LLM Pydantic 程序¶

本指南介绍如何使用我们的 LLMTextCompletionProgram 生成结构化数据。给定一个 LLM 以及一个输出 Pydantic 类，生成一个结构化的 Pydantic 对象。

对于目标对象，您可以选择直接指定 output_cls，或者指定一个 PydanticOutputParser 或任何其他生成 Pydantic 对象的 BaseOutputParser。

在下面的示例中，我们将展示将数据提取到 Album 对象（可以包含 Song 对象列表）的不同方法。

提取到 Album 类¶

这是一个将输出解析为 Album 模式的简单示例，Album 模式可以包含多首歌曲。

只需在初始化 LLMTextCompletionProgram 时将 Album 传递给 output_cls 属性即可。

如果您在 Colab 上打开此 Notebook，可能需要安装 LlamaIndex 🦙。

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!pip install llama-index

!pip install llama-index

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from pydantic import BaseModel
from typing import List

from llama_index.core.program import LLMTextCompletionProgram

from pydantic import BaseModel from typing import List from llama_index.core.program import LLMTextCompletionProgram

定义输出模式

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class Song(BaseModel):
    """Data model for a song."""

    title: str
    length_seconds: int


class Album(BaseModel):
    """Data model for an album."""

    name: str
    artist: str
    songs: List[Song]

class Song(BaseModel): """一首歌曲的数据模型。""" title: str length_seconds: int class Album(BaseModel): """一张专辑的数据模型。""" name: str artist: str songs: List[Song]

定义 LLM Pydantic 程序

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from llama_index.core.program import LLMTextCompletionProgram

from llama_index.core.program import LLMTextCompletionProgram

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prompt_template_str = """\
Generate an example album, with an artist and a list of songs. \
Using the movie {movie_name} as inspiration.\
"""
program = LLMTextCompletionProgram.from_defaults(
    output_cls=Album,
    prompt_template_str=prompt_template_str,
    verbose=True,
)

prompt_template_str = """\ 生成一个示例专辑，包含艺术家和歌曲列表。\ 以电影 {movie_name} 为灵感。\ """ program = LLMTextCompletionProgram.from_defaults( output_cls=Album, prompt_template_str=prompt_template_str, verbose=True, )

运行程序以获取结构化输出。

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output = program(movie_name="The Shining")

output = program(movie_name="The Shining")

输出是一个有效的 Pydantic 对象，我们可以用它来调用函数/API。

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output

output

Out[ ]

Album(name='The Overlook', artist='Jack Torrance', songs=[Song(title='Redrum', length_seconds=240), Song(title="Here's Johnny", length_seconds=180), Song(title='Room 237', length_seconds=300), Song(title='All Work and No Play', length_seconds=210), Song(title='The Maze', length_seconds=270)])

使用 Pydantic Output Parser 初始化¶

上述方法等同于定义一个 Pydantic 输出解析器并将其传入，而不是直接传入 output_cls。

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from llama_index.core.output_parsers import PydanticOutputParser

program = LLMTextCompletionProgram.from_defaults(
    output_parser=PydanticOutputParser(output_cls=Album),
    prompt_template_str=prompt_template_str,
    verbose=True,
)

from llama_index.core.output_parsers import PydanticOutputParser program = LLMTextCompletionProgram.from_defaults( output_parser=PydanticOutputParser(output_cls=Album), prompt_template_str=prompt_template_str, verbose=True, )

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output = program(movie_name="Lord of the Rings")
output

output = program(movie_name="Lord of the Rings") output

Out[ ]

Album(name='The Fellowship of the Ring', artist='Middle-earth Ensemble', songs=[Song(title='The Shire', length_seconds=240), Song(title='Concerning Hobbits', length_seconds=180), Song(title='The Ring Goes South', length_seconds=300), Song(title='A Knife in the Dark', length_seconds=270), Song(title='Flight to the Ford', length_seconds=210), Song(title='Many Meetings', length_seconds=240), Song(title='The Council of Elrond', length_seconds=330), Song(title='The Great Eye', length_seconds=180), Song(title='The Breaking of the Fellowship', length_seconds=360)])

定义自定义输出解析器¶

有时您可能想以自己的方式将输出解析为 JSON 对象。

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from llama_index.core.output_parsers import ChainableOutputParser


class CustomAlbumOutputParser(ChainableOutputParser):
    """Custom Album output parser.

    Assume first line is name and artist.

    Assume each subsequent line is the song.

    """

    def __init__(self, verbose: bool = False):
        self.verbose = verbose

    def parse(self, output: str) -> Album:
        """Parse output."""
        if self.verbose:
            print(f"> Raw output: {output}")
        lines = output.split("\n")
        name, artist = lines[0].split(",")
        songs = []
        for i in range(1, len(lines)):
            title, length_seconds = lines[i].split(",")
            songs.append(Song(title=title, length_seconds=length_seconds))

        return Album(name=name, artist=artist, songs=songs)

from llama_index.core.output_parsers import ChainableOutputParser class CustomAlbumOutputParser(ChainableOutputParser): """自定义 Album 输出解析器。假设第一行是专辑名称和艺术家。假设后续每一行都是歌曲。""" def __init__(self, verbose: bool = False): self.verbose = verbose def parse(self, output: str) -> Album: """解析输出。""" if self.verbose: print(f"> Raw output: {output}") lines = output.split("\n") name, artist = lines[0].split(",") songs = [] for i in range(1, len(lines)): title, length_seconds = lines[i].split(",") songs.append(Song(title=title, length_seconds=length_seconds)) return Album(name=name, artist=artist, songs=songs)

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prompt_template_str = """\
Generate an example album, with an artist and a list of songs. \
Using the movie {movie_name} as inspiration.\

Return answer in following format.
The first line is:
<album_name>, <album_artist>
Every subsequent line is a song with format:
<song_title>, <song_length_seconds>

"""
program = LLMTextCompletionProgram.from_defaults(
    output_parser=CustomAlbumOutputParser(verbose=True),
    output_cls=Album,
    prompt_template_str=prompt_template_str,
    verbose=True,
)

prompt_template_str = """\ 生成一个示例专辑，包含艺术家和歌曲列表。\ 以电影 {movie_name} 为灵感。\ 以以下格式返回答案。第一行是, 随后的每一行都是一首歌曲，格式为, """ program = LLMTextCompletionProgram.from_defaults( output_parser=CustomAlbumOutputParser(verbose=True), output_cls=Album, prompt_template_str=prompt_template_str, verbose=True, )

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output = program(movie_name="The Dark Knight")

output = program(movie_name="The Dark Knight")

> Raw output: Gotham's Reckoning, The Dark Knight
A Dark Knight Rises, 240
The Joker's Symphony, 180
Harvey Dent's Lament, 210
Gotham's Guardian, 195
The Batmobile Chase, 225
The Dark Knight's Theme, 150
The Joker's Mind Games, 180
Rachel's Tragedy, 210
Gotham's Last Stand, 240
The Dark Knight's Triumph, 180

In [ ]

output

output

Out[ ]

Album(name="Gotham's Reckoning", artist=' The Dark Knight', songs=[Song(title='A Dark Knight Rises', length_seconds=240), Song(title="The Joker's Symphony", length_seconds=180), Song(title="Harvey Dent's Lament", length_seconds=210), Song(title="Gotham's Guardian", length_seconds=195), Song(title='The Batmobile Chase', length_seconds=225), Song(title="The Dark Knight's Theme", length_seconds=150), Song(title="The Joker's Mind Games", length_seconds=180), Song(title="Rachel's Tragedy", length_seconds=210), Song(title="Gotham's Last Stand", length_seconds=240), Song(title="The Dark Knight's Triumph", length_seconds=180)])