AI大模型企业应用实战(07)-LangChain的Hello World项目

import os
os.environ["OPENAI_API_KEY"] = "xxx"
# 为了科学上网，所以需要添加
os.environ["OPENAI_PROXY"] = "xxx"

import openai
import os
openai.api_base =os.environ.get("OPENAI_PROXY")
openai.api_key = os.environ.get("OPENAI_API_KEY")
print("OPENAI_API_KEY:", openai_api_key)
print("OPENAI_PROXY:", openai_api_base)

! pip show langchain
! pip show openai

import openai
import os

openai.api_base =os.environ.get("OPENAI_PROXY")
openai.api_key = os.environ.get("OPENAI_API_KEY")

messages = [
{"role": "user", "content": "介绍下你自己"}
]

res = openai.ChatCompletion.create(
    model="gpt-3.5-turbo",
    messages=messages,
    stream=False,
)
print(res['choices'][0]['message']['content'])

from langchain.llms import OpenAI
import os

api_base =os.environ.get("OPENAI_PROXY")
api_key = os.environ.get("OPENAI_API_KEY")

llm = OpenAI(
    model="gpt-3.5-turbo",
    temperature=0,
    openai_api_key=api_key,
    openai_api_base=api_base
    )
llm.predict("介绍下你自己")

from langchain.llms import OpenAI
from langchain.prompts import PromptTemplate
import os
api_base =os.environ.get("OPENAI_PROXY")
api_key = os.environ.get("OPENAI_API_KEY")

llm = OpenAI(
    model="gpt-3.5-turbo-instruct",
    temperature=0,
    openai_api_key=api_key,
    openai_api_base=api_base
    )
prompt = PromptTemplate.from_template("你是一个起名大师,请模仿示例起3个{county}名字,比如男孩经常被叫做{boy},女孩经常被叫做{girl}")
message = prompt.format(county="中国特色的",boy="狗蛋",girl="翠花")
print(message)
llm.predict(message)

from langchain.schema import BaseOutputParser
#自定义class，继承了BaseOutputParser
class CommaSeparatedListOutputParser(BaseOutputParser):
    """Parse the output of an LLM call to a comma-separated list."""


    def parse(self, text: str):
        """Parse the output of an LLM call."""
        return text.strip().split(", ")

CommaSeparatedListOutputParser().parse("hi, bye")

['hi', 'bye']

#起名大师，输出格式为一个数组
from langchain.llms import OpenAI
from langchain.prompts import PromptTemplate
import os
from langchain.schema import BaseOutputParser

#自定义类
class CommaSeparatedListOutputParser(BaseOutputParser):
    """Parse the output of an LLM call to a comma-separated list."""

    def parse(self, text: str):
        """Parse the output of an LLM call."""
        print(text)
        return text.strip().split(",")


api_base = os.getenv("OPENAI_API_BASE")
api_key = os.getenv("OPENAI_KEY")
llm = OpenAI(
    model="gpt-3.5-turbo-instruct",
    temperature=0,
    openai_api_key=api_key,
    openai_api_base=api_base
    )
prompt = PromptTemplate.from_template("你是一个起名大师,请模仿示例起3个具有{county}特色的名字,示例：男孩常用名{boy},女孩常用名{girl}。请返回以逗号分隔的列表形式。仅返回逗号分隔的列表，不要返回其他内容。")
message = prompt.format(county="美国男孩",boy="sam",girl="lucy")
print(message)
strs = llm.predict(message)
CommaSeparatedListOutputParser().parse(strs)

['jack', ' michael', ' jason']