app.py

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

app = Flask(__name__)

GOOGLE_API_KEY =  os.environ.get("GEMINI_API_KEY")

client = genai.Client(
    api_key=GOOGLE_API_KEY,
    http_options={'api_version': 'v1alpha'},
)

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


@app.route('/free')
def indexx():
    return render_template('maj.html')
    


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

        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-2.0-flash-thinking-exp-01-21",
                    config={'thinking_config': {'include_thoughts': True}},
                    contents=[
                        {'inline_data': {'mime_type': 'image/png', 'data': img_str}},
                        " Résous ça en français. Write you answer with rendering Latex."
                    ]
                )
#Resous cette exercice. ça doit être bien présentable et espacé. je veux un jolie rendu
                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": str(e)})}\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': str(e)}), 500



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

        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-2.0-flash-exp",
                    contents=[
                        {'inline_data': {'mime_type': 'image/png', 'data': img_str}},
                        " Résous ça en français. Write you answer with rendering Latex."
                    ]
                )
#Resous cette exercice. ça doit être bien présentable et espacé. je veux un jolie rendu
                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": str(e)})}\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': str(e)}), 500
        



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