Source code for langchain_community.output_parsers.ernie_functions

import copy
import json
from typing import Any, Dict, List, Optional, Type, Union

import jsonpatch
from langchain_core.exceptions import OutputParserException
from langchain_core.output_parsers import (
    BaseCumulativeTransformOutputParser,
    BaseGenerationOutputParser,
)
from langchain_core.output_parsers.json import parse_partial_json
from langchain_core.outputs.chat_generation import (
    ChatGeneration,
    Generation,
)
from pydantic import BaseModel, model_validator


[docs] class OutputFunctionsParser(BaseGenerationOutputParser[Any]): """Parse an output that is one of sets of values.""" args_only: bool = True """Whether to only return the arguments to the function call."""
[docs] def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any: generation = result[0] if not isinstance(generation, ChatGeneration): raise OutputParserException( "This output parser can only be used with a chat generation." ) message = generation.message try: func_call = copy.deepcopy(message.additional_kwargs["function_call"]) except KeyError as exc: raise OutputParserException(f"Could not parse function call: {exc}") if self.args_only: return func_call["arguments"] return func_call
[docs] class JsonOutputFunctionsParser(BaseCumulativeTransformOutputParser[Any]): """Parse an output as the Json object.""" strict: bool = False """Whether to allow non-JSON-compliant strings. See: https://docs.python.org/3/library/json.html#encoders-and-decoders Useful when the parsed output may include unicode characters or new lines. """ args_only: bool = True """Whether to only return the arguments to the function call.""" @property def _type(self) -> str: return "json_functions" def _diff(self, prev: Optional[Any], next: Any) -> Any: return jsonpatch.make_patch(prev, next).patch
[docs] def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any: if len(result) != 1: raise OutputParserException( f"Expected exactly one result, but got {len(result)}" ) generation = result[0] if not isinstance(generation, ChatGeneration): raise OutputParserException( "This output parser can only be used with a chat generation." ) message = generation.message if "function_call" not in message.additional_kwargs: return None try: function_call = message.additional_kwargs["function_call"] except KeyError as exc: if partial: return None else: raise OutputParserException(f"Could not parse function call: {exc}") try: if partial: if self.args_only: return parse_partial_json( function_call["arguments"], strict=self.strict ) else: return { **function_call, "arguments": parse_partial_json( function_call["arguments"], strict=self.strict ), } else: if self.args_only: try: return json.loads( function_call["arguments"], strict=self.strict ) except (json.JSONDecodeError, TypeError) as exc: raise OutputParserException( f"Could not parse function call data: {exc}" ) else: try: return { **function_call, "arguments": json.loads( function_call["arguments"], strict=self.strict ), } except (json.JSONDecodeError, TypeError) as exc: raise OutputParserException( f"Could not parse function call data: {exc}" ) except KeyError: return None
# This method would be called by the default implementation of `parse_result` # but we're overriding that method so it's not needed.
[docs] def parse(self, text: str) -> Any: raise NotImplementedError()
[docs] class JsonKeyOutputFunctionsParser(JsonOutputFunctionsParser): """Parse an output as the element of the Json object.""" key_name: str """The name of the key to return."""
[docs] def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any: res = super().parse_result(result, partial=partial) if partial and res is None: return None return res.get(self.key_name) if partial else res[self.key_name]
[docs] class PydanticOutputFunctionsParser(OutputFunctionsParser): """Parse an output as a pydantic object.""" pydantic_schema: Union[Type[BaseModel], Dict[str, Type[BaseModel]]] """The pydantic schema to parse the output with.""" @model_validator(mode="before") @classmethod def validate_schema(cls, values: Dict) -> Any: schema = values["pydantic_schema"] if "args_only" not in values: values["args_only"] = isinstance(schema, type) and issubclass( schema, BaseModel ) elif values["args_only"] and isinstance(schema, Dict): raise ValueError( "If multiple pydantic schemas are provided then args_only should be" " False." ) return values
[docs] def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any: _result = super().parse_result(result) if self.args_only: pydantic_args = self.pydantic_schema.parse_raw(_result) # type: ignore else: fn_name = _result["name"] _args = _result["arguments"] pydantic_args = self.pydantic_schema[fn_name].parse_raw(_args) # type: ignore return pydantic_args
[docs] class PydanticAttrOutputFunctionsParser(PydanticOutputFunctionsParser): """Parse an output as an attribute of a pydantic object.""" attr_name: str """The name of the attribute to return."""
[docs] def parse_result(self, result: List[Generation], *, partial: bool = False) -> Any: result = super().parse_result(result) return getattr(result, self.attr_name)