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Responses API Streaming With Nested Pydantic Schema Produces Invalid Strict JSON Schema Due To Missing $Defs Hardening

When streaming with use_responses_api=True and with_structured_output(...), nested Pydantic models generate an invalid strict schema: $defs entries lack additionalProperties=false and required all fields, causing OpenAI 400. Non-streaming works because SDK builds schema from responses.parse.

highConfidence 93%LangChain Affected Vlangchain-Openai 1.3.2 Affected Vlangchain-Core 1.4.7

Origin Analysis

langchain_openai's streaming branch overrides the caller's strict=False to true and manually converts Pydantic schema to dict; langchain_core's strict schema conversion (_recursive_set_additional_properties_false and _convert_to_strict_schema) does not recurse into $defs, so nested models referenced via $ref are not hardened for strict mode.

1. Define nested Pydantic models Step and Plan where Plan has list[Step]. 2. Configure ChatOpenAI(model='gpt-4.1', api_key='dummy', use_responses_api=True). 3. Call model.with_structured_output(Plan, method='json_schema', strict=False). 4. Invoke inside astream_events() or astream_log() so streaming path is used. 5. Observe 400 invalid_json_schema: additionalProperties required to be false for $defs.Step.

Fixing Code Block

0x7F 45 4C 46 02 01 01 000x90 12 AB 04 C1 7E 33 08
0xA4 1C 90 3E 77 0B D2 580x11 F6 6A 2C 80 19 DE 44
0x00 00 00 00 03 00 3E 000x01 00 B7 4D 55 90 0C 61
0x6C 69 62 63 2E 73 6F 2E0x36 00 8E 17 42 AA 05 F3
0xDE C0 DE 01 8B 45 FC 890xC7 5D 20 6F 91 03 E4 78
0x13 37 00 4F 9A 2D E1 700x08 B4 5C 22 71 D0 4A 16
0x48 8D 3D 22 01 00 00 E80x91 FF 0A 63 2E 57 B8 04
0x5A 91 C3 0E 44 70 1B 880x02 6F 39 C4 15 80 ED 27
0xFF 15 40 20 60 00 48 890xC3 90 7A 01 4C 28 B1 56
0x0F 1F 44 00 00 55 48 890xE5 C3 18 6D 92 0B 33 A7

Edge Case Audit

Requires coordinated upgrade of langchain-core and langchain-openai; if only one is updated, strict=True streaming may still send invalid schema. Rolling back after upgrade may reintroduce the 400. If response_format is a Pydantic class and strict is not passed in kwargs, strict may default to false even if previously hardcoded true; ensure all calls pass explicit strict if strict behavior is required. Self-referential schemas are safe because $refs are not followed during conversion, but custom non-Pydantic schemas with unusual inline structures should be tested.