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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, | |
| ) | |
| def index(): | |
| return render_template('index.html') | |
| def indexx(): | |
| return render_template('maj.html') | |
| 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-2.5-pro-exp-03-25", | |
| contents=[ | |
| {'inline_data': {'mime_type': 'image/png', 'data': img_str}}, | |
| """Résous cet exercice en français avec du LaTeX. | |
| Si nécessaire, utilise du code Python pour effectuer les calculs complexes. | |
| Présente ta solution de façon claire et espacée.""" | |
| ], | |
| config=types.GenerateContentConfig( | |
| thinking_config=types.ThinkingConfig( | |
| thinking_budget=8000 | |
| ), | |
| tools=[types.Tool( | |
| code_execution=types.ToolCodeExecution() | |
| )] | |
| ) | |
| ) | |
| for chunk in response: | |
| for part in chunk.candidates[0].content.parts: | |
| if hasattr(part, 'thought') and part.thought: | |
| if mode != "thinking": | |
| yield 'data: ' + json.dumps({"mode": "thinking"}) + '\n\n' | |
| mode = "thinking" | |
| elif hasattr(part, 'executable_code') and part.executable_code: | |
| if mode != "executing_code": | |
| yield 'data: ' + json.dumps({"mode": "executing_code"}) + '\n\n' | |
| mode = "executing_code" | |
| code_block_open = "```python\n" | |
| code_block_close = "\n```" | |
| yield 'data: ' + json.dumps({"content": code_block_open + part.executable_code.code + code_block_close}) + '\n\n' | |
| elif hasattr(part, 'code_execution_result') and part.code_execution_result: | |
| if mode != "code_result": | |
| yield 'data: ' + json.dumps({"mode": "code_result"}) + '\n\n' | |
| mode = "code_result" | |
| result_block_open = "Résultat d'exécution:\n```\n" | |
| result_block_close = "\n```" | |
| yield 'data: ' + json.dumps({"content": result_block_open + part.code_execution_result.output + result_block_close}) + '\n\n' | |
| else: | |
| if mode != "answering": | |
| yield 'data: ' + json.dumps({"mode": "answering"}) + '\n\n' | |
| mode = "answering" | |
| if hasattr(part, 'text') and part.text: | |
| yield 'data: ' + json.dumps({"content": part.text}) + '\n\n' | |
| except Exception as e: | |
| print(f"Error during generation: {e}") | |
| yield '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 | |
| 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-2.5-flash-preview-04-17", | |
| contents=[ | |
| {'inline_data': {'mime_type': 'image/png', 'data': img_str}}, | |
| """Résous cet exercice en français avec du LaTeX. | |
| Si nécessaire, utilise du code Python pour effectuer les calculs complexes. | |
| Présente ta solution de façon claire et espacée.""" | |
| ], | |
| config=types.GenerateContentConfig( | |
| tools=[types.Tool( | |
| code_execution=types.ToolCodeExecution() | |
| )] | |
| ) | |
| ) | |
| for chunk in response: | |
| for part in chunk.candidates[0].content.parts: | |
| if hasattr(part, 'thought') and part.thought: | |
| if mode != "thinking": | |
| yield 'data: ' + json.dumps({"mode": "thinking"}) + '\n\n' | |
| mode = "thinking" | |
| elif hasattr(part, 'executable_code') and part.executable_code: | |
| if mode != "executing_code": | |
| yield 'data: ' + json.dumps({"mode": "executing_code"}) + '\n\n' | |
| mode = "executing_code" | |
| code_block_open = "```python\n" | |
| code_block_close = "\n```" | |
| yield 'data: ' + json.dumps({"content": code_block_open + part.executable_code.code + code_block_close}) + '\n\n' | |
| elif hasattr(part, 'code_execution_result') and part.code_execution_result: | |
| if mode != "code_result": | |
| yield 'data: ' + json.dumps({"mode": "code_result"}) + '\n\n' | |
| mode = "code_result" | |
| result_block_open = "Résultat d'exécution:\n```\n" | |
| result_block_close = "\n```" | |
| yield 'data: ' + json.dumps({"content": result_block_open + part.code_execution_result.output + result_block_close}) + '\n\n' | |
| else: | |
| if mode != "answering": | |
| yield 'data: ' + json.dumps({"mode": "answering"}) + '\n\n' | |
| mode = "answering" | |
| if hasattr(part, 'text') and part.text: | |
| yield 'data: ' + json.dumps({"content": part.text}) + '\n\n' | |
| except Exception as e: | |
| print(f"Error during generation: {e}") | |
| yield '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) |