Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,160 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
+from openai import OpenAI
+import sounddevice as sd
+import scipy.io.wavfile
+import io
+import base64
+import os
+import time
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+
+st.set_page_config(page_title="Voice Bot", layout="wide")
+
+# Configuration
+SAMPLE_RATE = 44100
+RECORD_DURATION = 5
+TEMP_AUDIO_FILE = "temp_audio.wav"
+
+# Initialize OpenAI client
+api_key = st.secrets['openai']
+client = OpenAI(api_key=api_key)
+
+# Initialize session state variables if they don't exist
+if 'recorded_audio' not in st.session_state:
+    st.session_state.recorded_audio = None
+if 'user_text' not in st.session_state:
+    st.session_state.user_text = None
+if 'ai_reply' not in st.session_state:
+    st.session_state.ai_reply = None
+
+def load_context():
+    """Load the context from file."""
+    try:
+        with open("context.txt", "r") as f:
+            return f.read()
+    except FileNotFoundError:
+        st.error("Context file not found!")
+        return ""
+
+def record_audio():
+    """Record audio and return the buffer."""
+    progress_bar = st.progress(0)
+    recording = sd.rec(int(RECORD_DURATION * SAMPLE_RATE), 
+                      samplerate=SAMPLE_RATE, 
+                      channels=1)
+    
+    # Update progress bar while recording
+    for i in range(RECORD_DURATION * 10):
+        progress_bar.progress((i + 1) / (RECORD_DURATION * 10))
+        time.sleep(0.1)
+    
+    sd.wait()
+    progress_bar.empty()  # Remove progress bar after recording
+    
+    buf = io.BytesIO()
+    scipy.io.wavfile.write(buf, SAMPLE_RATE, recording)
+    buf.seek(0)
+    return buf
+
+def transcribe_audio(audio_buffer):
+    """Transcribe audio using Whisper API."""
+    with open(TEMP_AUDIO_FILE, "wb") as f:
+        f.write(audio_buffer.getvalue())
+    
+    with open(TEMP_AUDIO_FILE, "rb") as audio_file:
+        transcript = client.audio.transcriptions.create(
+            model="whisper-1",
+            file=audio_file
+        )
+    return transcript.text
+
+def get_ai_response(user_text, context):
+    """Get AI response using GPT-4."""
+    system_prompt = f"""
+    You are Prakhar.
+    You must respond **only using the following context**:
+
+    {context}
+
+    If the user's question cannot be answered using this context, respond with:
+    "I'm not sure about that based on what I know."
+    """
+    
+    response = client.chat.completions.create(
+        model="gpt-4",
+        messages=[
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": user_text}
+        ]
+    )
+    return response.choices[0].message.content
+
+def text_to_speech(text):
+    """Convert text to speech using OpenAI TTS."""
+    speech = client.audio.speech.create(
+        model="tts-1",
+        voice="onyx",
+        input=text
+    )
+    return base64.b64encode(speech.content).decode()
+
+def handle_record_button():
+    """Handle recording button click"""
+    st.session_state.processing = True
+    info_placeholder = st.empty()
+    info_placeholder.info("Recording...")
+    audio_buffer = record_audio()
+    info_placeholder.empty()
+    st.session_state.recorded_audio = audio_buffer
+
+def main():
+    st.title("Voice Bot")
+    
+    if 'context' not in st.session_state:
+        st.session_state.context = load_context()
+    if 'processing' not in st.session_state:
+        st.session_state.processing = False
+
+    with st.container():
+
+        audio, script = st.columns(2, border=True)
+
+        with audio:
+            st.subheader("Audio Input")
+            st.button("🎙️ Record Voice", on_click=handle_record_button)
+            
+            # Create placeholder for processing status
+            process_placeholder = st.empty()
+            
+            # Handle processing if recording just completed
+            if st.session_state.processing:
+                with process_placeholder.container():
+                    with st.spinner("Processing..."):
+                        st.session_state.user_text = transcribe_audio(st.session_state.recorded_audio)
+                        st.session_state.ai_reply = get_ai_response(st.session_state.user_text, st.session_state.context)
+                        audio_b64 = text_to_speech(st.session_state.ai_reply)
+                        st.session_state.ai_audio = audio_b64
+                        st.session_state.processing = False
+            
+            # Display recorded audio if exists
+            if st.session_state.recorded_audio is not None:
+                st.audio(st.session_state.recorded_audio, format="audio/wav")
+                if hasattr(st.session_state, 'ai_audio'):
+                    st.audio(f"data:audio/mp3;base64,{st.session_state.ai_audio}", format="audio/mp3")
+
+        with script:
+            st.subheader("Conversation")
+            if st.session_state.user_text is not None:
+                st.markdown("**You said:**")
+                st.markdown(f"{st.session_state.user_text}")
+                st.markdown("**AI Response:**")
+                st.markdown(f"{st.session_state.ai_reply}")
+            
+            st.divider()
+
+    with st.container(border=True):
+        st.text_area("Context", value=st.session_state.context, height=270, disabled=False)
+        st.markdown("You can update the context in the `context.txt` file.")
+
+if __name__ == "__main__":
+    main()