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langchain/libs/partners/airbyte/langchain_airbyte/document_loaders.py

128 lines
4.0 KiB
Python

"""Airbyte vector stores."""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
AsyncIterator,
Dict,
Iterator,
List,
Mapping,
Optional,
TypeVar,
)
import airbyte as ab
from langchain_core.documents import Document
from langchain_core.prompts import PromptTemplate
from langchain_core.runnables import run_in_executor
from langchain_core.vectorstores import VectorStore
if TYPE_CHECKING:
from langchain_text_splitters import TextSplitter
VST = TypeVar("VST", bound=VectorStore)
class AirbyteLoader:
"""Airbyte Document Loader.
Example:
.. code-block:: python
from langchain_airbyte import AirbyteLoader
loader = AirbyteLoader(
source="github",
stream="pull_requests",
)
documents = loader.lazy_load()
"""
def __init__(
self,
source: str,
stream: str,
*,
config: Optional[Dict] = None,
include_metadata: bool = True,
template: Optional[PromptTemplate] = None,
):
self._airbyte_source = ab.get_source(source, config=config, streams=[stream])
self._stream = stream
self._template = template
self._include_metadata = include_metadata
def load(self) -> List[Document]:
"""Load source data into Document objects."""
return list(self.lazy_load())
def load_and_split(
self, text_splitter: Optional[TextSplitter] = None
) -> List[Document]:
"""Load Documents and split into chunks. Chunks are returned as Documents.
Args:
text_splitter: TextSplitter instance to use for splitting documents.
Defaults to RecursiveCharacterTextSplitter.
Returns:
List of Documents.
"""
if text_splitter is None:
try:
from langchain_text_splitters import RecursiveCharacterTextSplitter
except ImportError as e:
raise ImportError(
"Unable to import from langchain_text_splitters. Please specify "
"text_splitter or install langchain_text_splitters with "
"`pip install -U langchain-text-splitters`."
) from e
_text_splitter: TextSplitter = RecursiveCharacterTextSplitter()
else:
_text_splitter = text_splitter
docs = self.lazy_load()
return _text_splitter.split_documents(docs)
def lazy_load(self) -> Iterator[Document]:
"""A lazy loader for Documents."""
# if no prompt template defined, use default airbyte documents
if not self._template:
for document in self._airbyte_source.get_documents(self._stream):
# convert airbyte document to langchain document
metadata = (
{}
if not self._include_metadata
else {
**document.metadata,
"_last_modified": document.last_modified,
"_id": document.id,
}
)
yield Document(
page_content=document.content,
metadata=metadata,
)
else:
records: Iterator[Mapping[str, Any]] = self._airbyte_source.get_records(
self._stream
)
for record in records:
metadata = {} if not self._include_metadata else dict(record)
yield Document(
page_content=self._template.format(**record), metadata=metadata
)
async def alazy_load(self) -> AsyncIterator[Document]:
"""A lazy loader for Documents."""
iterator = await run_in_executor(None, self.lazy_load)
done = object()
while True:
doc = await run_in_executor(None, next, iterator, done) # type: ignore[call-arg, arg-type]
if doc is done:
break
yield doc # type: ignore[misc]