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68 lines
2.4 KiB
Python
68 lines
2.4 KiB
Python
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import logging
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from typing import Optional, Dict, List
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from langchain.document_loaders import CSVLoader as LCCSVLoader
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from langchain.document_loaders.helpers import detect_file_encodings
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from models.dataset import Document
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logger = logging.getLogger(__name__)
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class CSVLoader(LCCSVLoader):
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def __init__(
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self,
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file_path: str,
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source_column: Optional[str] = None,
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csv_args: Optional[Dict] = None,
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encoding: Optional[str] = None,
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autodetect_encoding: bool = True,
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):
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self.file_path = file_path
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self.source_column = source_column
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self.encoding = encoding
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self.csv_args = csv_args or {}
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self.autodetect_encoding = autodetect_encoding
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def load(self) -> List[Document]:
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"""Load data into document objects."""
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try:
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with open(self.file_path, newline="", encoding=self.encoding) as csvfile:
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docs = self._read_from_file(csvfile)
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except UnicodeDecodeError as e:
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if self.autodetect_encoding:
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detected_encodings = detect_file_encodings(self.file_path)
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for encoding in detected_encodings:
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logger.debug("Trying encoding: ", encoding.encoding)
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try:
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with open(self.file_path, newline="", encoding=encoding.encoding) as csvfile:
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docs = self._read_from_file(csvfile)
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break
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except UnicodeDecodeError:
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continue
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else:
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raise RuntimeError(f"Error loading {self.file_path}") from e
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return docs
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def _read_from_file(self, csvfile):
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docs = []
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csv_reader = csv.DictReader(csvfile, **self.csv_args) # type: ignore
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for i, row in enumerate(csv_reader):
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content = "\n".join(f"{k.strip()}: {v.strip()}" for k, v in row.items())
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try:
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source = (
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row[self.source_column]
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if self.source_column is not None
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else ''
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)
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except KeyError:
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raise ValueError(
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f"Source column '{self.source_column}' not found in CSV file."
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)
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metadata = {"source": source, "row": i}
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doc = Document(page_content=content, metadata=metadata)
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docs.append(doc)
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return docs
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