analysis.py

from transformers import pipeline

# Load a free model for text generation
llm_pipeline = pipeline("text-generation", model="mistralai/Mistral-7B-Instruct", device_map="auto")

def analyze_spending_pattern(df):
    prompt = f"""
    Here is the user's spending data:
    {df.to_string(index=False)}
    
    Identify spending trends, categorize expenses, and highlight areas for cost-saving.
    """
    response = llm_pipeline(prompt, max_length=200, do_sample=True)
    return response[0]['generated_text']

def get_financial_advice(df):
    prompt = f"""
    Given the following transaction history:
    {df.to_string(index=False)}
    
    Provide personalized recommendations to reduce expenses and improve financial health.
    """
    response = llm_pipeline(prompt, max_length=200, do_sample=True)
    return response[0]['generated_text']