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rfc: AIMessage.parsed and with_structured_output(..., tools=[])

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Bagatur 2024-10-29 19:35:51 -07:00
parent 5111063af2
commit d85ece9fe3
3 changed files with 94 additions and 23 deletions
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15
libs/core/langchain_core/messages/ai.py
View File

@ -2,7 +2,7 @@ import json
import operator
from typing import Any, Literal, Optional, Union, cast
from pydantic import model_validator
from pydantic import BaseModel, model_validator
from typing_extensions import NotRequired, Self, TypedDict
from langchain_core.messages.base import (
@ -166,6 +166,7 @@ class AIMessage(BaseMessage):
type: Literal["ai"] = "ai"
"""The type of the message (used for deserialization). Defaults to "ai"."""
parsed: Optional[Union[dict, BaseModel]] = None
def __init__(
self, content: Union[str, list[Union[str, dict]]], **kwargs: Any
@ -440,6 +441,17 @@ def add_ai_message_chunks(
else:
usage_metadata = None
has_parsed = [m for m in ([left, *others]) if m.parsed]
if len(has_parsed) >= 2:
msg = (
"Cannot concatenate two AIMessageChunks with non-null 'parsed' attributes."
)
raise ValueError(msg)
elif len(has_parsed) == 1:
parsed = has_parsed[0].parsed
else:
parsed = None
return left.__class__(
example=left.example,
content=content,
@ -448,6 +460,7 @@ def add_ai_message_chunks(
response_metadata=response_metadata,
usage_metadata=usage_metadata,
id=left.id,
parsed=parsed,
)

44
libs/core/langchain_core/output_parsers/base.py
View File

@ -61,10 +61,12 @@ class BaseLLMOutputParser(Generic[T], ABC):
class BaseGenerationOutputParser(
BaseLLMOutputParser, RunnableSerializable[LanguageModelOutput, T]
BaseLLMOutputParser, RunnableSerializable[LanguageModelOutput, Union[AnyMessage, T]]
):
"""Base class to parse the output of an LLM call."""
return_message: bool = False
@property
@override
def InputType(self) -> Any:
@ -73,11 +75,14 @@ class BaseGenerationOutputParser(
@property
@override
def OutputType(self) -> type[T]:
def OutputType(self) -> Union[type[AnyMessage], type[T]]:
"""Return the output type for the parser."""
# even though mypy complains this isn't valid,
# it is good enough for pydantic to build the schema from
return T # type: ignore[misc]
if self.return_message:
return AnyMessage
else:
# even though mypy complains this isn't valid,
# it is good enough for pydantic to build the schema from
return T # type: ignore[misc]
def invoke(
self,
@ -86,7 +91,7 @@ class BaseGenerationOutputParser(
**kwargs: Any,
) -> T:
if isinstance(input, BaseMessage):
return self._call_with_config(
parsed = self._call_with_config(
lambda inner_input: self.parse_result(
[ChatGeneration(message=inner_input)]
),
@ -94,6 +99,8 @@ class BaseGenerationOutputParser(
config,
run_type="parser",
)
if self.return_message:
return input.model_copy(update={"parsed": parsed})
else:
return self._call_with_config(
lambda inner_input: self.parse_result([Generation(text=inner_input)]),
@ -109,7 +116,7 @@ class BaseGenerationOutputParser(
**kwargs: Optional[Any],
) -> T:
if isinstance(input, BaseMessage):
return await self._acall_with_config(
parsed = await self._acall_with_config(
lambda inner_input: self.aparse_result(
[ChatGeneration(message=inner_input)]
),
@ -117,6 +124,8 @@ class BaseGenerationOutputParser(
config,
run_type="parser",
)
if self.return_message:
return input.model_copy(update={"parsed": parsed})
else:
return await self._acall_with_config(
lambda inner_input: self.aparse_result([Generation(text=inner_input)]),
@ -127,7 +136,7 @@ class BaseGenerationOutputParser(
class BaseOutputParser(
BaseLLMOutputParser, RunnableSerializable[LanguageModelOutput, T]
BaseLLMOutputParser, RunnableSerializable[LanguageModelOutput, Union[AnyMessage, T]]
):
"""Base class to parse the output of an LLM call.
@ -155,6 +164,8 @@ class BaseOutputParser(
return "boolean_output_parser"
""" # noqa: E501
return_message: bool = False
@property
@override
def InputType(self) -> Any:
@ -163,7 +174,7 @@ class BaseOutputParser(
@property
@override
def OutputType(self) -> type[T]:
def OutputType(self) -> Union[type[AnyMessage], type[T]]:
"""Return the output type for the parser.
This property is inferred from the first type argument of the class.
@ -171,6 +182,9 @@ class BaseOutputParser(
Raises:
TypeError: If the class doesn't have an inferable OutputType.
"""
if self.return_message:
return AnyMessage
for base in self.__class__.mro():
if hasattr(base, "__pydantic_generic_metadata__"):
metadata = base.__pydantic_generic_metadata__
@ -190,7 +204,7 @@ class BaseOutputParser(
**kwargs: Any,
) -> T:
if isinstance(input, BaseMessage):
return self._call_with_config(
parsed = self._call_with_config(
lambda inner_input: self.parse_result(
[ChatGeneration(message=inner_input)]
),
@ -198,6 +212,10 @@ class BaseOutputParser(
config,
run_type="parser",
)
if self.return_message:
return input.model_copy(update={"parsed": parsed})
else:
return parsed
else:
return self._call_with_config(
lambda inner_input: self.parse_result([Generation(text=inner_input)]),
@ -213,7 +231,7 @@ class BaseOutputParser(
**kwargs: Optional[Any],
) -> T:
if isinstance(input, BaseMessage):
return await self._acall_with_config(
parsed = await self._acall_with_config(
lambda inner_input: self.aparse_result(
[ChatGeneration(message=inner_input)]
),
@ -221,6 +239,10 @@ class BaseOutputParser(
config,
run_type="parser",
)
if self.return_message:
return input.model_copy(update={"parsed": parsed})
else:
return parsed
else:
return await self._acall_with_config(
lambda inner_input: self.aparse_result([Generation(text=inner_input)]),

58
libs/partners/openai/langchain_openai/chat_models/base.py
View File

@ -767,6 +767,7 @@ class BaseChatOpenAI(BaseChatModel):
message = response.choices[0].message # type: ignore[attr-defined]
if hasattr(message, "parsed"):
generations[0].message.additional_kwargs["parsed"] = message.parsed
cast(AIMessage, generations[0].message).parsed = message.parsed
if hasattr(message, "refusal"):
generations[0].message.additional_kwargs["refusal"] = message.refusal
@ -1144,10 +1145,18 @@ class BaseChatOpenAI(BaseChatModel):
method: Literal[
"function_calling", "json_mode", "json_schema"
] = "function_calling",
include_raw: bool = False,
include_raw: Union[
bool, Literal["raw_only", "parsed_only", "raw_and_parsed"]
] = False,
strict: Optional[bool] = None,
tools: Optional[
Sequence[Union[Dict[str, Any], Type, Callable, BaseTool]]
] = None,
tool_choice: Optional[
Union[dict, str, Literal["auto", "none", "required", "any"], bool]
] = None,
**kwargs: Any,
) -> Runnable[LanguageModelInput, _DictOrPydantic]:
) -> Runnable[LanguageModelInput, Union[_DictOrPydantic, BaseMessage]]:
"""Model wrapper that returns outputs formatted to match the given schema.
Args:
@ -1432,12 +1441,19 @@ class BaseChatOpenAI(BaseChatModel):
"schema must be specified when method is not 'json_mode'. "
"Received None."
)
tool_name = convert_to_openai_tool(schema)["function"]["name"]
bind_kwargs = self._filter_disabled_params(
tool_choice=tool_name, parallel_tool_calls=False, strict=strict
)
if not tools:
tool_name = convert_to_openai_tool(schema)["function"]["name"]
bind_kwargs = self._filter_disabled_params(
tool_choice=tool_name, parallel_tool_calls=False, strict=strict
)
llm = self.bind_tools([schema], **bind_kwargs)
else:
bind_kwargs = self._filter_disabled_params(
strict=strict, tool_choice=tool_choice
)
llm = self.bind_tools([schema, *tools], **bind_kwargs)
llm = self.bind_tools([schema], **bind_kwargs)
if is_pydantic_schema:
output_parser: Runnable = PydanticToolsParser(
tools=[schema], # type: ignore[list-item]
@ -1448,7 +1464,15 @@ class BaseChatOpenAI(BaseChatModel):
key_name=tool_name, first_tool_only=True
)
elif method == "json_mode":
llm = self.bind(response_format={"type": "json_object"})
if not tools:
llm = self.bind(response_format={"type": "json_object"})
else:
bind_kwargs = self._filter_disabled_params(
strict=strict,
tool_choice=tool_choice,
response_format={"type": "json_object"},
)
llm = self.bind_tools(tools, **bind_kwargs)
output_parser = (
PydanticOutputParser(pydantic_object=schema) # type: ignore[arg-type]
if is_pydantic_schema
@ -1461,7 +1485,15 @@ class BaseChatOpenAI(BaseChatModel):
"Received None."
)
response_format = _convert_to_openai_response_format(schema, strict=strict)
llm = self.bind(response_format=response_format)
if not tools:
llm = self.bind(response_format=response_format)
else:
bind_kwargs = self._filter_disabled_params(
strict=strict,
tool_choice=tool_choice,
response_format=response_format,
)
llm = self.bind_tools(tools, **bind_kwargs)
if is_pydantic_schema:
output_parser = _oai_structured_outputs_parser.with_types(
output_type=cast(type, schema)
@ -1474,7 +1506,7 @@ class BaseChatOpenAI(BaseChatModel):
f"'json_mode'. Received: '{method}'"
)
if include_raw:
if include_raw is True or include_raw == "raw_and_parsed":
parser_assign = RunnablePassthrough.assign(
parsed=itemgetter("raw") | output_parser, parsing_error=lambda _: None
)
@ -1483,6 +1515,8 @@ class BaseChatOpenAI(BaseChatModel):
[parser_none], exception_key="parsing_error"
)
return RunnableMap(raw=llm) | parser_with_fallback
elif include_raw == "raw_only":
return llm
else:
return llm | output_parser
@ -2174,7 +2208,9 @@ def _convert_to_openai_response_format(
@chain
def _oai_structured_outputs_parser(ai_msg: AIMessage) -> PydanticBaseModel:
if ai_msg.additional_kwargs.get("parsed"):
if ai_msg.parsed:
return cast(PydanticBaseModel, ai_msg.parsed)
elif ai_msg.additional_kwargs.get("parsed"):
return ai_msg.additional_kwargs["parsed"]
elif ai_msg.additional_kwargs.get("refusal"):
raise OpenAIRefusalError(ai_msg.additional_kwargs["refusal"])