app.py

import gradio as gr
import openai
import os
import json

# OpenAI API setup
openai.api_key = os.getenv("GROQ_API_KEY")
openai.api_base = "https://api.groq.com/openai/v1"

# File to store conversation history
CONVERSATION_FILE = "conversation_history.json"

# Function to load conversation history
def load_history():
    if not os.path.exists(CONVERSATION_FILE):
        # Create the file with an empty list as default content
        with open(CONVERSATION_FILE, "w") as file:
            json.dump([], file)
    try:
        with open(CONVERSATION_FILE, "r") as file:
            return json.load(file)
    except json.JSONDecodeError:
        return []

# Function to save conversation history
def save_history(history):
    try:
        with open(CONVERSATION_FILE, "w") as file:
            json.dump(history, file, indent=4)
    except Exception as e:
        print(f"Error saving history: {e}")

# Function to clear conversation history
def clear_conversation_history():
    try:
        with open(CONVERSATION_FILE, "w") as file:
            json.dump([], file)
        return "Conversation history cleared successfully."
    except Exception as e:
        return f"Error clearing history: {e}"

# Function to get response from the LLM
def get_groq_response(message, history=[]):
    try:
        messages = [{"role": "system", "content": "Precise answer"}] + history + [{"role": "user", "content": message}]
        response = openai.ChatCompletion.create(
            model="llama-3.3-70b-versatile",
            messages=messages
        )
        return response.choices[0].message["content"]
    except Exception as e:
        return f"Error: {str(e)}"

# Text-to-Speech function
def text_to_speech(latest_response):
    try:
        tts = gTTS(latest_response, lang="en")  # Generate speech from text
        audio_file = "response_audio.mp3"
        tts.save(audio_file)
        print(f"Audio file saved at: {audio_file}")  # Debugging print
        return audio_file  # Ensure correct file path is returned
    except Exception as e:
        print(f"Error generating audio: {e}")
        return None

# Chatbot function
def chatbot(user_input, history):
    # Load conversation history
    conversation_history = history or load_history()
    
    # Format history for the LLM
    formatted_history = [{"role": "user" if i % 2 == 0 else "assistant", "content": msg} for i, (msg, _) in enumerate(conversation_history)] + \
                        [{"role": "assistant", "content": response} for _, response in conversation_history]
    
    # Get bot response
    bot_response = get_groq_response(user_input, formatted_history)
    
    # Update history with the new conversation
    conversation_history.append((user_input, bot_response))
    
    # Save the updated history
    save_history(conversation_history)
    
    return conversation_history, conversation_history, ""  # Clear the user input field

# Gradio Interface with enhanced UI/UX
with gr.Blocks(css="""
    .gradio-container {
        font-family: 'Arial', sans-serif;
        background-color: #F2EFE7;
        padding: 20px;
        height: 100%;
    }

    .gr-chatbot {
        background-color: #FFFFFF;
        border-radius: 10px;
        padding: 20px;
        max-height: 600px;  /* Increased height */
        overflow-y: auto;
        box-shadow: 0px 0px 15px rgba(0, 0, 0, 0.1);
        scroll-behavior: smooth; /* Smooth scrolling */
    }

    .user-message {
        background-color: #9ACBD0;
        color: #FFF;
        padding: 12px;
        border-radius: 8px;
        margin: 10px 0;
        max-width: 60%;
        text-align: right;
        float: right;
        clear: both;
        transition: transform 0.3s ease;
    }

    .bot-message {
        background-color: #48A6A7;
        color: #FFF;
        padding: 12px;
        border-radius: 8px;
        margin: 10px 0;
        max-width: 60%;
        text-align: left;
        float: left;
        clear: both;
        transition: transform 0.3s ease;
    }

    .user-message:hover, .bot-message:hover {
        transform: scale(1.05);
        box-shadow: 0px 4px 12px rgba(0, 0, 0, 0.1);
    }

    .gr-button {
        background-color: #2973B2;
        color: white;
        padding: 10px 15px;
        border-radius: 8px;
        border: none;
        transition: background-color 0.3s ease;
    }

    .gr-button:hover {
        background-color: #21689D;
    }

    .gr-textbox input {
        padding: 15px;
        font-size: 16px;
    }

    .gr-markdown h1 {
        color: #3A5A6E;
        font-size: 28px;
        text-align: center;
    }
""") as demo:
    gr.Markdown("""# Mom: We have ChatGPT at Home, \n ChatGPT at Home: Feel free to ask questions. After you're done, remember to clear the history for privacy. """)

    # Chatbot UI
    chatbot_ui = gr.Chatbot()
    user_input = gr.Textbox(label="Type your message here:", placeholder="Ask me anything...", lines=1)
    hear_button = gr.Button("Hear Response")
    audio_output = gr.Audio(label="Bot's Voice", type="filepath", interactive=False)
    clear_button = gr.Button("Clear History")
    system_message = gr.Textbox(label="System Message", interactive=False)

    history_state = gr.State(load_history())

    # Chat interaction
    user_input.submit(chatbot, inputs=[user_input, history_state], outputs=[chatbot_ui, history_state, user_input])
    hear_button.click(
        lambda latest: text_to_speech(latest[-1][1] if latest else ""),  # Fetch latest bot response
        inputs=[history_state],  # Pass the conversation history
        outputs=audio_output # Output the file to the audio player
    )
    
    # Clear history button action
    clear_button.click(clear_conversation_history, inputs=None, outputs=system_message)
    clear_button.click(lambda: [], outputs=chatbot_ui)  # Clear the chatbot UI
    clear_button.click(lambda: [], outputs=history_state)  # Reset the history state

# Launch the app
demo.launch()