forked from phoenix/litellm-mirror
5 commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Krish Dholakia
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f79365df6e
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LiteLLM Minor Fixes & Improvements (10/30/2024) (#6519)
* 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> |
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Krrish Dholakia
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aa4c2827e8 | test: refactor gemini test to use mock, prevent ratelimit error | ||
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Krish Dholakia
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1e403a8447
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Litellm dev 10 29 2024 (#6502)
* fix(core_helpers.py): return None, instead of raising kwargs is None error Closes https://github.com/BerriAI/litellm/issues/6500 * docs(cost_tracking.md): cleanup doc * fix(vertex_and_google_ai_studio.py): handle function call with no params passed in Closes https://github.com/BerriAI/litellm/issues/6495 * test(test_router_timeout.py): add test for router timeout + retry logic * test: update test to use module level values * (fix) Prometheus - Log Postgres DB latency, status on prometheus (#6484) * fix logging DB fails on prometheus * unit testing log to otel wrapper * unit testing for service logger + prometheus * use LATENCY buckets for service logging * fix service logging * docs clarify vertex vs gemini * (router_strategy/) ensure all async functions use async cache methods (#6489) * fix router strat * use async set / get cache in router_strategy * add coverage for router strategy * fix imports * fix batch_get_cache * use async methods for least busy * fix least busy use async methods * fix test_dual_cache_increment * test async_get_available_deployment when routing_strategy="least-busy" * (fix) proxy - fix when `STORE_MODEL_IN_DB` should be set (#6492) * set store_model_in_db at the top * correctly use store_model_in_db global * (fix) `PrometheusServicesLogger` `_get_metric` should return metric in Registry (#6486) * fix logging DB fails on prometheus * unit testing log to otel wrapper * unit testing for service logger + prometheus * use LATENCY buckets for service logging * fix service logging * fix _get_metric in prom services logger * add clear doc string * unit testing for prom service logger * bump: version 1.51.0 → 1.51.1 * Add `azure/gpt-4o-mini-2024-07-18` to model_prices_and_context_window.json (#6477) * Update utils.py (#6468) Fixed missing keys * (perf) Litellm redis router fix - ~100ms improvement (#6483) * 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 * perf(cooldown_cache.py): improve cooldown cache, to store cache results in memory for 5s, prevents redis call from being made on each request reduces 100ms latency per call with caching enabled on router * fix: fix test * fix(cooldown_cache.py): handle if a result is None * fix(cooldown_cache.py): add debug statements * refactor(dual_cache.py): move to using an in-memory check for batch get cache, to prevent redis from being hit for every call * fix(cooldown_cache.py): fix linting erropr * refactor(prometheus.py): move to using standard logging payload for reading the remaining request / tokens Ensures prometheus token tracking works for anthropic as well * fix: fix linting error * fix(redis_cache.py): make sure ttl is always int (handle float values) Fixes issue where redis_client.ex was not working correctly due to float ttl * fix: fix linting error * test: update test * fix: fix linting error --------- Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com> Co-authored-by: Xingyao Wang <xingyao@all-hands.dev> Co-authored-by: vibhanshu-ob <115142120+vibhanshu-ob@users.noreply.github.com> |
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Krish Dholakia
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f44ab00de2
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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 |
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Krish Dholakia
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6005450c8f
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LiteLLM Minor Fixes & Improvements (10/09/2024) (#6139)
* fix(utils.py): don't return 'none' response headers Fixes https://github.com/BerriAI/litellm/issues/6123 * fix(vertex_and_google_ai_studio_gemini.py): support parsing out additional properties and strict value for tool calls Fixes https://github.com/BerriAI/litellm/issues/6136 * fix(cost_calculator.py): set default character value to none Fixes https://github.com/BerriAI/litellm/issues/6133#issuecomment-2403290196 * fix(google.py): fix cost per token / cost per char conversion Fixes https://github.com/BerriAI/litellm/issues/6133#issuecomment-2403370287 * build(model_prices_and_context_window.json): update gemini pricing Fixes https://github.com/BerriAI/litellm/issues/6133 * build(model_prices_and_context_window.json): update gemini pricing * fix(litellm_logging.py): fix streaming caching logging when 'turn_off_message_logging' enabled Stores unredacted response in cache * build(model_prices_and_context_window.json): update gemini-1.5-flash pricing * fix(cost_calculator.py): fix default prompt_character count logic Fixes error in gemini cost calculation * fix(cost_calculator.py): fix cost calc for tts models |