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GooseAI

GooseAI 是一个完全托管的自然语言处理即服务,通过API提供。GooseAI提供对这些模型的访问。

本笔记本介绍了如何使用Langchain与GooseAI

安装openai

使用GooseAI API需要openai包。使用pip install openai安装openai

%pip install --upgrade --quiet  langchain-openai

导入

<!--IMPORTS:[{"imported": "LLMChain", "source": "langchain.chains", "docs": "https://python.langchain.com/api_reference/langchain/chains/langchain.chains.llm.LLMChain.html", "title": "GooseAI"}, {"imported": "GooseAI", "source": "langchain_community.llms", "docs": "https://python.langchain.com/api_reference/community/llms/langchain_community.llms.gooseai.GooseAI.html", "title": "GooseAI"}, {"imported": "PromptTemplate", "source": "langchain_core.prompts", "docs": "https://python.langchain.com/api_reference/core/prompts/langchain_core.prompts.prompt.PromptTemplate.html", "title": "GooseAI"}]-->
import os

from langchain.chains import LLMChain
from langchain_community.llms import GooseAI
from langchain_core.prompts import PromptTemplate

设置环境 API 密钥

确保从 GooseAI 获取您的 API 密钥。您将获得 $10 的免费积分以测试不同的模型。

from getpass import getpass

GOOSEAI_API_KEY = getpass()
os.environ["GOOSEAI_API_KEY"] = GOOSEAI_API_KEY

创建 GooseAI 实例

您可以指定不同的参数,例如模型名称、生成的最大令牌、温度等。

llm = GooseAI()

创建提示词模板

我们将为问答创建一个提示词模板。

template = """Question: {question}

Answer: Let's think step by step."""

prompt = PromptTemplate.from_template(template)

初始化 LLMChain

llm_chain = LLMChain(prompt=prompt, llm=llm)

运行 LLMChain

提供一个问题并运行 LLMChain。

question = "What NFL team won the Super Bowl in the year Justin Beiber was born?"

llm_chain.run(question)

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