* 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
* test_openai_assistants_e2e_operations
* test openai assistants pass through
* fix GET request on pass through handler
* _make_non_streaming_http_request
* _is_assistants_api_request
* test_openai_assistants_e2e_operations
* test_openai_assistants_e2e_operations
* openai_proxy_route
* docs openai pass through
* docs openai pass through
* docs openai pass through
* test pass through handler
* Potential fix for code scanning alert no. 2240: Incomplete URL substring sanitization
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
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Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
* feat(pass_through_endpoints.py): fix anthropic end user cost tracking
* fix(anthropic/chat/transformation.py): use returned provider model for anthropic
handles anthropic `-latest` tag in request body throwing cost calculation errors
ensures we can be accurate in our model cost tracking
* feat(model_prices_and_context_window.json): add gemini-2.0-flash-thinking-exp pricing
* test: update test to use assumption that user_api_key_dict can get anthropic user id
* test: fix test
* fix: fix test
* fix(anthropic_pass_through.py): uncomment previous anthropic end-user cost tracking code block
can't guarantee user api key dict always has end user id - too many code paths
* fix(user_api_key_auth.py): this allows end user id from request body to always be read and set in auth object
* fix(auth_check.py): fix linting error
* test: fix auth check
* fix(auth_utils.py): fix get end user id to handle metadata = None
* run pass through logging async
* fix use thread_pool_executor for pass through logging
* test_pass_through_request_logging_failure_with_stream
* fix anthropic pt logging test
* test_pass_through_request_logging_failure
* feat - allow tagging vertex JS SDK request
* add unit testing for passing headers for pass through endpoints
* fix allow using vertex_ai as the primary way for pass through vertex endpoints
* docs on vertex js pass tags
* add e2e test for vertex pass through with spend tags
* add e2e tests for streaming vertex JS with tags
* fix vertex ai testing
* stash gemini JS test
* add vertex js sdj example
* handle vertex pass through separately
* tes vertex JS sdk
* fix vertex_proxy_route
* use PassThroughStreamingHandler
* fix PassThroughStreamingHandler
* use common _create_vertex_response_logging_payload_for_generate_content
* test vertex js
* add working vertex jest tests
* move basic bass through test
* use good name for test
* test vertex
* test_chunk_processor_yields_raw_bytes
* unit tests for streaming
* test_convert_raw_bytes_to_str_lines
* run unit tests 1st
* simplify local
* docs add usage example for js
* use get_litellm_virtual_key
* add unit tests for vertex pass through
* allow passing _litellm_metadata in pass through endpoints
* fix _create_anthropic_response_logging_payload
* include litellm_call_id in logging
* add e2e testing for anthropic spend logs
* add testing for spend logs payload
* add example with anthropic python SDK
* 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(model_prices_and_context_window.json): add cost tracking for more vertex llama3.1 model
8b and 70b models
* fix(proxy/utils.py): handle data being none on pre-call hooks
* fix(proxy/): create views on initial proxy startup
fixes base case, where user starts proxy for first time
Fixes https://github.com/BerriAI/litellm/issues/5756
* build(config.yml): fix vertex version for test
* feat(ui/): support enabling/disabling slack alerting
Allows admin to turn on/off slack alerting through ui
* feat(rerank/main.py): support langfuse logging
* fix(proxy/utils.py): fix linting errors
* fix(langfuse.py): log clean metadata
* test(tests): replace deprecated openai model
* 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
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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
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Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>