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It handles various input formats (PDF, DOCX, PPTX, images, HTML, Markdown, etc.) and provides both single-document and batch conversion capabilities. The conversion methods return a `ConversionResult` instance for each document, which wraps a `DoclingDocument` object if the conversion was successful, along with metadata about the conversion process. Attributes: allowed_formats: Allowed input formats. format_to_options: Mapping of formats to their options. initialized_pipelines: Cache of initialized pipelines keyed by (pipeline class, options hash). fileNallowed_formatsformat_optionsrac&UbUO[[5Ul0nU(aUR5HupEU[R:XarUR [ La_[R"SUR RS3[SS9 [URURURS9X4'MXSU'M URVs0sH#nUURU5=nc [!US9OU_M% snUl0Ulgs snf)aInitialize the converter based on format preferences. Args: allowed_formats: List of allowed input formats. By default, any format supported by Docling is allowed. format_options: Dictionary of format-specific options. Examples: Create a converter with default settings (all formats allowed): >>> converter = DocumentConverter() Allow only PDF and DOCX formats: >>> from docling.datamodel.base_models import InputFormat >>> converter = DocumentConverter( ... allowed_formats=[InputFormat.PDF, InputFormat.DOCX] ... ) Customize pipeline options for PDF: >>> from docling.datamodel.pipeline_options import PdfPipelineOptions >>> converter = DocumentConverter( ... format_options={ ... InputFormat.PDF: PdfFormatOption( ... pipeline_options=PdfPipelineOptions() ... ), ... } ... ) NzUsing z for InputFormat.IMAGE is deprecated. Images should use ImageDocumentBackend via ImageFormatOption. Automatically correcting the backend, please update your code to avoid this warning.) stacklevel)r^rnr_)r)listrEr itemsrrrwarningswarnrtDeprecationWarningrr^rnr_rrformat_to_optionsinitialized_pipelines)rer r normalized_format_optionsroption custom_options rf__init__DocumentConverter.__init__s*H /:O[@Q  FH! "0"6"6"8k///.BBMM !8!8 9:oo+#$ 9J%+%8%8)/)@)@(.(>(>9-5 9?f5'#96.. C / %>%B%B6%JJMS$62" # / C   "C s*DcUR$rc)rrps rf_get_initialized_pipelines,DocumentConverter._get_initialized_pipeliness)))rircDURUS9nUc[SU35eg)aInitialize the conversion pipeline for the selected format. Args: format: The input format for which to initialize the pipeline. Raises: ConversionError: If no pipeline could be initialized for the given format. RuntimeError: If `artifacts_path` is set in `docling.datamodel.settings.settings` when required by the pipeline, but points to a non-directory file. FileNotFoundError: If local model files are not found. ) doc_formatNz,No pipeline could be initialized for format ) _get_pipelinerR)rerpipelines rfinitialize_pipeline%DocumentConverter.initialize_pipelines9%%%8  !>vhG  riT)strict)configr`headersraises_on_error max_num_pages max_file_size page_rangec BURU/UUUUUS9n[U5$)aConvert one document fetched from a file path, URL, or DocumentStream. Note: If the document content is given as a string (Markdown or HTML content), use the `convert_string` method. Args: source: Source of input document given as file path, URL, DocumentStream, or HttpSource (a URL bundled with its own headers). headers: Optional headers given as a dictionary of string key-value pairs, in case of URL input source. Ignored for HttpSource inputs, which carry their own headers (these override the batch headers per key). raises_on_error: Whether to raise an error on the first conversion failure. If False, errors are captured in the ConversionResult objects. max_num_pages: Maximum number of pages accepted per document. Documents exceeding this number will not be converted. max_file_size: Maximum file size to convert. page_range: Range of pages to convert. Returns: The conversion result, which contains a `DoclingDocument` in the `document` attribute, and metadata about the conversion process. Raises: ConversionError: An error occurred during conversion. Examples: Convert a local PDF file: >>> from pathlib import Path >>> converter = DocumentConverter() >>> result = converter.convert("path/to/document.pdf") >>> print(result.document.export_to_markdown()) Convert a document from a URL: >>> result = converter.convert("https://example.com/paper.pdf") Convert from an in-memory stream: >>> from io import BytesIO >>> from docling.datamodel.base_models import DocumentStream >>> buf = BytesIO(b"Hello") >>> stream = DocumentStream(name="page.html", stream=buf) >>> result = converter.convert(stream) )r`r(r)r*r'r+) convert_allnext)rer`r'r(r)r*r+all_ress rfconvertDocumentConverter.converts:n""8+''! # G}ric #V# [UUUS9n[XUS9nURXS9n Sn U Hn Sn U(aU R[R [R 1;aSn U R(a9U RV s/sHoRPM nn SSRU53n [S U RRS U RRS U 35[U R5eU v M U (dU(a [S 5eg g s sn f7f)aConvert multiple documents from file paths, URLs, or DocumentStreams. Args: source: Source of input documents given as an iterable of file paths, URLs, DocumentStreams, or HttpSources (a URL bundled with its own headers). headers: Optional headers given as a (single) dictionary of string key-value pairs, in case of URL input source. Per-source HttpSource headers override these (merged per key) for that source only. raises_on_error: Whether to raise an error on the first conversion failure. max_num_pages: Maximum number of pages accepted per document. Documents exceeding this number will not be converted. max_file_size: Maximum file size in bytes. Documents exceeding this limit will be skipped. page_range: Range of pages to convert in each document. Yields: The conversion results, each containing a `DoclingDocument` in the `document` attribute and metadata about the conversion process. Raises: ConversionError: An error occurred during conversion. Examples: Convert a batch of local files: >>> from pathlib import Path >>> converter = DocumentConverter() >>> paths = list(Path("docs/").glob("*.pdf")) >>> for result in converter.convert_all(paths): ... print(result.document.export_to_markdown()[:100]) Convert with a file size limit of 20 MB: >>> results = converter.convert_all( ... paths, max_file_size=20 * 1024 * 1024 ... ) )r)r*r+)path_or_stream_iteratorlimitsr'r(FTz Errors: z; zConversion failed for: z with status: .zsConversion failed because the provided file has no recognizable format or it wasn't in the list of allowed formats.N)rOrH_convertstatusr?SUCCESSPARTIAL_SUCCESSerrors error_messagejoinrRinputr valuerJ)rer`r'r(r)r*r+r4 conv_input conv_res_iter had_resultconv_res error_detailserrerror_messagess rfr-DocumentConverter.convert_all?s2b ''!  .$*7  j R  %HJ8?? (( 00;$!# ??CK??%S?C&7&7?N%S&/ .0I/J$KM &-hnn.A.A-B.,,-Q}o?1@A '&*o!F .z&TsBD)D$BD)contentnamecU=(d$ [R"5RS5nU[R:XaOUR S5(dUS- n[ URS55n[X4S9nURU5$U[R:XaOUR S5(dUS- n[ URS55n[X4S9nURU5$U[R:XaOUR S5(dUS- n[ URS55n[X4S9nURU5$[SUS 35e) a.Convert a document given as a string using the specified format. Only Markdown (`InputFormat.MD`), HTML (`InputFormat.HTML`), and DocLang (`InputFormat.XML_DOCLANG`) formats are supported. The content is wrapped in a `DocumentStream` and passed to the main conversion pipeline. Args: content: The document content as a string. format: The format of the input content. name: The filename to associate with the document. If not provided, a timestamp-based name is generated. The appropriate file extension is appended if missing. Returns: The conversion result, which contains a `DoclingDocument` in the `document` attribute, and metadata about the conversion process. Raises: ValueError: If format is not supported by `convert_string`. ConversionError: An error occurred during conversion. Examples: Convert a Markdown string: >>> from docling.datamodel.base_models import InputFormat >>> converter = DocumentConverter() >>> result = converter.convert_string( ... "# Title Some text.", format=InputFormat.MD ... ) >>> print(result.document.export_to_markdown()) Convert an HTML string: >>> result = converter.convert_string( ... "

Title

Some text.

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