feat: remote Whisper via whisper.base_url — OpenAI-compatible upload

api/pipeline.py

@@ -37,6 +37,7 @@ async def run_pipeline():
             language=cfg["whisper"]["language"],
             model_name=cfg["whisper"]["model"],
             device=cfg["whisper"]["device"],
+            base_url=cfg["whisper"].get("base_url", ""),
         )
         await broadcast({"event": "transcribed", "raw": raw_text})
 

tests/test_transcription.py

@@ -1,4 +1,5 @@
 import asyncio
+import pytest
 from unittest.mock import MagicMock
 
 
@@ -23,3 +24,26 @@ def test_transcribe_file_calls_whisper(tmp_path):
     result = asyncio.run(eng.transcribe_file(str(wav), language="de"))
     assert result == "Hallo Welt"
     mock_model.transcribe.assert_called_once_with(str(wav), language="de")
+
+
+@pytest.mark.asyncio
+async def test_transcribe_uses_remote_when_base_url_set(tmp_path):
+    import wave, struct
+    wav = tmp_path / "test.wav"
+    with wave.open(str(wav), "wb") as wf:
+        wf.setnchannels(1); wf.setsampwidth(2); wf.setframerate(16000)
+        wf.writeframes(struct.pack("<100h", *([0] * 100)))
+
+    import respx, httpx
+    from transcription import TranscriptionEngine
+    eng = TranscriptionEngine()
+
+    with respx.mock:
+        respx.post("http://beastix:8000/v1/audio/transcriptions").mock(
+            return_value=httpx.Response(200, json={"text": "Hallo Welt"})
+        )
+        result = await eng.transcribe_file(
+            str(wav), language="de", model_name="large-v3",
+            device="auto", base_url="http://beastix:8000",
+        )
+    assert result == "Hallo Welt"

transcription.py

@@ -1,4 +1,5 @@
 import asyncio
+import httpx
 
 
 class TranscriptionEngine:
@@ -23,6 +24,27 @@ class TranscriptionEngine:
         language: str = "de",
         model_name: str = "large-v3",
         device: str = "auto",
+        base_url: str = "",
+    ) -> str:
+        if base_url:
+            return await self._transcribe_remote(audio_path, language, model_name, base_url)
+        return await self._transcribe_local(audio_path, language, model_name, device)
+
+    async def _transcribe_remote(
+        self, audio_path: str, language: str, model_name: str, base_url: str
+    ) -> str:
+        async with httpx.AsyncClient(timeout=300) as client:
+            with open(audio_path, "rb") as f:
+                r = await client.post(
+                    f"{base_url}/v1/audio/transcriptions",
+                    files={"file": ("audio.wav", f, "audio/wav")},
+                    data={"model": model_name, "language": language},
+                )
+            r.raise_for_status()
+            return r.json()["text"]
+
+    async def _transcribe_local(
+        self, audio_path: str, language: str, model_name: str, device: str
     ) -> str:
         loop = asyncio.get_event_loop()
         model = self._get_model(model_name, device)