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langchain.document_loaders.obsidian.ObsidianLoader¶ class langchain.document_loaders.obsidian.ObsidianLoader(path: str, encoding: str = 'UTF-8', collect_metadata: bool = True)[source]¶ Load Obsidian files from directory. Initialize with a path. Parameters path – Path to the directory containing the Obsidian files. enco...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.obsidian.ObsidianLoader.html
1ac175f56159-0
langchain.document_loaders.excel.UnstructuredExcelLoader¶ class langchain.document_loaders.excel.UnstructuredExcelLoader(file_path: str, mode: str = 'single', **unstructured_kwargs: Any)[source]¶ Load Microsoft Excel files using Unstructured. Like other Unstructured loaders, UnstructuredExcelLoader can be used in both ...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.excel.UnstructuredExcelLoader.html
1ac175f56159-1
lazy_load() → Iterator[Document]¶ A lazy loader for Documents. load() → List[Document]¶ Load file. load_and_split(text_splitter: Optional[TextSplitter] = None) → List[Document]¶ Load Documents and split into chunks. Chunks are returned as Documents. Parameters text_splitter – TextSplitter instance to use for splitting ...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.excel.UnstructuredExcelLoader.html
5c361ee9dcee-0
langchain.document_loaders.parsers.pdf.PDFPlumberParser¶ class langchain.document_loaders.parsers.pdf.PDFPlumberParser(text_kwargs: Optional[Mapping[str, Any]] = None, dedupe: bool = False)[source]¶ Parse PDF with PDFPlumber. Initialize the parser. Parameters text_kwargs – Keyword arguments to pass to pdfplumber.Page.e...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.parsers.pdf.PDFPlumberParser.html
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langchain.document_loaders.airbyte.AirbyteStripeLoader¶ class langchain.document_loaders.airbyte.AirbyteStripeLoader(config: Mapping[str, Any], stream_name: str, record_handler: Optional[Callable[[Any, Optional[str]], Document]] = None, state: Optional[Any] = None)[source]¶ Load from Stripe using an Airbyte source conn...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.airbyte.AirbyteStripeLoader.html
a35f36b5df45-1
load() → List[Document]¶ Load data into Document objects. load_and_split(text_splitter: Optional[TextSplitter] = None) → List[Document]¶ Load Documents and split into chunks. Chunks are returned as Documents. Parameters text_splitter – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacter...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.airbyte.AirbyteStripeLoader.html
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langchain.document_loaders.web_base.WebBaseLoader¶ class langchain.document_loaders.web_base.WebBaseLoader(web_path: Union[str, Sequence[str]] = '', header_template: Optional[dict] = None, verify_ssl: bool = True, proxies: Optional[dict] = None, continue_on_failure: bool = False, autoset_encoding: bool = True, encoding...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.web_base.WebBaseLoader.html
65282ea0b070-1
scrape([parser]) Scrape data from webpage and return it in BeautifulSoup format. scrape_all(urls[, parser]) Fetch all urls, then return soups for all results. __init__(web_path: Union[str, Sequence[str]] = '', header_template: Optional[dict] = None, verify_ssl: bool = True, proxies: Optional[dict] = None, continue_on_f...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.web_base.WebBaseLoader.html
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Load Documents and split into chunks. Chunks are returned as Documents. Parameters text_splitter – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter. Returns List of Documents. scrape(parser: Optional[str] = None) → Any[source]¶ Scrape data from webpage and return it in Be...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.web_base.WebBaseLoader.html
638427d99cf6-0
langchain.document_loaders.airbyte.AirbyteZendeskSupportLoader¶ class langchain.document_loaders.airbyte.AirbyteZendeskSupportLoader(config: Mapping[str, Any], stream_name: str, record_handler: Optional[Callable[[Any, Optional[str]], Document]] = None, state: Optional[Any] = None)[source]¶ Load from Zendesk Support usi...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.airbyte.AirbyteZendeskSupportLoader.html
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load() → List[Document]¶ Load data into Document objects. load_and_split(text_splitter: Optional[TextSplitter] = None) → List[Document]¶ Load Documents and split into chunks. Chunks are returned as Documents. Parameters text_splitter – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacter...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.airbyte.AirbyteZendeskSupportLoader.html
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langchain.document_loaders.roam.RoamLoader¶ class langchain.document_loaders.roam.RoamLoader(path: str)[source]¶ Load Roam files from a directory. Initialize with a path. Methods __init__(path) Initialize with a path. lazy_load() A lazy loader for Documents. load() Load documents. load_and_split([text_splitter]) Load D...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.roam.RoamLoader.html
ea8bb2e02a96-0
langchain.document_loaders.email.OutlookMessageLoader¶ class langchain.document_loaders.email.OutlookMessageLoader(file_path: str)[source]¶ Loads Outlook Message files using extract_msg. https://github.com/TeamMsgExtractor/msg-extractor Initialize with a file path. Parameters file_path – The path to the Outlook Message...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.email.OutlookMessageLoader.html
abab2d01f6bb-0
langchain.document_loaders.reddit.RedditPostsLoader¶ class langchain.document_loaders.reddit.RedditPostsLoader(client_id: str, client_secret: str, user_agent: str, search_queries: Sequence[str], mode: str, categories: Sequence[str] = ['new'], number_posts: Optional[int] = 10)[source]¶ Load Reddit posts. Read posts on a...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.reddit.RedditPostsLoader.html
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user_agent – Reddit user agent. search_queries – The search queries. mode – The mode. categories – The categories. Default: [“new”] number_posts – The number of posts. Default: 10 lazy_load() → Iterator[Document]¶ A lazy loader for Documents. load() → List[Document][source]¶ Load reddits. load_and_split(text_splitter: ...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.reddit.RedditPostsLoader.html
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langchain.document_loaders.dataframe.DataFrameLoader¶ class langchain.document_loaders.dataframe.DataFrameLoader(data_frame: Any, page_content_column: str = 'text')[source]¶ Load Pandas DataFrame. Initialize with dataframe object. Parameters data_frame – Pandas DataFrame object. page_content_column – Name of the column...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.dataframe.DataFrameLoader.html
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langchain.document_loaders.embaas.EmbaasBlobLoader¶ class langchain.document_loaders.embaas.EmbaasBlobLoader[source]¶ Bases: BaseEmbaasLoader, BaseBlobParser Load Embaas blob. To use, you should have the environment variable EMBAAS_API_KEY set with your API key, or pass it as a named parameter to the constructor. Examp...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.embaas.EmbaasBlobLoader.html
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Additional parameters to pass to the Embaas document extraction API. classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶ Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.embaas.EmbaasBlobLoader.html
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classmethod from_orm(obj: Any) → Model¶ json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_n...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.embaas.EmbaasBlobLoader.html
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classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶ classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on fields based on this Model, globalns and localns. classmethod validate(value: Any) → Model¶ Examples usi...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.embaas.EmbaasBlobLoader.html
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langchain.document_loaders.bilibili.BiliBiliLoader¶ class langchain.document_loaders.bilibili.BiliBiliLoader(video_urls: List[str])[source]¶ Load BiliBili video transcripts. Initialize with bilibili url. Parameters video_urls – List of bilibili urls. Methods __init__(video_urls) Initialize with bilibili url. lazy_load(...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.bilibili.BiliBiliLoader.html
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langchain.document_loaders.dropbox.DropboxLoader¶ class langchain.document_loaders.dropbox.DropboxLoader[source]¶ Bases: BaseLoader, BaseModel Load files from Dropbox. In addition to common files such as text and PDF files, it also supports Dropbox Paper files. Create a new model by parsing and validating input data fr...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.dropbox.DropboxLoader.html
134b3d4f66f4-1
the new model: you should trust this data deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[boo...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.dropbox.DropboxLoader.html
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Defaults to RecursiveCharacterTextSplitter. Returns List of Documents. classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶ classmethod parse_obj(obj: Any) → Model¶ classmethod parse_raw(b: Union[str, byt...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.dropbox.DropboxLoader.html
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langchain.document_loaders.docugami.DocugamiLoader¶ class langchain.document_loaders.docugami.DocugamiLoader[source]¶ Bases: BaseLoader, BaseModel Load from Docugami. To use, you should have the lxml python package installed. Create a new model by parsing and validating input data from keyword arguments. Raises Validat...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.docugami.DocugamiLoader.html
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Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include – fields to include in new model exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creat...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.docugami.DocugamiLoader.html
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load() → List[Document][source]¶ Load documents. load_and_split(text_splitter: Optional[TextSplitter] = None) → List[Document]¶ Load Documents and split into chunks. Chunks are returned as Documents. Parameters text_splitter – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplit...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.docugami.DocugamiLoader.html
e8cd759e37c1-0
langchain.document_loaders.csv_loader.CSVLoader¶ class langchain.document_loaders.csv_loader.CSVLoader(file_path: str, source_column: Optional[str] = None, csv_args: Optional[Dict] = None, encoding: Optional[str] = None)[source]¶ Load a CSV file into a list of Documents. Each document represents one row of the CSV file...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.csv_loader.CSVLoader.html
e8cd759e37c1-1
Parameters file_path – The path to the CSV file. source_column – The name of the column in the CSV file to use as the source. Optional. Defaults to None. csv_args – A dictionary of arguments to pass to the csv.DictReader. Optional. Defaults to None. encoding – The encoding of the CSV file. Optional. Defaults to None. l...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.csv_loader.CSVLoader.html
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langchain.document_loaders.embaas.EmbaasLoader¶ class langchain.document_loaders.embaas.EmbaasLoader[source]¶ Bases: BaseEmbaasLoader, BaseLoader Load from Embaas. To use, you should have the environment variable EMBAAS_API_KEY set with your API key, or pass it as a named parameter to the constructor. Example # Default...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.embaas.EmbaasLoader.html
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param file_path: str [Required]¶ The path to the file to load. param params: langchain.document_loaders.embaas.EmbaasDocumentExtractionParameters = {}¶ Additional parameters to pass to the Embaas document extraction API. classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶ Creates a new m...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.embaas.EmbaasLoader.html
f30f54849aa7-2
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. classmethod from_orm(obj: Any) → Model¶ json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False,...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.embaas.EmbaasLoader.html
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classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶ classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶ classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.embaas.EmbaasLoader.html
c86568f13c82-0
langchain.document_loaders.cube_semantic.CubeSemanticLoader¶ class langchain.document_loaders.cube_semantic.CubeSemanticLoader(cube_api_url: str, cube_api_token: str, load_dimension_values: bool = True, dimension_values_limit: int = 10000, dimension_values_max_retries: int = 10, dimension_values_retry_delay: int = 3)[s...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.cube_semantic.CubeSemanticLoader.html
c86568f13c82-1
Makes a call to Cube’s REST API metadata endpoint. Returns page_content=column_title + column_description metadata table_name column_name column_data_type column_member_type column_title column_description column_values cube_data_obj_type Return type A list of documents with attributes load_and_split(text_splitter: Opt...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.cube_semantic.CubeSemanticLoader.html
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langchain.document_loaders.chatgpt.concatenate_rows¶ langchain.document_loaders.chatgpt.concatenate_rows(message: dict, title: str) → str[source]¶ Combine message information in a readable format ready to be used. :param message: Message to be concatenated :param title: Title of the conversation Returns Concatenated me...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.chatgpt.concatenate_rows.html
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langchain.document_loaders.college_confidential.CollegeConfidentialLoader¶ class langchain.document_loaders.college_confidential.CollegeConfidentialLoader(web_path: Union[str, Sequence[str]] = '', header_template: Optional[dict] = None, verify_ssl: bool = True, proxies: Optional[dict] = None, continue_on_failure: bool ...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.college_confidential.CollegeConfidentialLoader.html
d5032622828e-1
scrape([parser]) Scrape data from webpage and return it in BeautifulSoup format. scrape_all(urls[, parser]) Fetch all urls, then return soups for all results. __init__(web_path: Union[str, Sequence[str]] = '', header_template: Optional[dict] = None, verify_ssl: bool = True, proxies: Optional[dict] = None, continue_on_f...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.college_confidential.CollegeConfidentialLoader.html
d5032622828e-2
Load Documents and split into chunks. Chunks are returned as Documents. Parameters text_splitter – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter. Returns List of Documents. scrape(parser: Optional[str] = None) → Any¶ Scrape data from webpage and return it in BeautifulS...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.college_confidential.CollegeConfidentialLoader.html
553c12c71043-0
langchain.document_loaders.obs_directory.OBSDirectoryLoader¶ class langchain.document_loaders.obs_directory.OBSDirectoryLoader(bucket: str, endpoint: str, config: Optional[dict] = None, prefix: str = '')[source]¶ Load from Huawei OBS directory. Initialize the OBSDirectoryLoader with the specified settings. Parameters b...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.obs_directory.OBSDirectoryLoader.html
553c12c71043-1
Methods __init__(bucket, endpoint[, config, prefix]) Initialize the OBSDirectoryLoader with the specified settings. lazy_load() A lazy loader for Documents. load() Load documents. load_and_split([text_splitter]) Load Documents and split into chunks. __init__(bucket: str, endpoint: str, config: Optional[dict] = None, pr...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.obs_directory.OBSDirectoryLoader.html
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``` config = { “ak”: “your-access-key”, “sk”: “your-secret-key” directory_loader = OBSDirectoryLoader(“your-bucket-name”, “your-end-endpoint”, config, “your-prefix”) lazy_load() → Iterator[Document]¶ A lazy loader for Documents. load() → List[Document][source]¶ Load documents. load_and_split(text_splitter: Optional[Tex...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.obs_directory.OBSDirectoryLoader.html
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langchain.document_loaders.hugging_face_dataset.HuggingFaceDatasetLoader¶ class langchain.document_loaders.hugging_face_dataset.HuggingFaceDatasetLoader(path: str, page_content_column: str = 'text', name: Optional[str] = None, data_dir: Optional[str] = None, data_files: Optional[Union[str, Sequence[str], Mapping[str, U...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.hugging_face_dataset.HuggingFaceDatasetLoader.html
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load() Load documents. load_and_split([text_splitter]) Load Documents and split into chunks. __init__(path: str, page_content_column: str = 'text', name: Optional[str] = None, data_dir: Optional[str] = None, data_files: Optional[Union[str, Sequence[str], Mapping[str, Union[str, Sequence[str]]]]] = None, cache_dir: Opti...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.hugging_face_dataset.HuggingFaceDatasetLoader.html
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Load Documents and split into chunks. Chunks are returned as Documents. Parameters text_splitter – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter. Returns List of Documents. Examples using HuggingFaceDatasetLoader¶ HuggingFace dataset
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.hugging_face_dataset.HuggingFaceDatasetLoader.html
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langchain.document_loaders.toml.TomlLoader¶ class langchain.document_loaders.toml.TomlLoader(source: Union[str, Path])[source]¶ Load TOML files. It can load a single source file or several files in a single directory. Initialize the TomlLoader with a source file or directory. Methods __init__(source) Initialize the Tom...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.toml.TomlLoader.html
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langchain.document_loaders.parsers.grobid.GrobidParser¶ class langchain.document_loaders.parsers.grobid.GrobidParser(segment_sentences: bool, grobid_server: str = 'http://localhost:8070/api/processFulltextDocument')[source]¶ Load article PDF files using Grobid. Methods __init__(segment_sentences[, grobid_server]) lazy...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.parsers.grobid.GrobidParser.html
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langchain.document_loaders.epub.UnstructuredEPubLoader¶ class langchain.document_loaders.epub.UnstructuredEPubLoader(file_path: Union[str, List[str]], mode: str = 'single', **unstructured_kwargs: Any)[source]¶ Load EPub files using Unstructured. You can run the loader in one of two modes: “single” and “elements”. If yo...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.epub.UnstructuredEPubLoader.html
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Parameters text_splitter – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter. Returns List of Documents. Examples using UnstructuredEPubLoader¶ EPub
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.epub.UnstructuredEPubLoader.html
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langchain.document_loaders.email.UnstructuredEmailLoader¶ class langchain.document_loaders.email.UnstructuredEmailLoader(file_path: str, mode: str = 'single', **unstructured_kwargs: Any)[source]¶ Load email files using Unstructured. Works with both .eml and .msg files. You can process attachments in addition to the e-m...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.email.UnstructuredEmailLoader.html
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Parameters text_splitter – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter. Returns List of Documents. Examples using UnstructuredEmailLoader¶ Email
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.email.UnstructuredEmailLoader.html
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langchain.document_loaders.helpers.detect_file_encodings¶ langchain.document_loaders.helpers.detect_file_encodings(file_path: str, timeout: int = 5) → List[FileEncoding][source]¶ Try to detect the file encoding. Returns a list of FileEncoding tuples with the detected encodings ordered by confidence. Parameters file_pat...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.helpers.detect_file_encodings.html
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langchain.document_loaders.youtube.GoogleApiYoutubeLoader¶ class langchain.document_loaders.youtube.GoogleApiYoutubeLoader(google_api_client: GoogleApiClient, channel_name: Optional[str] = None, video_ids: Optional[List[str]] = None, add_video_info: bool = True, captions_language: str = 'en', continue_on_failure: bool ...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.youtube.GoogleApiYoutubeLoader.html
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Validate that either folder_id or document_ids is set, but not both. __init__(google_api_client: GoogleApiClient, channel_name: Optional[str] = None, video_ids: Optional[List[str]] = None, add_video_info: bool = True, captions_language: str = 'en', continue_on_failure: bool = False) → None¶ lazy_load() → Iterator[Docum...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.youtube.GoogleApiYoutubeLoader.html
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langchain.document_loaders.unstructured.UnstructuredAPIFileLoader¶ class langchain.document_loaders.unstructured.UnstructuredAPIFileLoader(file_path: Union[str, List[str]] = '', mode: str = 'single', url: str = 'https://api.unstructured.io/general/v0/general', api_key: str = '', **unstructured_kwargs: Any)[source]¶ Loa...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.unstructured.UnstructuredAPIFileLoader.html
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lazy_load() A lazy loader for Documents. load() Load file. load_and_split([text_splitter]) Load Documents and split into chunks. __init__(file_path: Union[str, List[str]] = '', mode: str = 'single', url: str = 'https://api.unstructured.io/general/v0/general', api_key: str = '', **unstructured_kwargs: Any)[source]¶ Init...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.unstructured.UnstructuredAPIFileLoader.html
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langchain.document_loaders.pdf.PDFMinerLoader¶ class langchain.document_loaders.pdf.PDFMinerLoader(file_path: str, *, headers: Optional[Dict] = None)[source]¶ Load PDF files using PDFMiner. Initialize with file path. Attributes source Methods __init__(file_path, *[, headers]) Initialize with file path. lazy_load() Lazi...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.pdf.PDFMinerLoader.html
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langchain.document_loaders.azure_blob_storage_file.AzureBlobStorageFileLoader¶ class langchain.document_loaders.azure_blob_storage_file.AzureBlobStorageFileLoader(conn_str: str, container: str, blob_name: str)[source]¶ Load from Azure Blob Storage files. Initialize with connection string, container and blob name. Attri...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.azure_blob_storage_file.AzureBlobStorageFileLoader.html
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langchain.document_loaders.pdf.DocumentIntelligenceLoader¶ class langchain.document_loaders.pdf.DocumentIntelligenceLoader(file_path: str, client: Any, model: str = 'prebuilt-document', headers: Optional[Dict] = None)[source]¶ Loads a PDF with Azure Document Intelligence Initialize the object for file processing with A...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.pdf.DocumentIntelligenceLoader.html
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generates a Document node including metadata (source blob and page number) for each page. file_pathstrThe path to the file that needs to be parsed. client: AnyA DocumentAnalysisClient to perform the analysis of the blob modelstrThe model name or ID to be used for form recognition in Azure. >>> obj = DocumentIntelligenc...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.pdf.DocumentIntelligenceLoader.html
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langchain.document_loaders.etherscan.EtherscanLoader¶ class langchain.document_loaders.etherscan.EtherscanLoader(account_address: str, api_key: str = 'docs-demo', filter: str = 'normal_transaction', page: int = 1, offset: int = 10, start_block: int = 0, end_block: int = 99999999, sort: str = 'desc')[source]¶ Load trans...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.etherscan.EtherscanLoader.html
d9781d563811-1
lazy_load() → Iterator[Document][source]¶ Lazy load Documents from table. load() → List[Document][source]¶ Load transactions from spcifc account by Etherscan. load_and_split(text_splitter: Optional[TextSplitter] = None) → List[Document]¶ Load Documents and split into chunks. Chunks are returned as Documents. Parameters...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.etherscan.EtherscanLoader.html
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langchain.document_loaders.datadog_logs.DatadogLogsLoader¶ class langchain.document_loaders.datadog_logs.DatadogLogsLoader(query: str, api_key: str, app_key: str, from_time: Optional[int] = None, to_time: Optional[int] = None, limit: int = 100)[source]¶ Load Datadog logs. Logs are written into the page_content and into...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.datadog_logs.DatadogLogsLoader.html
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Initialize Datadog document loader. Requirements: Must have datadog_api_client installed. Install with pip install datadog_api_client. Parameters query – The query to run in Datadog. api_key – The Datadog API key. app_key – The Datadog APP key. from_time – Optional. The start of the time range to query. Supports date m...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.datadog_logs.DatadogLogsLoader.html
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langchain.document_loaders.unstructured.UnstructuredBaseLoader¶ class langchain.document_loaders.unstructured.UnstructuredBaseLoader(mode: str = 'single', post_processors: Optional[List[Callable]] = None, **unstructured_kwargs: Any)[source]¶ Base Loader that uses Unstructured. Initialize with file path. Methods __init_...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.unstructured.UnstructuredBaseLoader.html
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langchain.document_loaders.python.PythonLoader¶ class langchain.document_loaders.python.PythonLoader(file_path: str)[source]¶ Load Python files, respecting any non-default encoding if specified. Initialize with a file path. Parameters file_path – The path to the file to load. Methods __init__(file_path) Initialize with...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.python.PythonLoader.html
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langchain.document_loaders.acreom.AcreomLoader¶ class langchain.document_loaders.acreom.AcreomLoader(path: str, encoding: str = 'UTF-8', collect_metadata: bool = True)[source]¶ Load acreom vault from a directory. Initialize the loader. Attributes FRONT_MATTER_REGEX Regex to match front matter metadata in markdown files...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.acreom.AcreomLoader.html
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langchain.document_loaders.html_bs.BSHTMLLoader¶ class langchain.document_loaders.html_bs.BSHTMLLoader(file_path: str, open_encoding: Optional[str] = None, bs_kwargs: Optional[dict] = None, get_text_separator: str = '')[source]¶ Load HTML files and parse them with beautiful soup. Initialise with path, and optionally, f...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.html_bs.BSHTMLLoader.html
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load() → List[Document][source]¶ Load HTML document into document objects. load_and_split(text_splitter: Optional[TextSplitter] = None) → List[Document]¶ Load Documents and split into chunks. Chunks are returned as Documents. Parameters text_splitter – TextSplitter instance to use for splitting documents. Defaults to R...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.html_bs.BSHTMLLoader.html
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langchain.document_loaders.unstructured.get_elements_from_api¶ langchain.document_loaders.unstructured.get_elements_from_api(file_path: Optional[Union[str, List[str]]] = None, file: Optional[Union[IO, Sequence[IO]]] = None, api_url: str = 'https://api.unstructured.io/general/v0/general', api_key: str = '', **unstructur...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.unstructured.get_elements_from_api.html
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langchain.document_loaders.blob_loaders.schema.Blob¶ class langchain.document_loaders.blob_loaders.schema.Blob[source]¶ Bases: BaseModel Blob represents raw data by either reference or value. Provides an interface to materialize the blob in different representations, and help to decouple the development of data loaders...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.blob_loaders.schema.Blob.html
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Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include – fields to include in new model exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creat...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.blob_loaders.schema.Blob.html
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Parameters path – path like object to file to be read encoding – Encoding to use if decoding the bytes into a string mime_type – if provided, will be set as the mime-type of the data guess_type – If True, the mimetype will be guessed from the file extension, if a mime-type was not provided Returns Blob instance json(*,...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.blob_loaders.schema.Blob.html
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classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on fields based on this Model, globalns and localns. classmethod validate(value: Any) → Model¶ property source: Optional[str]¶ The source location of the blob as string if known otherwise none. Examples using Blob¶ docai.md Embaas
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.blob_loaders.schema.Blob.html
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langchain.document_loaders.confluence.ContentFormat¶ class langchain.document_loaders.confluence.ContentFormat(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶ Enumerator of the content formats of Confluence page. EDITOR = 'body.editor'¶ EXPORT_VIEW = 'body.export_view'¶ ANO...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.confluence.ContentFormat.html
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langchain.document_loaders.iugu.IuguLoader¶ class langchain.document_loaders.iugu.IuguLoader(resource: str, api_token: Optional[str] = None)[source]¶ Load from IUGU. Initialize the IUGU resource. Parameters resource – The name of the resource to fetch. api_token – The IUGU API token to use. Methods __init__(resource[, ...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.iugu.IuguLoader.html
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langchain.document_loaders.parsers.txt.TextParser¶ class langchain.document_loaders.parsers.txt.TextParser[source]¶ Parser for text blobs. Methods __init__() lazy_parse(blob) Lazily parse the blob. parse(blob) Eagerly parse the blob into a document or documents. __init__()¶ lazy_parse(blob: Blob) → Iterator[Document][s...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.parsers.txt.TextParser.html
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langchain.document_loaders.chromium.AsyncChromiumLoader¶ class langchain.document_loaders.chromium.AsyncChromiumLoader(urls: List[str])[source]¶ Scrape HTML pages from URLs using a headless instance of the Chromium. Initialize the loader with a list of URL paths. Parameters urls (List[str]) – A list of URLs to scrape c...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.chromium.AsyncChromiumLoader.html
047dfe38d8ec-1
Load and return all Documents from the provided URLs. Returns A list of Document objects containing the scraped content from each URL. Return type List[Document] load_and_split(text_splitter: Optional[TextSplitter] = None) → List[Document]¶ Load Documents and split into chunks. Chunks are returned as Documents. Paramet...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.chromium.AsyncChromiumLoader.html
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langchain.document_loaders.pdf.AmazonTextractPDFLoader¶ class langchain.document_loaders.pdf.AmazonTextractPDFLoader(file_path: str, textract_features: Optional[Sequence[str]] = None, client: Optional[Any] = None, credentials_profile_name: Optional[str] = None, region_name: Optional[str] = None, endpoint_url: Optional[...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.pdf.AmazonTextractPDFLoader.html
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load_and_split([text_splitter]) Load Documents and split into chunks. __init__(file_path: str, textract_features: Optional[Sequence[str]] = None, client: Optional[Any] = None, credentials_profile_name: Optional[str] = None, region_name: Optional[str] = None, endpoint_url: Optional[str] = None, headers: Optional[Dict] =...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.pdf.AmazonTextractPDFLoader.html
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langchain.document_loaders.markdown.UnstructuredMarkdownLoader¶ class langchain.document_loaders.markdown.UnstructuredMarkdownLoader(file_path: Union[str, List[str]], mode: str = 'single', **unstructured_kwargs: Any)[source]¶ Load Markdown files using Unstructured. You can run the loader in one of two modes: “single” a...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.markdown.UnstructuredMarkdownLoader.html
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Defaults to RecursiveCharacterTextSplitter. Returns List of Documents. Examples using UnstructuredMarkdownLoader¶ StarRocks
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.markdown.UnstructuredMarkdownLoader.html
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langchain.document_loaders.blob_loaders.youtube_audio.YoutubeAudioLoader¶ class langchain.document_loaders.blob_loaders.youtube_audio.YoutubeAudioLoader(urls: List[str], save_dir: str)[source]¶ Load YouTube urls as audio file(s). Methods __init__(urls, save_dir) yield_blobs() Yield audio blobs for each url. __init__(ur...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.blob_loaders.youtube_audio.YoutubeAudioLoader.html
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langchain.document_loaders.arcgis_loader.ArcGISLoader¶ class langchain.document_loaders.arcgis_loader.ArcGISLoader(layer: Union[str, arcgis.features.FeatureLayer], gis: Optional[arcgis.gis.GIS] = None, where: str = '1=1', out_fields: Optional[Union[List[str], str]] = None, return_geometry: bool = False, return_all_reco...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.arcgis_loader.ArcGISLoader.html
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langchain.document_loaders.evernote.EverNoteLoader¶ class langchain.document_loaders.evernote.EverNoteLoader(file_path: str, load_single_document: bool = True)[source]¶ Load from EverNote. Loads an EverNote notebook export file e.g. my_notebook.enex into Documents. Instructions on producing this file can be found at ht...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.evernote.EverNoteLoader.html
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Load Documents and split into chunks. Chunks are returned as Documents. Parameters text_splitter – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter. Returns List of Documents. Examples using EverNoteLoader¶ EverNote
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.evernote.EverNoteLoader.html
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langchain.document_loaders.image_captions.ImageCaptionLoader¶ class langchain.document_loaders.image_captions.ImageCaptionLoader(path_images: Union[str, List[str]], blip_processor: str = 'Salesforce/blip-image-captioning-base', blip_model: str = 'Salesforce/blip-image-captioning-base')[source]¶ Load image captions. By ...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.image_captions.ImageCaptionLoader.html
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Load Documents and split into chunks. Chunks are returned as Documents. Parameters text_splitter – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter. Returns List of Documents. Examples using ImageCaptionLoader¶ Image captions
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.image_captions.ImageCaptionLoader.html
82fcb39fdea6-0
langchain.document_loaders.xorbits.XorbitsLoader¶ class langchain.document_loaders.xorbits.XorbitsLoader(data_frame: Any, page_content_column: str = 'text')[source]¶ Load Xorbits DataFrame. Initialize with dataframe object. Requirements:Must have xorbits installed. You can install with pip install xorbits. Parameters d...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.xorbits.XorbitsLoader.html
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langchain.document_loaders.rocksetdb.ColumnNotFoundError¶ class langchain.document_loaders.rocksetdb.ColumnNotFoundError(missing_key: str, query: str)[source]¶ Column not found error.
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.rocksetdb.ColumnNotFoundError.html
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langchain.document_loaders.pubmed.PubMedLoader¶ class langchain.document_loaders.pubmed.PubMedLoader(query: str, load_max_docs: Optional[int] = 3)[source]¶ Load from the PubMed biomedical library. query¶ The query to be passed to the PubMed API. load_max_docs¶ The maximum number of documents to load. Initialize the Pub...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.pubmed.PubMedLoader.html
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langchain.document_loaders.parsers.registry.get_parser¶ langchain.document_loaders.parsers.registry.get_parser(parser_name: str) → BaseBlobParser[source]¶ Get a parser by parser name.
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.parsers.registry.get_parser.html
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langchain.document_loaders.image.UnstructuredImageLoader¶ class langchain.document_loaders.image.UnstructuredImageLoader(file_path: Union[str, List[str]], mode: str = 'single', **unstructured_kwargs: Any)[source]¶ Load PNG and JPG files using Unstructured. You can run the loader in one of two modes: “single” and “eleme...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.image.UnstructuredImageLoader.html
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Defaults to RecursiveCharacterTextSplitter. Returns List of Documents. Examples using UnstructuredImageLoader¶ Images
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.image.UnstructuredImageLoader.html
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langchain.document_loaders.mongodb.MongodbLoader¶ class langchain.document_loaders.mongodb.MongodbLoader(connection_string: str, db_name: str, collection_name: str, *, filter_criteria: Optional[Dict] = None)[source]¶ Load MongoDB documents. Methods __init__(connection_string, db_name, ...[, ...]) aload() Load data into...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.mongodb.MongodbLoader.html
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langchain.document_loaders.parsers.pdf.PyMuPDFParser¶ class langchain.document_loaders.parsers.pdf.PyMuPDFParser(text_kwargs: Optional[Mapping[str, Any]] = None)[source]¶ Parse PDF using PyMuPDF. Initialize the parser. Parameters text_kwargs – Keyword arguments to pass to fitz.Page.get_text(). Methods __init__([text_kw...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.parsers.pdf.PyMuPDFParser.html
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langchain.document_loaders.whatsapp_chat.WhatsAppChatLoader¶ class langchain.document_loaders.whatsapp_chat.WhatsAppChatLoader(path: str)[source]¶ Load WhatsApp messages text file. Initialize with path. Methods __init__(path) Initialize with path. lazy_load() A lazy loader for Documents. load() Load documents. load_and...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.whatsapp_chat.WhatsAppChatLoader.html
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langchain.document_loaders.parsers.generic.MimeTypeBasedParser¶ class langchain.document_loaders.parsers.generic.MimeTypeBasedParser(handlers: Mapping[str, BaseBlobParser], *, fallback_parser: Optional[BaseBlobParser] = None)[source]¶ Parser that uses mime-types to parse a blob. This parser is useful for simple pipelin...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.parsers.generic.MimeTypeBasedParser.html
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and return a document. fallback_parser – A fallback_parser parser to use if the mime-type is not found in the handlers. If provided, this parser will be used to parse blobs with all mime-types not found in the handlers. If not provided, a ValueError will be raised if the mime-type is not found in the handlers. lazy_par...
https://api.python.langchain.com/en/latest/document_loaders/langchain.document_loaders.parsers.generic.MimeTypeBasedParser.html