Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+from PIL import Image
+import pytesseract
+from PyPDF2 import PdfReader
+from reportlab.lib.pagesizes import letter
+from reportlab.pdfgen import canvas
+import os
+
+# Load the medical analysis model (e.g., BioGPT or PubMedBERT)
+medical_analyzer = pipeline("text-classification", model="microsoft/biogpt")
+
+# Function to extract text from images or PDFs
+def extract_text(file_path):
+    if file_path.endswith(".pdf"):
+        # Extract text from PDF
+        reader = PdfReader(file_path)
+        text = ""
+        for page in reader.pages:
+            text += page.extract_text()
+        return text.strip()
+    else:
+        # Extract text from image
+        return pytesseract.image_to_string(Image.open(file_path))
+
+# Function to generate a PDF report
+def create_pdf_report(analysis, output_path):
+    c = canvas.Canvas(output_path, pagesize=letter)
+    c.drawString(100, 750, "Blood Test Report Analysis")
+    c.drawString(100, 730, "---------------------------")
+    
+    y_position = 700
+    for line in analysis.split("\n"):
+        c.drawString(100, y_position, line)
+        y_position -= 20  # Move down for the next line
+    
+    c.save()
+    return output_path
+
+# Function to analyze blood test reports
+def analyze_blood_test(file):
+    # Step 1: Extract text
+    extracted_text = extract_text(file)
+    if not extracted_text:
+        return "Could not extract text. Please upload a valid file.", None
+
+    # Step 2: Use medical model to analyze extracted text
+    analysis_results = medical_analyzer(extracted_text)
+    analysis_report = "🔍 Analysis Results:\n"
+    for item in analysis_results[:5]:  # Limit results for simplicity
+        analysis_report += f"- {item['label']}: {item['score']:.2f}\n"
+
+    # Step 3: Generate downloadable PDF report
+    output_pdf = "analysis_report.pdf"
+    create_pdf_report(f"Extracted Text:\n{extracted_text}\n\n{analysis_report}", output_pdf)
+    
+    return analysis_report, output_pdf
+
+# Gradio interface setup
+interface = gr.Interface(
+    fn=analyze_blood_test,
+    inputs=gr.File(label="Upload your blood test report (PNG, JPG, JPEG, or PDF)"),
+    outputs=[
+        gr.Textbox(label="Analysis Results"),
+        gr.File(label="Download PDF Report")
+    ],
+    title="MedAI Analyzer",
+    description=(
+        "Upload your blood test report in image (PNG, JPG, JPEG) or PDF format. "
+        "The app will extract and analyze the values, flag abnormalities, and provide health recommendations. "
+        "You can also download a detailed PDF report of the analysis."
+    ),
+    allow_flagging="never"
+)
+
+if __name__ == "__main__":
+    interface.launch()