OpenAI Responses API model classes#1435
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Adds Responses and AsyncResponses classes that drive the OpenAI /v1/responses endpoint. The existing Chat / AsyncChat classes are unchanged because other plugins import them. gpt-5.5 (and gpt-5.5-2026-04-23) is now registered against Responses by default. Pass `-o chat_completions 1` to fall back to the older /v1/chat/completions code path. This is feature parity with the Chat path (text, tools, streaming, schema, reasoning_effort, verbosity, attachments, system prompts). Interleaved reasoning across tool round-trips is not exercised yet - encrypted reasoning items are accepted on the input side, but the plugin doesn't yet stash them on outgoing ReasoningParts.
When the Responses API returns a reasoning item alongside function calls, capture its opaque id + encrypted_content as provider_metadata on the resulting ReasoningPart. _build_responses_input already echoed that metadata back as a reasoning input item on the next turn - now the output side actually populates it. This preserves the model's hidden chain of thought across the tool round-trip. Without it, GPT-5-class models silently lose ~3% on SWE-bench (per OpenAI) when used with tools. Adds a dedicated VCR test that asserts the encrypted_content captured on the first turn appears verbatim in the second turn's outgoing request body.
The previous commit wired up encrypted_content round-trip but only tested that the data flows through correctly on a single tool round- trip. This adds a multi-turn cassette test that proves the full interleaved-reasoning capability: - Each turn produces fresh reasoning_tokens (not just the first) - Every prior reasoning block is round-tripped on every subsequent turn (the Nth turn echoes >= N-1 reasoning items) - ReasoningParts persisted on the assistant messages carry the same encrypted_content + id that gets sent back on the wire The puzzle is shaped so the model can't parallelize tool calls - each db_lookup result tells it the next key to use, forcing the model to think between calls. The recorded 4-turn chain shows reasoning_tokens of 45/98/196/17 across turns with reasoning items accumulating in every outgoing input. This is the GPT-5-class capability that Chat Completions can't deliver because it discards reasoning between turns.
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I had Codex run a manual testing run against the branch using Showboat, results here: https://gist.github.com/simonw/19cfef23659a939c12b1f8a6ccfe227a |
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Had Codex write and execute a script to test ALL the model IDs, which I used to help decide which ones to port to Responses: https://gist.github.com/simonw/4d1a1749475b092a328b92ae5f272e87 |
When building the `input` list for the OpenAI Responses API from prior
conversation turns, an assistant text-only turn was being serialized as:
{"role": "assistant",
"content": [{"type": "output_text", "text": "..."}]}
The openai-python SDK's EasyInputMessage shape uses a plain string for
this case, matching what a direct OpenAI Responses call would send. Use
the same shape so our history matches the SDK exactly, and add tests
covering both _build_responses_input and a two-turn response.reply()
flow.
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https://claude.ai/code/session_01S7UevnY7zKogbthSz4UXJv