feat: support structured outputs (response_format) in chat completions#43
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giwaov wants to merge 1 commit intoOpenGradient:mainfrom
Open
feat: support structured outputs (response_format) in chat completions#43giwaov wants to merge 1 commit intoOpenGradient:mainfrom
giwaov wants to merge 1 commit intoOpenGradient:mainfrom
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Wire the OpenAI-compatible response_format parameter through the chat completion pipeline: - Bind response_format to LangChain model via model.bind() for json_object and json_schema types (text is a no-op) - Apply to both streaming and non-streaming code paths - Include response_format in the canonical request dict so TEE hashing covers the requested output format - Add 14 unit tests covering parsing, hash-dict serialization, model binding, and interaction with tool calling Closes OpenGradient#14
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Summary
Implements OpenAI-compatible structured outputs support by wiring the
response_formatparameter through the chat completion pipeline, as requested in #14.Changes
tee_gateway/controllers/chat_controller.py_create_non_streaming_response): After tool binding, checksresponse_format. If the type isjson_objectorjson_schema, binds it to the LangChain model viamodel.bind(response_format=...). Thetexttype is a no-op (default behavior)._create_streaming_response): Identical logic applied after tool binding._chat_request_to_dict): Includesresponse_formatin the canonical serialized dict so the TEE signature covers the requested output format.tests/test_structured_outputs.py14 unit tests covering:
response_formatfrom request dicts (text, json_object, json_schema, and absent)bind_toolsandbind(response_format=...)chain correctly)Design Decisions
llm_backend.py: Theresponse_formatis bound per-request viamodel.bind()after retrieving the cached model, following the same pattern already used for tool binding. This keeps the LRU cache clean (keyed only on model/temperature/max_tokens).response_formatdict is forwarded as-is to LangChain, which handles provider-specific translation. This maintains OpenAI API compatibility and works with all supported providers (OpenAI, Anthropic, Google, xAI).Supported Formats
Per the OpenAPI spec already defined in the repo:
{type: text}plain text (default, no-op){type: json_object}JSON mode{type: json_schema, json_schema: {name: ..., schema: {...}, strict: true}}strict schema-constrained outputCloses #14