import gradio as gr
import requests
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("viber1/indian-law-dataset")['train']

def get_answer_from_dataset(query):
    for entry in dataset:
        if query.lower() in entry['Instruction'].lower():
            return entry['Response']
    return None

def get_answer_from_api(query):
    base_url = "https://www.courtlistener.com/api/rest/v4/search/"
    headers = {
        "Authorization": "Token 9c70738ed9eb3cce4f3782a91c7c8a218c180b89"  # Replace with your CourtListener API token
    }
    params = {
        "q": query,
        "page_size": 1  # Limit the number of results returned
    }
    
    response = requests.get(base_url, headers=headers, params=params)
    if response.status_code == 200:
        results = response.json()
        if results.get('count', 0) > 0:
            return results['results'][0]['case_name']  # Adjust based on actual response structure
    return "No legal information available for this query."

def respond(query):
    answer = get_answer_from_dataset(query)
    if answer:
        return answer
    else:
        return get_answer_from_api(query)

# Gradio interface
demo = gr.Interface(
    fn=respond,
    inputs="text",
    outputs="text",
    title="YOUR LEGAL GUIDE",
    description="Ask your legal queries regarding Indian laws.",
)

if __name__ == "__main__":
    demo.launch()