Update app.py

app.py

@@ -51,9 +51,14 @@ if SF_ENABLED:
 ENCRYPTION_KEY = os.getenv("ENCRYPTION_KEY") or Fernet.generate_key()
 fernet = Fernet(ENCRYPTION_KEY)
 
-# Initialize text-to-speech
-tts_engine = pyttsx3.init()
-tts_engine.setProperty("rate", 150)
+# Initialize text-to-speech with fallback
+tts_engine = None
+try:
+    tts_engine = pyttsx3.init()
+    tts_engine.setProperty("rate", 150)
+    logger.info("pyttsx3 initialized successfully")
+except Exception as e:
+    logger.warning(f"Failed to initialize pyttsx3: {str(e)}. Text-to-speech disabled.")
 
 # Initialize local models
 @retry(stop=stop_after_attempt(3), wait=wait_fixed(2))
@@ -300,6 +305,9 @@ def generate_report():
 
 async def speak_response(text):
     """Convert text to speech."""
+    if not tts_engine:
+        logger.warning("Text-to-speech unavailable; skipping")
+        return
     try:
         def sync_speak():
             tts_engine.say(text)
@@ -388,6 +396,55 @@ async def analyze_voice(audio_file, language="en", user_id="anonymous", consent_
         logger.error(f"Voice analysis failed: {str(e)}")
         return f"Error: {str(e)}"
 
+async def test_with_sample_audio(language="en", user_id="anonymous", consent_granted=True):
+    """Test with synthetic audio."""
+    temp_dir = os.path.join(tempfile.gettempdir(), "audio_samples")
+    if not ensure_writable_dir(temp_dir):
+        fallback_dir = os.path.join(os.getcwd(), "temp_audio_samples")
+        if not ensure_writable_dir(fallback_dir):
+            logger.error(f"Temp directories {temp_dir} and {fallback_dir} not writable")
+            return f"Error: Temp directories not writable"
+        temp_dir = fallback_dir
+    
+    sample_audio_path = os.path.join(temp_dir, "dummy_test.wav")
+    logger.info(f"Generating synthetic audio at: {sample_audio_path}")
+    sr = 16000
+    t = np.linspace(0, 2, 2 * sr)
+    freq_mod = 440 + 10 * np.sin(2 * np.pi * 0.5 * t)
+    amplitude_mod = 0.5 + 0.1 * np.sin(2 * np.pi * 0.3 * t)
+    noise = 0.01 * np.random.normal(0, 1, len(t))
+    dummy_audio = amplitude_mod * np.sin(2 * np.pi * freq_mod * t) + noise
+    try:
+        soundfile.write(dummy_audio, sr, sample_audio_path)
+        logger.info(f"Generated synthetic audio: {sample_audio_path}")
+    except Exception as e:
+        logger.error(f"Failed to write synthetic audio: {str(e)}")
+        return f"Error: Failed to generate synthetic audio: {str(e)}"
+    
+    if not os.path.exists(sample_audio_path):
+        logger.error(f"Synthetic audio not created: {sample_audio_path}")
+        return f"Error: Synthetic audio not created: {sample_audio_path}"
+    
+    mock_transcription = "I have a cough and sore throat"
+    logger.info(f"Mock transcription: {mock_transcription}")
+    prediction, score = analyze_symptoms(mock_transcription)
+    feedback = (
+        "No health condition detected, consult a doctor if symptoms persist. This is not a medical diagnosis."
+        if prediction == "No health condition detected"
+        else f"Possible {prediction.lower()} detected, consult a doctor. This is not a medical diagnosis."
+    )
+    logger.info(f"Test feedback: {feedback}, Prediction: {prediction}, Score: {score:.4f}")
+    
+    # Save to Salesforce
+    save_to_salesforce(user_id, mock_transcription, prediction, score, feedback, consent_granted)
+    
+    try:
+        os.remove(sample_audio_path)
+        logger.debug(f"Deleted test audio: {sample_audio_path}")
+    except Exception:
+        pass
+    return feedback
+
 async def voicebot_interface(audio_file, language="en", user_id="anonymous", consent_granted=True):
     """Gradio interface wrapper."""
     return await analyze_voice(audio_file, language, user_id, consent_granted)