lifestyle_agent.py

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

def get_lifestyle_tips(lifestyle_query):
    model_name = "m42-health/med42-70b"
    tokenizer = AutoTokenizer.from_pretrained(model_name)
    model = AutoModelForCausalLM.from_pretrained(model_name)
    prompt = f"Give healthy lifestyle tips based on the query: {lifestyle_query}."
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(**inputs, max_new_tokens=150)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)