Preserve speaker in OpenAI transcription segments (#3086)

* Preserve speaker in OpenAI transcription segments

* Tidy OpenAI speaker response test stub

examples/industrial_data_pretraining/fun_asr_nano/serve_vllm.py

@@ -184,6 +184,30 @@ def process_audio(audio_data, sr=16000, language=None, hotwords=None,
     }
 
 
+def build_openai_verbose_json(result, language=None):
+    """Build OpenAI-compatible verbose_json while preserving FunASR extensions."""
+    segments = []
+    for i, seg in enumerate(result["segments"]):
+        item = {
+            "id": i,
+            "start": seg["start"],
+            "end": seg["end"],
+            "text": seg["text"],
+            "words": seg.get("words", []),
+        }
+        if "speaker" in seg:
+            item["speaker"] = seg["speaker"]
+        segments.append(item)
+
+    return {
+        "task": "transcribe",
+        "language": language or "zh",
+        "duration": result["duration"],
+        "text": result["text"],
+        "segments": segments,
+    }
+
+
 # ============================================================
 # FastAPI App
 # ============================================================
@@ -240,22 +264,7 @@ async def openai_transcriptions(
     if response_format == "text":
         return JSONResponse(content=result["text"])
     elif response_format == "verbose_json":
-        return JSONResponse(content={
-            "task": "transcribe",
-            "language": language or "zh",
-            "duration": result["duration"],
-            "text": result["text"],
-            "segments": [
-                {
-                    "id": i,
-                    "start": seg["start"],
-                    "end": seg["end"],
-                    "text": seg["text"],
-                    "words": seg.get("words", []),
-                }
-                for i, seg in enumerate(result["segments"])
-            ],
-        })
+        return JSONResponse(content=build_openai_verbose_json(result, language=language))
     else:
         return JSONResponse(content={"text": result["text"]})
 

tests/test_fun_asr_nano_openai_response.py

@@ -0,0 +1,110 @@
+import importlib.util
+import sys
+import types
+from pathlib import Path
+
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+SERVICE_PATH = (
+    REPO_ROOT
+    / "examples"
+    / "industrial_data_pretraining"
+    / "fun_asr_nano"
+    / "serve_vllm.py"
+)
+
+
+def load_service_module(monkeypatch):
+    fastapi_stub = types.ModuleType("fastapi")
+
+    class FastAPIStub:
+        def __init__(self, *args, **kwargs):
+            pass
+
+        def on_event(self, *args, **kwargs):
+            return lambda func: func
+
+        def post(self, *args, **kwargs):
+            return lambda func: func
+
+        def websocket(self, *args, **kwargs):
+            return lambda func: func
+
+    fastapi_stub.FastAPI = FastAPIStub
+    fastapi_stub.File = lambda *args, **kwargs: None
+    fastapi_stub.Form = lambda *args, **kwargs: None
+    fastapi_stub.UploadFile = object
+    fastapi_stub.WebSocket = object
+    fastapi_stub.WebSocketDisconnect = Exception
+
+    responses_stub = types.ModuleType("fastapi.responses")
+
+    class JSONResponseStub:
+        def __init__(self, content=None):
+            self.content = content
+
+    responses_stub.JSONResponse = JSONResponseStub
+
+    funasr_stub = types.ModuleType("funasr")
+    funasr_stub.AutoModel = object
+
+    nano_stub = types.ModuleType("funasr.models.fun_asr_nano.inference_vllm")
+    nano_stub.FunASRNanoVLLM = object
+
+    vad_stub = types.ModuleType("funasr.models.fsmn_vad_streaming.dynamic_vad")
+    vad_stub.DynamicStreamingVAD = object
+
+    monkeypatch.setitem(sys.modules, "fastapi", fastapi_stub)
+    monkeypatch.setitem(sys.modules, "fastapi.responses", responses_stub)
+    monkeypatch.setitem(sys.modules, "uvicorn", types.ModuleType("uvicorn"))
+    monkeypatch.setitem(sys.modules, "soundfile", types.ModuleType("soundfile"))
+    monkeypatch.setitem(sys.modules, "torch", types.ModuleType("torch"))
+    monkeypatch.setitem(sys.modules, "funasr", funasr_stub)
+    monkeypatch.setitem(sys.modules, "funasr.models", types.ModuleType("funasr.models"))
+    monkeypatch.setitem(
+        sys.modules,
+        "funasr.models.fun_asr_nano",
+        types.ModuleType("funasr.models.fun_asr_nano"),
+    )
+    monkeypatch.setitem(
+        sys.modules, "funasr.models.fun_asr_nano.inference_vllm", nano_stub
+    )
+    monkeypatch.setitem(
+        sys.modules,
+        "funasr.models.fsmn_vad_streaming",
+        types.ModuleType("funasr.models.fsmn_vad_streaming"),
+    )
+    monkeypatch.setitem(
+        sys.modules, "funasr.models.fsmn_vad_streaming.dynamic_vad", vad_stub
+    )
+
+    module_name = "serve_vllm_under_test"
+    sys.modules.pop(module_name, None)
+    spec = importlib.util.spec_from_file_location(module_name, SERVICE_PATH)
+    module = importlib.util.module_from_spec(spec)
+    assert spec.loader is not None
+    spec.loader.exec_module(module)
+    return module
+
+
+def test_openai_verbose_json_keeps_segment_speaker(monkeypatch):
+    module = load_service_module(monkeypatch)
+
+    response = module.build_openai_verbose_json(
+        {
+            "duration": 1.2,
+            "text": "hello",
+            "segments": [
+                {
+                    "start": 0.0,
+                    "end": 1.2,
+                    "text": "hello",
+                    "words": [{"word": "hello", "start": 0.0, "end": 1.2}],
+                    "speaker": "SPK0",
+                }
+            ],
+        },
+        language="en",
+    )
+
+    assert response["segments"][0]["speaker"] == "SPK0"