Source code for langchain_core.output_parsers.json
from __future__ import annotations
import json
from json import JSONDecodeError
from typing import Any, List, Optional, Type, TypeVar, Union
import jsonpatch  # type: ignore[import]
import pydantic  # pydantic: ignore
from langchain_core.exceptions import OutputParserException
from langchain_core.output_parsers.format_instructions import JSON_FORMAT_INSTRUCTIONS
from langchain_core.output_parsers.transform import BaseCumulativeTransformOutputParser
from langchain_core.outputs import Generation
from langchain_core.utils.json import (
    parse_and_check_json_markdown,
    parse_json_markdown,
    parse_partial_json,
)
from langchain_core.utils.pydantic import PYDANTIC_MAJOR_VERSION
if PYDANTIC_MAJOR_VERSION < 2:
    PydanticBaseModel = pydantic.BaseModel
else:
    from pydantic.v1 import BaseModel  # pydantic: ignore
    # Union type needs to be last assignment to PydanticBaseModel to make mypy happy.
    PydanticBaseModel = Union[BaseModel, pydantic.BaseModel]  # type: ignore
TBaseModel = TypeVar("TBaseModel", bound=PydanticBaseModel)
[docs]class JsonOutputParser(BaseCumulativeTransformOutputParser[Any]):
    """Parse the output of an LLM call to a JSON object.
    When used in streaming mode, it will yield partial JSON objects containing
    all the keys that have been returned so far.
    In streaming, if `diff` is set to `True`, yields JSONPatch operations
    describing the difference between the previous and the current object.
    """
    pydantic_object: Optional[Type[TBaseModel]] = None  # type: ignore
    """The Pydantic object to use for validation. 
    If None, no validation is performed."""
    def _diff(self, prev: Optional[Any], next: Any) -> Any:
        return jsonpatch.make_patch(prev, next).patch
    def _get_schema(self, pydantic_object: Type[TBaseModel]) -> dict[str, Any]:
        if PYDANTIC_MAJOR_VERSION == 2:
            if issubclass(pydantic_object, pydantic.BaseModel):
                return pydantic_object.model_json_schema()
            elif issubclass(pydantic_object, pydantic.v1.BaseModel):
                return pydantic_object.schema()
        return pydantic_object.schema()
[docs]    def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any:
        """Parse the result of an LLM call to a JSON object.
        Args:
            result: The result of the LLM call.
            partial: Whether to parse partial JSON objects.
                If True, the output will be a JSON object containing
                all the keys that have been returned so far.
                If False, the output will be the full JSON object.
                Default is False.
        Returns:
            The parsed JSON object.
        Raises:
            OutputParserException: If the output is not valid JSON.
        """
        text = result[0].text
        text = text.strip()
        if partial:
            try:
                return parse_json_markdown(text)
            except JSONDecodeError:
                return None
        else:
            try:
                return parse_json_markdown(text)
            except JSONDecodeError as e:
                msg = f"Invalid json output: {text}"
                raise OutputParserException(msg, llm_output=text) from e 
[docs]    def parse(self, text: str) -> Any:
        """Parse the output of an LLM call to a JSON object.
        Args:
            text: The output of the LLM call.
        Returns:
            The parsed JSON object.
        """
        return self.parse_result([Generation(text=text)]) 
    @property
    def _type(self) -> str:
        return "simple_json_output_parser" 
# For backwards compatibility
SimpleJsonOutputParser = JsonOutputParser
parse_partial_json = parse_partial_json
parse_and_check_json_markdown = parse_and_check_json_markdown