fix: make transcript refinement language-aware

backend/tests/test_capture_language_pipeline.py

@@ -0,0 +1,117 @@
+from io import BytesIO
+from types import SimpleNamespace
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+from fastapi import UploadFile
+
+from backend.backends import TranscriptionResult
+from backend.mcp_server import tools
+from backend.routes import transcription as transcription_route
+from backend.services import captures, transcribe
+from backend.services.refinement import RefinementFlags
+from backend.utils import audio as audio_utils
+
+
+@pytest.mark.asyncio
+async def test_retranscribe_persists_auto_detected_language(monkeypatch, tmp_path):
+    audio_path = tmp_path / "capture.wav"
+    audio_path.write_bytes(b"audio")
+    row = SimpleNamespace(
+        id="capture-1",
+        audio_path="captures/capture.wav",
+        transcript_raw="old",
+        transcript_refined="old refined",
+        stt_model="base",
+        language=None,
+        llm_model="0.6B",
+        refinement_flags="{}",
+    )
+    db = MagicMock()
+    db.query.return_value.filter.return_value.first.return_value = row
+    whisper = SimpleNamespace(
+        model_size="turbo",
+        transcribe_with_metadata=AsyncMock(return_value=TranscriptionResult(text="bonjour le monde", language="fr")),
+    )
+    monkeypatch.setattr(captures.config, "resolve_storage_path", lambda _path: audio_path)
+    monkeypatch.setattr(captures, "get_whisper_model", lambda: whisper)
+    monkeypatch.setattr(captures, "_to_response", lambda value: value)
+
+    result = await captures.retranscribe_capture(
+        capture_id="capture-1",
+        stt_model=None,
+        language=None,
+        db=db,
+    )
+
+    assert result.transcript_raw == "bonjour le monde"
+    assert result.language == "fr"
+    assert result.transcript_refined is None
+
+
+@pytest.mark.asyncio
+async def test_mcp_transcribe_returns_detected_language(monkeypatch, tmp_path):
+    audio_path = tmp_path / "sample.wav"
+    audio_path.write_bytes(b"audio")
+    whisper = SimpleNamespace(
+        model_size="turbo",
+        is_loaded=lambda: True,
+        transcribe_with_metadata=AsyncMock(return_value=TranscriptionResult(text="hola mundo", language="es")),
+    )
+    monkeypatch.setattr(transcribe, "get_whisper_model", lambda: whisper)
+    monkeypatch.setattr(audio_utils, "load_audio", lambda _path: ([0.0] * 16000, 16000))
+
+    result = await tools._transcribe_file(audio_path, language=" ES ", model=None)
+
+    assert result["text"] == "hola mundo"
+    assert result["language"] == "es"
+    assert whisper.transcribe_with_metadata.await_args.args[1] == "es"
+
+
+@pytest.mark.asyncio
+async def test_http_transcribe_returns_detected_language(monkeypatch):
+    whisper = SimpleNamespace(
+        model_size="turbo",
+        is_loaded=lambda: True,
+        transcribe_with_metadata=AsyncMock(return_value=TranscriptionResult(text="hallo welt", language="de")),
+    )
+    monkeypatch.setattr(transcribe, "get_whisper_model", lambda: whisper)
+    monkeypatch.setattr(audio_utils, "load_audio", lambda _path: ([0.0] * 16000, 16000))
+    upload = UploadFile(filename="sample.wav", file=BytesIO(b"audio"))
+
+    response = await transcription_route.transcribe_audio(
+        upload,
+        language=" AUTO ",
+        model=None,
+    )
+
+    assert response.text == "hallo welt"
+    assert response.language == "de"
+    assert whisper.transcribe_with_metadata.await_args.args[1] is None
+
+
+@pytest.mark.asyncio
+async def test_capture_refinement_receives_persisted_language(monkeypatch):
+    row = SimpleNamespace(
+        id="capture-1",
+        transcript_raw="打开 package.json",
+        transcript_refined=None,
+        language="zh",
+        llm_model=None,
+        refinement_flags=None,
+    )
+    db = MagicMock()
+    db.query.return_value.filter.return_value.first.return_value = row
+    refine = AsyncMock(return_value=("打开 package.json。", "0.6B"))
+    monkeypatch.setattr(captures, "refine_transcript", refine)
+    monkeypatch.setattr(captures, "_to_response", lambda value: value)
+
+    result = await captures.refine_capture(
+        capture_id="capture-1",
+        flags=RefinementFlags(),
+        model_size="0.6B",
+        db=db,
+    )
+
+    assert result.transcript_refined == "打开 package.json。"
+    assert refine.await_args.kwargs["language"] == "zh"