ui made

sentiment_analysis.py

@@ -10,7 +10,7 @@ def get_analysis(file_path)->str:
     
     analysis = ask_gemini(transcript)
     
-    return analysis
+    return transcript , analysis
 
 if __name__ == "__main__":
     file_path = "harvard.wav"

streamlit_app.py

@@ -1,70 +1,61 @@
-from sentiment_analysis import get_analysis
-
 import streamlit as st
-import speech_recognition as sr
-import pyaudio
-import wave
 import time
+from streamlit_mic_recorder import mic_recorder
+import wave
+import pyaudio
+from sentiment_analysis import get_analysis
 
+def save_audio(audio_data, filename):
+    """Save the recorded audio in .wav format"""
+    # Open a .wav file for writing
+    with wave.open(filename, 'wb') as wf:
+        wf.setnchannels(1)  # Mono channel
+        wf.setsampwidth(pyaudio.PyAudio().get_sample_size(pyaudio.paInt16))  # 16-bit encoding
+        wf.setframerate(44100)  # Sample rate (44100 Hz)
+        wf.writeframes(audio_data)  # Write audio data to file
 
-# Function to record the user's voice and save it as a .wav file
-def record_voice():
-    recognizer = sr.Recognizer()
-    mic = sr.Microphone()
-
-    # Set up the microphone and record the audio
-    with mic as source:
-        st.write("Listening...")
-        recognizer.adjust_for_ambient_noise(source)
-        audio = recognizer.listen(source)
-        st.write("Recording complete!")
+def main():
+    st.title("Streamlit Voice Recorder")
 
-    # Save the audio to a .wav file
-    with open("recorded_audio.wav", "wb") as f:
-        with mic as source:
-            audio = recognizer.listen(source,timeout=5)
-            f.write(audio.get_wav_data())
+    if "messages" not in st.session_state:
+        st.session_state.messages = []
     
-    # Return the file name of the recorded audio
-    return "recorded_audio.wav", audio
-
-# Function to transcribe the audio file
-def transcribe_audio(audio):
-    recognizer = sr.Recognizer()
-
-    try:
-        # Recognize the speech using Google's speech recognition service
-        text = recognizer.recognize_google(audio)
-        st.write(f"Recognized text: {text}")
-        return text
-    except sr.UnknownValueError:
-        st.error("Sorry, I could not understand the audio.")
-    except sr.RequestError as e:
-        st.error(f"Error with the speech recognition service: {e}")
-    return None
-
-# Streamlit app setup
-st.title("Voice Chat App")
-
-st.sidebar.header("Controls")
-start_button = st.sidebar.button("Start Recording")
-
-if start_button:
-    st.write("Clicking this will start recording your voice...")
-    time.sleep(2)  # Pause for a moment before starting to record
-    audio_file, audio_data = record_voice()
-
-    # Saving and displaying the recorded audio
-    st.write(f"Audio saved as: {audio_file}")
-
-    # Transcribe the recorded audio
-    if audio_data:
-        transcription = transcribe_audio(audio_data)
-        if transcription:
-            st.text_area("Chat", value=transcription, height=200)
-        else:
-            st.write("Sorry, no transcription available.")
-    else:
-        st.write("No audio recorded.")
-
+    # Prompt for voice recording
+    st.write("Click the button below to start recording your voice.")
+
+    # Mic Recorder input
+    audio = mic_recorder(
+        start_prompt="Start recording",
+        stop_prompt="Stop recording",
+        just_once=False,
+        use_container_width=False,
+        format="wav",  # Specify format
+        callback=None,
+        args=(),
+        kwargs={},
+        key=None
+    )
+
+    if audio:
+        # Saving the audio to a .wav file
+        save_path = "recorded_audio.wav"
+        save_audio(audio["bytes"], save_path)
+
+        time.sleep(0.1)
+        with st.spinner('Fetching response from Gemini...'):
+            user_message, gemini_response = get_analysis("recorded_audio.wav")
+
+        st.session_state.messages.append({"role": "user", "content": user_message})
+        st.session_state.messages.append({"role": "gemini", "content": gemini_response})
+
+    # Display the chat history
+    for msg in st.session_state.messages:
+        if msg["role"] == "user":
+            st.chat_message(msg["role"]).markdown(f"**User:** {msg['content']}")
+        elif msg["role"] == "gemini":
+            st.chat_message(msg["role"]).markdown(f"**Gemini:** {msg['content']}")
+    
+    time.sleep(0.1)
 
+if __name__ == "__main__":
+    main()