feat: processing pipeline — Whisper + resemblyzer + speaker match + SQLite write

Implements process_utterance() with concurrent STT/embedding via asyncio.gather,
speaker matching with configurable thresholds, utterance DB write, and WAV clip save.
httpx imported lazily to keep the dev environment functional without full install.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

tests/test_processor.py

@@ -0,0 +1,89 @@
+import pytest
+import numpy as np
+from datetime import datetime, timezone
+from unittest.mock import AsyncMock, MagicMock, patch
+
+# Pre-import so mocker.patch can resolve the module before the test's local import
+import app.pipeline.processor  # noqa: F401
+
+
+@pytest.mark.asyncio
+async def test_process_utterance_known_speaker(mocker, settings, db):
+    # Setup: insert a room and speaker with embedding
+    db.execute("INSERT INTO rooms (name) VALUES (?)", ("Kitchen",))
+    db.execute("INSERT INTO speakers (name) VALUES (?)", ("Jeremy",))
+    db.commit()
+    room = db.execute("SELECT id FROM rooms WHERE name='Kitchen'").fetchone()
+    speaker = db.execute("SELECT id FROM speakers WHERE name='Jeremy'").fetchone()
+
+    from app.pipeline.recognition import pack_embedding
+    ref_emb = np.array([1.0] + [0.0] * 255, dtype=np.float32)
+    db.execute(
+        "INSERT INTO voice_embeddings (speaker_id, embedding) VALUES (?,?)",
+        (speaker["id"], pack_embedding(ref_emb)),
+    )
+    db.commit()
+
+    # Mock Whisper HTTP call
+    mocker.patch(
+        "app.pipeline.processor.transcribe_audio",
+        new=AsyncMock(return_value="hello world"),
+    )
+    # Mock resemblyzer — return a very similar embedding
+    query_emb = np.array([0.99] + [0.0] * 255, dtype=np.float32)
+    mocker.patch("app.pipeline.processor.embed_audio", return_value=query_emb)
+    # Mock clip saving
+    mocker.patch("app.pipeline.processor.save_clip", return_value="/data/clips/test.wav")
+
+    from app.pipeline.processor import process_utterance
+    start = datetime(2026, 1, 1, 10, 0, 0, tzinfo=timezone.utc)
+    end = datetime(2026, 1, 1, 10, 0, 3, tzinfo=timezone.utc)
+
+    utterance_id = await process_utterance(
+        room_id=room["id"],
+        audio_bytes=b"\x00" * 100,
+        start_time=start,
+        end_time=end,
+        settings=settings,
+        db=db,
+    )
+
+    assert utterance_id is not None
+    row = db.execute("SELECT * FROM utterances WHERE id=?", (utterance_id,)).fetchone()
+    assert row["transcript"] == "hello world"
+    assert row["match_status"] == "known"
+    assert row["speaker_id"] == speaker["id"]
+
+
+@pytest.mark.asyncio
+async def test_process_utterance_unknown_speaker(mocker, settings, db):
+    db.execute("INSERT INTO rooms (name) VALUES (?)", ("Office",))
+    db.commit()
+    room = db.execute("SELECT id FROM rooms WHERE name='Office'").fetchone()
+
+    mocker.patch(
+        "app.pipeline.processor.transcribe_audio",
+        new=AsyncMock(return_value="test transcript"),
+    )
+    mocker.patch(
+        "app.pipeline.processor.embed_audio",
+        return_value=np.zeros(256, dtype=np.float32),
+    )
+    mocker.patch("app.pipeline.processor.save_clip", return_value="/data/clips/test.wav")
+
+    from app.pipeline.processor import process_utterance
+    start = datetime(2026, 1, 1, 10, 0, 0, tzinfo=timezone.utc)
+    end = datetime(2026, 1, 1, 10, 0, 2, tzinfo=timezone.utc)
+
+    utterance_id = await process_utterance(
+        room_id=room["id"],
+        audio_bytes=b"\x00" * 100,
+        start_time=start,
+        end_time=end,
+        settings=settings,
+        db=db,
+    )
+
+    row = db.execute("SELECT * FROM utterances WHERE id=?", (utterance_id,)).fetchone()
+    assert row["match_status"] == "unknown"
+    assert row["speaker_id"] is None