* test: move test to just checking async
* fix(transformation.py): handle function call with no schema
* fix(utils.py): handle pydantic base model in message tool calls
Fix https://github.com/BerriAI/litellm/issues/9321
* fix(vertex_and_google_ai_studio.py): handle tools=[]
Fixes https://github.com/BerriAI/litellm/issues/9080
* test: remove max token restriction
* test: fix basic test
* fix(get_supported_openai_params.py): fix check
* fix(converse_transformation.py): support fake streaming for meta.llama3-3-70b-instruct-v1:0
* fix: fix test
* fix: parse out empty dictionary on dbrx streaming + tool calls
* fix(handle-'strict'-param-when-calling-fireworks-ai): fireworks ai does not support 'strict' param
* fix: fix ruff check
'
* fix: handle no strict in function
* fix: revert bedrock change - handle in separate PR
* 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(databricks/chat/transformation.py): add tools and 'tool_choice' param support
Closes https://github.com/BerriAI/litellm/issues/7788
* refactor: cleanup redundant file
* test: mark flaky test
* test: mark all parallel request tests as flaky
* fix(streaming_chunk_builder_utils.py): add test for groq tool calling + streaming + combine chunks
Addresses https://github.com/BerriAI/litellm/issues/7621
* fix(streaming_utils.py): fix modelresponseiterator for openai like chunk parser
ensures chunk parser uses the correct tool call id when translating the chunk
Fixes https://github.com/BerriAI/litellm/issues/7621
* build(model_hub.tsx): display cost pricing on model hub
* build(model_hub.tsx): show cost per token pricing + complete model information
* fix(types/utils.py): fix usage object handling
* 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
* refactor(fireworks_ai/): inherit from openai like base config
refactors fireworks ai to use a common config
* test: fix import in test
* refactor(watsonx/): refactor watsonx to use llm base config
refactors chat + completion routes to base config path
* fix: fix linting error
* refactor: inherit base llm config for oai compatible routes
* test: fix test
* test: fix test
* feat(base_llm): initial commit for common base config class
Addresses code qa critique https://github.com/andrewyng/aisuite/issues/113#issuecomment-2512369132
* feat(base_llm/): add transform request/response abstract methods to base config class
* feat(cohere-+-clarifai): refactor integrations to use common base config class
* fix: fix linting errors
* refactor(anthropic/): move anthropic + vertex anthropic to use base config
* test: fix xai test
* test: fix tests
* fix: fix linting errors
* test: comment out WIP test
* fix(transformation.py): fix is pdf used check
* fix: fix linting error
* 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(anthropic/chat/transformation.py): add json schema as values: json_schema
fixes passing pydantic obj to anthropic
Fixes https://github.com/BerriAI/litellm/issues/6766
* (feat): Add timestamp_granularities parameter to transcription API (#6457)
* Add timestamp_granularities parameter to transcription API
* add param to the local test
* fix(databricks/chat.py): handle max_retries optional param handling for openai-like calls
Fixes issue with calling finetuned vertex ai models via databricks route
* build(ui/): add team admins via proxy ui
* fix: fix linting error
* test: fix test
* docs(vertex.md): refactor docs
* test: handle overloaded anthropic model error
* test: remove duplicate test
* test: fix test
* test: update test to handle model overloaded error
---------
Co-authored-by: Show <35062952+BrunooShow@users.noreply.github.com>
* fix(streaming_handler.py): save finish_reasons which might show up mid-stream (store last received one)
Fixes https://github.com/BerriAI/litellm/issues/6104
* refactor: add readme to litellm_core_utils/
make it easier to navigate
* fix(team_endpoints.py): return team id + object for invalid team in `/team/list`
* fix(streaming_handler.py): remove import
* fix(pattern_match_deployments.py): default to user input if unable to map based on wildcards (#6646)
* fix(pattern_match_deployments.py): default to user input if unable to… (#6632)
* fix(pattern_match_deployments.py): default to user input if unable to map based on wildcards
* test: fix test
* test: reset test name
* test: update conftest to reload proxy server module between tests
* ci(config.yml): move langfuse out of local_testing
reduce ci/cd time
* ci(config.yml): cleanup langfuse ci/cd tests
* fix: update test to not use global proxy_server app module
* ci: move caching to a separate test pipeline
speed up ci pipeline
* test: update conftest to check if proxy_server attr exists before reloading
* build(conftest.py): don't block on inability to reload proxy_server
* ci(config.yml): update caching unit test filter to work on 'cache' keyword as well
* fix(encrypt_decrypt_utils.py): use function to get salt key
* test: mark flaky test
* test: handle anthropic overloaded errors
* refactor: create separate ci/cd pipeline for proxy unit tests
make ci/cd faster
* ci(config.yml): add litellm_proxy_unit_testing to build_and_test jobs
* ci(config.yml): generate prisma binaries for proxy unit tests
* test: readd vertex_key.json
* ci(config.yml): remove `-s` from proxy_unit_test cmd
speed up test
* ci: remove any 'debug' logging flag
speed up ci pipeline
* test: fix test
* test(test_braintrust.py): rerun
* test: add delay for braintrust test
* chore: comment for maritalk (#6607)
* Update gpt-4o-2024-08-06, and o1-preview, o1-mini models in model cost map (#6654)
* Adding supports_response_schema to gpt-4o-2024-08-06 models
* o1 models do not support vision
---------
Co-authored-by: Emerson Gomes <emerson.gomes@thalesgroup.com>
* (QOL improvement) add unit testing for all static_methods in litellm_logging.py (#6640)
* add unit testing for standard logging payload
* unit testing for static methods in litellm_logging
* add code coverage check for litellm_logging
* litellm_logging_code_coverage
* test_get_final_response_obj
* fix validate_redacted_message_span_attributes
* test validate_redacted_message_span_attributes
* (feat) log error class, function_name on prometheus service failure hook + only log DB related failures on DB service hook (#6650)
* 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
* Update several Azure AI models in model cost map (#6655)
* Adding Azure Phi 3/3.5 models to model cost map
* Update gpt-4o-mini models
* Adding missing Azure Mistral models to model cost map
* Adding Azure Llama3.2 models to model cost map
* Fix Gemini-1.5-flash pricing
* Fix Gemini-1.5-flash output pricing
* Fix Gemini-1.5-pro prices
* Fix Gemini-1.5-flash output prices
* Correct gemini-1.5-pro prices
* Correction on Vertex Llama3.2 entry
---------
Co-authored-by: Emerson Gomes <emerson.gomes@thalesgroup.com>
* fix(streaming_handler.py): fix linting error
* test: remove duplicate test
causes gemini ratelimit error
---------
Co-authored-by: nobuo kawasaki <nobu007@users.noreply.github.com>
Co-authored-by: Emerson Gomes <emerson.gomes@gmail.com>
Co-authored-by: Emerson Gomes <emerson.gomes@thalesgroup.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
* feat: initial commit for watsonx chat endpoint support
Closes https://github.com/BerriAI/litellm/issues/6562
* feat(watsonx/chat/handler.py): support tool calling for watsonx
Closes https://github.com/BerriAI/litellm/issues/6562
* fix(streaming_utils.py): return empty chunk instead of failing if streaming value is invalid dict
ensures streaming works for ibm watsonx
* fix(openai_like/chat/handler.py): ensure asynchttphandler is passed correctly for openai like calls
* fix: ensure exception mapping works well for watsonx calls
* fix(openai_like/chat/handler.py): handle async streaming correctly
* feat(main.py): Make it clear when a user is passing an invalid message
add validation for user content message
Closes https://github.com/BerriAI/litellm/issues/6565
* fix: cleanup
* fix(utils.py): loosen validation check, to just make sure content types are valid
make litellm robust to future content updates
* fix: fix linting erro
* fix: fix linting errors
* fix(utils.py): make validation check more flexible
* test: handle langfuse list index out of range error
* Litellm dev 11 02 2024 (#6561)
* 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]
* bump: version 1.51.4 → 1.51.5
* build(deps): bump cookie and express in /docs/my-website (#6566)
Bumps [cookie](https://github.com/jshttp/cookie) and [express](https://github.com/expressjs/express). These dependencies needed to be updated together.
Updates `cookie` from 0.6.0 to 0.7.1
- [Release notes](https://github.com/jshttp/cookie/releases)
- [Commits](https://github.com/jshttp/cookie/compare/v0.6.0...v0.7.1)
Updates `express` from 4.20.0 to 4.21.1
- [Release notes](https://github.com/expressjs/express/releases)
- [Changelog](https://github.com/expressjs/express/blob/4.21.1/History.md)
- [Commits](https://github.com/expressjs/express/compare/4.20.0...4.21.1)
---
updated-dependencies:
- dependency-name: cookie
dependency-type: indirect
- dependency-name: express
dependency-type: indirect
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
* docs(virtual_keys.md): update Dockerfile reference (#6554)
Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
* (proxy fix) - call connect on prisma client when running setup (#6534)
* critical fix - call connect on prisma client when running setup
* fix test_proxy_server_prisma_setup
* fix test_proxy_server_prisma_setup
* Add 3.5 haiku (#6588)
* feat: add claude-3-5-haiku-20241022 entries
* feat: add claude-3-5-haiku-20241022 and vertex_ai/claude-3-5-haiku@20241022 models
* add missing entries, remove vision
* remove image token costs
* Litellm perf improvements 3 (#6573)
* 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
* build: fix map
* build: fix map
* build: fix json for model map
* Litellm dev 11 02 2024 (#6561)
* 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]
* Litellm perf improvements 3 (#6573)
* 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 ImageObject conversion (#6584)
* (fix) litellm.text_completion raises a non-blocking error on simple usage (#6546)
* unit test test_huggingface_text_completion_logprobs
* fix return TextCompletionHandler convert_chat_to_text_completion
* fix hf rest api
* fix test_huggingface_text_completion_logprobs
* fix linting errors
* fix importLiteLLMResponseObjectHandler
* fix test for LiteLLMResponseObjectHandler
* fix test text completion
* fix allow using 15 seconds for premium license check
* testing fix bedrock deprecated cohere.command-text-v14
* (feat) add `Predicted Outputs` for OpenAI (#6594)
* bump openai to openai==1.54.0
* add 'prediction' param
* testing fix bedrock deprecated cohere.command-text-v14
* test test_openai_prediction_param.py
* test_openai_prediction_param_with_caching
* doc Predicted Outputs
* doc Predicted Output
* (fix) Vertex Improve Performance when using `image_url` (#6593)
* fix transformation vertex
* test test_process_gemini_image
* test_image_completion_request
* testing fix - bedrock has deprecated cohere.command-text-v14
* fix vertex pdf
* bump: version 1.51.5 → 1.52.0
* fix(lowest_tpm_rpm_routing.py): fix parallel rate limit check (#6577)
* fix(lowest_tpm_rpm_routing.py): fix parallel rate limit check
* fix(lowest_tpm_rpm_v2.py): return headers in correct format
* test: update test
* build(deps): bump cookie and express in /docs/my-website (#6566)
Bumps [cookie](https://github.com/jshttp/cookie) and [express](https://github.com/expressjs/express). These dependencies needed to be updated together.
Updates `cookie` from 0.6.0 to 0.7.1
- [Release notes](https://github.com/jshttp/cookie/releases)
- [Commits](https://github.com/jshttp/cookie/compare/v0.6.0...v0.7.1)
Updates `express` from 4.20.0 to 4.21.1
- [Release notes](https://github.com/expressjs/express/releases)
- [Changelog](https://github.com/expressjs/express/blob/4.21.1/History.md)
- [Commits](https://github.com/expressjs/express/compare/4.20.0...4.21.1)
---
updated-dependencies:
- dependency-name: cookie
dependency-type: indirect
- dependency-name: express
dependency-type: indirect
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
* docs(virtual_keys.md): update Dockerfile reference (#6554)
Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
* (proxy fix) - call connect on prisma client when running setup (#6534)
* critical fix - call connect on prisma client when running setup
* fix test_proxy_server_prisma_setup
* fix test_proxy_server_prisma_setup
* Add 3.5 haiku (#6588)
* feat: add claude-3-5-haiku-20241022 entries
* feat: add claude-3-5-haiku-20241022 and vertex_ai/claude-3-5-haiku@20241022 models
* add missing entries, remove vision
* remove image token costs
* Litellm perf improvements 3 (#6573)
* 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
* build: fix map
* build: fix map
* build: fix json for model map
* test: remove eol model
* fix(proxy_server.py): fix db config loading logic
* fix(proxy_server.py): fix order of config / db updates, to ensure fields not overwritten
* test: skip test if required env var is missing
* test: fix test
---------
Signed-off-by: dependabot[bot] <support@github.com>
Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: paul-gauthier <69695708+paul-gauthier@users.noreply.github.com>
* test: mark flaky test
* test: handle anthropic api instability
* test: update test
* test: bump num retries on langfuse tests - their api is quite bad
---------
Signed-off-by: dependabot[bot] <support@github.com>
Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: paul-gauthier <69695708+paul-gauthier@users.noreply.github.com>
* feat(litellm_logging.py): update standard logging payload to include debug information for cost failures
Also includes fixes for cohere rerank cost tracking + databricks llama2 model cost tracking
Easier to repro cost failures and improve reliability in prod
* fix(proxy_server.py): emit cost failure debug info for slack alerting
Improves debug information for cost tracking failures, on slack alerting
* add max_completion_tokens
* add max_completion_tokens
* add max_completion_tokens support for OpenAI models
* add max_completion_tokens param
* add max_completion_tokens for bedrock converse models
* add test for converse maxTokens
* fix openai o1 param mapping test
* move test optional params
* add max_completion_tokens for anthropic api
* fix conftest
* add max_completion tokens for vertex ai partner models
* add max_completion_tokens for fireworks ai
* add max_completion_tokens for hf rest api
* add test for param mapping
* add param mapping for vertex, gemini + testing
* predibase is the most unstable and unusable llm api in prod, can't handle our ci/cd
* add max_completion_tokens to openai supported params
* fix fireworks ai param mapping
* fix(cost_calculator.py): move to debug for noisy warning message on cost calculation error
Fixes https://github.com/BerriAI/litellm/issues/5610
* fix(databricks/cost_calculator.py): Handles model name issues for databricks models
* fix(main.py): fix stream chunk builder for multiple tool calls
Fixes https://github.com/BerriAI/litellm/issues/5591
* fix: correctly set user_alias when passed in
Fixes https://github.com/BerriAI/litellm/issues/5612
* fix(types/utils.py): allow passing role for message object
https://github.com/BerriAI/litellm/issues/5621
* fix(litellm_logging.py): Fix langfuse logging across multiple projects
Fixes issue where langfuse logger was re-using the old logging object
* feat(proxy/_types.py): support adding key-based tags for tag-based routing
Enable tag based routing at key-level
* fix(proxy/_types.py): fix inheritance
* test(test_key_generate_prisma.py): fix test
* test: fix test
* fix(litellm_logging.py): return used callback object
* fix(main.py): pass default azure api version as alternative in completion call
Fixes api error caused due to api version
Closes https://github.com/BerriAI/litellm/issues/5584
* Fixed gemini-1.5-flash pricing (#5590)
* add /key/list endpoint
* bump: version 1.44.21 → 1.44.22
* docs architecture
* Fixed gemini-1.5-flash pricing
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
* fix(bedrock/chat.py): fix converse api stop sequence param mapping
Fixes https://github.com/BerriAI/litellm/issues/5592
* fix(databricks/cost_calculator.py): handle databricks model name changes
Fixes https://github.com/BerriAI/litellm/issues/5597
* fix(azure.py): support azure api version 2024-08-01-preview
Closes https://github.com/BerriAI/litellm/issues/5377
* fix(proxy/_types.py): allow dev keys to call cohere /rerank endpoint
Fixes issue where only admin could call rerank endpoint
* fix(azure.py): check if model is gpt-4o
* fix(proxy/_types.py): support /v1/rerank on non-admin routes as well
* fix(cost_calculator.py): fix split on `/` logic in cost calculator
---------
Co-authored-by: F1bos <44951186+F1bos@users.noreply.github.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
