import openai

openai.api_base = "http://192.168.0.xx:80/v1"

# Enter any non-empty API key to pass the client library's check.
openai.api_key = "xxx"

# Enter any non-empty model name to pass the client library's check.
completion = openai.ChatCompletion.create(
    model="chatglm-6b",
    messages=[
        {"role": "user", "content": "你好"},
    ],
    stream=False,
)

print(completion.choices[0].message.content)
# 你好👋！我是人工智能助手 ChatGLM-6B，很高兴见到你，欢迎问我任何问题。

import openai

openai.api_base = "http://192.168.0.xx:80/v1"

# Enter any non-empty API key to pass the client library's check.
openai.api_key = "xxx"

# Enter any non-empty model name to pass the client library's check.
completion = openai.Completion.create(prompt="你好", model="chatglm-6b")

print(completion.choices[0].text)
# 你好👋！我是人工智能助手 ChatGLM-6B，很高兴见到你，欢迎问我任何问题。

import openai

openai.api_base = "http://192.168.0.xx:80/v1"

# Enter any non-empty API key to pass the client library's check.
openai.api_key = "xxx"

# compute the embedding of the text
embedding = openai.Embedding.create(
    input="什么是chatgpt？", 
    model="text2vec-large-chinese"
)

print(embedding['data'][0]['embedding'])

import os

os.environ["OPENAI_API_BASE"] = "http://192.168.0.xx:80/v1"
os.environ["OPENAI_API_KEY"] = "xxx"

from langchain.chat_models import ChatOpenAI
from langchain.schema import HumanMessage

chat = ChatOpenAI()
print(chat([HumanMessage(content="你好")]))
# content='你好👋！我是人工智能助手 ChatGLM-6B，很高兴见到你，欢迎问我任何问题。' additional_kwargs={}

import os

os.environ["OPENAI_API_BASE"] = "http://192.168.0.xx:80/v1"
os.environ["OPENAI_API_KEY"] = "xxx"

from langchain.llms import OpenAI

llm = OpenAI()
print(llm("你好"))
# 你好👋！我是人工智能助手 ChatGLM-6B，很高兴见到你，欢迎问我任何问题。

import os

os.environ["OPENAI_API_BASE"] = "http://192.168.0.xx:80/v1"
os.environ["OPENAI_API_KEY"] = "xxx"

from langchain.embeddings import OpenAIEmbeddings

embeddings = OpenAIEmbeddings()
query_result = embeddings.embed_query("什么是chatgpt？")
print(query_result)