StochasticAI

Stochastic 加速平台旨在简化深度学习模型的生命周期。从上传和版本控制模型，到训练、压缩和加速，再到投入生产。

此示例介绍了如何使用 LangChain 与StochasticAI 模型交互。

您必须获取 API_KEY 和 API_URL 此处。

from getpass import getpass

STOCHASTICAI_API_KEY = getpass()

 ········

import os

os.environ["STOCHASTICAI_API_KEY"] = STOCHASTICAI_API_KEY

YOUR_API_URL = getpass()

 ········

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

API 参考：LLMChain | StochasticAI | PromptTemplate

template = """Question: {question}

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

prompt = PromptTemplate.from_template(template)

llm = StochasticAI(api_url=YOUR_API_URL)

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

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

llm_chain.run(question)

"\n\nStep 1: In 1999, the St. Louis Rams won the Super Bowl.\n\nStep 2: In 1999, Beiber was born.\n\nStep 3: The Rams were in Los Angeles at the time.\n\nStep 4: So they didn't play in the Super Bowl that year.\n"

相关

• LLM 概念指南
• LLM 操作指南