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langchain/langchain/document_loaders/text.py

63 lines
2.2 KiB
Python

import logging
from typing import List, Optional, cast
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
logger = logging.getLogger(__name__)
class TextLoader(BaseLoader):
"""Load text files."""
def __init__(
self,
file_path: str,
encoding: Optional[str] = None,
autodetect_encoding: bool = False,
):
"""Initialize with file path."""
self.file_path = file_path
self.encoding = encoding
self.autodetect_encoding = autodetect_encoding
def load(self) -> List[Document]:
"""Load from file path."""
text = ""
with open(self.file_path, encoding=self.encoding) as f:
try:
text = f.read()
except UnicodeDecodeError as e:
if self.autodetect_encoding:
detected_encodings = self.detect_file_encodings()
for encoding in detected_encodings:
logger.debug("Trying encoding: ", encoding["encoding"])
try:
with open(
self.file_path, encoding=encoding["encoding"]
) as f:
text = f.read()
break
except UnicodeDecodeError:
continue
else:
raise RuntimeError(f"Error loading {self.file_path}") from e
except Exception as e:
raise RuntimeError(f"Error loading {self.file_path}") from e
metadata = {"source": self.file_path}
return [Document(page_content=text, metadata=metadata)]
def detect_file_encodings(self, timeout: int = 5) -> List[dict]:
"""Try to detect the file encoding."""
import chardet
with open(self.file_path, "rb") as f:
rawdata = f.read()
encodings = chardet.detect_all(rawdata)
if all(encoding["encoding"] is None for encoding in encodings):
raise RuntimeError(f"Could not detect encoding for {self.file_path}")
res = [encoding for encoding in encodings if encoding["encoding"] is not None]
return cast(List[dict], res)