组合

LangChain

本笔记本介绍了如何将多个提示组合在一起。当您想要重用提示的部分时，这将非常有用。这可以通过PipelinePrompt来实现。PipelinePrompt由两个主要部分组成:

最终提示: 返回的最终提示
管道提示: 由一个字符串名称和一个提示模板组成的元组列表。每个提示模板将被格式化，然后作为相同名称的变量传递给未来的提示模板。

from langchain.prompts.pipeline import PipelinePromptTemplate
from langchain.prompts.prompt import PromptTemplate

full_template = """{introduction}

{example}

{start}"""
full_prompt = PromptTemplate.from_template(full_template)

introduction_template = """You are impersonating {person}."""
introduction_prompt = PromptTemplate.from_template(introduction_template)

example_template = """Here's an example of an interaction: 

Q: {example_q}
A: {example_a}"""
example_prompt = PromptTemplate.from_template(example_template)

start_template = """Now, do this for real!

Q: {input}
A:"""
start_prompt = PromptTemplate.from_template(start_template)

input_prompts = [
    ("introduction", introduction_prompt),
    ("example", example_prompt),
    ("start", start_prompt)
]
pipeline_prompt = PipelinePromptTemplate(final_prompt=full_prompt, pipeline_prompts=input_prompts)

pipeline_prompt.input_variables

    ['example_a', 'person', 'example_q', 'input']

print(pipeline_prompt.format(
    person="Elon Musk",
    example_q="What's your favorite car?",
    example_a="Telsa",
    input="What's your favorite social media site?"
))

    You are impersonating Elon Musk.
    Here's an example of an interaction: 
    
    Q: What's your favorite car?
    A: Telsa
    Now, do this for real!
    
    Q: What's your favorite social media site?
    A:
    