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## 指定制定列的csv文件加载器
from langchain.document_loaders import CSVLoader
import csv
from io import TextIOWrapper
from typing import Dict, List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.helpers import detect_file_encodings
class FilteredCSVLoader(CSVLoader):
def __init__(
self,
file_path: str,
columns_to_read: List[str],
source_column: Optional[str] = None,
metadata_columns: List[str] = [],
csv_args: Optional[Dict] = None,
encoding: Optional[str] = None,
autodetect_encoding: bool = False,
):
super().__init__(
file_path=file_path,
source_column=source_column,
metadata_columns=metadata_columns,
csv_args=csv_args,
encoding=encoding,
autodetect_encoding=autodetect_encoding,
)
self.columns_to_read = columns_to_read
def load(self) -> List[Document]:
"""Load data into document objects."""
docs = []
try:
with open(self.file_path, newline="", encoding=self.encoding) as csvfile:
docs = self.__read_file(csvfile)
except UnicodeDecodeError as e:
if self.autodetect_encoding:
detected_encodings = detect_file_encodings(self.file_path)
for encoding in detected_encodings:
try:
with open(
self.file_path, newline="", encoding=encoding.encoding
) as csvfile:
docs = self.__read_file(csvfile)
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
return docs
def __read_file(self, csvfile: TextIOWrapper) -> List[Document]:
docs = []
csv_reader = csv.DictReader(csvfile, **self.csv_args) # type: ignore
for i, row in enumerate(csv_reader):
if self.columns_to_read[0] in row:
content = row[self.columns_to_read[0]]
# Extract the source if available
source = (
row.get(self.source_column, None)
if self.source_column is not None
else self.file_path
)
metadata = {"source": source, "row": i}
for col in self.metadata_columns:
if col in row:
metadata[col] = row[col]
doc = Document(page_content=content, metadata=metadata)
docs.append(doc)
else:
raise ValueError(f"Column '{self.columns_to_read[0]}' not found in CSV file.")
return docs
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