app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
import json 
import os
import re
from huggingface_hub import login



#hf_token = os.getenv("HK_TOKEN_MISTRL")  # Fetch Hugging Face API token

login(token=os.getenv("HK_TOKEN_MISTRL"))
 


# Load the model and tokenizer
model_name = "mistralai/Mistral-7B-Instruct-v0.2"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto")


def compare_claims(claim_json1, claim_json2):
    """
    Compare two health insurance claims using OpenAI GPT model and return structured JSON output.

    :param claim_json1: JSON string for first claim
    :param claim_json2: JSON string for second claim
    :return: JSON output with similarities, differences, and summary
    """
    # Parse input JSONs
    claim1 = json.loads(claim_json1)
    claim2 = json.loads(claim_json2)

  # Structured prompt for better JSON output
    prompt = f"""
    Compare the following insurance claims and identify similarities and differences.
    
    Claim 1:
    {json.dumps(claim1, indent=2)}
    
    Claim 2:
    {json.dumps(claim2, indent=2)}
    
    Provide a structured comparison highlighting commonalities and differences.
    """

    device = "cuda" if torch.cuda.is_available() else "cpu"  # Automatically select CPU if no GPU


    # Tokenize input correctly
    inputs = tokenizer(prompt, return_tensors="pt")  # Convert prompt to tensor
    input_ids = inputs["input_ids"].to(device)  # Move to CPU instead of GPU
    inputs["attention_mask"] = inputs["attention_mask"].to(device)



    # Generate response
    output = model.generate(input_ids=input_ids, max_new_tokens=300, pad_token_id=tokenizer.eos_token_id)

    # Decode output
    response = tokenizer.decode(output[0], skip_special_tokens=True)
    

    return response  # This should now work correctly!
    
   
 



def main():
    """
    Launch the Gradio interface for claim comparison.
    """
    # Define the Gradio interface
    interface = gr.Interface(
        fn=compare_claims,
        inputs=[
            gr.Textbox(label="claim_json1", placeholder="Enter first claim description..."),
            gr.Textbox(label="claim_json2", placeholder="Enter second claim description...")
        ],
        outputs="text",
        title="Claims Comparison",
        description="Enter two claims to compare their differences."
    )

    # Launch the Gradio app
    interface.launch()

if __name__ == "__main__":
    main()