mirror of
https://github.com/Mintplex-Labs/langchain-python.git
synced 2026-07-19 21:33:31 -04:00
Harrison Chase
3bfe7cf467
should be no functional changes also keep __init__ exposing a lot for backwards compat --------- Co-authored-by: Dev 2049 <dev.dev2049@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>
122 lines
4.0 KiB
Python
122 lines
4.0 KiB
Python
from __future__ import annotations
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from abc import ABC, abstractmethod
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from typing import Any, Dict, List
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from langchain.load.serializable import Serializable
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from langchain.schema.messages import AIMessage, BaseMessage, HumanMessage
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class BaseMemory(Serializable, ABC):
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"""Base abstract class for memory in Chains.
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Memory refers to state in Chains. Memory can be used to store information about
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past executions of a Chain and inject that information into the inputs of
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future executions of the Chain. For example, for conversational Chains Memory
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can be used to store conversations and automatically add them to future model
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prompts so that the model has the necessary context to respond coherently to
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the latest input.
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Example:
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.. code-block:: python
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class SimpleMemory(BaseMemory):
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memories: Dict[str, Any] = dict()
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@property
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def memory_variables(self) -> List[str]:
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return list(self.memories.keys())
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def load_memory_variables(self, inputs: Dict[str, Any]) -> Dict[str, str]:
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return self.memories
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def save_context(self, inputs: Dict[str, Any], outputs: Dict[str, str]) -> None:
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pass
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def clear(self) -> None:
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pass
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""" # noqa: E501
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class Config:
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"""Configuration for this pydantic object."""
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arbitrary_types_allowed = True
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@property
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@abstractmethod
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def memory_variables(self) -> List[str]:
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"""The string keys this memory class will add to chain inputs."""
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@abstractmethod
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def load_memory_variables(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
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"""Return key-value pairs given the text input to the chain."""
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@abstractmethod
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def save_context(self, inputs: Dict[str, Any], outputs: Dict[str, str]) -> None:
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"""Save the context of this chain run to memory."""
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@abstractmethod
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def clear(self) -> None:
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"""Clear memory contents."""
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class BaseChatMessageHistory(ABC):
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"""Abstract base class for storing chat message history.
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See `ChatMessageHistory` for default implementation.
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Example:
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.. code-block:: python
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class FileChatMessageHistory(BaseChatMessageHistory):
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storage_path: str
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session_id: str
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@property
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def messages(self):
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with open(os.path.join(storage_path, session_id), 'r:utf-8') as f:
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messages = json.loads(f.read())
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return messages_from_dict(messages)
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def add_message(self, message: BaseMessage) -> None:
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messages = self.messages.append(_message_to_dict(message))
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with open(os.path.join(storage_path, session_id), 'w') as f:
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json.dump(f, messages)
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def clear(self):
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with open(os.path.join(storage_path, session_id), 'w') as f:
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f.write("[]")
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"""
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messages: List[BaseMessage]
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"""A list of Messages stored in-memory."""
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def add_user_message(self, message: str) -> None:
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"""Convenience method for adding a human message string to the store.
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Args:
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message: The string contents of a human message.
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"""
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self.add_message(HumanMessage(content=message))
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def add_ai_message(self, message: str) -> None:
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"""Convenience method for adding an AI message string to the store.
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Args:
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message: The string contents of an AI message.
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"""
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self.add_message(AIMessage(content=message))
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# TODO: Make this an abstractmethod.
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def add_message(self, message: BaseMessage) -> None:
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"""Add a Message object to the store.
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Args:
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message: A BaseMessage object to store.
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"""
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raise NotImplementedError
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@abstractmethod
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def clear(self) -> None:
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"""Remove all messages from the store"""
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