import os
import requests
import gradio as gr

HF_API_KEY = os.getenv("HF_API_KEY")


# Step 2: Define the model you are using
MODEL_ID = "Aryaman02/InLawMate-peft"
API_URL = f"https://api-inference.huggingface.co/models/{MODEL_ID}"

# Step 3: Set up headers for authentication
headers = {"Authorization": f"Bearer {HF_API_KEY}"}

# Step 4: Define the chatbot function
def chatbot(query):
    payload = {"inputs": query}  # Input for the model
    response = requests.post(API_URL, headers=headers, json=payload, timeout=60)  # Send API request
    
    if response.status_code == 200:
        return response.json()[0]["generated_text"]  # Extract response
    else:
        return "Error: Model is loading or unavailable. Please try again later."

# Step 5: Create Gradio Interface
iface = gr.Interface(fn=chatbot, inputs="text", outputs="text", title="Nayay Legal Chatbot")
iface.launch()