langchain/libs/community/langchain_community/document_loaders/astradb.py

from __future__ import annotations

import json
import logging
import threading
from queue import Queue
from typing import (
    TYPE_CHECKING,
    Any,
    AsyncIterator,
    Callable,
    Dict,
    Iterator,
    List,
    Optional,
)

from langchain_core.documents import Document
from langchain_core.runnables import run_in_executor

from langchain_community.document_loaders.base import BaseLoader
from langchain_community.utilities.astradb import AstraDBEnvironment

if TYPE_CHECKING:
    from astrapy.db import AstraDB, AsyncAstraDB

logger = logging.getLogger(__name__)


class AstraDBLoader(BaseLoader):
    """Load DataStax Astra DB documents."""

    def __init__(
        self,
        collection_name: str,
        token: Optional[str] = None,
        api_endpoint: Optional[str] = None,
        astra_db_client: Optional[AstraDB] = None,
        async_astra_db_client: Optional[AsyncAstraDB] = None,
        namespace: Optional[str] = None,
        filter_criteria: Optional[Dict[str, Any]] = None,
        projection: Optional[Dict[str, Any]] = None,
        find_options: Optional[Dict[str, Any]] = None,
        nb_prefetched: int = 1000,
        extraction_function: Callable[[Dict], str] = json.dumps,
    ) -> None:
        astra_env = AstraDBEnvironment(
            token=token,
            api_endpoint=api_endpoint,
            astra_db_client=astra_db_client,
            async_astra_db_client=async_astra_db_client,
            namespace=namespace,
        )
        self.astra_env = astra_env
        self.collection = astra_env.astra_db.collection(collection_name)
        self.collection_name = collection_name
        self.filter = filter_criteria
        self.projection = projection
        self.find_options = find_options or {}
        self.nb_prefetched = nb_prefetched
        self.extraction_function = extraction_function

    def load(self) -> List[Document]:
        """Eagerly load the content."""
        return list(self.lazy_load())

    def lazy_load(self) -> Iterator[Document]:
        queue = Queue(self.nb_prefetched)
        t = threading.Thread(target=self.fetch_results, args=(queue,))
        t.start()
        while True:
            doc = queue.get()
            if doc is None:
                break
            yield doc
        t.join()

    async def aload(self) -> List[Document]:
        """Load data into Document objects."""
        return [doc async for doc in self.alazy_load()]

    async def alazy_load(self) -> AsyncIterator[Document]:
        if not self.astra_env.async_astra_db:
            iterator = run_in_executor(
                None,
                self.collection.paginated_find,
                filter=self.filter,
                options=self.find_options,
                projection=self.projection,
                sort=None,
                prefetched=True,
            )
            done = object()
            while True:
                item = await run_in_executor(None, lambda it: next(it, done), iterator)
                if item is done:
                    break
                yield item
            return
        async_collection = await self.astra_env.async_astra_db.collection(
            self.collection_name
        )
        async for doc in async_collection.paginated_find(
            filter=self.filter,
            options=self.find_options,
            projection=self.projection,
            sort=None,
            prefetched=True,
        ):
            yield Document(
                page_content=self.extraction_function(doc),
                metadata={
                    "namespace": async_collection.astra_db.namespace,
                    "api_endpoint": async_collection.astra_db.base_url,
                    "collection": self.collection_name,
                },
            )

    def fetch_results(self, queue: Queue):
        self.fetch_page_result(queue)
        while self.find_options.get("pageState"):
            self.fetch_page_result(queue)
        queue.put(None)

    def fetch_page_result(self, queue: Queue):
        res = self.collection.find(
            filter=self.filter,
            options=self.find_options,
            projection=self.projection,
            sort=None,
        )
        self.find_options["pageState"] = res["data"].get("nextPageState")
        for doc in res["data"]["documents"]:
            queue.put(
                Document(
                    page_content=self.extraction_function(doc),
                    metadata={
                        "namespace": self.collection.astra_db.namespace,
                        "api_endpoint": self.collection.astra_db.base_url,
                        "collection": self.collection.collection_name,
                    },
                )
            )