community[minor]: Implement lazy_load() for ArxivLoader (#18664)

Integration tests: `tests/integration_tests/utilities/test_arxiv.py` and
`tests/integration_tests/document_loaders/test_arxiv.py`
pull/18671/head
Christophe Bornet 3 months ago committed by GitHub
parent 2d96803ddd
commit 1100f8de7a
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GPG Key ID: B5690EEEBB952194

@ -1,4 +1,4 @@
from typing import Any, List, Optional
from typing import Any, Iterator, List, Optional
from langchain_core.documents import Document
@ -23,8 +23,8 @@ class ArxivLoader(BaseLoader):
doc_content_chars_max=doc_content_chars_max, **kwargs
)
def load(self) -> List[Document]:
return self.client.load(self.query)
def lazy_load(self) -> Iterator[Document]:
yield from self.client.lazy_load(self.query)
def get_summaries_as_docs(self) -> List[Document]:
return self.client.get_summaries_as_docs(self.query)

@ -2,7 +2,7 @@
import logging
import os
import re
from typing import Any, Dict, List, Optional
from typing import Any, Dict, Iterator, List, Optional
from langchain_core.documents import Document
from langchain_core.pydantic_v1 import BaseModel, root_validator
@ -177,7 +177,22 @@ class ArxivAPIWrapper(BaseModel):
Args:
query: a plaintext search query
""" # noqa: E501
"""
return list(self.lazy_load(query))
def lazy_load(self, query: str) -> Iterator[Document]:
"""
Run Arxiv search and get the article texts plus the article meta information.
See https://lukasschwab.me/arxiv.py/index.html#Search
Returns: documents with the document.page_content in text format
Performs an arxiv search, downloads the top k results as PDFs, loads
them as Documents, and returns them.
Args:
query: a plaintext search query
"""
try:
import fitz
except ImportError:
@ -200,9 +215,8 @@ class ArxivAPIWrapper(BaseModel):
).results()
except self.arxiv_exceptions as ex:
logger.debug("Error on arxiv: %s", ex)
return []
return
docs: List[Document] = []
for result in results:
try:
doc_file_name: str = result.download_pdf()
@ -231,9 +245,7 @@ class ArxivAPIWrapper(BaseModel):
"Summary": result.summary,
**extra_metadata,
}
doc = Document(
yield Document(
page_content=text[: self.doc_content_chars_max], metadata=metadata
)
docs.append(doc)
os.remove(doc_file_name)
return docs

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