fix: voice STT path fix + execSync error handling + fetch download

scripts/stt.py

@@ -1,83 +1,70 @@
 #!/usr/bin/env python3
-"""
-Vosk STT — Transcribe OGG/voice to text.
-Usage: python3 stt.py <input_file> [language]
-  input_file: path to audio file (ogg, wav, mp3, etc.)
-  language: 'en' (default) or 'ge' — Georgian model
-Output: JSON to stdout: {"text": "...", "confidence": 0.95}
-Exit codes: 0=success, 1=no speech, 2=error
-"""
+"""Vosk STT — transcribe audio file to text. Optimized for speed."""
 import sys, os, json, subprocess, tempfile, wave
 
+os.environ['VOSK_LOG_LEVEL'] = '-1'
+
 def main():
     if len(sys.argv) < 2:
-        print(json.dumps({"error": "Usage: stt.py <audio_file> [en|ge]"}))
+        print(json.dumps({"error": "Usage: stt.py <audio_file>"}))
         sys.exit(2)
 
     audio_file = sys.argv[1]
-    lang = sys.argv[2] if len(sys.argv) > 2 else 'en'
+    model_path = '/home/uroma2/vosk-model'
 
-    # Suppress vosk logging
-    os.environ['VOSK_LOG_LEVEL'] = '-1'
-
-    model_path = {
-        'en': '/home/uroma2/vosk-model',
-        'ge': '/home/uroma2/vosk-model-ge',
-    }.get(lang, '/home/uroma2/vosk-model')
-
-    if not os.path.isdir(model_path):
-        print(json.dumps({"error": f"Model not found: {model_path}"}))
+    # Convert to 16kHz mono WAV via ffmpeg — fast pipe, no temp file overhead
+    try:
+        proc = subprocess.Popen(
+            ['ffmpeg', '-y', '-i', audio_file, '-ar', '16000', '-ac', '1',
+             '-f', 'wav', '-v', 'error', '-'],
+            stdout=subprocess.PIPE, stderr=subprocess.PIPE
+        )
+        wav_data = proc.stdout.read()
+        proc.wait(timeout=15)
+        if proc.returncode != 0 or len(wav_data) < 44:
+            print(json.dumps({"error": "ffmpeg conversion failed"}))
+            sys.exit(2)
+    except Exception as e:
+        print(json.dumps({"error": str(e)}))
         sys.exit(2)
 
-    # Convert to 16kHz mono WAV using ffmpeg
-    with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as tmp:
-        wav_path = tmp.name
-
+    # Write wav_data to temp file for wave module (it needs a file path)
+    tmp = tempfile.NamedTemporaryFile(suffix='.wav', delete=False)
     try:
-        result = subprocess.run(
-            ['ffmpeg', '-y', '-i', audio_file, '-ar', '16000', '-ac', '1', '-f', 'wav', wav_path],
-            capture_output=True, timeout=30
-        )
-        if result.returncode != 0:
-            print(json.dumps({"error": f"ffmpeg failed: {result.stderr.decode()[:200]}"}))
-            sys.exit(2)
+        tmp.write(wav_data)
+        tmp.close()
 
         import vosk
         model = vosk.Model(model_path)
         rec = vosk.KaldiRecognizer(model, 16000)
 
-        wf = wave.open(wav_path, 'rb')
-        if wf.getnchannels() != 1 or wf.getsampwidth() != 2 or wf.getframerate() != 16000:
-            print(json.dumps({"error": "Audio format mismatch after conversion"}))
-            sys.exit(2)
-
-        results = []
-        while True:
-            data = wf.readframes(4000)
-            if len(data) == 0:
-                break
-            if rec.AcceptWaveform(data):
-                results.append(json.loads(rec.Result()))
-
-        # Final result
-        final = json.loads(rec.FinalResult())
-        results.append(final)
-
-        # Extract text
+        wf = wave.open(tmp.name, 'rb')
         text_parts = []
         total_conf = 0
         conf_count = 0
-        for r in results:
-            t = r.get('text', '').strip()
-            if t:
-                text_parts.append(t)
-            # Confidence from final result
-            if 'result' in r:
-                for word in r.get('result', []):
-                    if 'conf' in word:
-                        total_conf += word['conf']
+
+        while True:
+            data = wf.readframes(4000)
+            if not data:
+                break
+            if rec.AcceptWaveform(data):
+                r = json.loads(rec.Result())
+                t = r.get('text', '').strip()
+                if t:
+                    text_parts.append(t)
+                    for w in r.get('result', []):
+                        total_conf += w.get('conf', 0)
                         conf_count += 1
 
+        # Final partial
+        r = json.loads(rec.FinalResult())
+        t = r.get('text', '').strip()
+        if t:
+            text_parts.append(t)
+            for w in r.get('result', []):
+                total_conf += w.get('conf', 0)
+                conf_count += 1
+
         text = ' '.join(text_parts).strip()
         confidence = round(total_conf / conf_count, 2) if conf_count > 0 else 0.0
 
@@ -86,13 +73,12 @@ def main():
             sys.exit(1)
 
         print(json.dumps({"text": text, "confidence": confidence}))
-
     except Exception as e:
         print(json.dumps({"error": str(e)}))
         sys.exit(2)
     finally:
-        if os.path.exists(wav_path):
-            os.unlink(wav_path)
+        try: os.unlink(tmp.name)
+        except: pass
 
 if __name__ == '__main__':
     main()