from transformers import AutoTokenizer, AutoModelForCausalLM
from huggingface_hub import login
import os

def track_health_status(input_text: str) -> str:
    # Secure way to load token
    hf_token = os.getenv("HF_TOKEN")
    login(hf_token)

    model_name = "m42-health/med42-70b"

    tokenizer = AutoTokenizer.from_pretrained(model_name, token=hf_token)
    model = AutoModelForCausalLM.from_pretrained(model_name, token=hf_token)

    inputs = tokenizer.encode(input_text, return_tensors="pt", truncation=True)
    outputs = model.generate(inputs, max_length=512)
    result = tokenizer.decode(outputs[0], skip_special_tokens=True)
    
    return result