* fix(utils.py): don't pass 'anthropic-beta' header to vertex - will cause request to fail
* fix(utils.py): add flag to allow user to disable filtering invalid headers
ensure user can control behaviour
* style(utils.py): cleanup message
* test(test_utils.py): add unit test to cover invalid header filtering
* fix(proxy_server.py): fix custom openapi schema generation
* fix(utils.py): pass extra headers if set
* fix(main.py): fix image variation to use 'client' param
* fix(proxy_server.py): fix get model info when litellm_model_id is set
Fixes https://github.com/BerriAI/litellm/issues/7873
* test(test_models.py): add test to ensure get model info on specific deployment has same value as all model info
Fixes https://github.com/BerriAI/litellm/issues/7873
* fix(usage.tsx): make model analytics free
Fixes @iqballx's feedback
* fix(fix(invoke_handler.py):-fix-bedrock-error-chunk-parsing): return correct bedrock status code and error message if chunk in stream
Improves bedrock stream error handling
* fix(proxy_server.py): fix linting errors
* test(test_auth_checks.py): remove redundant test
* fix(proxy_server.py): fix linting errors
* test: fix flaky test
* test: fix test
* fix(gemini/): support gemini 'frequency_penalty' and 'presence_penalty'
Closes https://github.com/BerriAI/litellm/issues/7748
* feat(proxy_server.py): new env var to disable prisma health check on startup
* test: fix test
* 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
* build(model_prices_and_context_window.json): add azure o1 pricing
Closes https://github.com/BerriAI/litellm/issues/7712
* refactor: replace regex with string method for whitespace check in stop-sequences handling (#7713)
* Allows overriding keep_alive time in ollama (#7079)
* Allows overriding keep_alive time in ollama
* Also adds to ollama_chat
* Adds some info on the docs about this parameter
* fix: together ai warning (#7688)
Co-authored-by: Carl Senze <carl.senze@aleph-alpha.com>
* fix(proxy_server.py): handle config containing thread locked objects when using get_config_state
* fix(proxy_server.py): add exception to debug
* build(model_prices_and_context_window.json): update 'supports_vision' for azure o1
---------
Co-authored-by: Wolfram Ravenwolf <52386626+WolframRavenwolf@users.noreply.github.com>
Co-authored-by: Regis David Souza Mesquita <github@rdsm.dev>
Co-authored-by: Carl <45709281+capsenz@users.noreply.github.com>
Co-authored-by: Carl Senze <carl.senze@aleph-alpha.com>
* fix(vertex_ai/gemini/transformation.py): handle 'http://' in gemini process url
* refactor(router.py): refactor '_prompt_management_factory' to use logging obj get_chat_completion logic
deduplicates code
* fix(litellm_logging.py): update 'get_chat_completion_prompt' to update logging object messages
* docs(prompt_management.md): update prompt management to be in beta
given feedback - this still needs to be revised (e.g. passing in user message, not ignoring)
* refactor(prompt_management_base.py): introduce base class for prompt management
allows consistent behaviour across prompt management integrations
* feat(prompt_management_base.py): support adding client message to template message + refactor langfuse prompt management to use prompt management base
* fix(litellm_logging.py): log prompt id + prompt variables to langfuse if set
allows tracking what prompt was used for what purpose
* feat(litellm_logging.py): log prompt management metadata in standard logging payload + use in langfuse
allows logging prompt id / prompt variables to langfuse
* test: fix test
* fix(router.py): cleanup unused imports
* fix: fix linting error
* fix: fix trace param typing
* fix: fix linting errors
* fix: fix code qa check
- Ensured that `before` and `after` parameters are only passed when provided to avoid AttributeError.
- Implemented safe access using default values for `before` and `after` to prevent missing attribute issues.
- Added consistent handling of `order` and `limit` to improve flexibility and robustness in API calls.
* fix(redact_messages.py): fix redact messages for non-model response input to be dictionary
fixes issue with otel logging when message redaction is enabled
* fix(proxy_server.py): fix langfuse key leak in exception string
* test: fix test
* test: fix test
* test: fix tests
* fix(internal_user_endpoints.py): fix team list sort - handle team_alias being set + None
* fix(key_management_endpoints.py): allow team admin to create key for member via admin ui
Fixes https://github.com/BerriAI/litellm/issues/7482
* fix(proxy_server.py): allow querying info on specific model group via `/model_group/info`
allows client-side user to get model info from proxy
* fix(proxy_server.py): add docstring on `/model_group/info` showing how to filter by model name
* test(test_proxy_utils.py): add unit test for returning model group info filtered
* fix(proxy_server.py): fix query param
* fix(test_Get_model_info.py): handle no whitelisted bedrock modells
* fix(langfuse_prompt_management.py): migrate dynamic logging to langfuse custom logger compatible class
* fix(langfuse_prompt_management.py): support failure callback logging to langfuse as well
* feat(proxy_server.py): support setting custom tokenizer on config.yaml
Allows customizing value for `/utils/token_counter`
* fix(proxy_server.py): fix linting errors
* test: skip if file not found
* style: cleanup unused import
* docs(configs.md): add docs on setting custom tokenizer
* 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(utils.py): default custom_llm_provider=None for 'supports_response_schema'
Closes https://github.com/BerriAI/litellm/issues/7397
* refactor(langfuse/): call langfuse logger inside customlogger compatible langfuse class, refactor langfuse logger to use verbose_logger.debug instead of print_verbose
* refactor(litellm_pre_call_utils.py): move config based team callbacks inside dynamic team callback logic
enables simpler unit testing for config-based team callbacks
* fix(proxy/_types.py): handle teamcallbackmetadata - none values
drop none values if present. if all none, use default dict to avoid downstream errors
* test(test_proxy_utils.py): add unit test preventing future issues - asserts team_id in config state not popped off across calls
Fixes https://github.com/BerriAI/litellm/issues/6787
* fix(langfuse_prompt_management.py): add success + failure logging event support
* fix: fix linting error
* test: fix test
* test: fix test
* test: override o1 prompt caching - openai currently not working
* test: fix test
* feat(guardrails_endpoint.py): new `/guardrails/list` endpoint
Allow users to view what the available guardrails are
* docs: document new `/guardrails/list` endpoint
* docs(enterprise.md): update docs
* fix(openai/transcription/handler.py): support cost tracking on vtt + srt formats
* fix(openai/transcriptions/handler.py): default to 'verbose_json' response format if 'text' or 'json' response_format received. ensures 'duration' param is received for all audio transcription requests
* fix: fix linting errors
* fix: remove unused import
* 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
* fix(proxy_server.py): only update k,v pair if v is not empty/null
Fixes https://github.com/BerriAI/litellm/issues/6787
* test(test_router.py): cleanup duplicate calls
* test: add new test stream options drop params test
* test: update optional params / stream options test to test for vertex ai mistral route specifically
Addresses https://github.com/BerriAI/litellm/issues/7309
* fix(proxy_server.py): fix linting errors
* fix: fix linting errors
* 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(main.py): fix retries being multiplied when using openai sdk
Closes https://github.com/BerriAI/litellm/pull/7130
* docs(prompt_management.md): add langfuse prompt management doc
* feat(team_endpoints.py): allow teams to add their own models
Enables teams to call their own finetuned models via the proxy
* test: add better enforcement check testing for `/model/new` now that teams can add their own models
* docs(team_model_add.md): tutorial for allowing teams to add their own models
* test: fix test
* 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(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(cost_calculator.py): move to using `.get_model_info()` for cost per token calculations
ensures cost tracking is reliable - handles edge cases of parsing model cost map
* build(model_prices_and_context_window.json): add 'supports_response_schema' for select tgai models
Fixes https://github.com/BerriAI/litellm/pull/7037#discussion_r1872157329
* build(model_prices_and_context_window.json): remove 'pdf input' and 'vision' support from nova micro in model map
Bedrock docs indicate no support for micro - https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference-supported-models-features.html
* fix(converse_transformation.py): support amazon nova tool use
* fix(opentelemetry): Add missing LLM request type attribute to spans (#7041)
* feat(opentelemetry): add LLM request type attribute to spans
* lint
* fix: curl usage (#7038)
curl -d, --data <data> is lowercase d
curl -D, --dump-header <filename> is uppercase D
references:
https://curl.se/docs/manpage.html#-dhttps://curl.se/docs/manpage.html#-D
* fix(spend_tracking.py): handle empty 'id' in model response - when creating spend log
Fixes https://github.com/BerriAI/litellm/issues/7023
* fix(streaming_chunk_builder.py): handle initial id being empty string
Fixes https://github.com/BerriAI/litellm/issues/7023
* fix(anthropic_passthrough_logging_handler.py): add end user cost tracking for anthropic pass through endpoint
* docs(pass_through/): refactor docs location + add table on supported features for pass through endpoints
* feat(anthropic_passthrough_logging_handler.py): support end user cost tracking via anthropic sdk
* docs(anthropic_completion.md): add docs on passing end user param for cost tracking on anthropic sdk
* fix(litellm_logging.py): use standard logging payload if present in kwargs
prevent datadog logging error for pass through endpoints
* docs(bedrock.md): add rerank api usage example to docs
* bugfix/change dummy tool name format (#7053)
* fix viewing keys (#7042)
* ui new build
* build(model_prices_and_context_window.json): add bedrock region models to model cost map (#7044)
* bye (#6982)
* (fix) litellm router.aspeech (#6962)
* doc Migrating Databases
* fix aspeech on router
* test_audio_speech_router
* test_audio_speech_router
* docs show supported providers on batches api doc
* change dummy tool name format
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
Co-authored-by: yujonglee <yujonglee.dev@gmail.com>
* fix: fix linting errors
* test: update test
* fix(litellm_logging.py): fix pass through check
* fix(test_otel_logging.py): fix test
* fix(cost_calculator.py): update handling for cost per second
* fix(cost_calculator.py): fix cost check
* test: fix test
* (fix) adding public routes when using custom header (#7045)
* 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
* build: update ui build
---------
Co-authored-by: Doron Kopit <83537683+doronkopit5@users.noreply.github.com>
Co-authored-by: lloydchang <lloydchang@gmail.com>
Co-authored-by: hgulersen <haymigulersen@gmail.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: yujonglee <yujonglee.dev@gmail.com>
* 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(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
