使用 GPT-4 Vision API 处理大量图片时出现错误：速率限制及解决方案

import os
import base64
import requests
import pandas as pd
from google.colab import drive
import time

drive.mount('/content/drive')

image_folder = '/content/drive/MyDrive/Work related/FS/Imagenes/Metadescripciones HC '
api_key = 'my api code goes here XXXXX'

def encode_image(image_path):
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode('utf-8')

headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {api_key}"
}

results_df = pd.DataFrame(columns=['Nombre del Archivo', 'Metadescripcion'])

def get_metadescription(base64_image):
    payload = {
        "model": "gpt-4-vision-preview",
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "type": "text",
                        "text": "Write a meta description for the image of this product, optimized for SEO and in less than 150 words"
                    },
                    {
                        "type": "image_url",
                        "image_url": {
                            "url": f"data:image/jpeg;base64,{base64_image}",
                            "detail": "low"
                        }
                    }
                ]
            }
        ],
        "max_tokens": 400
    }

    max_retries = 5
    for attempt in range(max_retries):
        try:
            response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)
            response_json = response.json()
            if response.status_code == 200:
                return response_json['choices'][0]['message']['content']
            else:
                print(f"Attempt {attempt   1} failed with status code: {response.status_code}")
                if response.status_code == 429:  # Rate limit error
                    wait_time = (2 ** attempt)  # Exponential backoff
                    print(f"Rate limit exceeded. Waiting {wait_time} seconds before retrying.")
                    time.sleep(wait_time)
                else:
                    print(f"Unexpected error: {response_json}")
                    return 'Error'  # Return error for other status codes
        except Exception as e:
            print(f"An exception occurred: {e}")
            return 'Error'
    return 'Error'  # Return error after all retries failed


for filename in os.listdir(image_folder):
    if filename.endswith((".png", ".jpg", ".jpeg")):
        image_path = os.path.join(image_folder, filename)
        base64_image = encode_image(image_path)

        metadescription = get_metadescription(base64_image)

        new_row = pd.DataFrame({'Nombre del Archivo': [filename], 'Metadescripcion': [metadescription]})
        results_df = pd.concat([results_df, new_row], ignore_index=True)

results_df.to_excel('/content/drive/MyDrive/Work related/FS/Imagenes/Metadescripciones.xlsx', index=False)