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import gradio as gr | |
from langchain.chat_models import ChatOpenAI | |
# Ensure you have the necessary imports and installations | |
# If you're using Groq AI, make sure to import it correctly | |
# from groq import Groq # Uncomment if using Groq | |
# Initialize your model here (ensure you have the correct model setup) | |
# For example, if using Groq: | |
# client = Groq(api_key="YOUR_API_KEY") | |
with gr.Blocks() as iface: | |
gr.Markdown("# Mr AI") | |
gr.Markdown("Hi there! I'm your friendly assistant. Ask me anything, and I'll do my best to help! (By Thirumoorthi.A)") | |
chat_history_output = gr.Chatbot(label="Chat History", height=400) | |
with gr.Row(): | |
message_input = gr.Textbox(label="Your Question", placeholder="Type your question here...", lines=2) | |
submit_btn = gr.Button("Submit") | |
clear_btn = gr.Button("Clear Chat") | |
def respond(message, chat_history): | |
chat_history.append(("USER", message)) | |
# Replace this line with your model's response logic | |
response = "This is a placeholder response." # Replace with actual model call | |
# If using Groq, it might look like: | |
# response = client.chat.completions.create(messages=[{"role": "user", "content": message}]) | |
chat_history.append(("Assistant", response)) | |
return "", chat_history | |
def clear_chat(): | |
return [] | |
submit_btn.click(respond, inputs=[message_input, chat_history_output], outputs=[message_input, chat_history_output]) | |
clear_btn.click(clear_chat, outputs=chat_history_output) | |
iface.launch() | |