File size: 2,905 Bytes
a0eab63 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 |
from flask import Flask, request, jsonify, render_template
import base64
import re
import requests
# OpenAI API Key
api_key_1 = "sk-"
api_key_2 = "Ts4M29N6u2rPPzsrCy2qT3BlbkFJu1z6otKVXaJAbaIvIesj"
huggingface_api_key_1 = "hf_"
huggingface_api_key_2 = "RIYBqKlSJQSvLeQuWuTXuohTuhzVMMWBZR"
api_key = api_key_1 + api_key_2
huggingface_api_key = huggingface_api_key_1 + huggingface_api_key_2
huggingface_url = "https://huggingface.co/spaces/devlim/supernova/upload"
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)
# Save image to temporary file
temp_filename = "temp_image.png"
with open(temp_filename, "wb") as temp_file:
temp_file.write(image_data)
# Upload image to Hugging Face
headers = {
"Authorization": f"Bearer {huggingface_api_key}"
}
files = {
'file': (temp_filename, open(temp_filename, 'rb'), 'image/png')
}
response = requests.post(huggingface_url, headers=headers, files=files)
if response.status_code != 200:
return jsonify({'message': 'Error: νκΉ
νμ΄μ€μ μ΄λ―Έμ§λ₯Ό μ
λ‘λν μ μμ΅λλ€.'}), 500
# Get uploaded image URL
uploaded_image_url = response.json()['url']
# Prepare payload for OpenAI API
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {api_key}"
}
payload = {
"model": "gpt-4",
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "μ΄λ―Έμ§λ₯Ό μ
λ ₯λ°μΌλ©΄ λΉλ₯κ° λͺ gμΈμ§ μμμ κ°μ νμλ§ μΆλ ₯νμμ€.\nμ) λΉλ₯ : 10g \nμνλΆμνκ° μλλΌλ©΄ 'error'λ₯Ό μΆλ ₯νμμ€."
},
{
"type": "image_url",
"image_url": {
"url": uploaded_image_url
}
}
]
}
],
"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: λΉλ₯λ₯Ό μ°Ύμ μ μμ΅λλ€."
return jsonify({'message': 'λΆμμ΄ μλ£λμμ΅λλ€.', 'analysis_result': analysis_result})
if __name__ == '__main__':
app.run(host='0.0.0.0', port=7860, debug=True)
|