mvp

.gitignore

@@ -64,3 +64,6 @@ Thumbs.db
 .pytest_cache/
 .coverage
 coverage.xml
+
+# Ollama specific
+ollama-data/

coquitts/Dockerfile

@@ -8,6 +8,8 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
 	build-essential \
 	git \
 	wget \
+	espeak-ng \
+	espeak-ng-data \
  && rm -rf /var/lib/apt/lists/*
 
 COPY requirements.txt ./

coquitts/requirements.txt

@@ -1,5 +1,5 @@
 fastapi==0.100.0
 uvicorn[standard]==0.22.0
-TTS>=0.12.0
+coqui-tts==0.27.2
 soundfile==0.12.1
 numpy==1.26.0

coquitts/server.py

@@ -1,18 +1,35 @@
-from fastapi import FastAPI, HTTPException
+from fastapi import FastAPI, HTTPException, Body, BackgroundTasks
-from fastapi import Body
 from fastapi.responses import FileResponse, JSONResponse
 from TTS.api import TTS
 import tempfile
 import os
+import logging
 
 app = FastAPI()
 
-# Load a German-capable model. Model may be downloaded on first run.
+# Load TTS model at startup with a valid 4-part model name
-tts = TTS(model_name="tts_models/de/thorsten_hsmm")
+model_name = os.environ.get("TTS_MODEL", "tts_models/de/thorsten/tacotron2-DDC")
+try:
+    tts = TTS(model_name=model_name)
+    logging.info(f"Successfully loaded TTS model: {model_name}")
+except Exception as exc:
+    logging.exception("Failed to load TTS model '%s'", model_name)
+    raise RuntimeError(
+        f"Failed to load TTS model '{model_name}': {exc}.\n"
+        "Set the environment variable TTS_MODEL to a valid model id in the format 'tts_models/<lang>/<dataset>/<model>' "
+        "or install the model manually."
+    ) from exc
+
+
+def _cleanup_file(path: str) -> None:
+    try:
+        os.remove(path)
+    except Exception:
+        logging.exception("Failed to remove temporary file %s", path)
 
 
 @app.post("/speak")
-def speak(payload: dict = Body(...)):
+def speak(payload: dict = Body(...), background_tasks: BackgroundTasks = None):
     text = payload.get("text")
     language = payload.get("language", "de")
     if not text:
@@ -21,8 +38,18 @@ def speak(payload: dict = Body(...)):
     fd, path = tempfile.mkstemp(suffix=".wav")
     os.close(fd)
     try:
+        # Check if the model is multilingual before passing language parameter
+        if hasattr(tts, 'is_multi_lingual') and tts.is_multi_lingual:
             tts.tts_to_file(text=text, speaker=None, language=language, file_path=path)
+        else:
+            # For non-multilingual models, don't pass the language parameter
+            tts.tts_to_file(text=text, speaker=None, file_path=path)
+        # schedule cleanup after response has been sent
+        if background_tasks is not None:
+            background_tasks.add_task(_cleanup_file, path)
         return FileResponse(path, media_type="audio/wav", filename="response.wav")
-    finally:
+    except Exception:
-        # FileResponse will stream the file; don't remove immediately. Consumer can manage cleanup.
+        logging.exception("TTS generation failed")
-        pass
+        # try to remove file immediately on failure
+        _cleanup_file(path)
+        raise HTTPException(status_code=500, detail="TTS generation failed")

frontend/pages/index.js

@@ -31,17 +31,25 @@ export default function Home() {
   }
 
   async function sendAudio(blob) {
+    try {
       const form = new FormData()
       // Convert webm to wav on the client is complex; many servers accept webm/ogg.
       form.append('file', blob, 'recording.webm')
 
+      console.log('Sending request to backend...')
       const res = await fetch('http://localhost:8000/chat', { method: 'POST', body: form })
+      console.log('Response received:', res.status, res.statusText)
+
       if (!res.ok) {
         const text = await res.text()
         alert('Error: ' + res.status + ' ' + text)
         return
       }
+
+      console.log('Converting response to blob...')
       const audioBlob = await res.blob()
+      console.log('Audio blob created, size:', audioBlob.size)
+
       const url = URL.createObjectURL(audioBlob)
       if (audioRef.current) {
         audioRef.current.src = url
@@ -49,6 +57,10 @@ export default function Home() {
         setPlaying(true)
         audioRef.current.onended = () => setPlaying(false)
       }
+    } catch (error) {
+      console.error('Error in sendAudio:', error)
+      alert('Failed to process audio: ' + error.message)
+    }
   }
 
   return (

middleware/server.py

@@ -1,15 +1,34 @@
 from fastapi import FastAPI, File, UploadFile, HTTPException
 from fastapi.responses import StreamingResponse, JSONResponse
+from fastapi.middleware.cors import CORSMiddleware
 import httpx
 import tempfile
 import shutil
 import asyncio
+import os
+import json
+import logging
+import traceback
 
 app = FastAPI()
 
+# Add CORS middleware to allow frontend requests
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # In production, replace with specific origins like ["http://localhost:3000"]
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger("middleware")
+
 WHISPER_URL = "http://whisper:8001/transcribe"
 COQUITTS_URL = "http://coquitts:8002/speak"
-OLLAMA_URL = "http://ollama:11434/v1/complete"
+OLLAMA_URL = "http://ollama:11434/api/generate"
+LLM_MODEL = os.getenv("LLM_MODEL", "gemma3:270m")
+logger.info("Using LLM model: %s", LLM_MODEL)
 
 
 @app.post("/chat")
@@ -17,40 +36,134 @@ async def chat(file: UploadFile = File(...)):
     if not file.content_type.startswith("audio"):
         raise HTTPException(status_code=400, detail="File must be audio")
 
+    tmp_path = None
+    try:
         # save file to temp
         with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp:
             contents = await file.read()
             tmp.write(contents)
             tmp.flush()
             tmp_path = tmp.name
+            logger.info("Saved uploaded audio to %s", tmp_path)
 
         async with httpx.AsyncClient() as client:
             # Send audio to whisper
+            try:
                 with open(tmp_path, "rb") as f:
                     files = {"file": ("audio.wav", f, "audio/wav")}
                     r = await client.post(WHISPER_URL, files=files, timeout=120.0)
+            except httpx.RequestError as e:
+                logger.exception("Request to Whisper failed")
+                raise HTTPException(status_code=502, detail=f"Whisper request failed: {e}")
 
             if r.status_code != 200:
+                logger.error("Whisper returned non-200: %s body=%s", r.status_code, r.text)
                 raise HTTPException(status_code=502, detail=f"Whisper error: {r.status_code} {r.text}")
 
+            try:
                 text = r.json().get("text", "")
+            except Exception:
+                logger.exception("Failed to decode Whisper JSON: %s", r.text)
+                raise HTTPException(status_code=502, detail="Invalid JSON from Whisper")
 
-        # Send text to ollama for reasoning
+            logger.info("Whisper transcribed text: %s", text)
-        # We assume Ollama HTTP API accepts JSON {"model":"<model>", "prompt":"..."}
+
-        ollama_payload = {"model": "llama2", "prompt": text}
+            # Send text to ollama for reasoning. Ollama often streams incremental
-        ro = await client.post(OLLAMA_URL, json=ollama_payload, timeout=120.0)
+            # JSON objects (one per line) instead of returning a single JSON body.
+            # Use a streaming request and parse JSON lines as they arrive.
+            ollama_payload = {"model": LLM_MODEL, "prompt": text}
+            try:
+                async with client.stream("POST", OLLAMA_URL, json=ollama_payload, timeout=120.0) as ro:
                     if ro.status_code != 200:
-            raise HTTPException(status_code=502, detail=f"Ollama error: {ro.status_code} {ro.text}")
+                        # read body for error message
+                        body = await ro.aread()
+                        body_text = body.decode(errors="ignore")
+                        logger.error("Ollama returned non-200: %s body=%s", ro.status_code, body_text)
+                        raise HTTPException(status_code=502, detail=f"Ollama error: {ro.status_code} {body_text}")
 
-        answer_json = ro.json()
+                    parts = []
-        # Depending on API shape, try to extract text
+                    # Ollama can send multiple JSON objects line-by-line; collect 'response' parts
-        answer_text = answer_json.get("response") or answer_json.get("text") or answer_json.get("output") or str(answer_json)
+                    async for raw_line in ro.aiter_lines():
+                        if not raw_line:
+                            continue
+                        line = raw_line.strip()
+                        # handle Server-Sent Events style 'data: ...' prefixes
+                        if line.startswith("data:"):
+                            line = line[len("data:"):].strip()
+                        try:
+                            j = json.loads(line)
+                        except Exception:
+                            logger.debug("Skipping non-JSON line from Ollama: %s", line)
+                            continue
+
+                        # prefer 'response', fallback to other candidate fields
+                        piece = j.get("response") or j.get("text") or j.get("output")
+                        if piece:
+                            parts.append(str(piece))
+
+                        # stop when stream indicates completion
+                        if j.get("done") or j.get("done_reason"):
+                            break
+
+                    answer_text = "".join(parts).strip()
+            except httpx.RequestError as e:
+                logger.exception("Request to Ollama failed")
+                raise HTTPException(status_code=502, detail=f"Ollama request failed: {e}")
+
+            if not answer_text:
+                # as a last resort, try to fetch full text non-streamed
+                try:
+                    fallback = await client.post(OLLAMA_URL, json=ollama_payload, timeout=30.0)
+                    if fallback.status_code == 200:
+                        try:
+                            fallback_json = fallback.json()
+                            answer_text = (
+                                fallback_json.get("response")
+                                or fallback_json.get("text")
+                                or fallback_json.get("output")
+                                or str(fallback_json)
+                            )
+                        except Exception:
+                            answer_text = (await fallback.aread()).decode(errors="ignore")
+                    else:
+                        logger.debug("Ollama fallback non-200: %s %s", fallback.status_code, await fallback.aread())
+                except Exception:
+                    # nothing more to do; keep answer_text empty and let downstream handle it
+                    logger.debug("Ollama fallback failed", exc_info=True)
+
+            logger.info("Ollama returned: %s", answer_text)
 
             # Send answer to coquitts to generate German audio
             coquitts_payload = {"text": answer_text, "language": "de"}
+            try:
                 co = await client.post(COQUITTS_URL, json=coquitts_payload, timeout=120.0)
+            except httpx.RequestError as e:
+                logger.exception("Request to CoquiTTS failed")
+                raise HTTPException(status_code=502, detail=f"CoquiTTS request failed: {e}")
+
             if co.status_code != 200:
+                logger.error("CoquiTTS returned non-200: %s body=%s", co.status_code, co.text)
                 raise HTTPException(status_code=502, detail=f"CoquiTTS error: {co.status_code} {co.text}")
 
-        # stream the audio back
+            logger.info("CoquiTTS returned audio, streaming back to client")
-        return StreamingResponse(co.aiter_bytes(), media_type="audio/wav")
+
+            # Get the audio content as bytes instead of streaming
+            audio_content = await co.aread()
+
+            # Return the audio as a regular response with proper headers
+            return StreamingResponse(
+                iter([audio_content]),
+                media_type="audio/wav",
+                headers={
+                    "Content-Length": str(len(audio_content)),
+                    "Accept-Ranges": "bytes"
+                }
+            )
+    finally:
+        # cleanup temp file
+        try:
+            if tmp_path and os.path.exists(tmp_path):
+                os.remove(tmp_path)
+                logger.info("Removed temp file %s", tmp_path)
+        except Exception:
+            logger.warning("Failed to remove temp file %s: %s", tmp_path, traceback.format_exc())

whisper/requirements.txt

@@ -1,6 +1,6 @@
 fastapi==0.100.0
 uvicorn[standard]==0.22.0
-whisper==1.1.10
+openai-whisper
 pydub==0.25.1
 aiofiles==23.1.0
 python-multipart==0.0.6

whisper/server.py

@@ -3,30 +3,91 @@ from fastapi.responses import JSONResponse
 import whisper
 import tempfile
 import shutil
+import os
+import logging
+from pydub import AudioSegment
 
+logging.basicConfig(level=logging.INFO)
 app = FastAPI()
 
-model = whisper.load_model("small")
+# Load model at startup
+try:
+    model = whisper.load_model("small")
+except Exception:
+    logging.exception("Failed to load Whisper model")
+    # re-raise so container fails fast if model can't be loaded
+    raise
+
+
+def convert_to_wav(src_path: str) -> str:
+    """Convert an audio file (webm/ogg/mp3/...) to a 16 kHz mono WAV file using pydub/ffmpeg.
+
+    Returns path to the new WAV file (caller is responsible for cleanup).
+    """
+    audio = AudioSegment.from_file(src_path)
+    audio = audio.set_frame_rate(16000).set_channels(1)
+    wav_tmp = tempfile.NamedTemporaryFile(delete=False, suffix=".wav")
+    wav_tmp.close()
+    audio.export(wav_tmp.name, format="wav")
+    return wav_tmp.name
 
 
 @app.post("/transcribe")
 async def transcribe(file: UploadFile = File(...)):
-    if not file.content_type.startswith("audio"):
+    if not file.content_type or not file.content_type.startswith("audio"):
         raise HTTPException(status_code=400, detail="File must be audio")
 
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp:
+    # preserve original extension if possible
+    filename = file.filename or "upload"
+    ext = os.path.splitext(filename)[1] or ""
+    if not ext:
+        # try to infer common extension from content-type
+        if "webm" in file.content_type:
+            ext = ".webm"
+        elif "ogg" in file.content_type or "opus" in file.content_type:
+            ext = ".ogg"
+        elif "mpeg" in file.content_type or "mp3" in file.content_type:
+            ext = ".mp3"
+        else:
+            ext = ".wav"
+
+    with tempfile.NamedTemporaryFile(delete=False, suffix=ext) as tmp:
         contents = await file.read()
         tmp.write(contents)
         tmp.flush()
         tmp_path = tmp.name
 
+    logging.info("Received upload %s (%d bytes, content-type=%s)", filename, os.path.getsize(tmp_path), file.content_type)
+
+    # If the uploaded file is not a WAV, convert it to WAV first to ensure ffmpeg/pydub compatibility.
+    wav_path = tmp_path
+    converted = False
     try:
-        result = model.transcribe(tmp_path, language=None)
+        if not tmp_path.lower().endswith('.wav'):
+            try:
+                wav_path = convert_to_wav(tmp_path)
+                converted = True
+                logging.info("Converted to wav: %s (size=%d)", wav_path, os.path.getsize(wav_path))
+            except Exception as e:
+                # conversion failed; return a helpful error including ffmpeg/pydub message
+                logging.exception("Failed to convert uploaded audio to wav")
+                # try to surface the underlying error text
+                raise HTTPException(status_code=400, detail=f"Failed to convert audio: {e}")
+
+        try:
+            result = model.transcribe(wav_path, language=None)
             text = result.get("text", "")
-    finally:
+        except RuntimeError as e:
-        try:
+            # likely ffmpeg failed while loading audio; include error message for debugging
-            shutil.os.remove(tmp_path)
+            logging.exception("Whisper failed to transcribe audio")
-        except Exception:
+            raise HTTPException(status_code=500, detail=str(e))
-            pass
 
         return JSONResponse({"text": text})
+    finally:
+        # cleanup temp files
+        for path in {tmp_path, wav_path}:
+            try:
+                if path and os.path.exists(path):
+                    os.remove(path)
+            except Exception:
+                logging.exception("Failed to remove temp file %s", path)