A short wrapper of the OpenAI api call.
Project description
以下为 ChatGPT 自动生成的 README.md 文件(待修改),中文文档移步这里。
Openai API call
A simple wrapper for OpenAI API, which can send prompt message and return response.
Installation
pip install git+https://github.com/RexWzh/openai_api_call.git
Usage
Set API Key
import openai
openai.api_key = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
Or set OPENAI_API_KEY
in ~/.bashrc
to automatically set it when you start the terminal:
# Add the following code to ~/.bashrc
export OPENAI_API_KEY="sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
Set Proxy (Optional)
from openai_api_call import proxy_on, proxy_off, show_proxy
# Check the current proxy
show_proxy()
# Set local proxy, port number is 7890 by default
proxy_on("127.0.0.1", port=7890)
# Check the updated proxy
show_proxy()
# Turn off proxy
proxy_off()
Basic Usage
Example 1, send prompt and return information:
from openai_api_call import prompt2response, show_apikey
# Check if API key is set
show_apikey()
# Check if proxy is enabled
show_proxy()
# Send prompt and return response
prompt = "Hello, GPT-3.5!"
resp = prompt2response(prompt)
print(resp.content)
Example 2, customize the message template and return the information and the number of consumed tokens:
import openai_api_call
# Customize the sending template
openai_api_call.default_prompt = lambda msg: [
{"role": "system", "content": "帮我翻译这段文字"},
{"role": "user", "content": msg}
]
prompt = "Hello!"
# Set the number of retries to Inf
response = prompt2response(prompt, temperature=0.5, max_requests=-1)
print("Number of consumed tokens: ", response.total_tokens)
print("Returned content: ", response.content)
Advanced Usage
Continue chatting based on the last response:
# first call
prompt = "Hello, GPT-3.5!"
resp = prompt2response(prompt)
print(resp.content)
# next call
next_prompt = resp.next_prompt("How are you?")
print(next_prompt)
next_resp = prompt2response(next_prompt)
print(next_resp.content)
# print chat history
list(map(print,next_resp.chat_log()))
License
This package is licensed under the MIT license. See the LICENSE file for more details.
Features
- TODO
Credits
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
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