""" 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. """ from openai import OpenAI base_url = "http://127.0.0.1:8000/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.content print(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,请你用生动的话语给我讲一个小故事吧" } ] 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.content print(content) else: print("Error:", response.status_code) def embedding(): response = client.embeddings.create( model="bge-large-zh-1.5", input=["你好,给我讲一个故事,大概100字"], ) embeddings = response.data[0].embedding print("嵌入完成,维度:", len(embeddings)) if __name__ == "__main__": simple_chat(use_stream=False) simple_chat(use_stream=True) embedding() function_chat()