Update app.py

app.py

@@ -1,152 +1,159 @@
-import streamlit as st  
-from gradio_client import Client  
-import speech_recognition as sr  
-import pyttsx3  
-import threading  
-
-# Initialize session state  
-if "messages" not in st.session_state:  
-    st.session_state["messages"] = []  # Store chat history  
-
-# Function to generate a response using Gradio client  
-def generate_response(query):  
-    try:  
-        client = Client("Gopikanth123/llama2")  
-        result = client.predict(query=query, api_name="/predict")  
-        return result  
-    except Exception as e:  
-        return f"Error communicating with the Gradio backend: {e}"  
-
-# Function to handle user input and bot response  
-def handle_user_input(user_input):  
-    if user_input:  
-        # Add user message to session state  
-        st.session_state["messages"].append({"user": user_input})  
-
-        # Generate bot response  
-        response = generate_response(user_input)  
-        st.session_state["messages"].append({"bot": response})  
-
-        # Speak out bot response in a new thread to avoid blocking  
-        threading.Thread(target=speak_text, args=(response,), daemon=True).start()  
-
-# Function for Speech Recognition (Voice Input)  
-def recognize_speech():
+import streamlit as st
+import sounddevice as sd
+import numpy as np
+import speech_recognition as sr
+import pyttsx3
+import threading
+import io
+from gradio_client import Client
+
+# Initialize session state
+if "messages" not in st.session_state:
+    st.session_state["messages"] = []  # Store chat history
+
+# Function to generate a response using Gradio client
+def generate_response(query):
+    try:
+        client = Client("Gopikanth123/llama2")
+        result = client.predict(query=query, api_name="/predict")
+        return result
+    except Exception as e:
+        return f"Error communicating with the Gradio backend: {e}"
+
+# Function to handle user input and bot response
+def handle_user_input(user_input):
+    if user_input:
+        # Add user message to session state
+        st.session_state["messages"].append({"user": user_input})
+
+        # Generate bot response
+        response = generate_response(user_input)
+        st.session_state["messages"].append({"bot": response})
+
+        # Speak out bot response in a new thread to avoid blocking
+        threading.Thread(target=speak_text, args=(response,), daemon=True).start()
+
+        # Update chat history after each interaction
+        # update_chat_history()
+
+# Function to speak text (Voice Output)
+def speak_text(text):
+    engine = pyttsx3.init()
+    engine.stop()  # Ensure no previous loop is running
+    engine.say(text)
+    engine.runAndWait()
+
+# Function to update chat history dynamically
+def update_chat_history():
+    chat_history = st.session_state["messages"]
+    for msg in chat_history:
+        if "user" in msg:
+            st.markdown(f"<div class='chat-bubble user-message'><strong>You:</strong> {msg['user']}</div>", unsafe_allow_html=True)
+        if "bot" in msg:
+            st.markdown(f"<div class='chat-bubble bot-message'><strong>Bot:</strong> {msg['bot']}</div>", unsafe_allow_html=True)
+
+# Function to recognize speech using sounddevice
+def recognize_speech_sounddevice():
+    st.info("Listening... Speak into the microphone.")
+    fs = 16000  # Sample rate in Hz
+    duration = 5  # Duration in seconds
+
+    # Record the audio using sounddevice
+    audio_data = sd.rec(int(duration * fs), samplerate=fs, channels=1, dtype='int16')
+    sd.wait()
+
+    # Convert the audio data to the format expected by speech_recognition
     recognizer = sr.Recognizer()
-    with sr.Microphone() as source:
-        st.info("Listening... Speak into the microphone.")
-        try:
-            audio = recognizer.listen(source, timeout=5, phrase_time_limit=10)
-            recognized_text = recognizer.recognize_google(audio)
-            st.session_state["user_input"] = recognized_text  # Set recognized text to input field
-            st.success(f"Recognized Text: {recognized_text}")
-            handle_user_input(recognized_text)
-        except sr.WaitTimeoutError:
-            st.warning("Listening timed out. No speech detected. Please try again.")
-        except sr.UnknownValueError:
-            st.error("Sorry, I couldn't understand the audio. Try speaking more clearly.")
-        except sr.RequestError:
-            st.error("Could not request results; please check your internet connection.")
-        except Exception as e:
-            st.error(f"An unexpected error occurred: {e}")
-
-# Function to speak text (Voice Output)  
-def speak_text(text):  
-    engine = pyttsx3.init()  
-    engine.stop()  # Ensure no previous loop is running  
-    engine.say(text)  
-    engine.runAndWait()  
-
-# Main Streamlit app  
-st.set_page_config(page_title="Llama2 Chatbot", page_icon="🤖", layout="wide")  
-st.markdown(  
-    """  
-    <style>  
-    .stButton>button {  
-        background-color: #6C63FF;  
-        color: white;  
-        font-size: 16px;  
-        border-radius: 10px;  
-        padding: 10px 20px;  
-    }  
-    .stTextInput>div>input {  
-        border: 2px solid #6C63FF;  
-        border-radius: 10px;  
-        padding: 10px;  
-    }  
-    .chat-container {  
-        background-color: #F7F9FC;  
-        padding: 20px;  
-        border-radius: 15px;  
-        max-height: 400px;  
-        overflow-y: auto;  
-    }  
-    .chat-bubble {  
-        padding: 10px 15px;  
-        border-radius: 15px;  
-        margin: 5px 0;  
-        max-width: 80%;  
-        display: inline-block;  
-    }  
-    .user-message {  
-        background-color: #D1C4E9;  
-        text-align: left;  
-        margin-left: auto;  
-    }  
-    .bot-message {  
-        background-color: #BBDEFB;  
-        text-align: left;  
-        margin-right: auto;  
-    }  
-    .input-container {  
-        display: flex;  
-        justify-content: space-between;  
-        gap: 10px;  
-        padding: 10px 0;  
-    }  
-    </style>  
-    """,  
-    unsafe_allow_html=True  
-)  
-
-st.title("🤖 Chat with Llama2 Bot")  
-st.markdown(  
-    """  
+    audio = sr.AudioData(audio_data.tobytes(), fs, 2)
+
+    try:
+        recognized_text = recognizer.recognize_google(audio)
+        st.session_state["user_input"] = recognized_text
+        st.success(f"Recognized Text: {recognized_text}")
+        handle_user_input(recognized_text)
+    except sr.UnknownValueError:
+        st.error("Sorry, I couldn't understand the audio.")
+    except sr.RequestError:
+        st.error("Could not request results; please check your internet connection.")
+
+
+# Main Streamlit app
+st.set_page_config(page_title="Llama2 Chatbot", page_icon="🤖", layout="wide")
+st.markdown(
+    """
+    <style>
+    .stButton>button {
+        background-color: #6C63FF;
+        color: white;
+        font-size: 16px;
+        border-radius: 10px;
+        padding: 10px 20px;
+    }
+    .stTextInput>div>input {
+        border: 2px solid #6C63FF;
+        border-radius: 10px;
+        padding: 10px;
+    }
+    .chat-container {
+        background-color: #F7F9FC;
+        padding: 20px;
+        border-radius: 15px;
+        max-height: 400px;
+        overflow-y: auto;
+    }
+    .chat-bubble {
+        padding: 10px 15px;
+        border-radius: 15px;
+        margin: 5px 0;
+        max-width: 80%;
+        display: inline-block;
+    }
+    .user-message {
+        background-color: #D1C4E9;
+        text-align: left;
+        margin-left: auto;
+    }
+    .bot-message {
+        background-color: #BBDEFB;
+        text-align: left;
+        margin-right: auto;
+    }
+    .input-container {
+        display: flex;
+        justify-content: space-between;
+        gap: 10px;
+        padding: 10px 0;
+    }
+    </style>
+    """,
+    unsafe_allow_html=True
+)
+
+st.title("🤖 Chat with Llama2 Bot")
+st.markdown(
+    """
     Welcome to the *Llama2 Chatbot*!   
     - *Type* your message below, or   
     - *Use the microphone* to speak to the bot.   
-    """  
-)  
-
-# Display chat history  
-chat_history_container = st.container()  
-with chat_history_container:  
-    # st.markdown("### Chat History")  
-    # st.markdown("<div class='chat-container' id='chat-container'>", unsafe_allow_html=True)  
-
-    # Update chat history dynamically  
-    def update_chat_history():  
-        chat_history = st.session_state["messages"]  
-        for msg in chat_history:  
-            if "user" in msg:  
-                st.markdown(f"<div class='chat-bubble user-message'><strong>You:</strong> {msg['user']}</div>", unsafe_allow_html=True)  
-            if "bot" in msg:  
-                st.markdown(f"<div class='chat-bubble bot-message'><strong>Bot:</strong> {msg['bot']}</div>", unsafe_allow_html=True)  
-
-    # Add input field within a form  
-    with st.form(key='input_form', clear_on_submit=True):  
-        user_input = st.text_input("Type your message here...", placeholder="Hello, how are you?")  
-        submit_button = st.form_submit_button("Send")  
-
-        # Handle form submission  
-        if submit_button:  
-            handle_user_input(user_input)  
-            # update_chat_history()  
-
-    # Separate button for speech recognition outside of the form  
-    if st.button("Speak"):  
-        recognize_speech()  
-        # update_chat_history()  
+    """
+)
+
+# Display chat history
+chat_history_container = st.container()
+with chat_history_container:
+    # Add input field within a form
+    with st.form(key='input_form', clear_on_submit=True):
+        user_input = st.text_input("Type your message here...", placeholder="Hello, how are you?")
+        submit_button = st.form_submit_button("Send")
+
+        # Handle form submission
+        if submit_button:
+            handle_user_input(user_input)
+
+    # Separate button for speech recognition outside of the form
+    if st.button("Speak"):
+        recognize_speech_sounddevice()
+
     st.markdown("### Chat History")
-    # Update chat history on every interaction  
+    # Update chat history on every interaction
     update_chat_history()