138 lines
6.9 KiB
Python
138 lines
6.9 KiB
Python
from importlib import import_module
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from typing import Any, Dict
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from embedchain.chunkers.base_chunker import BaseChunker
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from embedchain.config import AddConfig
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from embedchain.config.add_config import ChunkerConfig, LoaderConfig
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from embedchain.helpers.json_serializable import JSONSerializable
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from embedchain.loaders.base_loader import BaseLoader
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from embedchain.models.data_type import DataType
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class DataFormatter(JSONSerializable):
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"""
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DataFormatter is an internal utility class which abstracts the mapping for
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loaders and chunkers to the data_type entered by the user in their
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.add or .add_local method call
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"""
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def __init__(self, data_type: DataType, config: AddConfig, kwargs: Dict[str, Any]):
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"""
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Initialize a dataformatter, set data type and chunker based on datatype.
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:param data_type: The type of the data to load and chunk.
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:type data_type: DataType
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:param config: AddConfig instance with nested loader and chunker config attributes.
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:type config: AddConfig
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"""
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self.loader = self._get_loader(data_type=data_type, config=config.loader, kwargs=kwargs)
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self.chunker = self._get_chunker(data_type=data_type, config=config.chunker, kwargs=kwargs)
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def _lazy_load(self, module_path: str):
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module_path, class_name = module_path.rsplit(".", 1)
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module = import_module(module_path)
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return getattr(module, class_name)
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def _get_loader(self, data_type: DataType, config: LoaderConfig, kwargs: Dict[str, Any]) -> BaseLoader:
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"""
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Returns the appropriate data loader for the given data type.
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:param data_type: The type of the data to load.
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:type data_type: DataType
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:param config: Config to initialize the loader with.
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:type config: LoaderConfig
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:raises ValueError: If an unsupported data type is provided.
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:return: The loader for the given data type.
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:rtype: BaseLoader
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"""
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loaders = {
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DataType.YOUTUBE_VIDEO: "embedchain.loaders.youtube_video.YoutubeVideoLoader",
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DataType.PDF_FILE: "embedchain.loaders.pdf_file.PdfFileLoader",
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DataType.WEB_PAGE: "embedchain.loaders.web_page.WebPageLoader",
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DataType.QNA_PAIR: "embedchain.loaders.local_qna_pair.LocalQnaPairLoader",
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DataType.TEXT: "embedchain.loaders.local_text.LocalTextLoader",
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DataType.DOCX: "embedchain.loaders.docx_file.DocxFileLoader",
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DataType.SITEMAP: "embedchain.loaders.sitemap.SitemapLoader",
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DataType.XML: "embedchain.loaders.xml.XmlLoader",
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DataType.DOCS_SITE: "embedchain.loaders.docs_site_loader.DocsSiteLoader",
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DataType.CSV: "embedchain.loaders.csv.CsvLoader",
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DataType.MDX: "embedchain.loaders.mdx.MdxLoader",
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DataType.IMAGES: "embedchain.loaders.images.ImagesLoader",
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DataType.UNSTRUCTURED: "embedchain.loaders.unstructured_file.UnstructuredLoader",
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DataType.JSON: "embedchain.loaders.json.JSONLoader",
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DataType.OPENAPI: "embedchain.loaders.openapi.OpenAPILoader",
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DataType.GMAIL: "embedchain.loaders.gmail.GmailLoader",
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DataType.NOTION: "embedchain.loaders.notion.NotionLoader",
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DataType.SUBSTACK: "embedchain.loaders.substack.SubstackLoader",
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DataType.GITHUB: "embedchain.loaders.github.GithubLoader",
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DataType.YOUTUBE_CHANNEL: "embedchain.loaders.youtube_channel.YoutubeChannelLoader",
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}
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custom_loaders = set(
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[
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DataType.POSTGRES,
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DataType.MYSQL,
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DataType.SLACK,
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DataType.DISCOURSE,
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]
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)
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if data_type in loaders:
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loader_class: type = self._lazy_load(loaders[data_type])
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return loader_class()
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elif data_type in custom_loaders:
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loader_class: type = kwargs.get("loader", None)
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if loader_class is not None:
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return loader_class
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raise ValueError(
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f"Cant find the loader for {data_type}.\
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We recommend to pass the loader to use data_type: {data_type},\
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check `https://docs.embedchain.ai/data-sources/overview`."
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)
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def _get_chunker(self, data_type: DataType, config: ChunkerConfig, kwargs: Dict[str, Any]) -> BaseChunker:
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"""Returns the appropriate chunker for the given data type (updated for lazy loading)."""
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chunker_classes = {
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DataType.YOUTUBE_VIDEO: "embedchain.chunkers.youtube_video.YoutubeVideoChunker",
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DataType.PDF_FILE: "embedchain.chunkers.pdf_file.PdfFileChunker",
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DataType.WEB_PAGE: "embedchain.chunkers.web_page.WebPageChunker",
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DataType.QNA_PAIR: "embedchain.chunkers.qna_pair.QnaPairChunker",
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DataType.TEXT: "embedchain.chunkers.text.TextChunker",
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DataType.DOCX: "embedchain.chunkers.docx_file.DocxFileChunker",
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DataType.SITEMAP: "embedchain.chunkers.sitemap.SitemapChunker",
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DataType.XML: "embedchain.chunkers.xml.XmlChunker",
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DataType.DOCS_SITE: "embedchain.chunkers.docs_site.DocsSiteChunker",
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DataType.CSV: "embedchain.chunkers.table.TableChunker",
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DataType.MDX: "embedchain.chunkers.mdx.MdxChunker",
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DataType.IMAGES: "embedchain.chunkers.images.ImagesChunker",
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DataType.UNSTRUCTURED: "embedchain.chunkers.unstructured_file.UnstructuredFileChunker",
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DataType.JSON: "embedchain.chunkers.json.JSONChunker",
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DataType.OPENAPI: "embedchain.chunkers.openapi.OpenAPIChunker",
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DataType.GMAIL: "embedchain.chunkers.gmail.GmailChunker",
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DataType.NOTION: "embedchain.chunkers.notion.NotionChunker",
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DataType.POSTGRES: "embedchain.chunkers.postgres.PostgresChunker",
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DataType.MYSQL: "embedchain.chunkers.mysql.MySQLChunker",
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DataType.SLACK: "embedchain.chunkers.slack.SlackChunker",
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DataType.DISCOURSE: "embedchain.chunkers.discourse.DiscourseChunker",
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DataType.SUBSTACK: "embedchain.chunkers.substack.SubstackChunker",
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DataType.GITHUB: "embedchain.chunkers.common_chunker.CommonChunker",
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DataType.YOUTUBE_CHANNEL: "embedchain.chunkers.common_chunker.CommonChunker",
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}
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if data_type in chunker_classes:
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if "chunker" in kwargs:
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chunker_class = kwargs.get("chunker")
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else:
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chunker_class = self._lazy_load(chunker_classes[data_type])
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chunker = chunker_class(config)
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chunker.set_data_type(data_type)
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return chunker
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else:
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raise ValueError(
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f"Cant find the chunker for {data_type}.\
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We recommend to pass the chunker to use data_type: {data_type},\
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check `https://docs.embedchain.ai/data-sources/overview`."
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)
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