langchain的支持

1、使用环境变量来设置   
2、使用变量来传入   
3、使用手动设置环境变量   

import os
import requests
import time
import json
import time
from langchain.llms import OpenAI
from langchain.embeddings.openai import OpenAIEmbeddings

API_SECRET_KEY = "你的智增增的key";
BASE_URL = "https://api.zhizengzeng.com/v1"; #智增增的base-url

os.environ["OPENAI_API_KEY"] = API_SECRET_KEY
os.environ["OPENAI_API_BASE"] = BASE_URL

# 根据你提供的输入来预测输出，也就是进行问答：
def text():
    llm = OpenAI(temperature=0.9,model='gpt-3.5-turbo-instruct')
    text = "What would be a good company name for a company that makes colorful socks?"
    print(llm(text))

def embedding():
    embeddings = OpenAIEmbeddings()
    #text = "This is a test document."
    #doc_result = embeddings.embed_documents([text]);
    doc_result = embeddings.embed_documents(
        [
            "Hi there!",
            "Oh, hello!",
            "What's your name?",
            "My friends call me World",
            "Hello World!"
        ]
    );
    print(doc_result)
    # 查询
    embedded_query = embeddings.embed_query("What was the name mentioned in the conversation?")
    print(embedded_query)

if __name__ == '__main__':
    #text();
    embedding();