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File size: 2,105 Bytes
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from flask import Flask, request, jsonify, render_template, send_from_directory
import base64
import re
import os
from datetime import datetime
import requests
# OpenAI API Key
api_key = "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"
app = Flask(__name__)
@app.route('/')
def index():
return render_template('index.html')
@app.route('/save_image', methods=['POST'])
def save_image():
data = request.get_json()
image_data = data['image']
# Decode the base64 image data
image_data = re.sub('^data:image/.+;base64,', '', image_data)
image_data = base64.b64decode(image_data)
# Encode image to base64 string
base64_image = base64.b64encode(image_data).decode('utf-8')
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {api_key}"
}
payload = {
"model": "gpt-4",
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "์ด๋ฏธ์ง๋ฅผ ์
๋ ฅ๋ฐ์ผ๋ฉด ๋น๋ฅ๊ฐ ๋ช g์ธ์ง ์์์ ๊ฐ์ ํ์๋ง ์ถ๋ ฅํ์์ค.\n์) ๋น๋ฅ : 10g \n์ํ๋ถ์ํ๊ฐ ์๋๋ผ๋ฉด 'error'๋ฅผ ์ถ๋ ฅํ์์ค."
},
{
"type": "image_url",
"image_url": {
"url": f"data:image/jpeg;base64,{base64_image}"
}
}
]
}
],
"max_tokens": 300
}
response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)
if response.status_code == 200:
result = response.json()
analysis_result = result['choices'][0]['message']['content']
else:
analysis_result = "Error: ๋น๋ฅ๋ฅผ ์ฐพ์ ์ ์์ต๋๋ค."
print(analysis_result)
return jsonify({'message': '๋ถ์์ด ์๋ฃ๋์์ต๋๋ค.', 'analysis_result': analysis_result})
if __name__ == '__main__':
app.run(host='0.0.0.0', port=7860, debug=True) |