vectorstore.py — langchain Source File

Source Code

"""Class for a VectorStore-backed memory object."""

from collections.abc import Sequence
from typing import Any

from langchain_core._api import deprecated
from langchain_core.documents import Document
from langchain_core.vectorstores import VectorStoreRetriever
from pydantic import Field

from langchain_classic.base_memory import BaseMemory
from langchain_classic.memory.utils import get_prompt_input_key


@deprecated(
    since="0.3.1",
    removal="1.0.0",
    message=(
        "Please see the migration guide at: "
        "https://python.langchain.com/docs/versions/migrating_memory/"
    ),
)
class VectorStoreRetrieverMemory(BaseMemory):
    """Vector Store Retriever Memory.

    Store the conversation history in a vector store and retrieves the relevant
    parts of past conversation based on the input.
    """

    retriever: VectorStoreRetriever = Field(exclude=True)
    """VectorStoreRetriever object to connect to."""

    memory_key: str = "history"
    """Key name to locate the memories in the result of load_memory_variables."""

    input_key: str | None = None
    """Key name to index the inputs to load_memory_variables."""

    return_docs: bool = False
    """Whether or not to return the result of querying the database directly."""

    exclude_input_keys: Sequence[str] = Field(default_factory=tuple)
    """Input keys to exclude in addition to memory key when constructing the document"""

    @property
    def memory_variables(self) -> list[str]:
        """The list of keys emitted from the load_memory_variables method."""
        return [self.memory_key]

    def _get_prompt_input_key(self, inputs: dict[str, Any]) -> str:
        """Get the input key for the prompt."""
        if self.input_key is None:
            return get_prompt_input_key(inputs, self.memory_variables)
        return self.input_key

    def _documents_to_memory_variables(
        self,
        docs: list[Document],
    ) -> dict[str, list[Document] | str]:
        result: list[Document] | str
// ... (63 more lines)