Co-authored-by: Cole Murray <colemurray.cs@gmail.com>
Co-authored-by: bravomark <62681807+bravomark@users.noreply.github.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
* LiteLLM Minor Fixes & Improvements (09/23/2024) (#5842)
* feat(auth_utils.py): enable admin to allow client-side credentials to be passed
Makes it easier for devs to experiment with finetuned fireworks ai models
* feat(router.py): allow setting configurable_clientside_auth_params for a model
Closes https://github.com/BerriAI/litellm/issues/5843
* build(model_prices_and_context_window.json): fix anthropic claude-3-5-sonnet max output token limit
Fixes https://github.com/BerriAI/litellm/issues/5850
* fix(azure_ai/): support content list for azure ai
Fixes https://github.com/BerriAI/litellm/issues/4237
* fix(litellm_logging.py): always set saved_cache_cost
Set to 0 by default
* fix(fireworks_ai/cost_calculator.py): add fireworks ai default pricing
handles calling 405b+ size models
* fix(slack_alerting.py): fix error alerting for failed spend tracking
Fixes regression with slack alerting error monitoring
* fix(vertex_and_google_ai_studio_gemini.py): handle gemini no candidates in streaming chunk error
* docs(bedrock.md): add llama3-1 models
* test: fix tests
* fix(azure_ai/chat): fix transformation for azure ai calls
* feat(azure_ai/embed): Add azure ai embeddings support
Closes https://github.com/BerriAI/litellm/issues/5861
* fix(azure_ai/embed): enable async embedding
* feat(azure_ai/embed): support azure ai multimodal embeddings
* fix(azure_ai/embed): support async multi modal embeddings
* feat(together_ai/embed): support together ai embedding calls
* feat(rerank/main.py): log source documents for rerank endpoints to langfuse
improves rerank endpoint logging
* fix(langfuse.py): support logging `/audio/speech` input to langfuse
* test(test_embedding.py): fix test
* test(test_completion_cost.py): fix helper util
* LiteLLM Minor Fixes & Improvements (09/23/2024) (#5842)
* feat(auth_utils.py): enable admin to allow client-side credentials to be passed
Makes it easier for devs to experiment with finetuned fireworks ai models
* feat(router.py): allow setting configurable_clientside_auth_params for a model
Closes https://github.com/BerriAI/litellm/issues/5843
* build(model_prices_and_context_window.json): fix anthropic claude-3-5-sonnet max output token limit
Fixes https://github.com/BerriAI/litellm/issues/5850
* fix(azure_ai/): support content list for azure ai
Fixes https://github.com/BerriAI/litellm/issues/4237
* fix(litellm_logging.py): always set saved_cache_cost
Set to 0 by default
* fix(fireworks_ai/cost_calculator.py): add fireworks ai default pricing
handles calling 405b+ size models
* fix(slack_alerting.py): fix error alerting for failed spend tracking
Fixes regression with slack alerting error monitoring
* fix(vertex_and_google_ai_studio_gemini.py): handle gemini no candidates in streaming chunk error
* docs(bedrock.md): add llama3-1 models
* test: fix tests
* fix(azure_ai/chat): fix transformation for azure ai calls
* fix(proxy_server.py): use default azure credentials to support azure non-client secret kms
* fix(langsmith.py): raise error if credentials missing
* feat(langsmith.py): support error logging for langsmith + standard logging payload
Fixes https://github.com/BerriAI/litellm/issues/5738
* Fix hardcoding of schema in view check (#5749)
* fix - deal with case when check view exists returns None (#5740)
* Revert "fix - deal with case when check view exists returns None (#5740)" (#5741)
This reverts commit 535228159b.
* test(test_router_debug_logs.py): move to mock response
* Fix hardcoding of schema
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
* fix(proxy_server.py): allow admin to disable ui via `DISABLE_ADMIN_UI` flag
* fix(router.py): fix default model name value
Fixes 55db19a1e4 (r1763712148)
* fix(utils.py): fix unbound variable error
* feat(rerank/main.py): add azure ai rerank endpoints
Closes https://github.com/BerriAI/litellm/issues/5667
* feat(secret_detection.py): Allow configuring secret detection params
Allows admin to control what plugins to run for secret detection. Prevents overzealous secret detection.
* docs(secret_detection.md): add secret detection guardrail docs
* fix: fix linting errors
* fix - deal with case when check view exists returns None (#5740)
* Revert "fix - deal with case when check view exists returns None (#5740)" (#5741)
This reverts commit 535228159b.
* Litellm fix router testing (#5748)
* test: fix testing - azure changed content policy error logic
* test: fix tests to use mock responses
* test(test_image_generation.py): handle api instability
* test(test_image_generation.py): handle azure api instability
* fix(utils.py): fix unbounded variable error
* fix(utils.py): fix unbounded variable error
* test: refactor test to use mock response
* test: mark flaky azure tests
* Bump next from 14.1.1 to 14.2.10 in /ui/litellm-dashboard (#5753)
Bumps [next](https://github.com/vercel/next.js) from 14.1.1 to 14.2.10.
- [Release notes](https://github.com/vercel/next.js/releases)
- [Changelog](https://github.com/vercel/next.js/blob/canary/release.js)
- [Commits](https://github.com/vercel/next.js/compare/v14.1.1...v14.2.10)
---
updated-dependencies:
- dependency-name: next
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
* [Fix] o1-mini causes pydantic warnings on `reasoning_tokens` (#5754)
* add requester_metadata in standard logging payload
* log requester_metadata in metadata
* use StandardLoggingPayload for logging
* docs StandardLoggingPayload
* fix import
* include standard logging object in failure
* add test for requester metadata
* handle completion_tokens_details
* add test for completion_tokens_details
* [Feat-Proxy-DataDog] Log Redis, Postgres Failure events on DataDog (#5750)
* dd - start tracking redis status on dd
* add async_service_succes_hook / failure hook in custom logger
* add async_service_failure_hook
* log service failures on dd
* fix import error
* add test for redis errors / warning
* [Fix] Router/ Proxy - Tag Based routing, raise correct error when no deployments found and tag filtering is on (#5745)
* fix tag routing - raise correct error when no model with tag based routing
* fix error string from tag based routing
* test router tag based routing
* raise 401 error when no tags avialable for deploymen
* linting fix
* [Feat] Log Request metadata on gcs bucket logging (#5743)
* add requester_metadata in standard logging payload
* log requester_metadata in metadata
* use StandardLoggingPayload for logging
* docs StandardLoggingPayload
* fix import
* include standard logging object in failure
* add test for requester metadata
* fix(litellm_logging.py): fix logging message
* fix(rerank_api/main.py): fix linting errors
* fix(custom_guardrails.py): maintain backwards compatibility for older guardrails
* fix(rerank_api/main.py): fix cost tracking for rerank endpoints
---------
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: steffen-sbt <148480574+steffen-sbt@users.noreply.github.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
