* fix(azure.py): ensure max_retries=0 is respected
Fixes https://github.com/BerriAI/litellm/issues/6129
* fix(test_openai.py): add unit test to ensure openai sdk calls always respect max_retries = 0
* test(test_azure_openai.py): add unit testing for azure_text/ route
* fix(azure.py): fix passing max retries on streaming
* fix(azure.py): fix azure max retries on async completion + streaming
* fix(completion/handler.py): fix azure text async completion + streaming
* test(test_azure_openai.py): ensure azure openai max retries always respected
* test(test_azure_o_series.py): add testing to ensure max retries always respected
* Added gemini providers for 2.0-flash and 2.0-flash lite (#8321)
* Update model_prices_and_context_window.json
added gemini providers for 2.0-flash and 2.0-flash light
* Update model_prices_and_context_window.json
fixed URL
---------
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
* Convert tool use arguments to string before counting tokens (#6989)
In at least some cases the `messages["tool_calls"]["function"]["arguments"]` is a dict, not a string. In order to tokenize it properly it needs to be a string. In the case that it is already a string this is a noop, which is also fine.
* build(model_prices_and_context_window.json): add gemini 2.0 flash lite pricing
* build(model_prices_and_context_window.json): add gemini commercial rate limits
* fix(utils.py): fix linting error
* refactor(utils.py): refactor to maintain function size
---------
Co-authored-by: Bardia Khosravi <bardiakhosravi95@gmail.com>
Co-authored-by: Josh Morrow <josh@jcmorrow.com>
* fix(convert_dict_to_response.py): only convert if response is the response_format tool call passed in
Fixes https://github.com/BerriAI/litellm/issues/8241
* fix(gpt_transformation.py): makes sure response format / tools conversion doesn't remove previous tool calls
* refactor(gpt_transformation.py): refactor out json schema converstion to base config
keeps logic consistent across providers
* fix(o_series_transformation.py): support o3 mini native streaming
Fixes https://github.com/BerriAI/litellm/issues/8274
* fix(gpt_transformation.py): remove unused variables
* test: update 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
* 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(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): 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 get_response_headers
* unit testing for get headers
* unit testing for anthropic / azure openai headers
* increase test coverage for test_completion_response_ratelimit_headers
* fix test rate limit headers
