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langchain/libs/core/langchain_core/prompt_values.py

97 lines
2.6 KiB
Python

from __future__ import annotations
from abc import ABC, abstractmethod
from typing import List, Literal, Sequence
from langchain_core.load.serializable import Serializable
from langchain_core.messages import (
AnyMessage,
BaseMessage,
HumanMessage,
get_buffer_string,
)
class PromptValue(Serializable, ABC):
"""Base abstract class for inputs to any language model.
PromptValues can be converted to both LLM (pure text-generation) inputs and
ChatModel inputs.
"""
@classmethod
def is_lc_serializable(cls) -> bool:
"""Return whether this class is serializable."""
return True
@classmethod
def get_lc_namespace(cls) -> List[str]:
"""Get the namespace of the langchain object."""
return ["langchain", "schema", "prompt"]
@abstractmethod
def to_string(self) -> str:
"""Return prompt value as string."""
@abstractmethod
def to_messages(self) -> List[BaseMessage]:
"""Return prompt as a list of Messages."""
class StringPromptValue(PromptValue):
"""String prompt value."""
text: str
"""Prompt text."""
type: Literal["StringPromptValue"] = "StringPromptValue"
@classmethod
def get_lc_namespace(cls) -> List[str]:
"""Get the namespace of the langchain object."""
return ["langchain", "prompts", "base"]
def to_string(self) -> str:
"""Return prompt as string."""
return self.text
def to_messages(self) -> List[BaseMessage]:
"""Return prompt as messages."""
return [HumanMessage(content=self.text)]
class ChatPromptValue(PromptValue):
"""Chat prompt value.
A type of a prompt value that is built from messages.
"""
messages: Sequence[BaseMessage]
"""List of messages."""
def to_string(self) -> str:
"""Return prompt as string."""
return get_buffer_string(self.messages)
def to_messages(self) -> List[BaseMessage]:
"""Return prompt as a list of messages."""
return list(self.messages)
@classmethod
def get_lc_namespace(cls) -> List[str]:
"""Get the namespace of the langchain object."""
return ["langchain", "prompts", "chat"]
class ChatPromptValueConcrete(ChatPromptValue):
"""Chat prompt value which explicitly lists out the message types it accepts.
For use in external schemas."""
messages: Sequence[AnyMessage]
type: Literal["ChatPromptValueConcrete"] = "ChatPromptValueConcrete"
@classmethod
def get_lc_namespace(cls) -> List[str]:
"""Get the namespace of the langchain object."""
return ["langchain", "prompts", "chat"]