Update app.py

app.py

@@ -1,11 +1,7 @@
 import streamlit as st
 from responser import responsr
-from io import BytesIO
-import speech_recognition as sr
-from streamlit_webrtc import webrtc_streamer, AudioProcessorBase, WebRtcMode
-import numpy as np
 from gtts import gTTS
-import asyncio
+from io import BytesIO
 
 # Function to convert text to speech and return audio file
 def text_to_speech(text):
@@ -15,83 +11,54 @@ def text_to_speech(text):
     audio_file.seek(0)
     return audio_file
 
-# Function to convert speech to text using SpeechRecognition
-def speech_to_text(audio_data):
-    recognizer = sr.Recognizer()
-    with sr.AudioFile(BytesIO(audio_data)) as source:
-        audio = recognizer.record(source)
-        return recognizer.recognize_google(audio)
-
-class AudioProcessor(AudioProcessorBase):
-    def __init__(self):
-        self.audio_buffer = BytesIO()
-
-    def recv(self, frame):
-        audio_data = frame.to_ndarray().tobytes()
-        self.audio_buffer.write(audio_data)
-        return frame
-
 def main():
-    st.title("Real-Time Audio Chat with AI")
-
+    # Layout with three columns
+    col1, col2, col3 = st.columns([3, 1, 1])
+    
+    with col1:
+        # Title with custom CSS styling for top margin
+        st.markdown('<div style="margin-top: -25px;" class="title-wrapper"><h1 style="text-align: center;">Your Health Guide</h1></div>', unsafe_allow_html=True)
+    
     # Initialize chat history if not already initialized
     if "chat_messages" not in st.session_state:
         st.session_state.chat_messages = []
 
-    # Display chat history with audio only
+    # Display chat history
     for message in st.session_state.chat_messages:
         if message["role"] == "user":
-            st.write("User:")
+            st.text_area("User:", message["content"], height=40, key=message["content"], disabled=True)
         else:
-            st.write("AI:")
-        st.audio(message["audio"], format="audio/mp3")
-
-    # Initialize WebRTC audio streamer
-    webrtc_ctx = webrtc_streamer(
-        key="speech-to-text",
-        mode=WebRtcMode.SENDRECV,
-        audio_processor_factory=AudioProcessor,
-        rtc_configuration={"iceServers": [{"urls": ["stun:stun.l.google.com:19302"]}]},
-        media_stream_constraints={"audio": True, "video": False},
-        async_processing=True,
-    )
-
-    if webrtc_ctx.state.playing:
-        processor = webrtc_ctx.audio_processor
-        if processor and processor.audio_buffer.getvalue():
-            # Convert audio buffer to speech
-            audio_data = processor.audio_buffer.getvalue()
-            user_text = speech_to_text(audio_data)
-            
-            # Convert the user's speech input to audio for playback
-            user_audio = text_to_speech(user_text)
-
-            # Add user message (as audio) to chat history
-            st.session_state.chat_messages.append({
-                "role": "user",
-                "content": user_text,
-                "audio": user_audio.getvalue()
-            })
-
-            # Get AI response using the responsr function
-            response = responsr(user_text)
-
-            # Convert AI response to speech
-            response_audio = text_to_speech(response)
-
-            # Add assistant's response (as audio) to chat history
-            st.session_state.chat_messages.append({
-                "role": "assistant",
-                "content": response,
-                "audio": response_audio.getvalue()
-            })
-
-            # Display the audio files for both user input and AI response
-            st.audio(user_audio, format="audio/mp3")
-            st.audio(response_audio, format="audio/mp3")
-
-            # Clear the audio buffer
-            processor.audio_buffer = BytesIO()
+            st.text_area("AI:", message["content"], height=40, key=message["content"], disabled=True)
+            # Display audio in chat interface
+            st.audio(message["audio"], format="audio/mp3")
+
+    # User input
+    if prompt := st.chat_input("Welcome - How can I help you?"):
+        # Display user's message in chat message container
+        with st.chat_message("user"):
+            st.markdown(prompt)
+        
+        # Add user message to chat history
+        st.session_state.chat_messages.append({"role": "user", "content": prompt})
+        
+        # Get AI response using responsr function
+        response = responsr(prompt)
+        
+        # Convert AI response to speech
+        audio_file = text_to_speech(response)
+        
+        # Display assistant's response in chat message container
+        with st.chat_message("assistant"):
+            st.markdown(response)
+            st.audio(audio_file, format="audio/mp3")
+        
+        # Add assistant's response and audio to chat history
+        st.session_state.chat_messages.append({
+            "role": "assistant",
+            "content": response,
+            "audio": audio_file.getvalue()
+        })
 
 if __name__ == "__main__":
     main()
+