6.2.llama-by-langchain.py

# 导入HuggingFace API Token
from dotenv import load_dotenv
load_dotenv(override=True)

# 导入必要的库
from langchain.prompts import PromptTemplate
from langchain.llms import HuggingFaceHub
from langchain.chains import LLMChain

# 初始化HF LLM
llm = HuggingFaceHub(
    repo_id="google/flan-t5-small",
    #repo_id="meta-llama/Llama-2-7b-chat-hf",
)

# 创建简单的question-answering提示模板
template = """Question: {question}
              Answer: """

# 创建Prompt
prompt = PromptTemplate(template=template, input_variables=["question"])

# 调用LLM Chain --- 我们以后会详细讲LLM Chain
llm_chain = LLMChain(
    prompt=prompt,
    llm=llm
)

# 准备问题
question = "Rose is which type of flower?"

# 调用模型并返回结果
print(llm_chain.run(question))