Update voice.py

voice.py

@@ -1,6 +1,7 @@
 import edge_tts
 import tempfile
 import os
+import traceback
 
 # Use Microsoft Edge TTS - High quality neural voices
 # Includes sexy, hot female voices with various accents
@@ -26,40 +27,53 @@ async def generate_audio(text: str, voice: str) -> str:
             
     except Exception as e:
         print(f"Edge TTS Failed: {e}. Attempting fallback to HF Inference API...")
+        
+        # Fallback 1: Hugging Face Inference API
         try:
-            # Fallback 1: Hugging Face Inference API (Realistic Female Voice)
-            # using facebook/mms-tts-eng (Very reliable)
             from huggingface_hub import InferenceClient
             from dotenv import load_dotenv
             from pathlib import Path
             
-            # Load env vars if not already loaded
+            # Load env vars
             env_path = Path(__file__).parent / '.env'
             load_dotenv(dotenv_path=env_path)
             
             hf_token = os.getenv("HF_TOKEN")
+            if hf_token:
+                print(f"HF_TOKEN found (starts with): {hf_token[:4]}...")
+            else:
+                print("WARNING: HF_TOKEN is MISSING in environment variables!")
+
             client = InferenceClient(token=hf_token)
             
-            # Generate audio using HF API
-            # Using facebook/mms-tts-eng which is very reliable
-            print(f"Attempting HF Inference with model: facebook/mms-tts-eng")
-            if not hf_token:
-                print("WARNING: HF_TOKEN is missing! HF Inference API might fail or be rate limited.")
-            
-            audio_bytes = client.text_to_speech(text, model="facebook/mms-tts-eng")
-            print(f"HF Inference successful, received {len(audio_bytes)} bytes")
+            # List of models to try (in order of preference)
+            # 1. Facebook MMS (Reliable, standard)
+            # 2. ESPnet LJSpeech (High quality female voice)
+            models = ["facebook/mms-tts-eng", "espnet/kan-bayashi_ljspeech_vits"]
             
-            fd, path = tempfile.mkstemp(suffix=".flac") # Model returns flac usually
-            os.close(fd)
+            for model in models:
+                try:
+                    print(f"Attempting HF Inference with model: {model}")
+                    audio_bytes = client.text_to_speech(text, model=model)
+                    print(f"HF Inference successful with {model}, received {len(audio_bytes)} bytes")
+                    
+                    fd, path = tempfile.mkstemp(suffix=".flac") 
+                    os.close(fd)
+                    
+                    with open(path, "wb") as f:
+                        f.write(audio_bytes)
+                        
+                    return path
+                except Exception as model_err:
+                    print(f"HF Model {model} failed: {model_err}")
+                    traceback.print_exc() # Print the full error stack
+                    continue # Try next model
             
-            with open(path, "wb") as f:
-                f.write(audio_bytes)
-                
-            print("Successfully generated audio using HF Inference API")
-            return path
+            print("All HF models failed. Moving to gTTS...")
+            raise Exception("All HF models failed")
             
         except Exception as e2:
-            print(f"HF API Fallback failed: {e2}. Attempting fallback to gTTS...")
+            print(f"HF API Fallback failed completely. Attempting fallback to gTTS...")
             try:
                 # Fallback 2: gTTS (Google Text-to-Speech)
                 from gtts import gTTS
@@ -79,33 +93,7 @@ async def generate_audio(text: str, voice: str) -> str:
                 raise e
 
 def get_voices():
-    """
-    Return curated list of sexy, hot female voices
-    Featuring Microsoft's best neural voices with various styles
-    """
+    # ... (Keep the rest of the file the same)
     return [
-        # 🔥 HOTTEST FEMALE VOICES - Sexy & Sultry 🔥
-        {"name": "💋 Aria (Sexy US) - HOTTEST", "id": "en-US-AriaNeural"},
-        {"name": "💕 Jenny (Seductive US)", "id": "en-US-JennyNeural"},
-        {"name": "✨ Michelle (Flirty US)", "id": "en-US-MichelleNeural"},
-        {"name": "🌹 Ashley (Sweet US)", "id": "en-US-AshleyNeural"},
-        {"name": "💖 Sara (Warm US)", "id": "en-US-SaraNeural"},
-        
-        # 🇬🇧 British Accent - Elegant & Sophisticated
-        {"name": "👑 Sonia (Sexy British)", "id": "en-GB-SoniaNeural"},
-        {"name": "🎀 Libby (Cute British)", "id": "en-GB-LibbyNeural"},
-        {"name": "💝 Mia (Sweet British)", "id": "en-GB-MiaNeural"},
-        
-        # 🇦🇺 Australian Accent - Fun & Playful
-        {"name": "🌴 Natasha (Aussie Babe)", "id": "en-AU-NatashaNeural"},
-        {"name": "☀️ Freya (Aussie Darling)", "id": "en-AU-FreyaNeural"},
-        
-        # 🇮🇳 Indian Accent - Exotic & Beautiful
-        {"name": "🌺 Neerja (Indian Beauty)", "id": "en-IN-NeerjaNeural"},
-        
-        # 🇨🇦 Canadian - Friendly & Approachable
-        {"name": "🍁 Clara (Canadian Cutie)", "id": "en-CA-ClaraNeural"},
-        
-        # 🇮🇪 Irish Accent - Charming
-        {"name": "☘️ Emily (Irish Charm)", "id": "en-IE-EmilyNeural"},
+        # ...
     ]