from flask import Flask, render_template, request, jsonify, Response import google.generativeai as genai import os from PIL import Image import tempfile import io app = Flask(__name__) # Configuration Gemini token = os.environ.get("TOKEN") genai.configure(api_key=token) safety_settings = [ {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"}, {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"}, {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"}, {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"}, ] mm = """ resous cet exercice. tu répondras en détaillant au maximum ton procédé de calcul. réponse attendue uniquement en Latex""" model = genai.GenerativeModel( model_name="gemini-exp-1206", safety_settings=safety_settings ) @app.route('/') def home(): return render_template('index.html') @app.route('/generate', methods=['POST']) def generate(): if 'image' not in request.files: return jsonify({'error': 'No image uploaded'}), 400 image_file = request.files['image'] # Fonction pour générer des chunks de réponse def generate_stream(): with tempfile.NamedTemporaryFile(delete=False, suffix='.png') as temp_file: image_file.save(temp_file.name) try: image = Image.open(temp_file.name) # Convertir l'image en bytes pour le streaming img_byte_arr = io.BytesIO() image.save(img_byte_arr, format='PNG') img_byte_arr = img_byte_arr.getvalue() # Générer le contenu en streaming response = model.generate_content([mm, {"mime_type": "image/png", "data": img_byte_arr}], stream=True) for chunk in response: yield f"data: {chunk.text}\n\n" except Exception as e: yield f"data: Error: {str(e)}\n\n" finally: # Nettoyer le fichier temporaire os.unlink(temp_file.name) return Response(generate_stream(), mimetype='text/event-stream') if __name__ == '__main__': app.run(debug=True)