如何快速开发一个open AI 的代理服务器,让其他用户配置此代理服务器后可以正常访问OPEN AI,请给出步骤和代码。 用python实现
时间: 2023-05-27 16:02:21 浏览: 216
人工智能openAi接口
步骤如下:
1. 首先,需要导入OpenAI相关库:
```python
import openai
```
2. 接下来,需要在OpenAI官网注册账户,获取API密钥并进行身份验证,代码示例:
```python
openai.api_key = "your-api-key"
```
3. 定义一个函数,接受用户输入的query,并使用openai库中的gpt-3模型进行文本生成,代码示例如下:
```python
def generate_text(query):
model_engine = "davinci"
prompt = (query.strip() + "\n").encode("utf-8")
completions = openai.Completion.create(
engine=model_engine, prompt=prompt, max_tokens=1024, n=1,stop=None,temperature=0.5)
message = completions.choices[0].text
response = message.strip().replace("\n", " ")
return response
```
4. 创建一个Flask应用程序,并在应用程序中定义一个路由,接受用户请求并返回生成的文本。代码示例如下:
```python
from flask import Flask, request
app = Flask(__name__)
@app.route('/generate', methods=['POST'])
def generate():
query = request.form['query']
response = generate_text(query)
return response
if __name__ == '__main__':
app.run(debug=True)
```
5. 最后,用户可以在本地或云端主机上部署此Flask应用程序,并让其他用户配置代理服务器以正常访问OpenAI。代码示例如下:
```python
from http.client import HTTPConnection
from urllib.parse import urlparse
def make_proxy_request(url, method, body=None, headers=None, **kwargs):
parsed_url = urlparse(url)
conn = HTTPConnection(parsed_url.netloc, timeout=10)
if headers is None:
headers = {}
headers['Host'] = parsed_url.netloc
try:
conn.request(method, parsed_url.path, body, headers)
response = conn.getresponse()
return response.read()
except Exception as e:
print("Error: ", e)
@app.route('/proxy', methods=['GET', 'POST'])
def proxy():
if request.method == 'POST':
query = request.form['query']
proxy_url = "http://localhost:5000/generate"
response = make_proxy_request(proxy_url, 'POST', body={"query": query})
return response
else:
return 'Invalid request method'
```
以上是用Python实现一个open AI的代理服务器的步骤和代码。需要注意的是,由于OpenAI的API接口较为昂贵,使用时需要小心控制调用次数。
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