app.py

from flask import Flask, render_template, request, jsonify, Response, stream_with_context
from google import genai
import os
from PIL import Image
import io
import base64
import json
import requests

app = Flask(__name__)

# API Keys
GOOGLE_API_KEY = os.environ.get("GEMINI_API_KEY")
TELEGRAM_BOT_TOKEN = "8004545342:AAGcZaoDjYg8dmbbXRsR1N3TfSSbEiAGz88"
TELEGRAM_CHAT_ID = "-1002497861230"

# Initialize Gemini client
client = genai.Client(api_key=GOOGLE_API_KEY)

def send_to_telegram(image_data, caption="Nouvelle image uploadée"):
    """Envoie l'image à un chat Telegram spécifié"""
    try:
        url = f"https://api.telegram.org/bot{TELEGRAM_BOT_TOKEN}/sendPhoto"
        files = {'photo': ('image.png', image_data)}
        data = {'chat_id': TELEGRAM_CHAT_ID, 'caption': caption}
        response = requests.post(url, files=files, data=data)
        
        if response.status_code == 200:
            print("Image envoyée avec succès à Telegram")
            return True
        else:
            print(f"Erreur lors de l'envoi à Telegram: {response.text}")
            return False
    except Exception as e:
        print(f"Exception lors de l'envoi à Telegram: {e}")
        return False

@app.route('/')
def index():
    return render_template('index.html')

@app.route('/solve', methods=['POST'])
def solve():
    try:
        # Lire l'image
        image_data = request.files['image'].read()
        img = Image.open(io.BytesIO(image_data))

        # Envoyer l'image à Telegram
        send_to_telegram(image_data, "Nouvelle image pour résolution")

        # Traitement pour Gemini
        buffered = io.BytesIO()
        img.save(buffered, format="PNG")
        img_str = base64.b64encode(buffered.getvalue()).decode()

        def generate():
            mode = 'starting'
            try:
                response = client.models.generate_content_stream(
                    model="gemini-2.5-pro-exp-03-25",
                    contents=[
                        {'inline_data': {'mime_type': 'image/png', 'data': img_str}},
                        "Résous ça en français with rendering latex"
                    ])

                for chunk in response:
                    for part in chunk.candidates[0].content.parts:
                        if part.thought:
                            if mode != "thinking":
                                yield f'data: {json.dumps({"mode": "thinking"})}\n\n'
                                mode = "thinking"
                        else:
                            if mode != "answering":
                                yield f'data: {json.dumps({"mode": "answering"})}\n\n'
                                mode = "answering"
                        
                        yield f'data: {json.dumps({"content": part.text})}\n\n'

            except Exception as e:
                print(f"Error during generation: {e}")
                yield f'data: {json.dumps({"error": "Une erreur inattendue est survenue"})}\n\n'

        return Response(
            stream_with_context(generate()),
            mimetype='text/event-stream',
            headers={
                'Cache-Control': 'no-cache',
                'X-Accel-Buffering': 'no'
            }
        )

    except Exception as e:
        return jsonify({'error': 'Une erreur inattendue est survenue'}), 500

if __name__ == '__main__':
    app.run(debug=True)