test(integration): add the openai_wire helper the backported chat template wire test imports

Copied unchanged from main. The line had this file from #47389's first attempt until 828ddf0c37 narrowed that backport and removed it.

tests/integration/_support/openai_wire.py

@@ -0,0 +1,126 @@
+from __future__ import annotations
+
+import json
+from collections.abc import Callable
+from typing import Final
+
+from integration._support.wire import Reply, Request, Wire
+from pydantic import JsonValue
+
+from tests.integration._support.provider import MODEL_DISCOVERY
+
+_USAGE: Final = {"prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8}
+
+
+def answering_model_discovery(respond: Callable[[Request], Reply]) -> Callable[[Request], Reply]:
+    def guarded(request: Request) -> Reply:
+        if (request.method, request.target) == MODEL_DISCOVERY:
+            return Reply(body=json.dumps({"object": "list", "data": []}).encode())
+        return respond(request)
+
+    return guarded
+
+
+def posted_targets(wire: Wire) -> tuple[str, ...]:
+    return tuple(request.target for request in wire.drain() if request.method == "POST")
+
+
+def openai_error(status: int) -> Reply:
+    return Reply(
+        status=status,
+        body=json.dumps({"error": {"message": f"scripted {status}", "type": "server_error", "code": None}}).encode(),
+    )
+
+
+def _data_frame(frame: dict[str, JsonValue]) -> bytes:
+    return b"data: " + json.dumps(frame).encode() + b"\n\n"
+
+
+def _typed_frame(event: dict[str, JsonValue]) -> bytes:
+    return f"event: {event['type']}\ndata: {json.dumps(event)}\n\n".encode()
+
+
+def chat_stream(identity: str, model: str, text: str) -> tuple[bytes, bytes, bytes]:
+    chunk: Final = {"id": identity, "object": "chat.completion.chunk", "created": 1, "model": model}
+    role_only: Final = _data_frame({**chunk, "choices": [{"index": 0, "delta": {"role": "assistant", "content": ""}}]})
+    content: Final = _data_frame({**chunk, "choices": [{"index": 0, "delta": {"content": text}}]})
+    finish: Final = _data_frame(
+        {**chunk, "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}], "usage": _USAGE}
+    )
+    return (role_only, content, finish + b"data: [DONE]\n\n")
+
+
+def chat_reply(identity: str, model: str, text: str, *, stream: bool) -> Reply:
+    if stream:
+        return Reply(content_type="text/event-stream", chunks=chat_stream(identity, model, text))
+    return Reply(
+        body=json.dumps(
+            {
+                "id": identity,
+                "object": "chat.completion",
+                "created": 1,
+                "model": model,
+                "choices": [{"index": 0, "message": {"role": "assistant", "content": text}, "finish_reason": "stop"}],
+                "usage": _USAGE,
+            }
+        ).encode()
+    )
+
+
+def _response_object(identity: str, model: str, text: str) -> dict[str, JsonValue]:
+    return {
+        "id": identity,
+        "object": "response",
+        "created_at": 1,
+        "status": "completed",
+        "model": model,
+        "output": [_message_item(identity, text, "completed")],
+        "usage": {"input_tokens": 5, "output_tokens": 3, "total_tokens": 8},
+    }
+
+
+def _message_item(identity: str, text: str, status: str) -> dict[str, JsonValue]:
+    return {
+        "id": f"msg_{identity}",
+        "type": "message",
+        "role": "assistant",
+        "status": status,
+        "content": [{"type": "output_text", "text": text, "annotations": []}] if status == "completed" else [],
+    }
+
+
+def responses_stream(identity: str, model: str, text: str) -> tuple[bytes, bytes, bytes]:
+    response: Final = _response_object(identity, model, text)
+    item: Final = _message_item(identity, text, "in_progress")
+    opened: Final = _typed_frame(
+        {
+            "type": "response.created",
+            "sequence_number": 0,
+            "response": {**response, "status": "in_progress", "output": []},
+        }
+    ) + _typed_frame({"type": "response.output_item.added", "sequence_number": 1, "output_index": 0, "item": item})
+    delta: Final = _typed_frame(
+        {
+            "type": "response.output_text.delta",
+            "sequence_number": 2,
+            "item_id": f"msg_{identity}",
+            "output_index": 0,
+            "content_index": 0,
+            "delta": text,
+        }
+    )
+    closed: Final = _typed_frame(
+        {
+            "type": "response.output_item.done",
+            "sequence_number": 3,
+            "output_index": 0,
+            "item": _message_item(identity, text, "completed"),
+        }
+    ) + _typed_frame({"type": "response.completed", "sequence_number": 4, "response": response})
+    return (opened, delta, closed)
+
+
+def responses_reply(identity: str, model: str, text: str, *, stream: bool) -> Reply:
+    if stream:
+        return Reply(content_type="text/event-stream", chunks=responses_stream(identity, model, text))
+    return Reply(body=json.dumps(_response_object(identity, model, text)).encode())