app.py

import gradio as gr
from transformers import pipeline

# Load a lightweight text-generation model for free usage
generator = pipeline("text-generation", model="tiiuae/falcon-rw-1b")

# Define chatbot function
def chatbot(message, history):
    # Combine message history for context
    prompt = message
    result = generator(prompt, max_new_tokens=100, do_sample=True, temperature=0.7)[0]['generated_text']
    return result.strip()

# Launch Gradio chat interface
gr.ChatInterface(
    fn=chatbot,
    title="E-Waste Chatbot",
    description="Ask questions about electronic waste, recycling, or environmental impact!",
    theme="compact"
).launch()