* 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 use new format for Cohere config
* fix base llm http handler
* Litellm code qa common config (#7116)
* 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
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
* use base transform helpers
* use base_llm_http_handler for cohere
* working cohere using base llm handler
* add async cohere chat completion support on base handler
* fix completion code
* working sync cohere stream
* add async support cohere_chat
* fix types get_model_response_iterator
* async / sync tests cohere
* feat cohere using base llm class
* fix linting errors
* fix _abc error
* add cohere params to transformation
* remove old cohere file
* fix type error
* fix merge conflicts
* fix cohere merge conflicts
* fix linting error
* fix litellm.llms.custom_httpx.http_handler.HTTPHandler.post
* fix passing cohere specific params
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
* 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
* use 1 file for AnthropicPassthroughLoggingHandler
* add support for anthropic streaming usage tracking
* ci/cd run again
* fix - add real streaming for anthropic pass through
* remove unused function stream_response
* working anthropic streaming logging
* fix code quality
* fix use 1 file for vertex success handler
* use helper for _handle_logging_vertex_collected_chunks
* enforce vertex streaming to use sse for streaming
* test test_basic_vertex_ai_pass_through_streaming_with_spendlog
* fix type hints
* add comment
* fix linting
* add pass through logging unit testing
* 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(ollama.py): fix get model info request
Fixes https://github.com/BerriAI/litellm/issues/6703
* feat(anthropic/chat/transformation.py): support passing user id to anthropic via openai 'user' param
* docs(anthropic.md): document all supported openai params for anthropic
* test: fix tests
* fix: fix tests
* feat(jina_ai/): add rerank support
Closes https://github.com/BerriAI/litellm/issues/6691
* test: handle service unavailable error
* fix(handler.py): refactor together ai rerank call
* test: update test to handle overloaded error
* test: fix test
* Litellm router trace (#6742)
* feat(router.py): add trace_id to parent functions - allows tracking retry/fallbacks
* feat(router.py): log trace id across retry/fallback logic
allows grouping llm logs for the same request
* test: fix tests
* fix: fix test
* fix(transformation.py): only set non-none stop_sequences
* Litellm router disable fallbacks (#6743)
* bump: version 1.52.6 → 1.52.7
* feat(router.py): enable dynamically disabling fallbacks
Allows for enabling/disabling fallbacks per key
* feat(litellm_pre_call_utils.py): support setting 'disable_fallbacks' on litellm key
* test: fix test
* fix(exception_mapping_utils.py): map 'model is overloaded' to internal server error
* test: handle gemini error
* test: fix test
* fix: new run
* fix(__init__.py): add 'watsonx_text' as mapped llm api route
Fixes https://github.com/BerriAI/litellm/issues/6663
* fix(opentelemetry.py): fix passing parallel tool calls to otel
Fixes https://github.com/BerriAI/litellm/issues/6677
* refactor(test_opentelemetry_unit_tests.py): create a base set of unit tests for all logging integrations - test for parallel tool call handling
reduces bugs in repo
* fix(__init__.py): update provider-model mapping to include all known provider-model mappings
Fixes https://github.com/BerriAI/litellm/issues/6669
* feat(anthropic): support passing document in llm api call
* docs(anthropic.md): add pdf anthropic call to docs + expose new 'supports_pdf_input' function
* fix(factory.py): fix linting error
* refactor: move gemini translation logic inside the transformation.py file
easier to isolate the gemini translation logic
* fix(gemini-transformation): support multiple tool calls in message body
Merges https://github.com/BerriAI/litellm/pull/6487/files
* test(test_vertex.py): add remaining tests from https://github.com/BerriAI/litellm/pull/6487
* fix(gemini-transformation): return tool calls for multiple tool calls
* fix: support passing logprobs param for vertex + gemini
* feat(vertex_ai): add logprobs support for gemini calls
* fix(anthropic/chat/transformation.py): fix disable parallel tool use flag
* fix: fix linting error
* fix(_logging.py): log stacktrace information in json logs
Closes https://github.com/BerriAI/litellm/issues/6497
* fix(utils.py): fix mem leak for async stream + completion
Uses a global executor pool instead of creating a new thread on each request
Fixes https://github.com/BerriAI/litellm/issues/6404
* fix(factory.py): handle tool call + content in assistant message for bedrock
* fix: fix import
* fix(factory.py): maintain support for content as a str in assistant response
* fix: fix import
* test: cleanup test
* fix(vertex_and_google_ai_studio/): return none for content if no str value
* test: retry flaky tests
* (UI) Fix viewing members, keys in a team + added testing (#6514)
* 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>
* ui new build
* Add retry strat (#6520)
Signed-off-by: dbczumar <corey.zumar@databricks.com>
* (fix) slack alerting - don't spam the failed cost tracking alert for the same model (#6543)
* fix use failing_model as cache key for failed_tracking_alert
* fix use standard logging payload for getting response cost
* fix kwargs.get("response_cost")
* fix getting response cost
* (feat) add XAI ChatCompletion Support (#6373)
* init commit for XAI
* add full logic for xai chat completion
* test_completion_xai
* docs xAI
* add xai/grok-beta
* test_xai_chat_config_get_openai_compatible_provider_info
* test_xai_chat_config_map_openai_params
* add xai streaming test
---------
Signed-off-by: dbczumar <corey.zumar@databricks.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Corey Zumar <39497902+dbczumar@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>
* 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
* 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>
* 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(utils.py): return citations for perplexity streaming
Fixes https://github.com/BerriAI/litellm/issues/5535
* fix(anthropic/chat.py): support fallbacks for anthropic streaming (#5542)
* fix(anthropic/chat.py): support fallbacks for anthropic streaming
Fixes https://github.com/BerriAI/litellm/issues/5512
* fix(anthropic/chat.py): use module level http client if none given (prevents early client closure)
* fix: fix linting errors
* fix(http_handler.py): fix raise_for_status error handling
* test: retry flaky test
* fix otel type
* fix(bedrock/embed): fix error raising
* test(test_openai_batches_and_files.py): skip azure batches test (for now) quota exceeded
* fix(test_router.py): skip azure batch route test (for now) - hit batch quota limits
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
* All `model_group_alias` should show up in `/models`, `/model/info` , `/model_group/info` (#5539)
* fix(router.py): support returning model_alias model names in `/v1/models`
* fix(proxy_server.py): support returning model alias'es on `/model/info`
* feat(router.py): support returning model group alias for `/model_group/info`
* fix(proxy_server.py): fix linting errors
* fix(proxy_server.py): fix linting errors
* build(model_prices_and_context_window.json): add amazon titan text premier pricing information
Closes https://github.com/BerriAI/litellm/issues/5560
* feat(litellm_logging.py): log standard logging response object for pass through endpoints. Allows bedrock /invoke agent calls to be correctly logged to langfuse + s3
* fix(success_handler.py): fix linting error
* fix(success_handler.py): fix linting errors
* fix(team_endpoints.py): Allows admin to update team member budgets
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
* Minor IAM AWS OIDC Improvements (#5246)
* AWS IAM: Temporary tokens are valid across all regions after being issued, so it is wasteful to request one for each region.
* AWS IAM: Include an inline policy, to help reduce misuse of overly permissive IAM roles.
* (test_bedrock_completion.py): Ensure we are testing cross AWS region OIDC flow.
* fix(router.py): log rejected requests
Fixes https://github.com/BerriAI/litellm/issues/5498
* refactor: don't use verbose_logger.exception, if exception is raised
User might already have handling for this. But alerting systems in prod will raise this as an unhandled error.
* fix(datadog.py): support setting datadog source as an env var
Fixes https://github.com/BerriAI/litellm/issues/5508
* docs(logging.md): add dd_source to datadog docs
* fix(proxy_server.py): expose `/customer/list` endpoint for showing all customers
* (bedrock): Fix usage with Cloudflare AI Gateway, and proxies in general. (#5509)
* feat(anthropic.py): support 'cache_control' param for content when it is a string
* Revert "(bedrock): Fix usage with Cloudflare AI Gateway, and proxies in gener…" (#5519)
This reverts commit 3fac0349c2.
* refactor: ci/cd run again
---------
Co-authored-by: David Manouchehri <david.manouchehri@ai.moda>
* feat(proxy/_types.py): add lago billing to callbacks ui
Closes https://github.com/BerriAI/litellm/issues/5472
* fix(anthropic.py): return anthropic prompt caching information
Fixes https://github.com/BerriAI/litellm/issues/5364
* feat(bedrock/chat.py): support 'json_schema' for bedrock models
Closes https://github.com/BerriAI/litellm/issues/5434
* fix(bedrock/embed/embeddings.py): support async embeddings for amazon titan models
* fix: linting fixes
* fix: handle key errors
* fix(bedrock/chat.py): fix bedrock ai21 streaming object
* feat(bedrock/embed): support bedrock embedding optional params
* fix(databricks.py): fix usage chunk
* fix(internal_user_endpoints.py): apply internal user defaults, if user role updated
Fixes issue where user update wouldn't apply defaults
* feat(slack_alerting.py): provide multiple slack channels for a given alert type
multiple channels might be interested in receiving an alert for a given type
* docs(alerting.md): add multiple channel alerting to docs
* fix(utils.py): support 'drop_params' for embedding requests
Fixes https://github.com/BerriAI/litellm/issues/5444
* feat(anthropic/cost_calculation.py): Support calculating cost for prompt caching on anthropic
* feat(types/utils.py): allows us to migrate to openai's equivalent, once that comes out
* fix: fix linting errors
* test: mark flaky test
