- Add OpenAITokenCounter using POST /v1/responses/input_tokens endpoint
- Add litellm.acount_tokens() public async API that auto-routes to provider APIs
- Add proxy endpoint POST /v1/responses/input_tokens for OpenAI-compatible counting
- Transform chat tools format to Responses API format for correct token counting
- Fall back to local tiktoken when provider API unavailable
Fixes#22302
When an OpenAI-compatible upstream provider emits minimal streaming event
payloads that omit required fields (e.g. created_at, output, output_index,
content_index), Pydantic raises a ValidationError crashing the SSE stream
and returning HTTP 500.
Fall back to model_construct() on ValidationError, consistent with the
existing pattern in transform_response_api_response for non-streaming.
Fixes https://github.com/BerriAI/litellm/issues/20570
Signed-off-by: Varun Chawla <varun_6april@hotmail.com>
* fix: check for model_response_choices before guardrail input
* test: add tests for responses api translation
* fix: protect other guardrail translations
* refactor: remove type ignores
* anthropic request body got mutated fix
* add warning when extra_body is provided but user is non premium
* fix: resolve mypy union-attr errors in anthropic guardrail handler
Cast choices[0] to Choices type before accessing .message attribute
to satisfy mypy's union type checking for Choices | StreamingChoices.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* add logger when model response has no choices for streaming /response and /messages
* update pyproject.toml as requested
* Revert "update pyproject.toml as requested"
This reverts commit 541a2b075a.
* update pyproject.toml as requested
* Revert "update pyproject.toml as requested"
This reverts commit 716ea0caa1.
---------
Co-authored-by: Xiaohan Fu <xiaohan@grayswan.ai>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
* fix(unified_guardrails.py): send all chunks on completion of final stream
* feat(generic_guardrail_api.py): handle tool call response on streaming LLM responses
* fix(anthropic/chat/guardrail_translation): initial commit adding anthropic tool response streaming guardrails
enables guardrail checks on tool response from llm's to work via `/v1/messages`
* feat(anthropic/): working guardrail checks on tool response from LLMs
ensures guardrail checks on anthropic /v1/messages works as expected
* feat(responses/guardrail_translation): support tool call response guardrails on streaming for /v1/responses
ensures complete coverage of tool call responses
* refactor(openai.py): refactor to use consistent pydantic model for responses api tool response on streaming
enables non-openai model tool call response to work correctly with guardrail checks on /v1/responses
* test: update tests
* fix: fix linting error
* fix: fix failing tests
* fix: fix import errors
* fix(openai/chat/guardrail_transformation): fix final chunk returned on streaming
* fix(unified_guardrail.py): support during_call event type for unified guardrails
allows guardrails overriding apply_guardrails to work 'during_call'
* feat(generic_guardrail_api.py): support new 'tool_calls' field for generic guardrail api
returns the tool calls emitted by the LLM API to the user
* fix(generic_guardrail_api.py): working anthropic /v1/messages tool call response
send llm tool calls to guardrail api when called via `/v1/messages` API
* fix(responses/): run generic_guardrail_api on responses api tool call responses
* fix: fix tests
* test: fix tests
* fix: fix tests
* fix(unified_guardrail.py): correctly map a v1/messages call to the anthropic unified guardrail
* fix: add more rigorous call type checks
* fix(anthropic_endpoints/endpoints.py): initialize logging object at the beginning of endpoint
ensures call id + trace id are emitted to guardrail api
* feat(anthropic/chat/guardrail_translation): support streaming guardrails
sample on every 5 chunks
* fix(openai/chat/guardrail_translation): support openai streaming guardrails
* fix: initial commit fixing output guardrails for responses api
* feat(openai/responses/guardrail_translation): handler.py - fix output checks on responses api
* fix(openai/responses/guardrail_translation/handler.py): ensure responses api guardrails work on streaming
* test: update tests
* test: update tests
* test: update tests
* fix(bedrock_guardrails.py): fix post call streaming iterator logic
* fix: fix return
* fix(bedrock_guardrails.py): fix
* fix(initial-commit): adding a way to get the right response type based on the api route
* feat(unified_guardrail.py): support streaming guardrails
* test: update tests
* fix: fix linting errors
* test: update tests
* Enhance error handling in OpenAIResponsesAPIConfig to coalesce null error codes into a default string, preventing validation errors and improving stability during streaming iterations.
* Add test for coalescing null error codes in streaming responses
This test ensures that when a streaming error event has error.code set to None, the system correctly transforms it to 'unknown_error' and returns an ErrorEvent instance without raising a ValidationError.
---------
Co-authored-by: Ku Wei Chiet <chietkuw@fpt.com>
* fix(presidio.py): handle content as a list of texts
covers openai + anthropic messages api
* fix(presidio.py): safe get messages
* test: add unit testing for presidio guardrails
* fix(unified_guardrail.py): initial commit
* fix(enkryptai.py): implement apply_guardrail to enkrypt guardrail
* fix(unified_guardrail.py): support unified guardrail on input
* feat(unified_guardrail.py): add post call success hook implementation
allows us to just have 1 place to handle llm translation to guardrail api spec
* refactor: refactor initial unified guardrail component
* refactor: more refactoring
* feat(responses/): add guardrails to responses api
allows existing guardrails to work for new llm endpoints
* docs(adding_guardrail_support.md): document new guardrail endpoint support
* test: add unit tests
* feat(image_generation/): add guardrail support for image generation endpoint
* feat(openai/text_completion): support guardrails on `/v1/completions` API
* docs: document guardrails support on new endpoints
* docs: clarify when guardrails run
* feat(openai/speech): add guardrail support for input
* docs(rerank/): add guardrail support on input query
* fix: fix ruff check
* fix response api for litellm proxy
* Add test for checking if status is getting removed
* add test in correct file
* remove hardcoded fields
* Make the handling simpler
* fix lint error:
