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序列化 （Serialization）

通常最好将提示存储为文件而不是Python代码。这样可以方便地共享、存储和版本化提示。本笔记本将介绍如何在LangChain中进行序列化，同时介绍了不同类型的提示和不同的序列化选项。

在高层次上，序列化遵循以下设计原则：

  1. 支持JSON和YAML。我们希望支持人类在磁盘上可读的序列化方法，而YAML和JSON是其中最流行的方法之一。请注意，此规则适用于提示。对于其他资产，如示例，可能支持不同的序列化方法。

  2. 我们支持将所有内容都存储在一个文件中，或者将不同的组件（模板、示例等）存储在不同的文件中并进行引用。对于某些情况，将所有内容存储在一个文件中是最合理的，但对于其他情况，最好拆分一些资产（长模板、大型示例、可复用组件）。LangChain同时支持两种方式。

还有一个单一入口点可以从磁盘加载提示，这样可以轻松加载任何类型的提示。

# 所有的提示都通过`load_prompt`函数加载。
from langchain.prompts import load_prompt

PromptTemplate​

本部分涵盖了加载PromptTemplate的示例。

从YAML加载​

下面是从YAML加载PromptTemplate的示例。

!cat simple_prompt.yaml
_type: prompt

input_variables:

    ["adjective", "content"]

template: 

    Tell me a {adjective} joke about {content}.
prompt = load_prompt("simple_prompt.yaml")
print(prompt.format(adjective="funny", content="chickens"))
Tell me a funny joke about chickens.

Loading from JSON​

This shows an example of loading a PromptTemplate from JSON.

!cat simple_prompt.json
{

    "_type": "prompt",

    "input_variables": ["adjective", "content"],

    "template": "Tell me a {adjective} joke about {content}."

}
prompt = load_prompt("simple_prompt.json")
print(prompt.format(adjective="funny", content="chickens"))

Tell me a funny joke about chickens.

Loading Template from a File​

This shows an example of storing the template in a separate file and then referencing it in the config. Notice that the key changes from template to template_path.

!cat simple_template.txt
Tell me a {adjective} joke about {content}.
!cat simple_prompt_with_template_file.json
{

    "_type": "prompt",

    "input_variables": ["adjective", "content"],

    "template_path": "simple_template.txt"

}
prompt = load_prompt("simple_prompt_with_template_file.json")
print(prompt.format(adjective="funny", content="chickens"))
Tell me a funny joke about chickens.

FewShotPromptTemplate​

This section covers examples for loading few shot prompt templates.

Examples​

This shows an example of what examples stored as json might look like.

!cat examples.json
[

    {"input": "happy", "output": "sad"},

    {"input": "tall", "output": "short"}

]

And here is what the same examples stored as yaml might look like.

!cat examples.yaml
- input: happy

  output: sad

- input: tall

  output: short

Loading from YAML​

This shows an example of loading a few shot example from YAML.

!cat few_shot_prompt.yaml
_type: few_shot

input_variables:

    ["adjective"]

prefix: 

    Write antonyms for the following words.

example_prompt:

    _type: prompt

    input_variables:

        ["input", "output"]

    template:

        "Input: {input}\nOutput: {output}"

examples:

    examples.json

suffix:

    "Input: {adjective}\nOutput:"
prompt = load_prompt("few_shot_prompt.yaml")
print(prompt.format(adjective="funny"))
Write antonyms for the following words.

Input: happy
Output: sad

Input: tall
Output: short

Input: funny
Output:

The same would work if you loaded examples from the yaml file.

!cat few_shot_prompt_yaml_examples.yaml
_type: few_shot

input_variables:

    ["adjective"]

prefix: 

    Write antonyms for the following words.

example_prompt:

    _type: prompt

    input_variables:

        ["input", "output"]

    template:

        "Input: {input}\nOutput: {output}"

examples:

    examples.yaml

suffix:

    "Input: {adjective}\nOutput:"
prompt = load_prompt("few_shot_prompt_yaml_examples.yaml")
print(prompt.format(adjective="funny"))
Write antonyms for the following words.

Input: happy
Output: sad

Input: tall
Output: short

Input: funny
Output:

Loading from JSON​

This shows an example of loading a few shot example from JSON.

!cat few_shot_prompt.json
{

    "_type": "few_shot",

    "input_variables": ["adjective"],

    "prefix": "Write antonyms for the following words.",

    "example_prompt": {

        "_type": "prompt",

        "input_variables": ["input", "output"],

        "template": "Input: {input}\nOutput: {output}"

    },

    "examples": "examples.json",

    "suffix": "Input: {adjective}\nOutput:"

}   
prompt = load_prompt("few_shot_prompt.json")
print(prompt.format(adjective="funny"))
Write antonyms for the following words.

Input: happy
Output: sad

Input: tall
Output: short

Input: funny
Output:

Examples in the Config​

This shows an example of referencing the examples directly in the config.

!cat few_shot_prompt_examples_in.json
{

    "_type": "few_shot",

    "input_variables": ["adjective"],

    "prefix": "Write antonyms for the following words.",

    "example_prompt": {

        "_type": "prompt",

        "input_variables": ["input", "output"],

        "template": "Input: {input}\nOutput: {output}"

    },

    "examples": [

        {"input": "happy", "output": "sad"},

        {"input": "tall", "output": "short"}

    ],

    "suffix": "Input: {adjective}\nOutput:"

}   
prompt = load_prompt("few_shot_prompt_examples_in.json")
print(prompt.format(adjective="funny"))
Write antonyms for the following words.

Input: happy
Output: sad

Input: tall
Output: short

Input: funny
Output:

Example Prompt from a File​

This shows an example of loading the PromptTemplate that is used to format the examples from a separate file. Note that the key changes from example_prompt to example_prompt_path.

!cat example_prompt.json
{

    "_type": "prompt",

    "input_variables": ["input", "output"],

    "template": "Input: {input}\nOutput: {output}" 

}
!cat few_shot_prompt_example_prompt.json
{

    "_type": "few_shot",

    "input_variables": ["adjective"],

    "prefix": "Write antonyms for the following words.",

    "example_prompt_path": "example_prompt.json",

    "examples": "examples.json",

    "suffix": "Input: {adjective}\nOutput:"

}   
prompt = load_prompt("few_shot_prompt_example_prompt.json")
print(prompt.format(adjective="funny"))
Write antonyms for the following words.

Input: happy
Output: sad

Input: tall
Output: short

Input: funny
Output:

PromptTempalte with OutputParser​

This shows an example of loading a prompt along with an OutputParser from a file.

! cat prompt_with_output_parser.json
{

    "input_variables": [

        "question",

        "student_answer"

    ],

    "output_parser": {

        "regex": "(.*?)\\nScore: (.*)",

        "output_keys": [

            "answer",

            "score"

        ],

        "default_output_key": null,

        "_type": "regex_parser"

    },

    "partial_variables": {},

    "template": "Given the following question and student answer, provide a correct answer and score the student answer.\nQuestion: {question}\nStudent Answer: {student_answer}\nCorrect Answer:",

    "template_format": "f-string",

    "validate_template": true,

    "_type": "prompt"

}
prompt = load_prompt("prompt_with_output_parser.json")
prompt.output_parser.parse(
    "George Washington was born in 1732 and died in 1799.\nScore: 1/2"
)
{'answer': 'George Washington was born in 1732 and died in 1799.',
 'score': '1/2'}