app.py

import fitz  # PyMuPDF
import google.generativeai as genai
import streamlit as st

def extract_text_from_pdf(pdf_path):
    """Extracts text from a PDF file."""
    text = ""
    try:
        with fitz.open(pdf_path) as doc:
            for page in doc:
                text += page.get_text("text") + "\n"
    except Exception as e:
        st.error(f"Error reading PDF: {e}")
    return text

def analyze_health_data(text):
    """Analyzes extracted text using Google Generative AI (Free Tier API)."""
    try:
        # Get a free API key from Google AI Studio: https://aistudio.google.com/
        genai.configure(api_key="AIzaSyAY6ZYxOzVV5N7mBZzDJ96WEPJGfuFx-mU")  # Replace with free API key
        model = genai.GenerativeModel("gemini-pro")  # Choose appropriate model
        response = model.generate_content(
            f"Analyze this blood report and provide trends, risks, and health suggestions:\n{text}"
        )
        return response.text
    except Exception as e:
        return f"Error in LLM response: {e}"

def main():
    st.title("Health Report Analyzer")
    uploaded_file = st.file_uploader("Upload your health report (PDF)", type=["pdf"])
    if uploaded_file is not None:
        with open("temp.pdf", "wb") as f:
            f.write(uploaded_file.getbuffer())
        extracted_text = extract_text_from_pdf("temp.pdf")
        st.subheader("Extracted Report Text:")
        st.text_area("Extracted Text", extracted_text[:1000], height=200)
        if st.button("Analyze Report"):
            with st.spinner("Analyzing..."):
                analysis = analyze_health_data(extracted_text)
            st.subheader("Health Analysis:")
            st.write(analysis)

if __name__ == "__main__":
    main()