Update app.py

app.py

@@ -13,12 +13,17 @@ import streamlit as st
 import numpy as np
 from io import BytesIO
 import wave
+import threading
+import queue
 
 # Initialize components
 objection_handler = ObjectionHandler("objections.csv")  # Use relative path
 product_recommender = ProductRecommender("recommendations.csv")  # Use relative path
 model = SentenceTransformer('all-MiniLM-L6-v2')
 
+# Queue to hold transcribed text
+transcription_queue = queue.Queue()
+
 def generate_comprehensive_summary(chunks):
     """
     Generate a comprehensive summary from conversation chunks
@@ -136,10 +141,8 @@ def transcribe_audio(audio_bytes, sample_rate=16000):
         print(f"Error transcribing audio: {e}")
     return None
 
-def real_time_analysis():
-    st.info("Listening... Say 'stop' to end the process.")
-
-    def audio_frame_callback(audio_frame):
+def audio_processing_thread(audio_frame):
+    """Thread function to process audio frames."""
     # Convert audio frame to bytes
     audio_data = audio_frame.to_ndarray()
     print(f"Audio data shape: {audio_data.shape}")  # Debug: Check audio data shape
@@ -150,6 +153,27 @@ def real_time_analysis():
     # Transcribe the audio
     text = transcribe_audio(audio_bytes)
     if text:
+        transcription_queue.put(text)  # Add transcribed text to the queue
+
+def real_time_analysis():
+    st.info("Listening... Say 'stop' to end the process.")
+
+    def audio_frame_callback(audio_frame):
+        # Start a new thread to process the audio frame
+        threading.Thread(target=audio_processing_thread, args=(audio_frame,)).start()
+        return audio_frame
+
+    # Start WebRTC audio stream
+    webrtc_ctx = webrtc_streamer(
+        key="real-time-audio",
+        mode=WebRtcMode.SENDONLY,
+        audio_frame_callback=audio_frame_callback,
+        media_stream_constraints={"audio": True, "video": False},
+    )
+
+    # Display transcribed text from the queue
+    while not transcription_queue.empty():
+        text = transcription_queue.get()
         st.write(f"*Recognized Text:* {text}")
 
         # Analyze sentiment
@@ -173,18 +197,6 @@ def real_time_analysis():
             st.write("*Product Recommendations:*")
             for rec in recommendations:
                 st.write(rec)
-    else:
-        st.error("No transcription returned.")  # Debug: Check if transcription fails
-
-    return audio_frame
-
-    # Start WebRTC audio stream
-    webrtc_ctx = webrtc_streamer(
-        key="real-time-audio",
-        mode=WebRtcMode.SENDONLY,
-        audio_frame_callback=audio_frame_callback,
-        media_stream_constraints={"audio": True, "video": False},
-    )
 
 def run_app():
     st.set_page_config(page_title="Sales Call Assistant", layout="wide")