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136 lines
4.4 KiB
136 lines
4.4 KiB
""" |
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Class for loading document type data |
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""" |
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import glob |
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from typing import List |
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from colossalqa.mylogging import get_logger |
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from langchain.document_loaders import ( |
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JSONLoader, |
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PyPDFLoader, |
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TextLoader, |
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UnstructuredHTMLLoader, |
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UnstructuredMarkdownLoader, |
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) |
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from langchain.document_loaders.csv_loader import CSVLoader |
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logger = get_logger() |
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SUPPORTED_DATA_FORMAT = [".csv", ".json", ".html", ".md", ".pdf", ".txt", ".jsonl"] |
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class DocumentLoader: |
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""" |
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Load documents from different files into list of langchain Documents |
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""" |
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def __init__(self, files: List, **kwargs) -> None: |
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""" |
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Args: |
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files: list of files (list[file path, name]) |
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**kwargs: keyword type arguments, useful for certain document types |
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""" |
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self.data = {} |
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self.kwargs = kwargs |
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for item in files: |
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path = item[0] if isinstance(item, list) else item |
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logger.info(f"Loading data from {path}") |
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self.load_data(path) |
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logger.info("Data loaded") |
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self.all_data = [] |
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for key in self.data: |
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if isinstance(self.data[key], list): |
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for item in self.data[key]: |
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if isinstance(item, list): |
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self.all_data.extend(item) |
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else: |
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self.all_data.append(item) |
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def load_data(self, path: str) -> None: |
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""" |
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Load data. Please refer to https://python.langchain.com/docs/modules/data_connection/document_loaders/ |
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for specific format requirements. |
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Args: |
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path: path to a file |
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To load files with glob path, here are some examples. |
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Load all file from directory: folder1/folder2/* |
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Load all pdf file from directory: folder1/folder2/*.pdf |
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""" |
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files = [] |
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# Handle glob expression |
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try: |
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files = glob.glob(path) |
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except Exception as e: |
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logger.error(e) |
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if len(files) == 0: |
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raise ValueError("Unsupported file/directory format. For directories, please use glob expression") |
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elif len(files) == 1: |
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path = files[0] |
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else: |
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for file in files: |
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self.load_data(file) |
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return |
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# Load data if the path is a file |
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logger.info(f"load {path}", verbose=True) |
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if path.endswith(".csv"): |
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# Load csv |
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loader = CSVLoader(file_path=path, encoding="utf8") |
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data = loader.load() |
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self.data[path] = data |
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elif path.endswith(".txt"): |
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# Load txt |
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loader = TextLoader(path, encoding="utf8") |
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data = loader.load() |
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self.data[path] = data |
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elif path.endswith("html"): |
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# Load html |
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loader = UnstructuredHTMLLoader(path, encoding="utf8") |
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data = loader.load() |
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self.data[path] = data |
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elif path.endswith("json"): |
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# Load json |
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loader = JSONLoader( |
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file_path=path, |
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jq_schema=self.kwargs.get("jq_schema", ".data[]"), |
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content_key=self.kwargs.get("content_key", "content"), |
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metadata_func=self.kwargs.get("metadata_func", None), |
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) |
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data = loader.load() |
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self.data[path] = data |
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elif path.endswith("jsonl"): |
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# Load jsonl |
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loader = JSONLoader( |
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file_path=path, jq_schema=self.kwargs.get("jq_schema", ".data[].content"), json_lines=True |
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) |
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data = loader.load() |
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self.data[path] = data |
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elif path.endswith(".md"): |
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# Load markdown |
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loader = UnstructuredMarkdownLoader(path) |
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data = loader.load() |
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self.data[path] = data |
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elif path.endswith(".pdf"): |
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# Load pdf |
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loader = PyPDFLoader(path) |
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data = loader.load_and_split() |
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self.data[path] = data |
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else: |
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if "." in path.split("/")[-1]: |
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raise ValueError(f"Unsupported file format {path}. Supported formats: {SUPPORTED_DATA_FORMAT}") |
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else: |
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# May ba a directory, we strictly follow the glob path and will not load files in subdirectories |
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pass |
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def clear(self): |
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""" |
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Clear loaded data. |
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""" |
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self.data = {} |
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self.kwargs = {} |
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self.all_data = []
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