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77 lines
2.7 KiB
Python
77 lines
2.7 KiB
Python
"""Loads a CSV file into a list of documents.
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Each document represents one row of the CSV file. Every row is converted into a
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key/value pair and outputted to a new line in the document's page_content.
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The source for each document loaded from csv is set to the value of the
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`file_path` argument for all documents by default.
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You can override this by setting the `source_column` argument to the
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name of a column in the CSV file.
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The source of each document will then be set to the value of the column
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with the name specified in `source_column`.
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Output Example:
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.. code-block:: txt
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column1: value1
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column2: value2
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column3: value3
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"""
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from typing import Optional, Dict, List
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import csv
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from langchain.document_loaders.base import BaseLoader
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from langchain.schema import Document
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class NewCSVLoader(BaseLoader):
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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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):
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"""
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Args:
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file_path: The path to the CSV file.
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source_column: The name of the column in the CSV file to use as the source.
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Optional. Defaults to None.
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csv_args: A dictionary of arguments to pass to the csv.DictReader.
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Optional. Defaults to None.
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encoding: The encoding of the CSV file. Optional. Defaults to None.
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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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def load(self) -> List[Document]:
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"""Load data into document objects."""
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docs = []
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with open(self.file_path, newline="", encoding=self.encoding) as csvfile:
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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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strs = []
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for k, v in row.items():
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if k is None or v is None:
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continue
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strs.append(f"{k.strip()}: {v.strip()}")
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content = "\n".join(strs)
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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 self.file_path
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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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