conda activate chatglm3
cd openai_api_demo
python openai_api.py

启动ok，然后内网映射后

anaconda启动jupyter

!pip install openai==1.6.1 -i https://pypi.tuna.tsinghua.edu.cn/simple/

"""
This script is an example of using the OpenAI API to create various interactions with a ChatGLM3 model. It includes functions to:
1. Conduct a basic chat session, asking about weather conditions in multiple cities.
2. Initiate a simple chat in Chinese, asking the model to tell a short story.
3. Retrieve and print embeddings for a given text input.
Each function demonstrates a different aspect of the API's capabilities, showcasing how to make requests and handle responses.
"""
import os
from openai import OpenAIbase_url = "https://16h5v06565.zicp.fun/v1/"
client = OpenAI(api_key="EMPTY", base_url=base_url)

def function_chat():messages = [{"role": "user", "content": "What's the weather like in San Francisco, Tokyo, and Paris?"}]tools = [{"type": "function","function": {"name": "get_current_weather","description": "Get the current weather in a given location","parameters": {"type": "object","properties": {"location": {"type": "string","description": "The city and state, e.g. San Francisco, CA",},"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},},"required": ["location"],},},}]response = client.chat.completions.create(model="chatglm3-6b",messages=messages,tools=tools,tool_choice="auto",)if response:content = response.choices[0].message.contentprint(content)else:print("Error:", response.status_code)def simple_chat(use_stream=True):messages = [{"role": "system","content": "You are ChatGLM3, a large language model trained by Zhipu.AI. Follow the user's instructions carefully. Respond using markdown.",},{"role": "user","content": "你好，带在华政搞计算机有前途么"}]response = client.chat.completions.create(model="chatglm3-6b",messages=messages,stream=use_stream,max_tokens=256,temperature=0.8,presence_penalty=1.1,top_p=0.8)if response:if use_stream:for chunk in response:print(chunk.choices[0].delta.content)else:content = response.choices[0].message.contentprint(content)else:print("Error:", response.status_code)

if __name__ == "__main__":simple_chat(use_stream=False)# simple_chat(use_stream=True)#embedding()# function_chat()