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110 lines
3.8 KiB
Python
110 lines
3.8 KiB
Python
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"""Regression for #2410: the buffered-CCR Responses -> SSE reconstruction must
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replay the incremental output-item/text events, not just response.created +
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response.completed, so AI-SDK / OpenCode clients render the output."""
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from __future__ import annotations
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import json
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from headroom.proxy.handlers.openai import _openai_responses_to_sse
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def _parse(events: list[bytes]) -> list[dict]:
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out: list[dict] = []
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for e in events:
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s = e.decode()
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if s.startswith("data: [DONE]"):
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out.append({"type": "[DONE]"})
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continue
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out.append(json.loads(s.split("data: ", 1)[1]))
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return out
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def test_responses_sse_replays_incremental_output_text() -> None:
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resp = {
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"id": "resp_1",
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"object": "response",
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"status": "completed",
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"model": "gpt-5.3-codex",
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"output": [
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{"type": "reasoning", "id": "rs_1", "summary": []},
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{
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"type": "message",
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"id": "msg_1",
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"status": "completed",
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"role": "assistant",
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"content": [{"type": "output_text", "text": "Hello world", "annotations": []}],
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},
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],
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"usage": {"input_tokens": 10, "output_tokens": 3},
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}
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parsed = _parse(_openai_responses_to_sse(resp))
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types = [p["type"] for p in parsed]
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assert types[0] == "response.created"
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assert types[1] == "response.in_progress"
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assert types[-2] == "response.completed"
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assert types[-1] == "[DONE]"
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# The visible assistant text is streamed as an output_text.delta.
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deltas = [p for p in parsed if p["type"] == "response.output_text.delta"]
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assert len(deltas) == 1
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assert deltas[0]["delta"] == "Hello world"
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assert deltas[0]["output_index"] == 1
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assert deltas[0]["content_index"] == 0
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# The message item gets the full content-part sequence; the reasoning item
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# gets add/done with no content parts.
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assert types.count("response.output_item.added") == 2
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assert types.count("response.output_item.done") == 2
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assert "response.content_part.added" in types
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assert "response.output_text.done" in types
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assert "response.content_part.done" in types
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# created / in_progress carry an empty output; completed carries the full one.
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created = next(p for p in parsed if p["type"] == "response.created")
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assert created["response"]["output"] == []
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completed = next(p for p in parsed if p["type"] == "response.completed")
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assert completed["response"]["output"] == resp["output"]
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# Sequence numbers are contiguous from 0.
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seqs = [p["sequence_number"] for p in parsed if p["type"] != "[DONE]"]
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assert seqs == list(range(len(seqs)))
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def test_responses_sse_empty_output_still_valid() -> None:
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resp = {"id": "resp_2", "status": "completed", "output": [], "usage": {}}
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types = [p["type"] for p in _parse(_openai_responses_to_sse(resp))]
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assert types == ["response.created", "response.in_progress", "response.completed", "[DONE]"]
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def test_responses_sse_non_message_item_added_and_done() -> None:
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resp = {
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"id": "resp_3",
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"status": "completed",
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"output": [
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{
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"type": "function_call",
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"id": "fc_1",
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"call_id": "c1",
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"name": "grep",
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"arguments": "{}",
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}
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],
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"usage": {},
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}
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parsed = _parse(_openai_responses_to_sse(resp))
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types = [p["type"] for p in parsed]
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assert types == [
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"response.created",
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"response.in_progress",
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"response.output_item.added",
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"response.output_item.done",
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"response.completed",
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"[DONE]",
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]
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# The function_call item is preserved whole on added and done.
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done = next(p for p in parsed if p["type"] == "response.output_item.done")
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assert done["item"]["name"] == "grep"
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