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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()
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