Update app.py

app.py

@@ -3,24 +3,24 @@ import pandas as pd
 import uuid
 import shutil
 import re
+from gtts import gTTS
 from sentence_transformers import SentenceTransformer, util
 import os
 import tempfile
-import asyncio
-import edge_tts
 
 # Load Bhagavad Gita dataset
 df = pd.read_csv("bhagavad_gita.csv")
 
-# Load sentence transformer model and precompute embeddings (once)
+# Load sentence transformer model (semantic search)
 model = SentenceTransformer("all-MiniLM-L6-v2")
 verse_embeddings = model.encode(df['meaning_in_english'].tolist(), convert_to_tensor=True)
 
 bg_music_path = "krishna_bg_music.mp3"
 
-# Create temp directory for audio files
+# Temporary directory for generated audio
 TEMP_DIR = tempfile.mkdtemp()
 
+
 def shorten_explanation(text, max_sentences=2):
     sentences = text.split('. ')
     shortened = '. '.join(sentences[:max_sentences]).strip()
@@ -28,43 +28,30 @@ def shorten_explanation(text, max_sentences=2):
         shortened += '.'
     return shortened
 
+
 def clean_english(text):
     text = re.sub(r'[^\x00-\x7F]+', ' ', text)
     text = ' '.join(text.split())
     return text
 
-async def generate_voice_edge_tts_async(text, use_krishna_voice):
-    """Generate speech using Edge TTS with en-IN-PrabhatNeural."""
+
+def generate_voice(text):
+    """Generate offline TTS using gTTS."""
     if not text.strip():
         return None
-
     filename = os.path.join(TEMP_DIR, f"voice_{uuid.uuid4()}.mp3")
-
     try:
-        communicate = edge_tts.Communicate(
-            text=text,
-            voice="en-IN-PrabhatNeural",
-            rate="-2%",
-            volume="+0%"
-        )
-        await communicate.save(filename)
+        tts = gTTS(text=text, lang="en", tld="com")
+        tts.save(filename)
         return filename
     except Exception as e:
-        print(f"Edge TTS ERROR: {e}")
+        print(f"Voice generation failed: {e}")
         return None
 
-def generate_voice_edge_tts(text, use_krishna_voice):
-    """Wrapper to run the async Edge TTS speech synthesis synchronously."""
-    try:
-        return asyncio.run(generate_voice_edge_tts_async(text, use_krishna_voice))
-    except RuntimeError:
-        loop = asyncio.get_event_loop()
-        return loop.run_until_complete(generate_voice_edge_tts_async(text, use_krishna_voice))
 
 def get_unique_bgm():
     if not os.path.exists(bg_music_path):
         return None
-
     unique_path = os.path.join(TEMP_DIR, f"bgm_{uuid.uuid4()}.mp3")
     try:
         shutil.copy(bg_music_path, unique_path)
@@ -73,7 +60,8 @@ def get_unique_bgm():
         print(f"BGM Error: {e}")
         return None
 
-def versewise_bot(question, play_music, use_krishna_voice):
+
+def versewise_bot(question, play_music):
     if not question.strip():
         return "Please ask a valid question.", None, None
 
@@ -98,11 +86,13 @@ def versewise_bot(question, play_music, use_krishna_voice):
 🌼 Stay strong — Krishna walks with you."""
 
     voice_text = clean_english(f"{translation}. {explanation}")
-    audio_path = generate_voice_edge_tts(voice_text, use_krishna_voice)
+    audio_path = generate_voice(voice_text)
+
     music = get_unique_bgm() if play_music else None
 
     return reply, audio_path, music
 
+
 def get_quote_of_the_day():
     verse = df.sample(1).iloc[0]
     sanskrit = verse['verse_in_sanskrit']
@@ -112,9 +102,10 @@ def get_quote_of_the_day():
     <i>[translate:{sanskrit[:60]}...]</i><br>
     <span style="color:#2d2d2d;">"{translation}"</span></div>"""
 
+
 custom_css = """
 body, .gradio-container, .gradio-interface, html {
-  background-image: url('https://static.vecteezy.com/system/resources/previews/022/592/272/large_2x/image-of-divine-beautiful-closed-eyes-blue-colored-krishna-generative-ai-free-photo.jpeg') !important;
+  background-image: url('https://static.vecteezy.com/system/resources/previews/022/592/272/large_2x/image-of-divine-...' ) !important;
   background-size: cover !important;
   background-repeat: no-repeat !important;
   background-position: center center !important;
@@ -134,12 +125,11 @@ interface = gr.Interface(
     fn=versewise_bot,
     inputs=[
         gr.Textbox(label="Ask Krishna", placeholder="Why am I struggling in life?", lines=2),
-        gr.Checkbox(label="Play Background Music", value=True),
-        gr.Checkbox(label="Use Krishna's Voice (Male Voice)", value=True)
+        gr.Checkbox(label="Play Background Music", value=True)
     ],
     outputs=[
         gr.Textbox(label="🧘‍♂ Krishna's Answer"),
-        gr.Audio(label="🔊 Listen to Krishna's Voice", type="filepath"),
+        gr.Audio(label="🔊 Krishna Speaks", type="filepath"),
         gr.Audio(label="🎶 Background Music", autoplay=True, type="filepath")
     ],
     title="🕉 VerseWise - Divine Wisdom from the Gita",
@@ -153,3 +143,4 @@ interface = gr.Interface(
 if __name__ == "__main__":
     print(f"Temp directory for audio: {TEMP_DIR}")
     interface.launch()
+