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.gitattributes

@@ -40,3 +40,4 @@ img4.png filter=lfs diff=lfs merge=lfs -text
 img5.png filter=lfs diff=lfs merge=lfs -text
 img6.png filter=lfs diff=lfs merge=lfs -text
 logo.png filter=lfs diff=lfs merge=lfs -text
+share_now.png filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,50 @@
+from flask import Flask, request, jsonify, send_file
+from analysis import get_comprehensive_analysis, generate_html_report
+from pdf_generator import generate_pdf
+import os
+import uuid
+
+app = Flask(__name__)
+
+@app.route("/analyze", methods=["POST"])
+def analyze():
+    if "image" not in request.files:
+        return jsonify({"success": False, "error": "No image uploaded"}), 400
+
+    image_file = request.files["image"]
+
+    # Save temp image
+    temp_name = f"upload_{uuid.uuid4().hex}.jpg"
+    image_file.save(temp_name)
+
+    # Run AI analysis
+    analysis = get_comprehensive_analysis(temp_name)
+    if not analysis:
+        return jsonify({"success": False, "error": "Analysis failed"}), 500
+
+    # Generate HTML and PDF
+    html_path = generate_html_report(analysis, "new_report.html")
+    pdf_path = generate_pdf(html_path, "report.pdf")
+
+    # Delete input image
+    os.remove(temp_name)
+
+    # If user wants PDF, return file
+    if request.form.get("return_pdf") == "true":
+        return send_file(pdf_path, mimetype="application/pdf", as_attachment=True)
+
+    # JSON only
+    return jsonify({
+        "success": True,
+        "analysis": analysis,
+        "pdf_ready": True
+    })
+
+
+@app.route("/")
+def home():
+    return "YOUV.AI Flask API is running!"
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=7860)
+