Update app.py

app.py

@@ -1,5 +1,5 @@
 import streamlit as st
-from streamlit_webrtc import webrtc_streamer, WebRtcMode, ClientSettings
+from streamlit_webrtc import webrtc_streamer, WebRtcMode
 import av
 import whisper
 import openai
@@ -8,59 +8,53 @@ import os
 from gtts import gTTS
 from pydub import AudioSegment
 
+# Set your API Key (Groq-compatible)
+openai.api_key = os.getenv("GROQ_API_KEY", "your-groq-api-key")
+
 # Load Whisper model
 model = whisper.load_model("base")
 
-# Set OpenAI (Groq-compatible) API Key
-openai.api_key = os.getenv("GROQ_API_KEY", "your-groq-api-key")
-
 st.title("🎙️ Voice-to-Voice Conversational App")
 
-# Record audio using streamlit-webrtc
-st.info("🎤 Please record your question below:")
-
-audio_placeholder = st.empty()
+st.info("🎤 Record your voice and click 'Stop' to process:")
 
 webrtc_ctx = webrtc_streamer(
-    key="speech",
+    key="example",
     mode=WebRtcMode.SENDRECV,
-    client_settings=ClientSettings(
-        media_stream_constraints={"audio": True, "video": False},
-        rtc_configuration={"iceServers": [{"urls": ["stun:stun.l.google.com:19302"]}]}
-    ),
     audio_receiver_size=1024,
+    media_stream_constraints={"audio": True, "video": False},
 )
 
-if "audio_buffer" not in st.session_state:
-    st.session_state.audio_buffer = b""
+if "audio_bytes" not in st.session_state:
+    st.session_state.audio_bytes = b""
 
 if webrtc_ctx.audio_receiver:
     audio_frames = webrtc_ctx.audio_receiver.get_frames(timeout=1)
     for frame in audio_frames:
-        st.session_state.audio_buffer += frame.to_ndarray().tobytes()
+        st.session_state.audio_bytes += frame.to_ndarray().tobytes()
 
 if st.button("🛑 Process Voice"):
     with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as f:
-        f.write(st.session_state.audio_buffer)
+        f.write(st.session_state.audio_bytes)
         audio_path = f.name
 
     st.audio(audio_path)
 
-    st.info("Transcribing with Whisper...")
+    st.info("🔠 Transcribing...")
     result = model.transcribe(audio_path)
-    user_text = result["text"]
-    st.success(f"You said: {user_text}")
+    user_input = result["text"]
+    st.success(f"You said: {user_input}")
 
-    st.info("Generating AI response...")
+    st.info("🧠 Thinking...")
     response = openai.ChatCompletion.create(
         model="mixtral-8x7b-32768",
-        messages=[{"role": "user", "content": user_text}]
+        messages=[{"role": "user", "content": user_input}]
     )
-    reply = response['choices'][0]['message']['content']
-    st.success(f"AI says: {reply}")
+    answer = response["choices"][0]["message"]["content"]
+    st.success(f"AI says: {answer}")
 
-    # Convert to speech
-    tts = gTTS(reply)
-    tts_path = "reply.mp3"
+    # Convert to voice
+    tts = gTTS(answer)
+    tts_path = "output.mp3"
     tts.save(tts_path)
     st.audio(tts_path, format="audio/mp3")