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():
    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(  
    """  
    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()  
    st.markdown("### Chat History")
    # Update chat history on every interaction  
    update_chat_history()