如何使用修正输出解析器

这个输出解析器包装了另一个输出解析器，当第一个解析器失败时，它会调用另一个LLM来修复任何错误。

但我们除了抛出错误之外还可以做其他事情。具体来说，我们可以将格式错误的输出与格式化的指令一起传递给模型，并要求它进行修复。

在这个例子中，我们将使用上述的Pydantic输出解析器。如果我们向它传递一个不符合模式的结果，会发生什么呢：

from typing import List
from langchain_core.output_parsers import PydanticOutputParser
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_openai import ChatOpenAI

class Actor(BaseModel):
    name: str = Field(description="演员的姓名")
    film_names: List[str] = Field(description="他们主演的电影名称列表")
actor_query = "为一个随机演员生成电影作品列表。"
parser = PydanticOutputParser(pydantic_object=Actor)

misformatted = "{'name': 'Tom Hanks', 'film_names': ['Forrest Gump']}"

parser.parse(misformatted)

---------------------------------------------------------------------------

JSONDecodeError                           Traceback (most recent call last)

File ~/workplace/langchain/libs/langchain/langchain/output_parsers/pydantic.py:29, in PydanticOutputParser.parse(self, text)
     28     json_str = match.group()
---> 29 json_object = json.loads(json_str, strict=False)
     30 return self.pydantic_object.parse_obj(json_object)

File ~/.pyenv/versions/3.10.1/lib/python3.10/json/__init__.py:359, in loads(s, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)
    358     kw['parse_constant'] = parse_constant
--> 359 return cls(**kw).decode(s)

File ~/.pyenv/versions/3.10.1/lib/python3.10/json/decoder.py:337, in JSONDecoder.decode(self, s, _w)
    333 """Return the Python representation of ``s`` (a ``str`` instance
    334 containing a JSON document).
    335 
    336 """
--> 337 obj, end = self.raw_decode(s, idx=_w(s, 0).end())
    338 end = _w(s, end).end()

File ~/.pyenv/versions/3.10.1/lib/python3.10/json/decoder.py:353, in JSONDecoder.raw_decode(self, s, idx)
    352 try:
--> 353     obj, end = self.scan_once(s, idx)
    354 except StopIteration as err:

JSONDecodeError: Expecting property name enclosed in double quotes: line 1 column 2 (char 1)

在处理上述异常时，发生了另一个异常：

OutputParserException                     Traceback (most recent call last)

Cell In[4], line 1
----> 1 parser.parse(misformatted)

File ~/workplace/langchain/libs/langchain/langchain/output_parsers/pydantic.py:35, in PydanticOutputParser.parse(self, text)
     33 name = self.pydantic_object.__name__
     34 msg = f"Failed to parse {name} from completion {text}. Got: {e}"
---> 35 raise OutputParserException(msg, llm_output=text)

OutputParserException: Failed to parse Actor from completion {'name': 'Tom Hanks', 'film_names': ['Forrest Gump']}. Got: Expecting property name enclosed in double quotes: line 1 column 2 (char 1)

现在我们可以构建并使用一个OutputFixingParser。这个输出解析器接受另一个输出解析器作为参数，同时还需要一个LLM，用于尝试纠正任何格式错误。

from langchain.output_parsers import OutputFixingParser
new_parser = OutputFixingParser.from_llm(parser=parser, llm=ChatOpenAI())

new_parser.parse(misformatted)

Actor(name='Tom Hanks', film_names=['Forrest Gump'])

查看OutputFixingParser的API文档。