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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) |