Update app.py

app.py

@@ -1,63 +1,50 @@
-# Install dependencies
-
-
 import os
 import gradio as gr
 import whisper
-import ffmpeg
 from groq import Groq
 from gtts import gTTS
+import tempfile
 
-# ============ SETUP ============
-# 🔑 Put your Groq API key here
-GROQ_API_KEY = "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"
-client = Groq(api_key = GROQ_API_KEY)
+# Load Groq API key from Hugging Face secrets
+GROQ_API_KEY = os.environ.get("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")
+if not GROQ_API_KEY:
+    raise ValueError("❌ Missing GROQ_API_KEY. Please set it in Hugging Face → Settings → Secrets")
+
+client = Groq(api_key=GROQ_API_KEY)
 
 # Load Whisper model
 whisper_model = whisper.load_model("base")
 
-# ============ FUNCTIONS ============
 def transcribe_and_chat(audio_file):
     if audio_file is None:
         return "No audio received", "Error: Please record again.", None
-    try:
-        # Convert audio to wav (Whisper requirement)
-        wav_file = "converted.wav"
-        (
-            ffmpeg
-            .input(audio_file)
-            .output(wav_file, format="wav")
-            .overwrite_output()
-            .run(quiet=True)
-        )
 
-        # Transcription
-        result = whisper_model.transcribe(wav_file)
+    try:
+        # 1. Transcribe
+        result = whisper_model.transcribe(audio_file)
         user_text = result.get("text", "").strip()
         if not user_text:
             return "Could not transcribe", "Error: Empty transcription", None
 
-        # Query Groq LLM
-        try:
-            chat_completion = client.chat.completions.create(
-                messages=[{"role": "user", "content": user_text}],
-                model="llama-3.3-70b-versatile"
-            )
-            bot_text = chat_completion.choices[0].message.content
-        except Exception as e:
-            return user_text, f"LLM Error: {str(e)}", None
+        # 2. Query Groq
+        chat_completion = client.chat.completions.create(
+            messages=[{"role": "user", "content": user_text}],
+            model="llama-3.1-8b-instant"  # ✅ stable model
+        )
+        bot_text = chat_completion.choices[0].message.content
 
-        # Text to speech
+        # 3. TTS
         tts = gTTS(bot_text)
-        reply_audio = "reply.mp3"
-        tts.save(reply_audio)
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp:
+            tts.save(tmp.name)
+            reply_audio = tmp.name
 
         return user_text, bot_text, reply_audio
 
     except Exception as e:
         return "Transcription error", str(e), None
 
-# ============ GRADIO UI ============
+# Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("## 🎙️ Real-time Voice-to-Voice Chatbot (Whisper + Groq + gTTS)")
 
@@ -73,4 +60,5 @@ with gr.Blocks() as demo:
         outputs=[user_text_out, bot_text_out, audio_out]
     )
 
-demo.launch(share=True, debug=True)
+demo.launch()
+