app.py

import os
import gradio as gr
from langchain_google_genai.chat_models import ChatGoogleGenerativeAI

# Set the path to the service account key
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "./firm-catalyst-437006-s4-407500537db5.json"

# Initialize the language model with required parameters
# Replace 'your-model-name' with the actual model you intend to use
llm = ChatGoogleGenerativeAI(model='gemini-1.5-pro')  

def chat_with_gemini(message, chat_history):
    # Placeholder function to simulate bot response
    bot_response = "You said: " + message
    chat_history.append((message, bot_response))
    return chat_history, chat_history

# Create a Gradio interface
with gr.Blocks() as iface:
    gr.Markdown("# Ken Chatbot")
    gr.Markdown("Ask me anything!")

    chatbot = gr.Chatbot(elem_id="chatbot")  # Initialize the chatbot with an element ID for styling
    msg = gr.Textbox(label="Type your message here...", placeholder="Enter your message and press enter to send your message...")
    state = gr.State([])  # Store chat history

    # Set up the interaction for when the user submits a message
    msg.submit(chat_with_gemini, [msg, state], [chatbot, state])  # Update chatbot and state with new messages
    msg.submit(lambda: "", None, msg)  # Clear the input box after submission

    # CSS for styling the chatbot messages
    iface.css("""
    #chatbot .message.user {
        background-color: #DCF8C6;
        border-radius: 15px;
        padding: 8px 12px;
        margin: 5px 50px 5px auto;
        max-width: 70%;
        text-align: right;
    }
    #chatbot .message.bot {
        background-color: #E1E1E1;
        border-radius: 15px;
        padding: 8px 12px;
        margin: 5px auto 5px 50px;
        max-width: 70%;
        text-align: left;
    }
    """)

# Launch the interface with debugging enabled
iface.launch(debug=True)