* feat(containers): Azure container routing, managed IDs, and delete response wire format
- Add AzureContainerConfig and safe URL joining for paths with api-version query
- Encode/decode managed container IDs in responses, streaming, and proxy handlers
- Accept OpenAI delete response object literal container.file.deleted
- Tests for Azure URL regression and DeleteContainerFileResponse parsing
Made-with: Cursor
* fix(responses): gate response id update on parsed_chunk having response
Delta stream events do not include a response body; Mock-based tests
(and any truthy synthetic .response on transforms) must not trigger
_update_responses_api_response_id_with_model_id. Fixes
test_stop_async_iteration_not_logged_as_failure (TypeError: Mock not iterable).
Made-with: Cursor
* feat(containers): encode container IDs in SDK responses for routing
- Add ContainerRequestUtils.encode_container_id_in_response utility
- Encode container_id in create/retrieve/delete responses (SDK path)
- Fix streaming iterator: gate response ID update on parsed_chunk key
- Follows responses API pattern (encode after handler, not in handler)
Made-with: Cursor
* fix(containers): module-level imports and managed cntr_ ID encoding
- Move ResponsesAPIRequestUtils imports to module scope (utils, main, handler_factory).
- Serialize absent model_id as empty segment instead of literal None; decode empty
and legacy "None" segments as missing for router affinity.
- Add unit tests for build/decode round-trip and legacy IDs.
Made-with: Cursor
* fix(containers): decode managed IDs in endpoint_factory SDK path
- Add decode_managed_container_id_for_request in containers/utils and reuse from main.
- Strip LiteLLM cntr_ wrappers before generic_container_handler (64-char API limit).
- Resolve provider for logging/errors; add unit test for decode helper.
- Use resolved_custom_llm_provider after decode for mypy-safe provider typing.
Made-with: Cursor
* Fix p1 concern
* Fix p1 concern
* fix(vertex_ai): forward extra_body to completion transformation handler
The responses() function accepted extra_body as a named parameter but
did not pass it to response_api_handler when responses_api_provider_config
was None (completion transformation path), silently dropping it.
Also adds deep-merge support for extra_body in Vertex AI Gemini
transformation, so dict values like generationConfig are merged rather
than replaced.
* refactor(vertex_ai): extract _merge_extra_body to fix PLR0915 lint
Move the extra_body merge loop into a helper function to keep
_transform_request_body under the 50-statement limit.
When using the responses API with provider-specific params (aws_*, vertex_*)
without explicitly passing custom_llm_provider, the code crashed with:
AttributeError: 'NoneType' object has no attribute 'startswith'
Root cause: local_vars was captured via locals() before get_llm_provider()
detected the provider from the model string (e.g., "bedrock/..."), so
custom_llm_provider remained None when processing provider-specific params.
Fix: Update local_vars["custom_llm_provider"] after get_llm_provider() call
so the detected provider is available for param processing.
Affected provider-specific params:
- aws_* (aws_region_name, aws_access_key_id, etc.) for Bedrock/SageMaker
- vertex_* (vertex_project, vertex_location, etc.) for Vertex AI
Calculate `total_tokens` in usage data in Response manually if:
- `total_tokens` is missing
- `total_tokens` can be calculated from input and output tokens
Run the test for this feature with:
`poetry run pytest tests/test_litellm/responses/test_responses_utils.py -k "test_transform_response_api_usage_calculates_total_from_input_and_output_tokens_if_available" -v`
