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Responses API: Parsed_arguments Leaks From ParsedResponseFunctionToolCall Into AIMessage Content, Breaking The Next Turn

When using ChatOpenAI with output_version='responses/v1' and structured output plus tools, the second turn of a ReAct loop fails because the AIMessage content block contains an unexpected 'parsed_arguments' field, which OpenAI rejects as an unknown parameter.

highConfidence 95%Langchain-Openai Affected V1.1.12 Affected V1.2.2

Origin Analysis

In langchain_openai/chat_models/base.py, _construct_lc_result_from_responses_api serializes OpenAI response objects using plain model_dump(exclude_none=True, mode='json'), which does not honor the OpenAI SDK's __api_exclude__ attribute. This causes the client-side-only parsed_arguments field to be included in AIMessage content blocks and subsequently sent back in the next request, where the API rejects it.

1. Create a ChatOpenAI instance with output_version='responses/v1'. 2. Bind a structured output schema (method='json_schema', strict=True) along with a tool call. 3. Invoke the runnable with a user message that triggers a tool call; the first turn succeeds. 4. Re-send the returned raw AIMessage along with the tool result as the input for the second turn. 5. The request fails with a 400 error citing unknown parameter 'input[N].parsed_arguments'.

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

If a model has a __api_exclude__ attribute that is not a set of strings, pydantic may raise an error; consider converting to a set or validating the type. Also, if other code relies on the previously leaked fields being present in AIMessage content, this change removes them and could break downstream consumers. Rolling back is straightforward: revert the three calls to the original model_dump. Test with both responses/v1 and chat completions paths to ensure no regressions.