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Kotlin (Android) API Reference

Kotlin (Android) API Reference v5.0.0-rc.30

Functions

extractBytes()

Extract content from a byte array.

This is the main entry point for in-memory extraction. It performs the following steps:

  1. Validate MIME type
  2. Handle legacy format conversion if needed
  3. Select appropriate extractor from registry
  4. Extract content
  5. Run post-processing pipeline

Returns:

An ExtractionResult containing the extracted content and metadata.

Errors:

Returns KreuzbergError.Validation if MIME type is invalid. Returns KreuzbergError.UnsupportedFormat if MIME type is not supported.

Signature:

@Throws(Error::class)
fun extractBytes(content: ByteArray, mimeType: String, config: ExtractionConfig): ExtractionResult

Example:

val result = extractBytes("data".toByteArray(), "value", ExtractionConfig())

Parameters:

Name Type Required Description
content ByteArray Yes The byte array to extract
mimeType String Yes MIME type of the content
config ExtractionConfig Yes Extraction configuration

Returns: ExtractionResult

Errors: Throws Error.


extractFile()

Extract content from a file.

This is the main entry point for file-based extraction. It performs the following steps:

  1. Check cache for existing result (if caching enabled)
  2. Detect or validate MIME type
  3. Select appropriate extractor from registry
  4. Extract content
  5. Run post-processing pipeline
  6. Store result in cache (if caching enabled)

Returns:

An ExtractionResult containing the extracted content and metadata.

Errors:

Returns KreuzbergError.Io if the file doesn't exist (NotFound) or for other file I/O errors. Returns KreuzbergError.UnsupportedFormat if MIME type is not supported.

Signature:

@Throws(Error::class)
fun extractFile(path: Path, mimeType: String? = null, config: ExtractionConfig): ExtractionResult

Example:

val result = extractFile("value", "value", ExtractionConfig())

Parameters:

Name Type Required Description
path Path Yes Path to the file to extract
mimeType String? No Optional MIME type override. If None, will be auto-detected
config ExtractionConfig Yes Extraction configuration

Returns: ExtractionResult

Errors: Throws Error.


extractFileSync()

Synchronous wrapper for extract_file.

This is a convenience function that blocks the current thread until extraction completes. For async code, use extract_file directly.

Uses the global Tokio runtime for 100x+ performance improvement over creating a new runtime per call. Always uses the global runtime to avoid nested runtime issues.

This function is only available with the tokio-runtime feature. For WASM targets, use a truly synchronous extraction approach instead.

Signature:

@Throws(Error::class)
fun extractFileSync(path: Path, mimeType: String? = null, config: ExtractionConfig): ExtractionResult

Example:

val result = extractFileSync("value", "value", ExtractionConfig())

Parameters:

Name Type Required Description
path Path Yes Path to the file
mimeType String? No The mime type
config ExtractionConfig Yes The configuration options

Returns: ExtractionResult

Errors: Throws Error.


extractBytesSync()

Synchronous wrapper for extract_bytes.

Uses the global Tokio runtime for 100x+ performance improvement over creating a new runtime per call.

With the tokio-runtime feature, this blocks the current thread using the global Tokio runtime. Without it (WASM), this calls a truly synchronous implementation.

Signature:

@Throws(Error::class)
fun extractBytesSync(content: ByteArray, mimeType: String, config: ExtractionConfig): ExtractionResult

Example:

val result = extractBytesSync("data".toByteArray(), "value", ExtractionConfig())

Parameters:

Name Type Required Description
content ByteArray Yes The content to process
mimeType String Yes The mime type
config ExtractionConfig Yes The configuration options

Returns: ExtractionResult

Errors: Throws Error.


extractBytesSync()

Synchronous wrapper for extract_bytes (WASM-compatible version).

This is a truly synchronous implementation without tokio runtime dependency. It calls extract_bytes_sync_impl() to perform the extraction.

Signature:

@Throws(Error::class)
fun extractBytesSync(content: ByteArray, mimeType: String, config: ExtractionConfig): ExtractionResult

Example:

val result = extractBytesSync("data".toByteArray(), "value", ExtractionConfig())

Parameters:

Name Type Required Description
content ByteArray Yes The content to process
mimeType String Yes The mime type
config ExtractionConfig Yes The configuration options

Returns: ExtractionResult

Errors: Throws Error.


batchExtractFilesSync()

Synchronous wrapper for batch_extract_files.

Uses the global Tokio runtime for optimal performance. Only available with tokio-runtime (WASM has no filesystem).

Signature:

@Throws(Error::class)
fun batchExtractFilesSync(items: List<BatchFileItem>, config: ExtractionConfig): List<ExtractionResult>

Example:

val result = batchExtractFilesSync([], ExtractionConfig())

Parameters:

Name Type Required Description
items List<BatchFileItem> Yes The items
config ExtractionConfig Yes The configuration options

Returns: List<ExtractionResult>

Errors: Throws Error.


batchExtractBytesSync()

Synchronous wrapper for batch_extract_bytes.

Uses the global Tokio runtime for optimal performance. With the tokio-runtime feature, this blocks the current thread using the global Tokio runtime. Without it (WASM), this calls a truly synchronous implementation that iterates through items and calls extract_bytes_sync().

Signature:

@Throws(Error::class)
fun batchExtractBytesSync(items: List<BatchBytesItem>, config: ExtractionConfig): List<ExtractionResult>

Example:

val result = batchExtractBytesSync([], ExtractionConfig())

Parameters:

Name Type Required Description
items List<BatchBytesItem> Yes The items
config ExtractionConfig Yes The configuration options

Returns: List<ExtractionResult>

Errors: Throws Error.


batchExtractBytesSync()

Synchronous wrapper for batch_extract_bytes (WASM-compatible version).

Iterates through items sequentially, applying per-file config overrides.

Signature:

@Throws(Error::class)
fun batchExtractBytesSync(items: List<BatchBytesItem>, config: ExtractionConfig): List<ExtractionResult>

Example:

val result = batchExtractBytesSync([], ExtractionConfig())

Parameters:

Name Type Required Description
items List<BatchBytesItem> Yes The items
config ExtractionConfig Yes The configuration options

Returns: List<ExtractionResult>

Errors: Throws Error.


batchExtractFiles()

Extract content from multiple files concurrently.

This function processes multiple files in parallel, automatically managing concurrency to prevent resource exhaustion. The concurrency limit can be configured via ExtractionConfig.max_concurrent_extractions or defaults to (num_cpus * 1.5).ceil().

Each file can optionally specify a FileExtractionConfig that overrides specific fields from the batch-level config. Pass null for a file to use the batch defaults. Batch-level settings like max_concurrent_extractions and use_cache are always taken from the batch-level config.

per-file configuration overrides.

  • config - Batch-level extraction configuration (provides defaults and batch settings)

Returns:

A vector of ExtractionResult in the same order as the input items.

Errors:

Individual file errors are captured in the result metadata. System errors (IO, RuntimeError equivalents) will bubble up and fail the entire batch.

Simple usage with no per-file overrides:

Per-file configuration overrides:

Signature:

@Throws(Error::class)
fun batchExtractFiles(items: List<BatchFileItem>, config: ExtractionConfig): List<ExtractionResult>

Example:

val result = batchExtractFiles([], ExtractionConfig())

Parameters:

Name Type Required Description
items List<BatchFileItem> Yes Vector of BatchFileItem structs, each containing a path and optional
config ExtractionConfig Yes Batch-level extraction configuration (provides defaults and batch settings)

Returns: List<ExtractionResult>

Errors: Throws Error.


batchExtractBytes()

Extract content from multiple byte arrays concurrently.

This function processes multiple byte arrays in parallel, automatically managing concurrency to prevent resource exhaustion. The concurrency limit can be configured via ExtractionConfig.max_concurrent_extractions or defaults to (num_cpus * 1.5).ceil().

Each item can optionally specify a FileExtractionConfig that overrides specific fields from the batch-level config. Pass null as the config to use the batch-level defaults for that item.

MIME type, and optional per-item configuration overrides.

  • config - Batch-level extraction configuration

Returns:

A vector of ExtractionResult in the same order as the input items.

Simple usage with no per-item overrides:

Per-item configuration overrides:

Signature:

@Throws(Error::class)
fun batchExtractBytes(items: List<BatchBytesItem>, config: ExtractionConfig): List<ExtractionResult>

Example:

val result = batchExtractBytes([], ExtractionConfig())

Parameters:

Name Type Required Description
items List<BatchBytesItem> Yes Vector of BatchBytesItem structs, each containing content bytes,
config ExtractionConfig Yes Batch-level extraction configuration

Returns: List<ExtractionResult>

Errors: Throws Error.


detectMimeTypeFromBytes()

Detect MIME type from raw file bytes.

Uses magic byte signatures to detect file type from content. Falls back to infer crate for comprehensive detection.

For ZIP-based files, inspects contents to distinguish Office Open XML formats (DOCX, XLSX, PPTX) from plain ZIP archives.

Returns:

The detected MIME type string.

Errors:

Returns KreuzbergError.UnsupportedFormat if MIME type cannot be determined.

Signature:

@Throws(Error::class)
fun detectMimeTypeFromBytes(content: ByteArray): String

Example:

val result = detectMimeTypeFromBytes("data".toByteArray())

Parameters:

Name Type Required Description
content ByteArray Yes Raw file bytes

Returns: String

Errors: Throws Error.


getExtensionsForMime()

Get file extensions for a given MIME type.

Returns all known file extensions that map to the specified MIME type.

Returns:

A vector of file extensions (without leading dot) for the MIME type.

Signature:

@Throws(Error::class)
fun getExtensionsForMime(mimeType: String): List<String>

Example:

val result = getExtensionsForMime("value")

Parameters:

Name Type Required Description
mimeType String Yes The MIME type to look up

Returns: List<String>

Errors: Throws Error.


listSupportedFormats()

List all supported document formats.

Returns every file extension Kreuzberg recognizes together with its corresponding MIME type, derived from the central format registry. Formats that have no registered file extension (such as source code, which is detected dynamically) are not included.

The list is sorted alphabetically by file extension.

Returns:

A vector of SupportedFormat entries sorted by extension.

Signature:

fun listSupportedFormats(): List<SupportedFormat>

Example:

val result = listSupportedFormats()

Returns: List<SupportedFormat>


detectQrCodes()

Detect QR codes in the bytes of an ExtractedImage.

format_hint is currently unused — the image crate auto-detects the container format from magic bytes — but the parameter is retained so future backends (e.g. a WebP-via-webp-decoder variant) can use it without an API break.

Returns an empty listtor on any of:

  • Empty input.
  • Image-decode failure.
  • No QR grids detected.
  • All detected grids fail to decode.

Successfully decoded QR codes carry their payload, a confidence of 1.0 (rqrr does not expose per-grid confidence; a successful decode is treated as high-confidence by convention), and the pixel-space bounding box derived from the four corner points of the grid.

Signature:

fun detectQrCodes(imageBytes: ByteArray, formatHint: String? = null): List<QrCode>

Example:

val result = detectQrCodes("data".toByteArray(), "value")

Parameters:

Name Type Required Description
imageBytes ByteArray Yes The image bytes
formatHint String? No The format hint

Returns: List<QrCode>


clearEmbeddingBackends()

Clear all embedding backends from the global registry.

Calls shutdown() on every registered backend, then empties the registry.

Errors:

  • Any error returned by a backend's shutdown() method. The first error encountered stops processing of remaining backends.

Signature:

@Throws(Error::class)
fun clearEmbeddingBackends()

Example:

clearEmbeddingBackends()

Returns: No return value.

Errors: Throws Error.


listEmbeddingBackends()

List the names of all registered embedding backends.

Used by kreuzberg-cli, the api/mcp endpoints, and generated language bindings.

Signature:

@Throws(Error::class)
fun listEmbeddingBackends(): List<String>

Example:

val result = listEmbeddingBackends()

Returns: List<String>

Errors: Throws Error.


listDocumentExtractors()

List names of all registered document extractors.

Signature:

@Throws(Error::class)
fun listDocumentExtractors(): List<String>

Example:

val result = listDocumentExtractors()

Returns: List<String>

Errors: Throws Error.


clearDocumentExtractors()

Clear all document extractors from the global registry.

Calls shutdown() on every registered extractor, then empties the registry.

Errors:

  • Any error returned by an extractor's shutdown() method. The first error encountered stops processing of remaining extractors.

Signature:

@Throws(Error::class)
fun clearDocumentExtractors()

Example:

clearDocumentExtractors()

Returns: No return value.

Errors: Throws Error.


listOcrBackends()

List all registered OCR backends.

Returns the names of all OCR backends currently registered in the global registry.

Returns:

A vector of OCR backend names.

Signature:

@Throws(Error::class)
fun listOcrBackends(): List<String>

Example:

val result = listOcrBackends()

Returns: List<String>

Errors: Throws Error.


clearOcrBackends()

Clear all OCR backends from the global registry.

Removes all OCR backends and calls their shutdown() methods.

Returns:

  • Ok(()) if all backends were cleared successfully
  • Err(...) if any shutdown method failed

Signature:

@Throws(Error::class)
fun clearOcrBackends()

Example:

clearOcrBackends()

Returns: No return value.

Errors: Throws Error.


registerBuiltin()

Register every built-in post-processor enabled by the active feature set.

This is the single entry point that callers (including register_default_post_processors) use to populate the global post-processor registry with the in-tree built-ins. Each submodule's own register function is gated by its feature flag so this aggregate stays safe to call on any target.

Signature:

@Throws(Error::class)
fun registerBuiltin()

Example:

registerBuiltin()

Returns: No return value.

Errors: Throws Error.


listPostProcessors()

List all registered post-processor names.

Returns a vector of all post-processor names currently registered in the global registry.

Returns:

  • Ok(List<String>) - Vector of post-processor names
  • Err(...) if the registry lock is poisoned

Signature:

@Throws(Error::class)
fun listPostProcessors(): List<String>

Example:

val result = listPostProcessors()

Returns: List<String>

Errors: Throws Error.


clearPostProcessors()

Remove all registered post-processors.

Signature:

@Throws(Error::class)
fun clearPostProcessors()

Example:

clearPostProcessors()

Returns: No return value.

Errors: Throws Error.


listRenderers()

List names of all registered renderers.

Errors:

Returns an error if the registry lock is poisoned.

Signature:

@Throws(Error::class)
fun listRenderers(): List<String>

Example:

val result = listRenderers()

Returns: List<String>

Errors: Throws Error.


clearRenderers()

Clear all renderers from the global registry.

Removes every renderer, including the built-in defaults (markdown, html, djot, plain). After calling this no renderers are registered; re-register as needed.

Errors:

Returns an error if the registry lock is poisoned.

Signature:

@Throws(Error::class)
fun clearRenderers()

Example:

clearRenderers()

Returns: No return value.

Errors: Throws Error.


clearRerankerBackends()

Clear all reranker backends from the global registry.

Calls shutdown() on every registered backend, then empties the registry.

Errors:

  • Any error returned by a backend's shutdown() method. The first error encountered stops processing of remaining backends.

Since v5.0.

Signature:

@Throws(Error::class)
fun clearRerankerBackends()

Example:

clearRerankerBackends()

Returns: No return value.

Errors: Throws Error.


listRerankerBackends()

List the names of all registered reranker backends.

Used by kreuzberg-cli, the api/mcp endpoints, and generated language bindings.

Since v5.0.

Signature:

@Throws(Error::class)
fun listRerankerBackends(): List<String>

Example:

val result = listRerankerBackends()

Returns: List<String>

Errors: Throws Error.


listValidators()

List names of all registered validators.

Signature:

@Throws(Error::class)
fun listValidators(): List<String>

Example:

val result = listValidators()

Returns: List<String>

Errors: Throws Error.


clearValidators()

Remove all registered validators.

Signature:

@Throws(Error::class)
fun clearValidators()

Example:

clearValidators()

Returns: No return value.

Errors: Throws Error.


classifyPages()

Run page classification against an extraction result.

Mutates result.page_classifications with one entry per non-empty page and appends every LLM call's usage to result.llm_usage.

Errors:

Returns the first error encountered when rendering the prompt or calling the LLM. Partially produced classifications are discarded so callers do not see a half-populated vector.

Signature:

@Throws(Error::class)
fun classifyPages(result: ExtractionResult, config: PageClassificationConfig)

Example:

classifyPages(ExtractionResult(), PageClassificationConfig())

Parameters:

Name Type Required Description
result ExtractionResult Yes The extraction result
config PageClassificationConfig Yes The configuration options

Returns: No return value.

Errors: Throws Error.


classifyText()

Classify a single piece of text without requiring an ExtractionResult.

Use this when the caller already has plain text (e.g. a RAG ingest pipeline receiving documents off a queue) and wants a label list back without manufacturing extractor-side metadata.

Errors:

Same as classify_pages: a validation error when config.labels is empty, or any error returned by prompt rendering or the underlying LLM call.

Signature:

@Throws(Error::class)
fun classifyText(text: String, config: PageClassificationConfig): List<ClassificationLabel>

Example:

val result = classifyText("value", PageClassificationConfig())

Parameters:

Name Type Required Description
text String Yes The text
config PageClassificationConfig Yes The configuration options

Returns: List<ClassificationLabel>

Errors: Throws Error.


classifyDocument()

Classify a single document (as multiple pages or a single text block).

Aggregates classifications across all pages in the provided text, returning a combined label set that represents the document as a whole.

using the configured LLM, and results are aggregated.

  • config - Classification configuration including labels and LLM settings.

Returns:

A vector of ClassificationLabel entries representing the document's overall classification.

Errors:

Returns an error if config.labels is empty or if LLM calls fail.

Signature:

@Throws(Error::class)
fun classifyDocument(pages: List<String>, config: PageClassificationConfig): List<ClassificationLabel>

Example:

val result = classifyDocument([], PageClassificationConfig())

Parameters:

Name Type Required Description
pages List<String> Yes Slice of page texts to classify. Each page is classified independently
config PageClassificationConfig Yes Classification configuration including labels and LLM settings.

Returns: List<ClassificationLabel>

Errors: Throws Error.


downloadModel()

Eagerly download a NER model into the kreuzberg cache.

name is a HuggingFace repo id (e.g. urchade/gliner_multi-v2.1). The CLI flag kreuzberg warm --ner delegates here.

Signature:

@Throws(Error::class)
fun downloadModel(name: String, cacheDir: Path? = null): Path

Example:

val result = downloadModel("value", "value")

Parameters:

Name Type Required Description
name String Yes The name
cacheDir Path? No The cache dir

Returns: Path

Errors: Throws Error.


downloadModel()

Signature:

@Throws(Error::class)
fun downloadModel(name: String, cacheDir: Path? = null): Path

Example:

val result = downloadModel("value", "value")

Parameters:

Name Type Required Description
name String Yes The name
cacheDir Path? No The cache dir

Returns: Path

Errors: Throws Error.


defaultModelName()

Pinned default NER model identifier.

Signature:

fun defaultModelName(): String

Example:

val result = defaultModelName()

Returns: String


defaultModelName()

Signature:

fun defaultModelName(): String

Example:

val result = defaultModelName()

Returns: String


knownModels()

All NER models kreuzberg knows about (used by --all-ner-models).

Signature:

fun knownModels(): List<String>

Example:

val result = knownModels()

Returns: List<String>


knownModels()

Signature:

fun knownModels(): List<String>

Example:

val result = knownModels()

Returns: List<String>


downloadModel()

Download a NER model into the kreuzberg cache.

Signature:

@Throws(Error::class)
fun downloadModel(name: String, cacheDir: Path? = null): Path

Example:

val result = downloadModel("value", "value")

Parameters:

Name Type Required Description
name String Yes The name
cacheDir Path? No The cache dir

Returns: Path

Errors: Throws Error.


defaultModelName()

Default NER model identifier.

Signature:

fun defaultModelName(): String

Example:

val result = defaultModelName()

Returns: String


knownModels()

All NER models kreuzberg knows about.

Signature:

fun knownModels(): List<String>

Example:

val result = knownModels()

Returns: List<String>


redact()

Run pattern redaction (and optional NER-driven redaction) over result and rewrite every textual field. Populates result.redaction_report.

Signature:

@Throws(Error::class)
fun redact(result: ExtractionResult, config: RedactionConfig)

Example:

redact(ExtractionResult(), RedactionConfig())

Parameters:

Name Type Required Description
result ExtractionResult Yes The extraction result
config RedactionConfig Yes The configuration options

Returns: No return value.

Errors: Throws Error.


summarize()

Score and return the top-N sentences from text, joined in original order.

language is an ISO 639 (or locale) code used to pick a stopword list; pass null (or an unknown code) to fall back to English. max_tokens bounds the summary length by whitespace-separated tokens; null falls back to DEFAULT_MAX_TOKENS.

Signature:

fun summarize(text: String, language: String? = null, maxTokens: Int? = null): String?

Example:

val result = summarize("value", "value", 42)

Parameters:

Name Type Required Description
text String Yes The text
language String? No The language
maxTokens Int? No The max tokens

Returns: String?


tokenCount()

Count whitespace-separated tokens (used for token-budget bookkeeping by callers).

Signature:

fun tokenCount(text: String): Int

Example:

val result = tokenCount("value")

Parameters:

Name Type Required Description
text String Yes The text

Returns: Int


translateResult()

Translate the extraction result in place.

Populates result.translation with the translated content, optionally the translated formatted_content (when preserve_markup = true), and rewrites every chunk's content field. Every LLM call's usage is appended to result.llm_usage.

Signature:

@Throws(Error::class)
fun translateResult(result: ExtractionResult, config: TranslationConfig)

Example:

translateResult(ExtractionResult(), TranslationConfig())

Parameters:

Name Type Required Description
result ExtractionResult Yes The extraction result
config TranslationConfig Yes The configuration options

Returns: No return value.

Errors: Throws Error.


findFootnoteAnchors()

Find all footnote anchor references in markdown text.

Returns a vector of footnote anchors ([^label] use-sites), including byte offsets. Footnote definitions ([^label]: ...) are NOT included in the results.

Returns:

A vector of FootnoteAnchor entries, each with the label and byte offset.

Signature:

fun findFootnoteAnchors(markdown: String): List<FootnoteAnchor>

Example:

val result = findFootnoteAnchors("value")

Parameters:

Name Type Required Description
markdown String Yes The markdown text to search

Returns: List<FootnoteAnchor>


parseFootnoteDefinitions()

Parse footnote definitions from markdown text.

Returns a vector of footnote definitions found in the markdown. Handles multi-line definitions with continuation/indented lines (CommonMark format).

Returns:

A vector of FootnoteDefinition entries, each with label, content, and byte offset.

Signature:

fun parseFootnoteDefinitions(markdown: String): List<FootnoteDefinition>

Example:

val result = parseFootnoteDefinitions("value")

Parameters:

Name Type Required Description
markdown String Yes The markdown text to search

Returns: List<FootnoteDefinition>


findInferenceMarkers()

Find inference markers in markdown text.

Returns byte offsets of every [*inference*] marker found in the text.

Returns:

A vector of byte offsets where inference markers appear.

Signature:

fun findInferenceMarkers(markdown: String): List<Long>

Example:

val result = findInferenceMarkers("value")

Parameters:

Name Type Required Description
markdown String Yes The markdown text to search

Returns: List<Long>


findUnmarkedClaims()

Find unmarked claims in markdown text.

Returns lines that assert a claim but carry neither a footnote citation anchor ([^...]) nor an inference marker ([*inference*]).

The heuristic is simple: a line that contains alphabetic words, ends with sentence punctuation, and is not a heading, blank line, or markup-only line is considered a claim. Exclude lines that appear in the citation block (after --- + <!-- citations ... -->).

Returns:

A vector of trimmed line text strings for unmarked claims.

Signature:

fun findUnmarkedClaims(markdown: String): List<String>

Example:

val result = findUnmarkedClaims("value")

Parameters:

Name Type Required Description
markdown String Yes The markdown text to search

Returns: List<String>


parseCitations()

Parse the structured citation block from markdown.

Extracts citations from the block after a --- thematic break followed by <!-- citations ... --> comment. Parses each entry as: [^srcN]: <source>, <optional-locator>, excerpt: "<text>"

Returns parsed citations with source, optional locator, and optional excerpt.

Returns:

A vector of Citation entries parsed from the citation block.

Signature:

fun parseCitations(markdown: String): List<Citation>

Example:

val result = parseCitations("value")

Parameters:

Name Type Required Description
markdown String Yes The markdown text to search

Returns: List<Citation>


verifyExcerpt()

Verify that an excerpt appears verbatim in source text.

Performs exact matching by default. Also tries whitespace-normalized matching (collapsing runs of whitespace on both sides) since PDF-extracted text often has irregular spacing.

Returns:

true if the excerpt appears (exactly or with normalized whitespace), false otherwise.

Signature:

fun verifyExcerpt(excerpt: String, sourceText: String): Boolean

Example:

val result = verifyExcerpt("value", "value")

Parameters:

Name Type Required Description
excerpt String Yes The text snippet to find
sourceText String Yes The full source text to search

Returns: Boolean


chunkForRag()

Chunk text for RAG retrieval, ensuring every chunk carries a heading_path.

Delegates to chunk_text using the caller's config (defaulting to ChunkerType.Markdown when the config uses the default Text type, so that heading hierarchy is resolved). After chunking, derives ChunkMetadata.heading_path from each chunk's heading_context.

underlying splitter; use ChunkerType.Markdown for documents with ATX headings.

Returns:

A ChunkingResult where every chunk's heading_path is populated from its heading_context (empty when the chunk is not under any heading).

Errors:

Propagates any error from the underlying chunker (e.g. invalid overlap).

Signature:

@Throws(Error::class)
fun chunkForRag(text: String, config: ChunkingConfig): ChunkingResult

Example:

val result = chunkForRag("value", ChunkingConfig())

Parameters:

Name Type Required Description
text String Yes The text
config ChunkingConfig Yes The configuration options

Returns: ChunkingResult

Errors: Throws Error.


compare()

Compare two extraction results and return a structured diff.

The comparison is purely structural — no I/O, no side effects. All fields of ExtractionDiff are populated according to the provided DiffOptions.

Signature:

fun compare(a: ExtractionResult, b: ExtractionResult, opts: DiffOptions): ExtractionDiff

Example:

val result = compare(ExtractionResult(), ExtractionResult(), DiffOptions())

Parameters:

Name Type Required Description
a ExtractionResult Yes The extraction result
b ExtractionResult Yes The extraction result
opts DiffOptions Yes The options to use

Returns: ExtractionDiff


extractRegionWithVlm()

Extract content from a pre-cropped image region using a VLM.

The caller is responsible for cropping the page image to the region's bounding box before calling this function. The image_bytes parameter must contain the raw bytes of the cropped region image (JPEG, PNG, WebP, etc.).

Returns:

Extracted Markdown text from the VLM, or an error if the VLM call fails.

Errors:

  • Ocr if the VLM call fails or returns no content.
  • MissingDependency if the liter-llm client cannot be initialised.

Signature:

@Throws(Error::class)
fun extractRegionWithVlm(imageBytes: ByteArray, imageMime: String, regionKind: RegionKind, llmConfig: LlmConfig, customPrompt: String? = null): String

Example:

val result = extractRegionWithVlm("data".toByteArray(), "value", RegionKind(), LlmConfig(), "value")

Parameters:

Name Type Required Description
imageBytes ByteArray Yes The image bytes
imageMime String Yes The image mime
regionKind RegionKind Yes The region kind
llmConfig LlmConfig Yes The llm config
customPrompt String? No The custom prompt

Returns: String

Errors: Throws Error.


rerankAsync()

Rerank documents asynchronously.

Async counterpart to rerank. Offloads blocking ONNX inference to a dedicated blocking thread pool via Tokio's spawn_blocking, keeping the async executor free.

Since v5.0.

Signature:

@Throws(Error::class)
fun rerankAsync(query: String, documents: List<String>, config: RerankerConfig): List<RerankedDocument>

Example:

val result = rerankAsync("value", [], RerankerConfig())

Parameters:

Name Type Required Description
query String Yes The query
documents List<String> Yes The documents
config RerankerConfig Yes The configuration options

Returns: List<RerankedDocument>

Errors: Throws Error.


extractKeywords()

Extract keywords from text using the specified algorithm.

This is the unified entry point for keyword extraction. The algorithm used is determined by config.algorithm.

Returns:

A vector of keywords sorted by relevance (highest score first).

Errors:

Returns an error if:

  • The specified algorithm feature is not enabled
  • Keyword extraction fails

Signature:

@Throws(Error::class)
fun extractKeywords(text: String, config: KeywordConfig): List<Keyword>

Example:

val result = extractKeywords("value", KeywordConfig())

Parameters:

Name Type Required Description
text String Yes The text to extract keywords from
config KeywordConfig Yes Keyword extraction configuration

Returns: List<Keyword>

Errors: Throws Error.


analyzeDocument()

Analyze a document and determine the optimal chunking strategy.

Decision logic (in priority order):

  1. If user provides disable_chunking → no chunking
  2. If user provides page_ranges → use user overrides
  3. If chunking is not enabled → no chunking
  4. If format doesn't support chunking → no chunking
  5. If file is small (below both thresholds) and not force_chunking → no chunking
  6. If PDF has a substantial text layer AND !force_ocr → no chunking (only when heuristics-pdf feature is enabled; otherwise skipped)

  7. Otherwise → chunk the document

Errors:

Returns an error only when the heuristics-pdf feature is active and the PDF text-layer analysis itself returns a hard error. In all other cases the function returns a ChunkingDecision.

Signature:

@Throws(Error::class)
fun analyzeDocument(metadata: DocumentMetadata, config: HeuristicsConfig, documentBytes: ByteArray? = null): ChunkingDecision

Example:

val result = analyzeDocument(DocumentMetadata(), HeuristicsConfig(), "data".toByteArray())

Parameters:

Name Type Required Description
metadata DocumentMetadata Yes The document metadata
config HeuristicsConfig Yes The configuration options
documentBytes ByteArray? No The document bytes

Returns: ChunkingDecision

Errors: Throws Error.


analyzeWithUserChunks()

Analyze a document with user-specified chunk ranges.

Creates a chunk plan based on user-provided page ranges.

Signature:

fun analyzeWithUserChunks(userRanges: List<PageRange>, totalPages: Int, sizeBytes: Long, config: HeuristicsConfig): ChunkingDecision

Example:

val result = analyzeWithUserChunks([], 42, 42, HeuristicsConfig())

Parameters:

Name Type Required Description
userRanges List<PageRange> Yes The user ranges
totalPages Int Yes The total pages
sizeBytes Long Yes The size bytes
config HeuristicsConfig Yes The configuration options

Returns: ChunkingDecision


scoreConfidence()

Score a ConfidenceSignals triple into an ExtractionConfidence using the supplied weights.

When signals.ocr_aggregate is null, the OCR weight folds into text_coverage so the weighted sum still totals 1.0.

Signature:

fun scoreConfidence(signals: ConfidenceSignals, weights: ConfidenceWeights): ExtractionConfidence

Example:

val result = scoreConfidence(ConfidenceSignals(), ConfidenceWeights())

Parameters:

Name Type Required Description
signals ConfidenceSignals Yes The confidence signals
weights ConfidenceWeights Yes The confidence weights

Returns: ExtractionConfidence


checkFormatLimits()

Decision returned for pre-extraction rejection based on XLSX/PPTX-specific resource bounds. Returns Some(reason) to reject; null to proceed.

Callers must provide counts from a pre-extraction peek (e.g. parsing xl/workbook.xml for sheet count).

Signature:

fun checkFormatLimits(mimeType: String, sheetCount: Int? = null, workbookCells: Long? = null, embeddedCount: Int? = null, config: HeuristicsConfig): String?

Example:

val result = checkFormatLimits("value", 42, 42, 42, HeuristicsConfig())

Parameters:

Name Type Required Description
mimeType String Yes The mime type
sheetCount Int? No The sheet count
workbookCells Long? No The workbook cells
embeddedCount Int? No The embedded count
config HeuristicsConfig Yes The configuration options

Returns: String?


boundariesFromExtractionResult()

Derive document boundaries from an already-produced ExtractionResult.

Builds a MultidocInput from result.pages (one PageSignals per PageContent entry), then delegates to detect_boundaries.

Fallback behaviour

  • If result.pages is null or empty the whole document is treated as a single document: returns [Start(1), End(1)], matching the contract of detect_boundaries for a one-page input.

Text density

PageContent does not carry a pre-computed density score. This function approximates density as non_whitespace_chars / total_chars (clamped to [0.0, 1.0]), which is a reasonable proxy for how text-dense a page is relative to itself. Pass a custom MultidocInput to detect_boundaries directly when you need a higher-fidelity density measurement (e.g. chars-per-pt² from a PDF extractor).

Signature:

fun boundariesFromExtractionResult(result: ExtractionResult, thresholds: MultidocThresholds): List<DocumentBoundary>

Example:

val result = boundariesFromExtractionResult(ExtractionResult(), MultidocThresholds())

Parameters:

Name Type Required Description
result ExtractionResult Yes The extraction result
thresholds MultidocThresholds Yes The multidoc thresholds

Returns: List<DocumentBoundary>


detectBoundaries()

Detect document boundaries in a multi-document PDF.

Returns a list of detected boundaries, always including implicit boundaries at start (page 1) and end (page_count). Boundaries are returned in ascending order of start_page.

Returns:

Ordered list of document boundaries.

Signature:

fun detectBoundaries(input: MultidocInput, thresholds: MultidocThresholds): List<DocumentBoundary>

Example:

val result = detectBoundaries(MultidocInput(), MultidocThresholds())

Parameters:

Name Type Required Description
input MultidocInput Yes Page signals for the PDF
thresholds MultidocThresholds Yes Detection thresholds

Returns: List<DocumentBoundary>


chooseCallMode()

Decide which call mode best fits this document.

Rules applied in order:

  1. image/*StructuredCallMode.VisionOnly (no text layer to start from).
  2. application/pdfStructuredCallMode.TextOnly regardless of text_coverage or embedded image count. Kreuzberg's OCR + text-layer extraction produces text for scanned PDFs; the orchestrator's post-call confidence gate handles any vision escalation actually needed.

  3. DOCX / text/html / text/* / application/json / application/xml / application/rtf with avg_chars_per_page > docx_text_min_densityStructuredCallMode.TextOnly.

  4. Anything else → StructuredCallMode.Skip.

After rule selection two post-rule promotions apply (in order):

  • user_force_vision promotes TextOnlyTextPlusVision (Skip stays Skip — caller meant to opt out).

  • enable_vision_fallback promotes TextOnlyTextOnlyWithVisionFallback (does not upgrade TextPlusVision or Skip).

Signature:

fun chooseCallMode(input: StructuredInput, t: StructuredThresholds): StructuredCallMode

Example:

val result = chooseCallMode(StructuredInput(), StructuredThresholds())

Parameters:

Name Type Required Description
input StructuredInput Yes The input data
t StructuredThresholds Yes The structured thresholds

Returns: StructuredCallMode


calculateChunkPlan()

Calculate a chunking plan for a document.

Returns:

A ChunkPlan with optimal chunk boundaries.

Signature:

fun calculateChunkPlan(pageCount: Int, sizeBytes: Long, needsOcr: Boolean, config: HeuristicsConfig): ChunkPlan

Example:

val result = calculateChunkPlan(42, 42, true, HeuristicsConfig())

Parameters:

Name Type Required Description
pageCount Int Yes Total number of pages in the document
sizeBytes Long Yes File size in bytes
needsOcr Boolean Yes Whether OCR will be required
config HeuristicsConfig Yes Heuristics configuration

Returns: ChunkPlan


calculatePlanFromOverrides()

Calculate a chunk plan from user-specified page ranges.

Validates and processes user overrides into a proper chunk plan.

Signature:

fun calculatePlanFromOverrides(userChunks: List<PageRange>, totalPages: Int, sizeBytes: Long, config: HeuristicsConfig): ChunkPlan

Example:

val result = calculatePlanFromOverrides([], 42, 42, HeuristicsConfig())

Parameters:

Name Type Required Description
userChunks List<PageRange> Yes The user chunks
totalPages Int Yes The total pages
sizeBytes Long Yes The size bytes
config HeuristicsConfig Yes The configuration options

Returns: ChunkPlan


fingerprint()

Stable sha256 fingerprint of raw, formatted as sha256:<hex>.

Signature:

fun fingerprint(raw: ByteArray): String

Example:

val result = fingerprint("data".toByteArray())

Parameters:

Name Type Required Description
raw ByteArray Yes The raw

Returns: String


resolve()

Resolve (preset, custom_schema_override, context) into a ResolvedPreset.

  • custom_schema overrides preset.schema when set.
  • context substitutes {{key}} tokens in preset.context_template; the rendered string is appended to system_prompt so the model sees it.

Signature:

@Throws(ResolveError::class)
fun resolve(preset: Preset, customSchema: Any? = null, context: Map<String, String>): ResolvedPreset

Example:

val result = resolve(Preset(), emptyMap(), emptyMap())

Parameters:

Name Type Required Description
preset Preset Yes The preset
customSchema Any? No The custom schema
context Map<String, String> Yes The context

Returns: ResolvedPreset

Errors: Throws ResolveError.


extractStructuredJson()

Extract structured JSON from a document using JSON-encoded preset spec and options.

This is the synchronous JSON-in / JSON-out entry point suitable for FFI and language-binding call paths.

cache). Pass "{}" to use all defaults.

Returns:

JSON-serialised StructuredOutput on success.

Errors:

Returns Validation when either JSON argument is malformed. All other failures from the underlying extract_structured_sync call are mapped onto KreuzbergError via From<StructuredError>.

Signature:

@Throws(Error::class)
fun extractStructuredJson(bytes: ByteArray, mime: String, presetSpecJson: String, optionsJson: String): String

Example:

val result = extractStructuredJson("data".toByteArray(), "value", "value", "value")

Parameters:

Name Type Required Description
bytes ByteArray Yes The bytes
mime String Yes The mime
presetSpecJson String Yes The preset spec json
optionsJson String Yes The options json

Returns: String

Errors: Throws Error.


splitAndExtractJson()

Split a multi-document PDF and extract structured JSON from each segment, returning a JSON array of StructuredOutput objects.

Non-PDF documents are passed through as a single-element array.

Same as extract_structured_json.

Returns:

JSON-serialised List<StructuredOutput> (a JSON array) on success.

Errors:

Returns Validation when either JSON argument is malformed. All other failures from the underlying split_and_extract_sync call are mapped onto KreuzbergError via From<StructuredError>.

Signature:

@Throws(Error::class)
fun splitAndExtractJson(bytes: ByteArray, mime: String, presetSpecJson: String, optionsJson: String): String

Example:

val result = splitAndExtractJson("data".toByteArray(), "value", "value", "value")

Parameters:

Name Type Required Description
bytes ByteArray Yes The bytes
mime String Yes The mime
presetSpecJson String Yes The preset spec json
optionsJson String Yes The options json

Returns: String

Errors: Throws Error.


renderPdfPageToPng()

Render a single PDF page to PNG bytes.

Returns raw PNG-encoded bytes for the specified page at the given DPI. Uses pdf_oxide with tiny-skia for pure-Rust rendering.

For pages with extreme dimensions (very wide vector diagrams, etc.) the effective DPI may be automatically reduced to avoid rasterizer failure. A warning is logged when this happens.

Errors:

Returns KreuzbergError.Parsing if the PDF cannot be opened, authenticated, or rendered, or if page_index is out of range.

Signature:

@Throws(Error::class)
fun renderPdfPageToPng(pdfBytes: ByteArray, pageIndex: Long, dpi: Int? = null, password: String? = null): ByteArray

Example:

val result = renderPdfPageToPng("data".toByteArray(), 42, 42, "value")

Parameters:

Name Type Required Description
pdfBytes ByteArray Yes Raw PDF file bytes
pageIndex Long Yes Zero-based page index
dpi Int? No Resolution in dots per inch (default: 150)
password String? No Optional password for encrypted PDFs

Returns: ByteArray

Errors: Throws Error.


captionImage()

Caption a single image from bytes.

RegionKind.Caption prompt when null.

Returns:

The generated caption text.

Errors:

Returns an error if the VLM call fails or if image format detection fails.

Signature:

@Throws(Error::class)
fun captionImage(imageBytes: ByteArray, llmConfig: LlmConfig, customPrompt: String? = null): String

Example:

val result = captionImage("data".toByteArray(), LlmConfig(), "value")

Parameters:

Name Type Required Description
imageBytes ByteArray Yes The image data.
llmConfig LlmConfig Yes LLM configuration for the VLM call.
customPrompt String? No Optional custom caption prompt. Uses the default

Returns: String

Errors: Throws Error.


captionImageFile()

Caption a single image from a file path.

RegionKind.Caption prompt when null.

Returns:

The generated caption text.

Errors:

Returns an error if the file cannot be read, if image format detection fails, or if the VLM call fails.

Signature:

@Throws(Error::class)
fun captionImageFile(path: Path, llmConfig: LlmConfig, customPrompt: String? = null): String

Example:

val result = captionImageFile("value", LlmConfig(), "value")

Parameters:

Name Type Required Description
path Path Yes Path to the image file.
llmConfig LlmConfig Yes LLM configuration for the VLM call.
customPrompt String? No Optional custom caption prompt. Uses the default

Returns: String

Errors: Throws Error.


detectMimeType()

Detect the MIME type of a file at the given path.

Uses the file extension and optionally the file content to determine the MIME type. Set check_exists to true to verify the file exists before detection.

Signature:

@Throws(Error::class)
fun detectMimeType(path: String, checkExists: Boolean): String

Example:

val result = detectMimeType("value", true)

Parameters:

Name Type Required Description
path String Yes Path to the file
checkExists Boolean Yes The check exists

Returns: String

Errors: Throws Error.


getEmbeddingPreset()

Get an embedding preset by name.

Returns null if no preset with the given name exists. Returns an owned clone so the value is safe to pass across FFI boundaries.

Signature:

fun getEmbeddingPreset(name: String): EmbeddingPreset?

Example:

val result = getEmbeddingPreset("value")

Parameters:

Name Type Required Description
name String Yes The name

Returns: EmbeddingPreset?


listEmbeddingPresets()

List the names of all available embedding presets.

Returns owned Strings so the values are safe to pass across FFI boundaries.

Signature:

fun listEmbeddingPresets(): List<String>

Example:

val result = listEmbeddingPresets()

Returns: List<String>


getEmbeddingPreset()

Returns null for builds without the embedding-presets feature.

Signature:

fun getEmbeddingPreset(name: String): EmbeddingPreset?

Example:

val result = getEmbeddingPreset("value")

Parameters:

Name Type Required Description
name String Yes The name

Returns: EmbeddingPreset?


listEmbeddingPresets()

Returns an empty list for builds without the embedding-presets feature.

Signature:

fun listEmbeddingPresets(): List<String>

Example:

val result = listEmbeddingPresets()

Returns: List<String>


rerank()

Rerank a list of documents by relevance to a query.

Returns documents sorted descending by score. Applies top_k truncation if configured.

Errors:

  • KreuzbergError.Validation if query is empty or blank.
  • KreuzbergError.MissingDependency if ONNX Runtime is not installed (ONNX path).
  • KreuzbergError.Reranking if the preset is unknown or model download fails.

Since v5.0.

Signature:

@Throws(Error::class)
fun rerank(query: String, documents: List<String>, config: RerankerConfig): List<RerankedDocument>

Example:

val result = rerank("value", [], RerankerConfig())

Parameters:

Name Type Required Description
query String Yes The query
documents List<String> Yes The documents
config RerankerConfig Yes The configuration options

Returns: List<RerankedDocument>

Errors: Throws Error.


rerank()

Stub for builds without the reranker feature — keeps the symbol available on no-ORT targets (Android x86_64 emulator, WASM) so language bindings compile.

Since v5.0.

Signature:

@Throws(Error::class)
fun rerank(query: String, documents: List<String>, config: RerankerConfig): List<RerankedDocument>

Example:

val result = rerank("value", [], RerankerConfig())

Parameters:

Name Type Required Description
query String Yes The query
documents List<String> Yes The documents
config RerankerConfig Yes The reranker config

Returns: List<RerankedDocument>

Errors: Throws Error.


rerankAsync()

Stub for builds without the reranker feature.

Since v5.0.

Signature:

@Throws(Error::class)
fun rerankAsync(query: String, documents: List<String>, config: RerankerConfig): List<RerankedDocument>

Example:

val result = rerankAsync("value", [], RerankerConfig())

Parameters:

Name Type Required Description
query String Yes The query
documents List<String> Yes The documents
config RerankerConfig Yes The reranker config

Returns: List<RerankedDocument>

Errors: Throws Error.


getRerankerPreset()

Get a reranker preset by name.

Returns null if no preset with the given name exists. Returns an owned clone so the value is safe to pass across FFI boundaries.

Since v5.0.

Signature:

fun getRerankerPreset(name: String): RerankerPreset?

Example:

val result = getRerankerPreset("value")

Parameters:

Name Type Required Description
name String Yes The name

Returns: RerankerPreset?


listRerankerPresets()

List the names of all available reranker presets.

Returns owned Strings so the values are safe to pass across FFI boundaries.

Since v5.0.

Signature:

fun listRerankerPresets(): List<String>

Example:

val result = listRerankerPresets()

Returns: List<String>


getRerankerPreset()

Returns null for builds without the reranker-presets feature.

Since v5.0.

Signature:

fun getRerankerPreset(name: String): RerankerPreset?

Example:

val result = getRerankerPreset("value")

Parameters:

Name Type Required Description
name String Yes The name

Returns: RerankerPreset?


listRerankerPresets()

Returns an empty list for builds without the reranker-presets feature.

Since v5.0.

Signature:

fun listRerankerPresets(): List<String>

Example:

val result = listRerankerPresets()

Returns: List<String>


Types

AccelerationConfig

Hardware acceleration configuration for ONNX Runtime models.

Controls which execution provider (CPU, CoreML, CUDA, TensorRT) is used for inference in layout detection and embedding generation.

Field Type Default Description
provider ExecutionProviderType ExecutionProviderType.Auto Execution provider to use for ONNX inference.
deviceId Int GPU device ID (for CUDA/TensorRT). Ignored for CPU/CoreML/Auto.

ArchiveEntry

A single file extracted from an archive.

When archives (ZIP, TAR, 7Z, GZIP) are extracted with recursive extraction enabled, each processable file produces its own full ExtractionResult.

Field Type Default Description
path String Archive-relative file path (e.g. "folder/document.pdf").
mimeType String Detected MIME type of the file.
result ExtractionResult Full extraction result for this file.

ArchiveMetadata

Archive (ZIP/TAR/7Z) metadata.

Extracted from compressed archive files containing file lists and size information.

Field Type Default Description
format String Archive format ("ZIP", "TAR", "7Z", etc.)
fileCount Int Total number of files in the archive
fileList List<String> \[\] List of file paths within the archive
totalSize Long Total uncompressed size in bytes
compressedSize Long? null Compressed size in bytes (if available)

AudioMetadata

Audio/video file metadata.

Populated from container tags (ID3v2, MP4 atoms, Vorbis comments, etc.) and PCM decode properties. Available when the transcription-types feature is enabled.

Field Type Default Description
durationMs Long? null Duration in milliseconds derived from the decoded audio stream.
codec String? null Audio codec (e.g. "mp3", "aac", "opus", "flac").
container String? null Container format (e.g. "mpeg", "mp4", "ogg", "wav").
sampleRateHz Int? null Sample rate in Hz after decode (always 16000 when resampled for Whisper).
channels Short? null Number of audio channels (1 = mono, 2 = stereo).
bitrate Int? null Audio bitrate in kbps from the source file tags/properties.

BBox

Bounding box in original image coordinates (x1, y1) top-left, (x2, y2) bottom-right.

Field Type Default Description
x1 Float Left edge (x-coordinate of the top-left corner).
y1 Float Top edge (y-coordinate of the top-left corner).
x2 Float Right edge (x-coordinate of the bottom-right corner).
y2 Float Bottom edge (y-coordinate of the bottom-right corner).

BatchBytesItem

Batch item for byte array extraction.

Used with batch_extract_bytes and batch_extract_bytes_sync to represent a single item in a batch extraction job.

Field Type Default Description
content ByteArray The content bytes to extract from
mimeType String MIME type of the content (e.g., "application/pdf", "text/html")
config FileExtractionConfig? null Per-item configuration overrides (None uses batch-level defaults)

BatchFileItem

Batch item for file extraction.

Used with batch_extract_files and batch_extract_files_sync to represent a single file in a batch extraction job.

Field Type Default Description
path Path Path to the file to extract from
config FileExtractionConfig? null Per-file configuration overrides (None uses batch-level defaults)

BibtexMetadata

BibTeX bibliography metadata.

Field Type Default Description
entryCount Long Number of entries in the bibliography.
citationKeys List<String> \[\] BibTeX citation keys (e.g. "knuth1984") for all entries.
authors List<String> \[\] Author names collected across all bibliography entries.
yearRange YearRange? null Earliest and latest publication years found in the bibliography.
entryTypes Map<String, Long>? {} Count of entries grouped by BibTeX entry type (e.g. "article" → 5).

BoundingBox

Bounding box coordinates for element positioning.

Field Type Default Description
x0 Double Left x-coordinate
y0 Double Bottom y-coordinate
x1 Double Right x-coordinate
y1 Double Top y-coordinate

CacheStats

Aggregate statistics for a kreuzberg cache directory.

Field Type Default Description
totalFiles Long Total number of files currently in the cache directory.
totalSizeMb Double Combined size of all cache files in megabytes.
availableSpaceMb Double Free disk space available on the cache volume, in megabytes.
oldestFileAgeDays Double Age of the oldest cache file in days (0.0 if the cache is empty).
newestFileAgeDays Double Age of the most recently written cache file in days (0.0 if the cache is empty).

CaptioningConfig

Since: v5.0

Configuration for the VLM captioning post-processor.

Field Type Default Description
llm LlmConfig LLM configuration used for the VLM call.
prompt String? null Optional custom caption prompt. null uses the default RegionKind.Caption prompt that ships with crate.llm.region_extractor.
minImageArea Int serde(default = "default_min_image_area") Skip images whose width * height is below this threshold (in pixels). Default 1_000 filters out icons and decorations.

CaptioningEnrichmentConfig

Captioning enrichment knob: which LLM to use for image captions.

The enrichment stage calls caption_image for every image in ExtractionResult.images that has non-empty data. Images with empty byte data (e.g. reference-only images populated via source_path) are skipped rather than forwarded to the VLM.

Field Type Default Description
config LlmConfig LLM / VLM configuration forwarded verbatim to each caption_image call.
customPrompt String? null Optional custom prompt override forwarded to every caption_image call. null uses the default RegionKind.Caption prompt.

CellChange

A single changed cell within a table.

Defined here (rather than only in crate.diff) so RevisionDelta can reference it unconditionally, without requiring the diff Cargo feature. crate.diff re-exports this type verbatim.

Field Type Default Description
row Long Zero-based row index.
col Long Zero-based column index.
from String Value before the change.
to String Value after the change.

Chunk

A text chunk with optional embedding and metadata.

Chunks are created when chunking is enabled in ExtractionConfig. Each chunk contains the text content, optional embedding vector (if embedding generation is configured), and metadata about its position in the document.

Field Type Default Description
content String The text content of this chunk.
chunkType ChunkType /* serde(default) */ Semantic structural classification of this chunk. Assigned by the heuristic classifier based on content patterns and heading context. Defaults to ChunkType.Unknown when no rule matches.
embedding List<Float>? null Optional embedding vector for this chunk. Only populated when EmbeddingConfig is provided in chunking configuration. The dimensionality depends on the chosen embedding model.
metadata ChunkMetadata Metadata about this chunk's position and properties.

ChunkInfo

Information about a single chunk.

Field Type Default Description
index Int Zero-based chunk index.
pages PageRange Page range for this chunk.
estimatedTimeMs Long Estimated processing time for this chunk in milliseconds.

ChunkMetadata

Metadata about a chunk's position in the original document.

Field Type Default Description
byteStart Long Byte offset where this chunk starts in the original text (UTF-8 valid boundary).
byteEnd Long Byte offset where this chunk ends in the original text (UTF-8 valid boundary).
tokenCount Long? null Number of tokens in this chunk (if available). This is calculated by the embedding model's tokenizer if embeddings are enabled.
chunkIndex Long Zero-based index of this chunk in the document.
totalChunks Long Total number of chunks in the document.
firstPage Int? null First page number this chunk spans (1-indexed). Only populated when page tracking is enabled in extraction configuration.
lastPage Int? null Last page number this chunk spans (1-indexed, equal to first_page for single-page chunks). Only populated when page tracking is enabled in extraction configuration.
headingContext HeadingContext? /* serde(default) */ Heading context when using Markdown chunker. Contains the heading hierarchy this chunk falls under. Only populated when ChunkerType.Markdown is used.
headingPath List<String> /* serde(default) */ Flattened heading trail from document root to this chunk's section. Each element is a heading's text, outermost first. Derived from heading_context when present; empty otherwise. Provides a binding-friendly, RAG-shaped breadcrumb without requiring callers to walk the nested HeadingContext structure.
imageIndices List<Int> /* serde(default) */ Indices into ExtractionResult.images for images on pages covered by this chunk. Contains zero-based indices into the top-level images collection for every image whose page_number falls within \[first_page, last_page\]. Empty when image extraction is disabled or the chunk spans no pages with images.

ChunkPlan

Complete chunking plan for a document.

Field Type Default Description
totalChunks Int 0 Total number of chunks.
chunks List<ChunkInfo> \[\] Individual chunk information.
totalEstimatedTimeMs Long 0 Estimated total processing time in milliseconds.
useDiskProcessing Boolean false Whether to use disk-based processing for large files.
reason ChunkingReason ChunkingReason.LargeFile Reason for chunking.
Methods
default()

An empty plan (no chunks). The reason is a placeholder since an empty plan has no chunking rationale; callers always overwrite it when a real plan is built.

Signature:

@JvmStatic
fun default(): ChunkPlan

Example:

val result = ChunkPlan.default()

Returns: ChunkPlan

totalPages()

Get the total number of pages across all chunks.

Signature:

fun totalPages(): Int

Example:

val result = instance.totalPages()

Returns: Int


ChunkingConfig

Chunking configuration.

Configures text chunking for document content, including chunk size, overlap, trimming behavior, and optional embeddings.

Use ..the default constructor when constructing to allow for future field additions:

Field Type Default Description
maxCharacters Long 1000 Maximum size per chunk (in units determined by sizing). When sizing is Characters (default), this is the max character count. When using token-based sizing, this is the max token count. Default: 1000
overlap Long 200 Overlap between chunks (in units determined by sizing). Default: 200
trim Boolean true Whether to trim whitespace from chunk boundaries. Default: true
chunkerType ChunkerType ChunkerType.Text Type of chunker to use (Text or Markdown). Default: Text
embedding EmbeddingConfig? null Optional embedding configuration for chunk embeddings.
preset String? null Use a preset configuration (overrides individual settings if provided).
sizing ChunkSizing ChunkSizing.Characters How to measure chunk size. Default: Characters (Unicode character count). Enable chunking-tiktoken or chunking-tokenizers features for token-based sizing.
prependHeadingContext Boolean false When true and chunker_type is Markdown, prepend the heading hierarchy path (e.g. "# Title > ## Section\n\n") to each chunk's content string. This is useful for RAG pipelines where each chunk needs self-contained context about its position in the document structure. Default: false
topicThreshold Float? null Optional cosine similarity threshold for semantic topic boundary detection. Only used when chunker_type is Semantic and an EmbeddingConfig is provided. You almost never need to set this. When omitted, defaults to 0.75 which works well for most documents. Lower values detect more topic boundaries (more, smaller chunks); higher values detect fewer. Range: 0.0..=1.0.
tableChunking TableChunkingMode TableChunkingMode.Split How to handle markdown tables that exceed the chunk size limit. Only applies when chunker_type is Markdown. - Split (default) — tables are split at row boundaries; continuation chunks do not repeat the header. - RepeatHeader — the table header row and separator are prepended to every continuation chunk so each chunk is self-contained. Default: Split
Methods
default()

Signature:

@JvmStatic
fun default(): ChunkingConfig

Example:

val result = ChunkingConfig.default()

Returns: ChunkingConfig


ChunkingResult

Result of a text chunking operation.

Contains the generated chunks and metadata about the chunking.

Field Type Default Description
chunks List<Chunk> List of text chunks
chunkCount Long Total number of chunks generated

Citation

A structured citation from a citation block.

Parsed from entries like: [^srcN]: source, locator, excerpt: "text"

Field Type Default Description
label String The label of the citation (e.g., "src1" in \[^src1\]: ...).
source String The source reference (path, URL, or identifier).
locator String? null Optional locator within the source (e.g., "page 3" or "section 2.1").
excerpt String? null Optional excerpt — quoted text from the source.

CitationMetadata

Citation file metadata (RIS, PubMed, EndNote).

Field Type Default Description
citationCount Long Total number of citation records in the file.
format String? null Detected citation file format (e.g. "ris", "pubmed", "endnote").
authors List<String> \[\] Author names collected across all citation records.
yearRange YearRange? null Earliest and latest publication years found in the file.
dois List<String> \[\] DOI identifiers found in the citation records.
keywords List<String> \[\] Keywords collected from all citation records.

ClassificationEnrichmentConfig

Classification enrichment knob: how to label the document.

Field Type Default Description
config PageClassificationConfig Label set and LLM settings for the classification stage.

ClassificationLabel

A single label + confidence pair.

Field Type Default Description
label String Label name as configured in PageClassificationConfig.labels.
confidence Float? null Backend-reported confidence in \[0.0, 1.0\]. null when the backend (e.g. an LLM prompt without explicit confidence schema) did not report one.

ConfidenceSignals

Input signals for confidence scoring.

Caller fills these from the extraction result and the LLM response.

Field Type Default Description
textCoverage Float Fraction of pages with usable text in \[0, 1\].
ocrAggregate Float? null Mean OCR per-element recognition confidence; null when OCR did not run.
schemaCompliance SchemaCompliance Schema-validation result of the merged output.
Methods
fromExtractionResult()

Build ConfidenceSignals from an ExtractionResult.

  • result — The extraction result whose ocr_elements are inspected.
  • schema_compliance — Caller-supplied schema validation outcome.
  • text_coverage — Caller-supplied fraction of pages with usable text (e.g. 1.0 for native text formats, value from PDF analysis for PDFs).

The ocr_aggregate is computed as the arithmetic mean of all ocr_elements[].confidence.recognition values. When ocr_elements is null or empty the field is set to null.

Signature:

@JvmStatic
fun fromExtractionResult(result: ExtractionResult, schemaCompliance: SchemaCompliance, textCoverage: Float): ConfidenceSignals

Example:

val result = ConfidenceSignals.fromExtractionResult(ExtractionResult(), SchemaCompliance(), 0.5)

Parameters:

Name Type Required Description
result ExtractionResult Yes The extraction result
schemaCompliance SchemaCompliance Yes The schema compliance
textCoverage Float Yes The text coverage

Returns: ConfidenceSignals


ConfidenceWeights

Tunable weights for the confidence scoring formula.

Defaults picked by inspection; callers tune them via config.

Field Type Default Description
textCoverage Float 0.3 Weight assigned to text_coverage. Default 0.30.
ocrAggregate Float 0.3 Weight assigned to ocr_aggregate when OCR ran. Default 0.30 — folds into text_coverage weight when OCR did not run.
schemaCompliance Float 0.4 Weight assigned to schema_compliance. Default 0.40.
Methods
default()

Signature:

@JvmStatic
fun default(): ConfidenceWeights

Example:

val result = ConfidenceWeights.default()

Returns: ConfidenceWeights

isNormalized()

Validate that weights sum to approximately 1.0.

Signature:

fun isNormalized(): Boolean

Example:

val result = instance.isNormalized()

Returns: Boolean


ContentFilterConfig

Cross-extractor content filtering configuration.

Controls whether "furniture" content (headers, footers, page numbers, watermarks, repeating text) is included in or stripped from extraction results. Applies across all extractors (PDF, DOCX, RTF, ODT, HTML, etc.) with format-specific implementation.

When null on ExtractionConfig, each extractor uses its current default behavior unchanged.

Field Type Default Description
includeHeaders Boolean false Include running headers in extraction output. - PDF: Disables top-margin furniture stripping and prevents the layout model from treating PageHeader-classified regions as furniture. - DOCX: Includes document headers in text output. - RTF/ODT: Headers already included; this is a no-op when true. - HTML/EPUB: Keeps <header> element content. Default: false (headers are stripped or excluded).
includeFooters Boolean false Include running footers in extraction output. - PDF: Disables bottom-margin furniture stripping and prevents the layout model from treating PageFooter-classified regions as furniture. - DOCX: Includes document footers in text output. - RTF/ODT: Footers already included; this is a no-op when true. - HTML/EPUB: Keeps <footer> element content. Default: false (footers are stripped or excluded).
stripRepeatingText Boolean true Enable the heuristic cross-page repeating text detector. When true (default), text that repeats verbatim across a supermajority of pages is classified as furniture and stripped. Disable this if brand names or repeated headings are being incorrectly removed by the heuristic. Note: when a layout-detection model is active, the model may independently classify page-header / page-footer regions as furniture on a per-page basis. To preserve those regions, set include_headers = true, include_footers = true, or both, in addition to disabling this flag. Primarily affects PDF extraction. Default: true.
includeWatermarks Boolean false Include watermark text in extraction output. - PDF: Keeps watermark artifacts and arXiv identifiers. - Other formats: No effect currently. Default: false (watermarks are stripped).
Methods
default()

Signature:

@JvmStatic
fun default(): ContentFilterConfig

Example:

val result = ContentFilterConfig.default()

Returns: ContentFilterConfig


ContributorRole

JATS contributor with role.

Field Type Default Description
name String Contributor display name.
role String? null Contributor role (e.g. "author", "editor").

CoreProperties

Dublin Core metadata from docProps/core.xml

Contains standard metadata fields defined by the Dublin Core standard and Office-specific extensions.

Field Type Default Description
title String? null Document title
subject String? null Document subject/topic
creator String? null Document creator/author
keywords String? null Keywords or tags
description String? null Document description/abstract
lastModifiedBy String? null User who last modified the document
revision String? null Revision number
created String? null Creation timestamp (ISO 8601)
modified String? null Last modification timestamp (ISO 8601)
category String? null Document category
contentStatus String? null Content status (Draft, Final, etc.)
language String? null Document language
identifier String? null Unique identifier
version String? null Document version
lastPrinted String? null Last print timestamp (ISO 8601)

CsvMetadata

CSV/TSV file metadata.

Field Type Default Description
rowCount Int Total number of data rows (excluding the header row if present).
columnCount Int Number of columns detected.
delimiter String? null Field delimiter character (e.g. "," or "\t").
hasHeader Boolean Whether the first row was treated as a header.
columnTypes List<String>? \[\] Inferred data type for each column (e.g. "string", "integer", "float").

DbfFieldInfo

dBASE field information.

Field Type Default Description
name String Field (column) name.
fieldType String dBASE field type character (e.g. "C" for character, "N" for numeric).

DbfMetadata

dBASE (DBF) file metadata.

Field Type Default Description
recordCount Long Total number of data records in the DBF file.
fieldCount Long Number of field (column) definitions.
fields List<DbfFieldInfo> \[\] Descriptor for each field in the table schema.

DetectResponse

MIME type detection response.

Field Type Default Description
mimeType String Detected MIME type
filename String? null Original filename (if provided)

DetectionResult

Page-level detection result containing all detections and page metadata.

Field Type Default Description
pageWidth Int Page width in pixels (as seen by the model).
pageHeight Int Page height in pixels (as seen by the model).
detections List<LayoutDetection> All layout detections on this page after postprocessing.

DiffHunk

A single contiguous hunk in a unified diff.

Field Type Default Description
fromLine Long Starting line number in the old content (0-indexed).
fromCount Long Number of lines from the old content in this hunk.
toLine Long Starting line number in the new content (0-indexed).
toCount Long Number of lines from the new content in this hunk.
lines List<DiffLine> Lines that make up this hunk.

DiffOptions

Options controlling how two ExtractionResult values are compared.

Field Type Default Description
includeMetadata Boolean true Include metadata changes in the diff. Default: true.
includeEmbedded Boolean true Include embedded-children changes in the diff. Default: true.
maxContentChars Long? null Truncate content to this many characters before diffing. Useful for very large documents where only the first N characters matter. null means no truncation.
Methods
default()

Signature:

@JvmStatic
fun default(): DiffOptions

Example:

val result = DiffOptions.default()

Returns: DiffOptions


DjotContent

Comprehensive Djot document structure with semantic preservation.

This type captures the full richness of Djot markup, including:

  • Block-level structures (headings, lists, blockquotes, code blocks, etc.)
  • Inline formatting (emphasis, strong, highlight, subscript, superscript, etc.)
  • Attributes (classes, IDs, key-value pairs)
  • Links, images, footnotes
  • Math expressions (inline and display)
  • Tables with full structure

Available when the djot feature is enabled.

Field Type Default Description
plainText String Plain text representation for backwards compatibility
blocks List<FormattedBlock> Structured block-level content
metadata Metadata Metadata from YAML frontmatter
tables List<Table> Extracted tables as structured data
images List<DjotImage> Extracted images with metadata
links List<DjotLink> Extracted links with URLs
footnotes List<Footnote> Footnote definitions

DjotImage

Image element in Djot.

Field Type Default Description
src String Image source URL or path
alt String Alternative text
title String? null Optional title

Link element in Djot.

Field Type Default Description
url String Link URL
text String Link text content
title String? null Optional title

DocumentBoundary

Detected document boundary within a PDF.

Field Type Default Description
startPage Int 1-indexed start page (inclusive).
endPage Int 1-indexed end page (inclusive).
confidence Float Confidence in this boundary, \[0.0, 1.0\].
reason BoundaryReason Reason for the boundary detection.

DocumentExtractor

Trait for document extractor plugins.

Implement this trait to add support for new document formats or to override built-in extraction behavior with custom logic.

Return Type

Extractors return InternalDocument, a flat intermediate representation. The pipeline converts this into the public ExtractionResult via the derivation step.

Priority System

When multiple extractors support the same MIME type, the registry selects the extractor with the highest priority value. Use this to:

  • Override built-in extractors (priority > 50)
  • Provide fallback extractors (priority < 50)
  • Implement specialized extractors for specific use cases

Default priority is 50.

Thread Safety

Extractors must be thread-safe (Send + Sync) to support concurrent extraction.

Methods
extractBytes()

Extract content from a byte array.

This is the core extraction method that processes in-memory document data.

Returns:

An InternalDocument containing the extracted elements, metadata, and tables. The pipeline will convert this into the public ExtractionResult.

Errors:

  • KreuzbergError.Parsing - Document parsing failed
  • KreuzbergError.Validation - Invalid document structure
  • KreuzbergError.Io - I/O errors (these always bubble up)
  • KreuzbergError.MissingDependency - Required dependency not available

Signature:

@Throws(Error::class)
fun extractBytes(content: ByteArray, mimeType: String, config: ExtractionConfig): InternalDocument

Example:

val result = instance.extractBytes("data".toByteArray(), "value", ExtractionConfig())

Parameters:

Name Type Required Description
content ByteArray Yes Raw document bytes
mimeType String Yes MIME type of the document (already validated)
config ExtractionConfig Yes Extraction configuration

Returns: InternalDocument

Errors: Throws Error.

extractFile()

Extract content from a file.

Default implementation reads the file and calls extract_bytes. Override for custom file handling, streaming, or memory optimizations.

Returns:

An InternalDocument containing the extracted elements, metadata, and tables.

Errors:

Same as extract_bytes, plus file I/O errors.

Signature:

@Throws(Error::class)
fun extractFile(path: Path, mimeType: String, config: ExtractionConfig): InternalDocument

Example:

val result = instance.extractFile("value", "value", ExtractionConfig())

Parameters:

Name Type Required Description
path Path Yes Path to the document file
mimeType String Yes MIME type of the document (already validated)
config ExtractionConfig Yes Extraction configuration

Returns: InternalDocument

Errors: Throws Error.

supportedMimeTypes()

Get the list of MIME types supported by this extractor.

Can include exact MIME types and prefix patterns:

  • Exact: "application/pdf", "text/plain"
  • Prefix: "image/*" (matches any image type)

Returns:

A slice of MIME type strings.

Signature:

fun supportedMimeTypes(): List<String>

Example:

val result = instance.supportedMimeTypes()

Returns: List<String>

priority()

Get the priority of this extractor.

Higher priority extractors are preferred when multiple extractors support the same MIME type.

Priority Guidelines
  • 0-25: Fallback/low-quality extractors
  • 26-49: Alternative extractors
  • 50: Default priority (built-in extractors)
  • 51-75: Premium/enhanced extractors
  • 76-100: Specialized/high-priority extractors

Returns:

Priority value (default: 50)

Signature:

fun priority(): Int

Example:

val result = instance.priority()

Returns: Int

canHandle()

Optional: Check if this extractor can handle a specific file.

Allows for more sophisticated detection beyond MIME types. Defaults to true (rely on MIME type matching).

Returns:

true if the extractor can handle this file, false otherwise.

Signature:

fun canHandle(path: Path, mimeType: String): Boolean

Example:

val result = instance.canHandle("value", "value")

Parameters:

Name Type Required Description
path Path Yes The path
mimeType String Yes The mime type

Returns: Boolean


DocumentMetadata

Metadata about a document for analysis.

Field Type Default Description
mimeType String MIME type of the document.
sizeBytes Long File size in bytes.
pageCount Int? null Page count (if known, e.g., from previous analysis).
forceOcr Boolean Whether OCR is forced regardless of text layer.
userChunkConfig UserChunkConfig? null User-provided chunk configuration overrides.
chunkingEnabled Boolean Whether chunking is enabled for this job.

DocumentNode

A single node in the document tree.

Each node has deterministic id, typed content, optional parent/children for tree structure, and metadata like page number, bounding box, and content layer.

Field Type Default Description
content NodeContent Node content — tagged enum, type-specific data only.
parent Int? null Parent node index (null = root-level node).
children List<Int> /* serde(default) */ Child node indices in reading order.
contentLayer ContentLayer /* serde(default) */ Content layer classification. Always serialised — Kotlin-Android (and any other typed binding) treats the field as non-nullable, so omitting it from the JSON wire would break consumer deserialisation. #\[serde(default)\] covers the missing-field case on inbound JSON.
page Int? null Page number where this node starts (1-indexed).
pageEnd Int? null Page number where this node ends (for multi-page tables/sections).
bbox BoundingBox? null Bounding box in document coordinates.
annotations List<TextAnnotation> /* serde(default) */ Inline annotations (formatting, links) on this node's text content. Only meaningful for text-carrying nodes; empty for containers.
attributes Map<String, String>? null Format-specific key-value attributes. Extensible bag for miscellaneous data without a dedicated typed field: CSS classes, LaTeX environment names, Excel cell formulas, slide layout names, etc.

DocumentRelationship

A resolved relationship between two nodes in the document tree.

Field Type Default Description
source Int Source node index (the referencing node).
target Int Target node index (the referenced node).
kind RelationshipKind Semantic kind of the relationship.

DocumentRevision

A single tracked change embedded in a document.

Populated by per-format extractors that understand change-tracking metadata (DOCX w:ins/w:del/w:rPrChange, ODT text:change-*, …). Every extractor defaults to ExtractionResult.revisions = None until a format-specific implementation is added.

Field Type Default Description
revisionId String Format-specific revision identifier. For DOCX this is the w:id attribute value on the change element (e.g. "42"). When the attribute is absent a synthetic fallback is generated ("docx-ins-0", "docx-del-3", …).
author String? null Display name of the author who made this change, when available.
timestamp String? null ISO-8601 timestamp of the change, when available. Stored as a plain string so this type remains FFI-friendly and unconditionally available without the chrono optional dep. DOCX populates this from the w:date attribute (e.g. "2024-03-15T10:30:00Z").
kind RevisionKind Semantic kind of this revision.
anchor RevisionAnchor? null Best-effort document location for this revision. Resolution is format-dependent and may be null when the location cannot be determined (e.g. changes inside table cells before table-cell anchor support is added).
delta RevisionDelta The content changes that make up this revision.

DocumentStructure

Top-level structured document representation.

A flat array of nodes with index-based parent/child references forming a tree. Root-level nodes have parent: None. Use body_roots() and furniture_roots() to iterate over top-level content by layer.

Validation

Call validate() after construction to verify all node indices are in bounds and parent-child relationships are bidirectionally consistent.

Field Type Default Description
nodes List<DocumentNode> \[\] All nodes in document/reading order.
sourceFormat String? null Origin format identifier (e.g. "docx", "pptx", "html", "pdf"). Allows renderers to apply format-aware heuristics when converting the document tree to output formats.
relationships List<DocumentRelationship> \[\] Resolved relationships between nodes (footnote refs, citations, anchor links, etc.). Populated during derivation from the internal document representation. Empty when no relationships are detected.
nodeTypes List<String> \[\] Sorted, deduplicated list of node type names present in this document. Each value is the snake_case node_type tag of the corresponding NodeContent variant (e.g. "paragraph", "heading", "table", …). Computed from nodes via DocumentStructure.finalize_node_types. Empty until that method is called (internal construction paths call it at the end of derivation).
Methods
finalizeNodeTypes()

Compute and populate the node_types field from the current nodes.

Call this after all nodes have been added to the structure. Internal construction paths (builder, derivation) call this automatically.

Signature:

fun finalizeNodeTypes()

Example:

instance.finalizeNodeTypes()

Returns: No return value.

isEmpty()

Check if the document structure is empty.

Signature:

fun isEmpty(): Boolean

Example:

val result = instance.isEmpty()

Returns: Boolean

default()

Signature:

@JvmStatic
fun default(): DocumentStructure

Example:

val result = DocumentStructure.default()

Returns: DocumentStructure


DocumentSummary

Summary of an extracted document.

Field Type Default Description
text String Summary text (plain prose).
strategy SummaryStrategy Strategy that produced this summary.
tokenCount Int? null Approximate token count of the summary, when known.

DocxAppProperties

Application properties from docProps/app.xml for DOCX

Contains Word-specific document statistics and metadata.

Field Type Default Description
application String? null Application name (e.g., "Microsoft Office Word")
appVersion String? null Application version
template String? null Template filename
totalTime Int? null Total editing time in minutes
pages Int? null Number of pages
words Int? null Number of words
characters Int? null Number of characters (excluding spaces)
charactersWithSpaces Int? null Number of characters (including spaces)
lines Int? null Number of lines
paragraphs Int? null Number of paragraphs
company String? null Company name
docSecurity Int? null Document security level
scaleCrop Boolean? null Scale crop flag
linksUpToDate Boolean? null Links up to date flag
sharedDoc Boolean? null Shared document flag
hyperlinksChanged Boolean? null Hyperlinks changed flag

DocxMetadata

Word document metadata.

Extracted from DOCX files using shared Office Open XML metadata extraction. Integrates with office_metadata module for core/app/custom properties.

Field Type Default Description
coreProperties CoreProperties? null Core properties from docProps/core.xml (Dublin Core metadata) Contains title, creator, subject, keywords, dates, etc. Shared format across DOCX/PPTX/XLSX documents.
appProperties DocxAppProperties? null Application properties from docProps/app.xml (Word-specific statistics) Contains word count, page count, paragraph count, editing time, etc. DOCX-specific variant of Office application properties.
customProperties Map<String, Any>? {} Custom properties from docProps/custom.xml (user-defined properties) Contains key-value pairs defined by users or applications. Values can be strings, numbers, booleans, or dates.

Element

Semantic element extracted from document.

Represents a logical unit of content with semantic classification, unique identifier, and metadata for tracking origin and position.

Field Type Default Description
elementType ElementType Semantic type of this element
text String Text content of the element
metadata ElementMetadata Metadata about the element

ElementMetadata

Metadata for a semantic element.

Field Type Default Description
pageNumber Int? null Page number (1-indexed)
filename String? null Source filename or document name
coordinates BoundingBox? null Bounding box coordinates if available
elementIndex Long? null Position index in the element sequence
additional Map<String, String> Additional custom metadata

EmailAttachment

Email attachment representation.

Contains metadata and optionally the content of an email attachment.

Field Type Default Description
name String? null Attachment name (from Content-Disposition header)
filename String? null Filename of the attachment
mimeType String? null MIME type of the attachment
size Long? null Size in bytes
isImage Boolean Whether this attachment is an image
data ByteArray? null Attachment data (if extracted). Uses bytes.Bytes for cheap cloning of large buffers.

EmailConfig

Configuration for email extraction.

Field Type Default Description
msgFallbackCodepage Int? null Windows codepage number to use when an MSG file contains no codepage property. Defaults to null, which falls back to windows-1252. If an unrecognized or invalid codepage number is supplied (including 0), the behavior silently falls back to windows-1252 — the same as when the MSG file itself contains an unrecognized codepage. No error or warning is emitted. Users should verify output when supplying unusual values. Common values: - 1250: Central European (Polish, Czech, Hungarian, etc.) - 1251: Cyrillic (Russian, Ukrainian, Bulgarian, etc.) - 1252: Western European (default) - 1253: Greek - 1254: Turkish - 1255: Hebrew - 1256: Arabic - 932: Japanese (Shift-JIS) - 936: Simplified Chinese (GBK)

EmailExtractionResult

Email extraction result.

Complete representation of an extracted email message (.eml or .msg) including headers, body content, and attachments.

Field Type Default Description
subject String? null Email subject line
fromEmail String? null Sender email address
toEmails List<String> Primary recipient email addresses
ccEmails List<String> CC recipient email addresses
bccEmails List<String> BCC recipient email addresses
date String? null Email date/timestamp
messageId String? null Message-ID header value
plainText String? null Plain text version of the email body
htmlContent String? null HTML version of the email body
content String Cleaned/processed text content. Aliased as cleaned_text for back-compat.
attachments List<EmailAttachment> List of email attachments
metadata Map<String, String> Additional email headers and metadata

EmailMetadata

Email metadata extracted from .eml and .msg files.

Includes sender/recipient information, message ID, and attachment list.

Field Type Default Description
fromEmail String? null Sender's email address
fromName String? null Sender's display name
toEmails List<String> \[\] Primary recipients
ccEmails List<String> \[\] CC recipients
bccEmails List<String> \[\] BCC recipients
messageId String? null Message-ID header value
attachments List<String> \[\] List of attachment filenames

EmbeddedChanges

Changes to embedded archive children between two results.

Field Type Default Description
added List<ArchiveEntry> \[\] Children present in b but not in a (matched by path).
removed List<ArchiveEntry> \[\] Children present in a but not in b (matched by path).
changed List<EmbeddedDiff> \[\] Children present in both but with differing content (matched by path). Each entry holds the diff of the nested ExtractionResult.

EmbeddedDiff

Diff for a single embedded archive entry that appears in both results.

Field Type Default Description
path String Archive-relative path identifying this entry.
diff ExtractionDiff The recursive diff of the entry's extraction result.

EmbeddedFile

Embedded file descriptor extracted from the PDF name tree.

Field Type Default Description
name String The filename as stored in the PDF name tree.
data ByteArray Raw file bytes from the embedded stream (already decompressed by lopdf).
compressedSize Long Compressed byte count of the original stream (before decompression). Used by callers to compute the decompression ratio and detect zip-bomb-style attacks that embed a tiny compressed stream expanding to gigabytes of data.
mimeType String? null MIME type if specified in the filespec, otherwise null.

EmbeddingBackend

Trait for in-process embedding backend plugins.

Async to match the convention used by OcrBackend, DocumentExtractor, and PostProcessor. Host-language bridges (PyO3, napi-rs, Rustler, extendr, magnus, ext-php-rs, C FFI, etc.) wrap their synchronous host callables in spawn_blocking or the equivalent to satisfy the async signature.

Thread safety

Backends must be Send + Sync + 'static. They are stored in Arc<dyn EmbeddingBackend> and called concurrently from kreuzberg's chunking pipeline. If the backend's underlying model isn't thread-safe, the backend itself must serialize access internally (e.g. via Mutex<Inner>).

Contract
  • embed(texts) MUST return exactly texts.len() vectors, each of length self.dimensions(). The dispatcher in crate.embeddings.embed_texts validates this before returning to downstream consumers; a non-conforming backend surfaces as a KreuzbergError.Validation, not a panic.

  • embed may be called from any thread. Its future must be Send (enforced by async_trait when #[async_trait] is used on non-WASM targets).

  • dimensions() is called exactly once at registration, immediately after initialize() succeeds. The returned value is cached by the registry and used for all subsequent shape validation. Lazy-loading implementations can defer model loading into initialize() and report the real dimension afterwards. Later mutations of the backend's reported dimension are not observed by kreuzberg — implementations that need to change dimension must unregister and re-register.

  • shutdown() (inherited from Plugin) may be invoked concurrently with an in-flight embed() call. Implementations must tolerate this — e.g. by letting in-flight calls finish using resources held via the Arc<dyn EmbeddingBackend> reference, and only releasing shared state that isn't needed by embed.

Runtime

The synchronous embed_texts entry uses tokio.task.block_in_place to await the trait's async embed, which requires a multi-thread tokio runtime. Callers running inside a current_thread runtime (e.g. #[tokio.test] without flavor = "multi_thread", or tokio.runtime.Builder.new_current_thread()) must use embed_texts_async instead, which awaits directly without block_in_place.

Methods
dimensions()

Embedding vector dimension. Must be > 0 and must match the length of every vector returned by embed.

Signature:

fun dimensions(): Long

Example:

val result = instance.dimensions()

Returns: Long

embed()

Embed a batch of texts, returning one vector per input in order.

Errors:

Implementations should return Plugin for backend-specific failures. The dispatcher layers its own validation (length, per-vector dimension) on top.

Signature:

@Throws(Error::class)
fun embed(texts: List<String>): List<List<Float>>

Example:

val result = instance.embed([])

Parameters:

Name Type Required Description
texts List<String> Yes The texts

Returns: List<List<Float>>

Errors: Throws Error.


EmbeddingConfig

Embedding configuration for text chunks.

Configures embedding generation using ONNX models via the vendored embedding engine. Requires the embeddings feature to be enabled.

Field Type Default Description
model EmbeddingModelType EmbeddingModelType.Preset The embedding model to use (defaults to "balanced" preset if not specified)
normalize Boolean true Whether to normalize embedding vectors (recommended for cosine similarity)
batchSize Long 32 Batch size for embedding generation
showDownloadProgress Boolean false Show model download progress
cacheDir Path? null Custom cache directory for model files Defaults to ~/.cache/kreuzberg/embeddings/ if not specified. Allows full customization of model download location.
acceleration AccelerationConfig? null Hardware acceleration for the embedding ONNX model. When set, controls which execution provider (CPU, CUDA, CoreML, TensorRT) is used for inference. Defaults to null (auto-select per platform).
maxEmbedDurationSecs Long? null Maximum wall-clock duration (in seconds) for a single embed() call when using EmbeddingModelType.Plugin. Applies only to the in-process plugin path — protects against hung host-language backends (e.g. a Python callback deadlocked on the GIL, a model stuck on CUDA OOM retries, etc.). On timeout, the dispatcher returns Plugin instead of blocking forever. null disables the timeout. The default (60 seconds) is conservative for common in-process inference; increase for large batches on slow hardware.
Methods
default()

Signature:

@JvmStatic
fun default(): EmbeddingConfig

Example:

val result = EmbeddingConfig.default()

Returns: EmbeddingConfig


EmbeddingPreset

Preset configurations for common RAG use cases.

Each preset combines chunk size, overlap, and embedding model to provide an optimized configuration for specific scenarios.

All string fields are owned String for FFI compatibility — instances are safe to clone and pass across language boundaries.

Field Type Default Description
name String Short identifier for this preset (e.g. "balanced", "fast", "quality").
chunkSize Long Target chunk size in characters.
overlap Long Overlap between consecutive chunks in characters.
modelRepo String HuggingFace repository name for the model.
pooling String Pooling strategy: "cls" or "mean".
modelFile String Path to the ONNX model file within the repo.
dimensions Long Embedding vector dimension produced by this model.
description String Human-readable description of the preset's intended use case.

EnrichOptions

Which enrichment passes to run on a piece of text.

All fields default to false / empty so callers can opt in precisely.

Field Type Default Description
keywords Boolean Run keyword extraction on the input text. When true, the enrichment backend identifies the most salient terms and returns them in EnrichResult.keywords.
entities Boolean Run named-entity recognition (NER) on the input text. When true, the enrichment backend identifies named entities (persons, organisations, locations, etc.) and returns them in EnrichResult.entities.
labels List<String> \[\] Custom labels to pass through to the result without modification. These are caller-supplied tags that the enrichment pipeline propagates verbatim into EnrichResult.labels. Useful for attaching project- or document-level metadata to every enrichment result.

EnrichResult

Structured output produced by a completed enrichment pass.

Fields are populated only when the corresponding EnrichOptions flag was set.

Field Type Default Description
keywords List<String> \[\] Salient terms extracted from the text. Populated when EnrichOptions.keywords was true. The ordering is backend-defined (typically by descending relevance score).
entities List<Entity> \[\] Named entities found in the text. Populated when EnrichOptions.entities was true. Uses the shared OSS entity schema (Entity / EntityCategory) so consumers can pattern-match on entity categories without JSON gymnastics.
labels List<String> \[\] Caller-supplied labels echoed from EnrichOptions.labels.

Entity

A single named entity detected in the extracted text.

Field Type Default Description
category EntityCategory Canonical category the entity belongs to (PERSON, ORG, LOCATION, etc.).
text String Raw mention text exactly as it appeared in the source.
start Int Byte-offset span in ExtractionResult.content where the mention starts.
end Int Byte-offset span in ExtractionResult.content where the mention ends (exclusive).
confidence Float? null Backend-reported confidence in \[0.0, 1.0\]. null when the backend does not expose confidence scores.

EpubMetadata

EPUB metadata (Dublin Core extensions).

Field Type Default Description
coverage String? null Dublin Core coverage field (geographic or temporal scope).
dcFormat String? null Dublin Core format field (media type of the resource).
relation String? null Dublin Core relation field (related resource identifier).
source String? null Dublin Core source field (origin resource identifier).
dcType String? null Dublin Core type field (nature or genre of the resource).
coverImage String? null Path or identifier of the cover image within the EPUB container.

ErrorMetadata

Error metadata (for batch operations).

Field Type Default Description
errorType String Machine-readable error type identifier (e.g. "UnsupportedFormat").
message String Human-readable error description.

ExcelMetadata

Excel/spreadsheet format metadata.

Identifies the document as a spreadsheet source via the FormatMetadata.Excel discriminant. Sheet count and sheet names are stored inside this struct.

Field Type Default Description
sheetCount Int? null Number of sheets in the workbook.
sheetNames List<String>? \[\] Names of all sheets in the workbook.

ExcelSheet

Single Excel worksheet.

Represents one sheet from an Excel workbook with its content converted to Markdown format and dimensional statistics.

Field Type Default Description
name String Sheet name as it appears in Excel
markdown String Sheet content converted to Markdown tables
rowCount Long Number of rows
colCount Long Number of columns
cellCount Long Total number of non-empty cells
tableCells List<List<String>>? null Pre-extracted table cells (2D vector of cell values) Populated during markdown generation to avoid re-parsing markdown. None for empty sheets.

ExcelWorkbook

Excel workbook representation.

Contains all sheets from an Excel file (.xlsx, .xls, etc.) with extracted content and metadata.

Field Type Default Description
sheets List<ExcelSheet> All sheets in the workbook
metadata Map<String, String> Workbook-level metadata (author, creation date, etc.)
revisions List<DocumentRevision>? /* serde(default) */ Collaborative-edit revision headers from xl/revisions/revisionHeaders.xml. Populated for legacy shared-workbook .xlsx files that contain the xl/revisions/ directory. Each <header> element maps to one DocumentRevision { kind: FormatChange } carrying the header's guid (→ revision_id), userName (→ author), and dateTime (→ timestamp). anchor and delta are null/empty for v1 (per-cell log parsing is a follow-up). null when xl/revisions/revisionHeaders.xml is absent.

ExtractedImage

Extracted image from a document.

Contains raw image data, metadata, and optional nested OCR results. Raw bytes allow cross-language compatibility - users can convert to PIL.Image (Python), Sharp (Node.js), or other formats as needed.

Field Type Default Description
data ByteArray Raw image data (PNG, JPEG, WebP, etc. bytes). Uses bytes.Bytes for cheap cloning of large buffers.
format String Image format (e.g., "jpeg", "png", "webp") Uses Cow<'static, str> to avoid allocation for static literals.
imageIndex Int Zero-indexed position of this image in the document/page
pageNumber Int? null Page/slide number where image was found (1-indexed)
width Int? null Image width in pixels
height Int? null Image height in pixels
colorspace String? null Colorspace information (e.g., "RGB", "CMYK", "Gray")
bitsPerComponent Int? null Bits per color component (e.g., 8, 16)
isMask Boolean Whether this image is a mask image
description String? null Optional description of the image
ocrResult ExtractionResult? null Nested OCR extraction result (if image was OCRed) When OCR is performed on this image, the result is embedded here rather than in a separate collection, making the relationship explicit.
boundingBox BoundingBox? null Bounding box of the image on the page (PDF coordinates: x0=left, y0=bottom, x1=right, y1=top). Only populated for PDF-extracted images when position data is available from the PDF extractor.
sourcePath String? null Original source path of the image within the document archive (e.g., "media/image1.png" in DOCX). Used for rendering image references when the binary data is not extracted.
imageKind ImageKind? null Heuristic classification of what this image likely depicts. null if classification was disabled or inconclusive.
kindConfidence Float? null Confidence score for image_kind, in the range 0.0 to 1.0.
clusterId Int? null Identifier shared across images that form a single logical figure (e.g. all raster tiles of one technical drawing). null for singletons.
caption String? null VLM-generated caption describing the image, when captioning is configured. Populated by the captioning post-processor (crates/kreuzberg/src/plugins/processor/builtin/captioning.rs), which routes each image through crate.llm.region_extractor.extract_region_with_vlm in caption mode. null when captioning is disabled or the VLM declined to caption.
qrCodes List<QrCode>? \[\] QR codes decoded from this image, when QR detection is enabled. Populated by the QR post-processor (crates/kreuzberg/src/extractors/qr.rs) via the pure-Rust rqrr decoder. null when QR detection is disabled; an empty Some(\[\]) when detection ran but found nothing.
dataBase64 String? null Base64-encoded copy of data; populated when ImageExtractionConfig.include_data_base64 is true. Omitted from JSON by default; use instead of data in JSON-only clients.

ExtractedUri

A URI extracted from a document.

Represents any link, reference, or resource pointer found during extraction. The kind field classifies the URI semantically, while label carries optional human-readable display text.

Field Type Default Description
url String The URL or path string.
label String? null Optional display text / label for the link.
page Int? null Optional page number where the URI was found (1-indexed).
kind UriKind Semantic classification of the URI.

ExtractionConfidence

Combined confidence on [0, 1].

When OCR did not run, the ocr_aggregate weight folds into text_coverage so the weighted sum still totals 1.0.

Field Type Default Description
textCoverage Float Fraction of pages with a usable text layer.
ocrAggregate Float? null Mean OCR per-element recognition confidence when OCR ran; null when it did not.
schemaCompliance SchemaCompliance Whether the merged output validates against the preset schema.
combined Float Weighted blend in \[0, 1\]. The value compared against the fallback threshold.

ExtractionConfig

Main extraction configuration.

This struct contains all configuration options for the extraction process. It can be loaded from TOML, YAML, or JSON files, or created programmatically.

Field Type Default Description
useCache Boolean true Enable caching of extraction results
enableQualityProcessing Boolean true Enable quality post-processing
ocr OcrConfig? null OCR configuration (None = OCR disabled)
forceOcr Boolean false Force OCR even for searchable PDFs
forceOcrPages List<Int>? null Force OCR on specific pages only (1-indexed page numbers, must be >= 1). When set, only the listed pages are OCR'd regardless of text layer quality. Unlisted pages use native text extraction. Ignored when force_ocr is true. Only applies to PDF documents. Duplicates are automatically deduplicated. An ocr config is recommended for backend/language selection; defaults are used if absent.
disableOcr Boolean false Disable OCR entirely, even for images. When true, OCR is skipped for all document types. Images return metadata only (dimensions, format, EXIF) without text extraction. PDFs use only native text extraction without OCR fallback. Cannot be true simultaneously with force_ocr. Added in v4.7.0.
chunking ChunkingConfig? null Text chunking configuration (None = chunking disabled)
contentFilter ContentFilterConfig? null Content filtering configuration (None = use extractor defaults). Controls whether document "furniture" (headers, footers, watermarks, repeating text) is included in or stripped from extraction results. See ContentFilterConfig for per-field documentation.
images ImageExtractionConfig? null Image extraction configuration (None = no image extraction)
pdfOptions PdfConfig? null PDF-specific options (None = use defaults)
tokenReduction TokenReductionOptions? null Token reduction configuration (None = no token reduction)
languageDetection LanguageDetectionConfig? null Language detection configuration (None = no language detection)
pages PageConfig? null Page extraction configuration (None = no page tracking)
keywords KeywordConfig? null Keyword extraction configuration (None = no keyword extraction)
postprocessor PostProcessorConfig? null Post-processor configuration (None = use defaults)
htmlOutput HtmlOutputConfig? null Styled HTML output configuration. When set alongside output_format = OutputFormat.Html, the extraction pipeline uses StyledHtmlRenderer which emits stable kb-* CSS class hooks on every structural element and optionally embeds theme CSS or user-supplied CSS in a <style> block. When null, the existing plain comrak-based HTML renderer is used.
extractionTimeoutSecs Long? null Default per-file timeout in seconds for batch extraction. When set, each file in a batch will be canceled after this duration unless overridden by FileExtractionConfig.timeout_secs. Defaults to Some(60) to prevent pathological files (e.g. deeply nested archives, documents with millions of cells) from running indefinitely and exhausting caller resources. Set to null to disable the timeout for trusted input or long-running workloads.
maxConcurrentExtractions Long? null Maximum concurrent extractions in batch operations (None = (num_cpus × 1.5).ceil()). Limits parallelism to prevent resource exhaustion when processing large batches. Defaults to (num_cpus × 1.5).ceil() when not set.
resultFormat ResultFormat ResultFormat.Unified Result structure format Controls whether results are returned in unified format (default) with all content in the content field, or element-based format with semantic elements (for Unstructured-compatible output).
securityLimits SecurityLimits? null Security limits for archive extraction. Controls maximum archive size, compression ratio, file count, and other security thresholds to prevent decompression bomb attacks. Also caps nesting depth, iteration count, entity / token length, total content size, and table cell count for every extraction path that ingests user-controlled bytes. When null, default limits are used.
maxEmbeddedFileBytes Long? null Maximum uncompressed size in bytes for a single embedded file before recursive extraction is attempted (default: 50 MiB). Applies to embedded objects inside OOXML containers (DOCX, PPTX) and to email attachments processed via recursive extraction. Files that exceed this limit are skipped with a ProcessingWarning rather than passed to the extraction pipeline, preventing a single oversized embedded object from consuming unbounded memory or time. Set to null to disable the per-embedded-file cap (falls back to security_limits.max_archive_size as the only guard).
outputFormat OutputFormat OutputFormat.Plain Content text format (default: Plain). Controls the format of the extracted content: - Plain: Raw extracted text (default) - Markdown: Markdown formatted output - Djot: Djot markup format (requires djot feature) - Html: HTML formatted output When set to a structured format, extraction results will include formatted output. The formatted_content field may be populated when format conversion is applied.
layout LayoutDetectionConfig? null Layout detection configuration (None = layout detection disabled). When set, PDF pages and images are analyzed for document structure (headings, code, formulas, tables, figures, etc.) using RT-DETR models via ONNX Runtime. For PDFs, layout hints override paragraph classification in the markdown pipeline. For images, per-region OCR is performed with markdown formatting based on detected layout classes. Requires the layout-detection feature to run inference; the field is present whenever the layout-types feature is active (which includes layout-detection as well as the no-ORT target groups).
transcription TranscriptionConfig? null Transcription (speech-to-text) configuration for audio/video files. When set and enabled, files with audio/video MIME types (mp3, mp4, m4a, wav, webm, etc.) are routed to the Whisper-based transcription pipeline. The actual heavy dependencies are only active under the transcription feature; the field is visible under transcription-types (including on WASM and Android targets that use the no-ORT preset). Default: null (transcription disabled). This is an additive, non-breaking change.
useLayoutForMarkdown Boolean false Run layout detection on the non-OCR PDF markdown path. When true and layout is Some(_), layout regions inform heading, table, list, and figure detection in the structure pipeline that would otherwise rely on font-clustering heuristics alone. Significantly improves SF1 (structural F1) at the cost of inference latency (~150-300ms/page CPU, ~20-50ms/page GPU). Default: false. Requires the layout-detection feature.
includeDocumentStructure Boolean false Enable structured document tree output. When true, populates the document field on ExtractionResult with a hierarchical DocumentStructure containing heading-driven section nesting, table grids, content layer classification, and inline annotations. Independent of result_format — can be combined with Unified or ElementBased.
acceleration AccelerationConfig? null Hardware acceleration configuration for ONNX Runtime models. Controls execution provider selection for layout detection and embedding models. When null, uses platform defaults (CoreML on macOS, CUDA on Linux, CPU on Windows).
cacheNamespace String? null Cache namespace for tenant isolation. When set, cache entries are stored under {cache_dir}/{namespace}/. Must be alphanumeric, hyphens, or underscores only (max 64 chars). Different namespaces have isolated cache spaces on the same filesystem.
cacheTtlSecs Long? null Per-request cache TTL in seconds. Overrides the global max_age_days for this specific extraction. When 0, caching is completely skipped (no read or write). When null, the global TTL applies.
email EmailConfig? null Email extraction configuration (None = use defaults). Currently supports configuring the fallback codepage for MSG files that do not specify one. See EmailConfig for details.
maxArchiveDepth Long Maximum recursion depth for archive extraction (default: 3). Set to 0 to disable recursive extraction (legacy behavior).
treeSitter TreeSitterConfig? null Tree-sitter language pack configuration (None = tree-sitter disabled). When set, enables code file extraction using tree-sitter parsers. Controls grammar download behavior and code analysis options.
structuredExtraction StructuredExtractionConfig? null Structured extraction via LLM (None = disabled). When set, the extracted document content is sent to an LLM with the provided JSON schema. The structured response is stored in ExtractionResult.structured_output.
ner NerConfig? null Named-entity recognition configuration. When set, the NER post-processor runs at the Middle stage and populates ExtractionResult.entities.
redaction RedactionConfig? null Redaction / anonymisation configuration. When set, the redaction post-processor runs at the Late stage and rewrites every textual field in ExtractionResult, emitting an audit trail in ExtractionResult.redaction_report.
summarization SummarizationConfig? null Summarisation configuration. When set, the summarisation post-processor runs at the Middle stage and populates ExtractionResult.summary.
translation TranslationConfig? null Translation configuration. When set, the translation post-processor runs at the Middle stage and populates ExtractionResult.translation.
pageClassification PageClassificationConfig? null Per-page classification configuration. When set, the classification post-processor runs at the Middle stage and populates ExtractionResult.page_classifications.
captioning CaptioningConfig? null VLM captioning configuration for extracted images. When set, the captioning post-processor runs at the Middle stage and writes a caption into each ExtractedImage.caption.
qrCodes Boolean? null Enable QR-code detection in extracted images. When true, the QR post-processor runs at the Middle stage and populates ExtractedImage.qr_codes.
Methods
default()

Signature:

@JvmStatic
fun default(): ExtractionConfig

Example:

val result = ExtractionConfig.default()

Returns: ExtractionConfig

needsImageData()

Check if image processing is needed by examining OCR and image extraction settings.

Returns true if either OCR is enabled or image extraction is configured, indicating that image decompression and processing should occur. Returns false if both are disabled, allowing optimization to skip unnecessary image decompression for text-only extraction workflows.

Optimization Impact

For text-only extractions (no OCR, no image extraction), skipping image decompression can improve CPU utilization by 5-10% by avoiding wasteful image I/O and processing when results won't be used. Returns true when image binary data should be extracted.

True when config.images.extract_images is set or when captioning is configured — captioning requires image bytes regardless of whether the caller also requested images extraction.

Signature:

fun needsImageData(): Boolean

Example:

val result = instance.needsImageData()

Returns: Boolean

needsImageProcessing()

Returns true when any image processing is needed during extraction.

Optimization Impact

For text-only extractions (no OCR, no image extraction, no captioning), skipping image decompression can improve CPU utilization by 5-10% by avoiding wasteful image I/O and processing when results won't be used.

Signature:

fun needsImageProcessing(): Boolean

Example:

val result = instance.needsImageProcessing()

Returns: Boolean


ExtractionDiff

The complete diff between two ExtractionResult values.

Field Type Default Description
contentDiff List<DiffHunk> \[\] Unified-diff hunks for the content field. Empty when the content is identical.
tablesAdded List<Table> \[\] Tables present in b but not in a (by index position, excess right-side tables).
tablesRemoved List<Table> \[\] Tables present in a but not in b (by index position, excess left-side tables).
tablesChanged List<TableDiff> \[\] Cell-level changes for table pairs that share the same index and dimensions.
metadataChanged Any Metadata difference, encoded as a JSON object with three top-level keys: added (keys present in b but not a), removed (keys present in a but not b), and changed (keys whose values differ — each entry is { "from": <value-in-a>, "to": <value-in-b> }). This is NOT RFC 6902 JSON Patch — we deliberately chose a flatter shape to avoid pulling in a json-patch crate. If you need RFC 6902 semantics (with JSON Pointer paths) feed a.metadata and b.metadata to your preferred json-patch impl directly.
embeddedChanges EmbeddedChanges Changes to embedded archive children.

ExtractionResult

General extraction result used by the core extraction API.

This is the main result type returned by all extraction functions.

Field Type Default Description
content String Plain-text representation of the extracted document content.
mimeType String MIME type of the source document (e.g. "application/pdf").
metadata Metadata Document-level metadata (author, title, dates, format-specific fields).
extractionMethod ExtractionMethod? null Extraction strategy used to produce the returned text. Populated when the extractor can reliably distinguish native text extraction, OCR-only extraction, or mixed native/OCR output.
tables List<Table> \[\] Tables extracted from the document, each with structured cell data.
detectedLanguages List<String>? \[\] ISO 639-1 language codes detected in the document content.
chunks List<Chunk>? \[\] Text chunks when chunking is enabled. When chunking configuration is provided, the content is split into overlapping chunks for efficient processing. Each chunk contains the text, optional embeddings (if enabled), and metadata about its position.
images List<ExtractedImage>? \[\] Extracted images from the document. When image extraction is enabled via ImageExtractionConfig, this field contains all images found in the document with their raw data and metadata. Each image may optionally contain a nested ocr_result if OCR was performed.
pages List<PageContent>? \[\] Per-page content when page extraction is enabled. When page extraction is configured, the document is split into per-page content with tables and images mapped to their respective pages.
elements List<Element>? \[\] Semantic elements when element-based result format is enabled. When result_format is set to ElementBased, this field contains semantic elements with type classification, unique identifiers, and metadata for Unstructured-compatible element-based processing.
djotContent DjotContent? null Rich Djot content structure (when extracting Djot documents). When extracting Djot documents with structured extraction enabled, this field contains the full semantic structure including: - Block-level elements with nesting - Inline formatting with attributes - Links, images, footnotes - Math expressions - Complete attribute information The content field still contains plain text for backward compatibility. Always null for non-Djot documents.
ocrElements List<OcrElement>? \[\] OCR elements with full spatial and confidence metadata. When OCR is performed with element extraction enabled, this field contains the structured representation of detected text including: - Bounding geometry (rectangles or quadrilaterals) - Confidence scores (detection and recognition) - Rotation information - Hierarchical relationships (Tesseract only) This field preserves all metadata that would otherwise be lost when converting to plain text or markdown output formats. Only populated when OcrElementConfig.include_elements is true.
document DocumentStructure? null Structured document tree (when document structure extraction is enabled). When include_document_structure is true in ExtractionConfig, this field contains the full hierarchical representation of the document including: - Heading-driven section nesting - Table grids with cell-level metadata - Content layer classification (body, header, footer, footnote) - Inline text annotations (formatting, links) - Bounding boxes and page numbers Independent of result_format — can be combined with Unified or ElementBased.
extractedKeywords List<Keyword>? \[\] Extracted keywords when keyword extraction is enabled. When keyword extraction (RAKE or YAKE) is configured, this field contains the extracted keywords with scores, algorithm info, and position data. Previously stored in metadata.additional\["keywords"\].
qualityScore Double? null Document quality score from quality analysis. A value between 0.0 and 1.0 indicating the overall text quality. Previously stored in metadata.additional\["quality_score"\].
processingWarnings List<ProcessingWarning> \[\] Non-fatal warnings collected during processing pipeline stages. Captures errors from optional pipeline features (embedding, chunking, language detection, output formatting) that don't prevent extraction but may indicate degraded results. Previously stored as individual keys in metadata.additional.
annotations List<PdfAnnotation>? \[\] PDF annotations extracted from the document. When annotation extraction is enabled via PdfConfig.extract_annotations, this field contains text notes, highlights, links, stamps, and other annotations found in PDF documents.
children List<ArchiveEntry>? \[\] Nested extraction results from archive contents. When extracting archives, each processable file inside produces its own full extraction result. Set to null for non-archive formats. Use max_archive_depth in config to control recursion depth.
uris List<ExtractedUri>? \[\] URIs/links discovered during document extraction. Contains hyperlinks, image references, citations, email addresses, and other URI-like references found in the document. Always extracted when present in the source document.
revisions List<DocumentRevision>? \[\] Tracked changes embedded in the source document. Populated by per-format extractors that understand change-tracking metadata (DOCX w:ins/w:del/w:rPrChange, ODT text:change-*, …). Every extractor defaults to null until its format-specific implementation is added. Extractors that do populate this field follow the "accepted-changes" convention: inserted text is present in content, deleted text is absent — the revision list is the separate audit trail.
structuredOutput Any? null Structured extraction output from LLM-based JSON schema extraction. When structured_extraction is configured in ExtractionConfig, the extracted document content is sent to a VLM with the provided JSON schema. The response is parsed and stored here as a JSON value matching the schema.
codeIntelligence Any? null Code intelligence results from tree-sitter analysis. Populated when extracting source code files with the tree-sitter feature. Contains metrics, structural analysis, imports/exports, comments, docstrings, symbols, diagnostics, and optionally chunked code segments. Stored as an opaque JSON value so that all language bindings (Go, Java, C#, …) can deserialize it as a raw JSON object rather than a typed struct. The underlying type is tree_sitter_language_pack.ProcessResult.
llmUsage List<LlmUsage>? \[\] LLM token usage and cost data for all LLM calls made during this extraction. Contains one entry per LLM call. Multiple entries are produced when VLM OCR, structured extraction, or LLM embeddings run during the same extraction. null when no LLM was used.
entities List<Entity>? \[\] Named entities detected in content by the NER post-processor. null when no NER backend is configured. Populated by the gline-rs ONNX backend or the LLM-driven backend (see crates/kreuzberg/src/text/ner/).
summary DocumentSummary? null Summary of content produced by the summarisation post-processor. null when summarisation is not configured. Populated by the TextRank extractive backend (deterministic, no external service) or by the liter-llm-driven abstractive backend.
extractionConfidence ExtractionConfidence? null Confidence score computed by the heuristics pipeline. Populated when the heuristics feature is enabled and confidence scoring has been performed. Combines text-coverage, OCR aggregate confidence, and schema-compliance into a single \[0, 1\] value. null when confidence scoring is not configured or the feature is absent.
translation Translation? null Translation of content produced by the translation post-processor. null when translation is not configured.
pageClassifications List<PageClassification>? \[\] Per-page classifications produced by the page-classification post-processor. null when classification is not configured.
redactionReport RedactionReport? null Audit report of redactions applied by the redaction post-processor. The redaction processor rewrites content, formatted_content, every chunk's text, and the textual fields of entities / summary / translation / page_classifications in place. This report describes what was found and how it was replaced. null when redaction is not configured.
formulas List<Formula> \[\] Mathematical formulas recognized in the document. Populated by the layout-guided formula pipeline when the layout-detection feature is enabled and the document contains regions classified as formulas. Empty otherwise.
formFields List<PdfFormField> \[\] Form fields extracted from a PDF's AcroForm or XFA structure. Populated by the PDF extractor when PdfConfig.extract_form_fields is enabled (default) and the document is a fillable form. Empty otherwise.
formattedContent String? null Pre-rendered content in the requested output format. Populated during derive_extraction_result before tree derivation consumes element data. apply_output_format swaps this into content at the end of the pipeline, after post-processors have operated on plain text.
Methods
fromOcr()

Convert from an OCR result.

Signature:

@JvmStatic
fun fromOcr(ocr: OcrExtractionResult): ExtractionResult

Example:

val result = ExtractionResult.fromOcr(OcrExtractionResult())

Parameters:

Name Type Required Description
ocr OcrExtractionResult Yes The ocr extraction result

Returns: ExtractionResult


FictionBookMetadata

FictionBook (FB2) metadata.

Field Type Default Description
genres List<String> \[\] Genre tags as declared in the FB2 <genre> elements.
sequences List<String> \[\] Book series (sequence) names, if any.
annotation String? null Short annotation / summary from the FB2 <annotation> element.

FileExtractionConfig

Per-file extraction configuration overrides for batch processing.

All fields are Option<T>null means "use the batch-level default." This type is used with batch_extract_files and batch_extract_bytes to allow heterogeneous extraction settings within a single batch.

Excluded Fields

The following ExtractionConfig fields are batch-level only and cannot be overridden per file:

  • max_concurrent_extractions — controls batch parallelism
  • use_cache — global caching policy
  • acceleration — shared ONNX execution provider
  • security_limits — global archive security policy
Field Type Default Description
enableQualityProcessing Boolean? null Override quality post-processing for this file.
ocr OcrConfig? null Override OCR configuration for this file (None in the Option = use batch default).
forceOcr Boolean? null Override force OCR for this file.
forceOcrPages List<Int>? \[\] Override force OCR pages for this file (1-indexed page numbers).
disableOcr Boolean? null Override disable OCR for this file.
chunking ChunkingConfig? null Override chunking configuration for this file.
contentFilter ContentFilterConfig? null Override content filtering configuration for this file.
images ImageExtractionConfig? null Override image extraction configuration for this file.
pdfOptions PdfConfig? null Override PDF options for this file.
tokenReduction TokenReductionOptions? null Override token reduction for this file.
languageDetection LanguageDetectionConfig? null Override language detection for this file.
pages PageConfig? null Override page extraction for this file.
keywords KeywordConfig? null Override keyword extraction for this file.
postprocessor PostProcessorConfig? null Override post-processor for this file.
resultFormat ResultFormat? null Override result format for this file.
outputFormat OutputFormat? null Override output content format for this file.
includeDocumentStructure Boolean? null Override document structure output for this file.
layout LayoutDetectionConfig? null Override layout detection for this file.
transcription TranscriptionConfig? null Transcription configuration (see ExtractionConfig for docs).
timeoutSecs Long? null Override per-file extraction timeout in seconds. When set, the extraction for this file will be canceled after the specified duration. A timed-out file produces an error result without affecting other files in the batch.
treeSitter TreeSitterConfig? null Override tree-sitter configuration for this file.
structuredExtraction StructuredExtractionConfig? null Override structured extraction configuration for this file. When set, enables LLM-based structured extraction with a JSON schema for this specific file. The extracted content is sent to a VLM/LLM and the response is parsed according to the provided schema.

Footnote

Footnote in Djot.

Field Type Default Description
label String Footnote label
content List<FormattedBlock> Footnote content blocks

FootnoteAnchor

A footnote anchor reference in markdown text.

Represents a [^label] use-site (not a definition).

Field Type Default Description
label String The label of the footnote reference (e.g., "1" in \[^1\]).
offset Long Byte offset of the anchor in the markdown text.

FootnoteConfig

Configuration for markdown footnote and citation parsing.

Field Type Default Description
parseCitations Boolean true Whether to parse the structured citation block (default: true). When enabled, the parser will look for and extract citations from the block after --- + <!-- citations ... -->.
Methods
default()

Signature:

@JvmStatic
fun default(): FootnoteConfig

Example:

val result = FootnoteConfig.default()

Returns: FootnoteConfig

withParseCitations()

Set whether to parse the citation block.

Signature:

fun withParseCitations(enabled: Boolean): FootnoteConfig

Example:

val result = instance.withParseCitations(true)

Parameters:

Name Type Required Description
enabled Boolean Yes The enabled

Returns: FootnoteConfig


FootnoteDefinition

A footnote definition from markdown text.

Represents [^label]: content declarations (including multi-line continuations).

Field Type Default Description
label String The label of the footnote (e.g., "1" in \[^1\]: ...).
content String The full content of the footnote definition.
offset Long Byte offset of the definition line in the markdown text.

FormattedBlock

Block-level element in a Djot document.

Represents structural elements like headings, paragraphs, lists, code blocks, etc.

Field Type Default Description
blockType BlockType Type of block element
level Long? null Heading level (1-6) for headings, or nesting level for lists
inlineContent List<InlineElement> Inline content within the block
language String? null Language identifier for code blocks
code String? null Raw code content for code blocks
children List<FormattedBlock> /* serde(default) */ Nested blocks for containers (blockquotes, list items, divs)

Formula

A mathematical formula detected and recognized in a document.

Populated by the layout-guided formula pipeline: regions classified as LayoutClass.Formula are routed to the formula OCR task, which returns the LaTeX source for the region. The field is always present on ExtractionResult but only populated when the layout-detection feature is active and the document contains formula regions.

Field Type Default Description
latex String LaTeX source of the recognized formula, without surrounding $$ delimiters. This field contains the raw LaTeX code as produced by the OCR backend. To render the formula in Markdown or other formats, wrap with $$..$$ delimiters as needed.
bbox BoundingBox Bounding box of the formula region on its page, in rendered-image pixel coordinates. The coordinates are in the space of the OCR-rendered page image at the OCR DPI (typically 300 DPI). These coordinates are NOT comparable to bounding boxes from native PDF text extraction, which use PDF point coordinates.
page Int 1-indexed page number the formula appears on in the document. This is set by the extraction pipeline based on which page the formula was found on.

GridCell

Individual grid cell with position and span metadata.

Field Type Default Description
content String Cell text content.
row Int Zero-indexed row position.
col Int Zero-indexed column position.
rowSpan Int serde(default = "default_span") Number of rows this cell spans.
colSpan Int serde(default = "default_span") Number of columns this cell spans.
isHeader Boolean /* serde(default) */ Whether this is a header cell.
bbox BoundingBox? null Bounding box for this cell (if available).

HeaderMetadata

Header/heading element metadata.

Field Type Default Description
level Byte Header level: 1 (h1) through 6 (h6)
text String Normalized text content of the header
id String? null HTML id attribute if present
depth Int Document tree depth at the header element
htmlOffset Int Byte offset in original HTML document

HeadingContext

Heading context for a chunk within a Markdown document.

Contains the heading hierarchy from document root to this chunk's section.

Field Type Default Description
headings List<HeadingLevel> The heading hierarchy from document root to this chunk's section. Index 0 is the outermost (h1), last element is the most specific.

HeadingLevel

A single heading in the hierarchy.

Field Type Default Description
level Byte Heading depth (1 = h1, 2 = h2, etc.)
text String The text content of the heading.

HeuristicsConfig

Configuration for document chunking and analysis heuristics.

Every threshold is a public field so callers can override any subset via struct-update syntax: HeuristicsConfig { text_layer_threshold: 0.5, ..the default constructor }.

Field Type Default Description
enablePdfTextHeuristics Boolean true Enable PDF text-layer detection heuristics. When true, PDFs with a substantial text layer will skip chunking. Default: true.
textLayerThreshold Float 0.7 Minimum fraction of pages that must have text to skip chunking. Range 0.0..=1.0. Default: 0.7 (70 % of pages).
fileSizeThresholdBytes Long 10485760 File size threshold in bytes for considering chunking. Files smaller than this are processed without chunking. Default: 10 MiB (10 × 1 024 × 1 024).
pageCountThreshold Int 50 Page count threshold for considering chunking. Documents with fewer pages are processed without chunking. Default: 50.
targetPagesPerChunk Int 10 Target number of pages per chunk for optimal parallel processing. Default: 10.
maxPagesPerChunk Int 25 Hard cap on pages per chunk. No chunk will exceed this limit. Must be ≥ target_pages_per_chunk. Default: 25.
diskProcessingThresholdBytes Long 52428800 File size threshold for disk-based processing. Files larger than this are buffered to disk to prevent OOM. Default: 50 MiB (50 × 1 024 × 1 024).
minCharsPerPage Int 50 Minimum characters per page to consider a page as having text. Default: 50.
maxXlsxSheetCount Int 200 Maximum sheet count allowed in an XLSX workbook. Workbooks beyond this are rejected pre-extraction to avoid OOM / abusive billing inflation. Default: 200.
maxXlsxWorkbookCells Long 5000000 Maximum cell count (sheets × rows × columns approximation) in an XLSX workbook. Default: 5 000 000 (≈ 200 sheets × 25 k cells).
maxPptxEmbeddedCount Int 50 Maximum number of OLE-embedded objects extractable from a single PPTX or DOCX. Protects against zip-bomb-style nested-document abuse. Default: 50.
Methods
default()

Signature:

@JvmStatic
fun default(): HeuristicsConfig

Example:

val result = HeuristicsConfig.default()

Returns: HeuristicsConfig

validate()

Validate the configuration.

Errors:

Returns HeuristicsError.ConfigError when:

  • target_pages_per_chunk is 0
  • max_pages_per_chunk < target_pages_per_chunk
  • file_size_threshold_bytes is 0

Signature:

@Throws(Error::class)
fun validate()

Example:

instance.validate()

Returns: No return value.

Errors: Throws Error.


HierarchicalBlock

A text block with hierarchy level assignment.

Represents a block of text with semantic heading information extracted from font size clustering and hierarchical analysis.

Field Type Default Description
text String The text content of this block
fontSize Float The font size of the text in this block
level String The hierarchy level of this block (H1-H6 or Body) Levels correspond to HTML heading tags: - "h1": Top-level heading - "h2": Secondary heading - "h3": Tertiary heading - "h4": Quaternary heading - "h5": Quinary heading - "h6": Senary heading - "body": Body text (no heading level)

HierarchyConfig

Hierarchy extraction configuration for PDF text structure analysis.

Enables extraction of document hierarchy levels (H1-H6) based on font size clustering and semantic analysis. When enabled, hierarchical blocks are included in page content.

Field Type Default Description
enabled Boolean true Enable hierarchy extraction
kClusters Long 3 Number of font size clusters to use for hierarchy levels (1-7) Default: 6, which provides H1-H6 heading levels with body text. Larger values create more fine-grained hierarchy levels.
includeBbox Boolean true Include bounding box information in hierarchy blocks
ocrCoverageThreshold Float? null OCR coverage threshold for smart OCR triggering (0.0-1.0) Determines when OCR should be triggered based on text block coverage. OCR is triggered when text blocks cover less than this fraction of the page. Default: 0.5 (trigger OCR if less than 50% of page has text)
Methods
default()

Signature:

@JvmStatic
fun default(): HierarchyConfig

Example:

val result = HierarchyConfig.default()

Returns: HierarchyConfig


HtmlMetadata

HTML metadata extracted from HTML documents.

Includes document-level metadata, Open Graph data, Twitter Card metadata, and extracted structural elements (headers, links, images, structured data).

Field Type Default Description
title String? null Document title from <title> tag
description String? null Document description from <meta name="description"> tag
keywords List<String> \[\] Document keywords from <meta name="keywords"> tag, split on commas
author String? null Document author from <meta name="author"> tag
canonicalUrl String? null Canonical URL from <link rel="canonical"> tag
baseHref String? null Base URL from <base href=""> tag for resolving relative URLs
language String? null Document language from lang attribute
textDirection TextDirection? null Document text direction from dir attribute
openGraph Map<String, String> {} Open Graph metadata (og:* properties) for social media Keys like "title", "description", "image", "url", etc.
twitterCard Map<String, String> {} Twitter Card metadata (twitter:* properties) Keys like "card", "site", "creator", "title", "description", "image", etc.
metaTags Map<String, String> {} Additional meta tags not covered by specific fields Keys are meta name/property attributes, values are content
headers List<HeaderMetadata> \[\] Extracted header elements with hierarchy
links List<LinkMetadata> \[\] Extracted hyperlinks with type classification
images List<ImageMetadataType> \[\] Extracted images with source and dimensions
structuredData List<StructuredData> \[\] Extracted structured data blocks

HtmlOutputConfig

Configuration for styled HTML output.

When set on html_output alongside output_format = OutputFormat.Html, the pipeline builds a StyledHtmlRenderer instead of the plain comrak-based renderer.

Field Type Default Description
css String? null Inline CSS string injected into the output after the theme stylesheet. Concatenated after css_file content when both are set.
cssFile Path? null Path to a CSS file loaded once at renderer construction time. Concatenated before css when both are set.
theme HtmlTheme HtmlTheme.Unstyled Built-in colour/typography theme. Default: HtmlTheme.Unstyled.
classPrefix String CSS class prefix applied to every emitted class name. Default: "kb-". Change this if your host application already uses classes that start with kb-.
embedCss Boolean true When true (default), write the resolved CSS into a <style> block immediately after the opening <div class="{prefix}doc">. Set to false to emit only the structural markup and wire up your own stylesheet targeting the kb-* class names.
Methods
default()

Signature:

@JvmStatic
fun default(): HtmlOutputConfig

Example:

val result = HtmlOutputConfig.default()

Returns: HtmlOutputConfig


ImageExtractionConfig

Image extraction configuration.

Field Type Default Description
extractImages Boolean true Extract images from documents
targetDpi Int 300 Target DPI for image normalization
maxImageDimension Int 4096 Maximum dimension for images (width or height)
injectPlaceholders Boolean true Whether to inject image reference placeholders into markdown output. When true (default), image references like !\[Image 1\](embedded:p1_i0) are appended to the markdown. Set to false to extract images as data without polluting the markdown output.
autoAdjustDpi Boolean true Automatically adjust DPI based on image content
minDpi Int 72 Minimum DPI threshold
maxDpi Int 600 Maximum DPI threshold
maxImagesPerPage Int? null Maximum number of image objects to extract per PDF page. Some PDFs (e.g. technical diagrams stored as thousands of raster fragments) can trigger extremely long or indefinite extraction times when every image object on a dense page is decoded individually via the PDF extractor. Setting this limit causes kreuzberg to stop collecting individual images once the count per page reaches the cap and emit a warning instead. null (default) means no limit — all images are extracted.
classify Boolean false When true, extracted images are classified by kind and grouped into clusters where they appear to belong to one figure. Defaults to false — opt in explicitly to avoid unexpected ML overhead.
includePageRasters Boolean false When true, full-page renders produced during OCR preprocessing are captured and returned as ImageKind.PageRaster entries in ExtractionResult.images. PDF + OCR only. No rasters are captured for non-PDF inputs or when the document-level OCR bypass is active (whole-document backend). When OCR is enabled and this flag is set but the active backend skips per-page rendering, a ProcessingWarning is emitted in ExtractionResult.processing_warnings. Defaults to false. Enable when downstream consumers need page thumbnails (e.g. citation previews, visual grounding).
runOcrOnImages Boolean true Run OCR on extracted images and include the recognized text in the document content. When true (default) and ExtractionConfig.ocr is configured, extracted images are processed with the configured OCR backend. Set to false to extract images without OCR processing, even when OCR is enabled.
ocrTextOnly Boolean false When true, image OCR results are rendered as plain text without the !\[...\](...) markdown placeholder. Only takes effect when run_ocr_on_images is also true.
appendOcrText Boolean false When true and ocr_text_only is false, append the OCR text after the image placeholder in the rendered output.
outputFormat ImageOutputFormat ImageOutputFormat.Native Target format for re-encoding extracted images. When set to anything other than Native, each extracted image is re-encoded to the requested format before being returned. This lets callers receive uniform output without duplicating encode logic downstream. Defaults to Native — no re-encode pass is performed and ExtractedImage.format reflects the source extractor's output.
svg SvgOptions SVG-specific knobs for the image-encode pipeline. Controls sanitization and rasterization DPI when the source or output format is SVG. Only available when the svg feature is active.
includeDataBase64 Boolean false When true, populate ExtractedImage.data_base64 with a Base64-encoded copy of the raw image bytes. Useful for JSON-only clients that cannot efficiently parse the default integer-array serialization of data. Defaults to false; enabling it doubles the in-memory image representation for the duration of the response.
Methods
default()

Signature:

@JvmStatic
fun default(): ImageExtractionConfig

Example:

val result = ImageExtractionConfig.default()

Returns: ImageExtractionConfig


ImageMetadata

Image metadata extracted from image files.

Includes dimensions, format, and EXIF data.

Field Type Default Description
width Int Image width in pixels
height Int Image height in pixels
format String Image format (e.g., "PNG", "JPEG", "TIFF")
exif Map<String, String> {} EXIF metadata tags

ImageMetadataType

Image element metadata.

Field Type Default Description
src String Image source (URL, data URI, or SVG content)
alt String? null Alternative text from alt attribute
title String? null Title attribute
imageType ImageType Image type classification

ImagePreprocessingConfig

Image preprocessing configuration for OCR.

These settings control how images are preprocessed before OCR to improve text recognition quality. Different preprocessing strategies work better for different document types.

Field Type Default Description
targetDpi Int 300 Target DPI for the image (300 is standard, 600 for small text).
autoRotate Boolean false Auto-detect and correct image rotation.
deskew Boolean true Correct skew (tilted images).
denoise Boolean false Remove noise from the image.
contrastEnhance Boolean false Enhance contrast for better text visibility.
binarizationMethod String "otsu" Binarization method: "otsu", "sauvola", "adaptive".
invertColors Boolean false Invert colors (white text on black → black on white).
Methods
default()

Signature:

@JvmStatic
fun default(): ImagePreprocessingConfig

Example:

val result = ImagePreprocessingConfig.default()

Returns: ImagePreprocessingConfig


ImagePreprocessingMetadata

Image preprocessing metadata.

Tracks the transformations applied to an image during OCR preprocessing, including DPI normalization, resizing, and resampling.

Field Type Default Description
targetDpi Int Target DPI from configuration
scaleFactor Double Scaling factor applied to the image
autoAdjusted Boolean Whether DPI was auto-adjusted based on content
finalDpi Int Final DPI after processing
resampleMethod String Resampling algorithm used ("LANCZOS3", "CATMULLROM", etc.)
dimensionClamped Boolean Whether dimensions were clamped to max_image_dimension
calculatedDpi Int? null Calculated optimal DPI (if auto_adjust_dpi enabled)
skippedResize Boolean Whether resize was skipped (dimensions already optimal)
resizeError String? null Error message if resize failed

InlineElement

Inline element within a block.

Represents text with formatting, links, images, etc.

Field Type Default Description
elementType InlineType Type of inline element
content String Text content
metadata Map<String, String>? null Additional metadata (e.g., href for links, src/alt for images)

JatsMetadata

JATS (Journal Article Tag Suite) metadata.

Field Type Default Description
copyright String? null Copyright statement from the article's <permissions> element.
license String? null Open-access license URI from the article's <license> element.
historyDates Map<String, String> {} Publication history dates keyed by event type (e.g. "received", "accepted").
contributorRoles List<ContributorRole> \[\] Authors and contributors with their stated roles.

Keyword

Extracted keyword with metadata.

Field Type Default Description
text String The keyword text.
score Float Relevance score (higher is better, algorithm-specific range).
algorithm KeywordAlgorithm Algorithm that extracted this keyword.
positions List<Long>? null Optional positions where keyword appears in text (character offsets).

KeywordConfig

Keyword extraction configuration.

Field Type Default Description
algorithm KeywordAlgorithm KeywordAlgorithm.Yake Algorithm to use for extraction.
maxKeywords Long 10 Maximum number of keywords to extract (default: 10).
minScore Float 0 Minimum score threshold (0.0-1.0, default: 0.0). Keywords with scores below this threshold are filtered out. Note: Score ranges differ between algorithms.
language String? null Language code for stopword filtering (e.g., "en", "de", "fr"). If None, no stopword filtering is applied.
yakeParams YakeParams? null YAKE-specific tuning parameters.
rakeParams RakeParams? null RAKE-specific tuning parameters.
Methods
default()

Signature:

@JvmStatic
fun default(): KeywordConfig

Example:

val result = KeywordConfig.default()

Returns: KeywordConfig


LanguageDetectionConfig

Language detection configuration.

Field Type Default Description
enabled Boolean true Enable language detection
minConfidence Double 0.8 Minimum confidence threshold (0.0-1.0)
detectMultiple Boolean false Detect multiple languages in the document
Methods
default()

Signature:

@JvmStatic
fun default(): LanguageDetectionConfig

Example:

val result = LanguageDetectionConfig.default()

Returns: LanguageDetectionConfig


LayoutDetection

A single layout detection result.

Field Type Default Description
className LayoutClass Detected layout class (e.g. Table, Text, Title).
confidence Float Detection confidence score in \[0.0, 1.0\].
bbox BBox Bounding box in image pixel coordinates.

LayoutDetectionConfig

Layout detection configuration.

Controls layout detection behavior in the extraction pipeline. When set on ExtractionConfig, layout detection is enabled for PDF extraction.

Field Type Default Description
confidenceThreshold Float? null Confidence threshold override (None = use model default).
applyHeuristics Boolean true Whether to apply postprocessing heuristics (default: true).
tableModel TableModel TableModel.Tatr Table structure recognition model. Controls which model is used for table cell detection within layout-detected table regions. Defaults to TableModel.Tatr.
acceleration AccelerationConfig? null Hardware acceleration for ONNX models (layout detection + table structure). When set, controls which execution provider (CPU, CUDA, CoreML, TensorRT) is used for inference. Defaults to null (auto-select per platform).
enableChartUnderstanding Boolean false Route regions classified as charts to the chart-understanding OCR task. When true, layout regions detected as charts are sent to the VLM chart task (data-series/axis recovery) instead of being treated as generic image regions. Defaults to false — chart understanding is opt-in and has no effect on standard text/table extraction scores.
Methods
default()

Signature:

@JvmStatic
fun default(): LayoutDetectionConfig

Example:

val result = LayoutDetectionConfig.default()

Returns: LayoutDetectionConfig


LayoutRegion

A detected layout region on a page.

When layout detection is enabled, each page may have layout regions identifying different content types (text, pictures, tables, etc.) with confidence scores and spatial positions.

Field Type Default Description
className String Layout class name (e.g. "picture", "table", "text", "section_header").
confidence Double Confidence score from the layout detection model (0.0 to 1.0).
boundingBox BoundingBox Bounding box in document coordinate space.
areaFraction Double Fraction of the page area covered by this region (0.0 to 1.0).

LinkMetadata

Link element metadata.

Field Type Default Description
href String The href URL value
text String Link text content (normalized)
title String? null Optional title attribute
linkType LinkType Link type classification
rel List<String> Rel attribute values

LlmBackend

liter-llm-backed NER backend.

Methods
new()

Create a new LLM-backed NER backend with the given LLM configuration.

Signature:

@JvmStatic
fun new(config: LlmConfig): LlmBackend

Example:

val result = LlmBackend.new(LlmConfig())

Parameters:

Name Type Required Description
config LlmConfig Yes The configuration options

Returns: LlmBackend

detect()

Signature:

@Throws(Error::class)
fun detect(text: String, categories: List<EntityCategory>): List<Entity>

Example:

val result = instance.detect("value", [])

Parameters:

Name Type Required Description
text String Yes The text
categories List<EntityCategory> Yes The categories

Returns: List<Entity>

Errors: Throws Error.

detectWithCustom()

Signature:

@Throws(Error::class)
fun detectWithCustom(text: String, categories: List<EntityCategory>, customLabels: List<String>): List<Entity>

Example:

val result = instance.detectWithCustom("value", [], [])

Parameters:

Name Type Required Description
text String Yes The text
categories List<EntityCategory> Yes The categories
customLabels List<String> Yes The custom labels

Returns: List<Entity>

Errors: Throws Error.


LlmConfig

Configuration for an LLM provider/model via liter-llm.

Each feature (VLM OCR, VLM embeddings, structured extraction) carries its own LlmConfig, allowing different providers per feature.

Field Type Default Description
model String Provider/model string using liter-llm routing format. Examples: "openai/gpt-4o", "anthropic/claude-sonnet-4-20250514", "groq/llama-3.1-70b-versatile".
apiKey String? null API key for the provider. When null, liter-llm falls back to the provider's standard environment variable (e.g., OPENAI_API_KEY).
baseUrl String? null Custom base URL override for the provider endpoint.
timeoutSecs Long? null Request timeout in seconds (default: 60).
maxRetries Int? null Maximum retry attempts (default: 3).
temperature Double? null Sampling temperature for generation tasks.
maxTokens Long? null Maximum tokens to generate.

LlmUsage

Token usage and cost data for a single LLM call made during extraction.

Populated when VLM OCR, structured extraction, or LLM-based embeddings are used. Multiple entries may be present when multiple LLM calls occur within one extraction (e.g. VLM OCR + structured extraction).

Field Type Default Description
model String The LLM model identifier (e.g. "openai/gpt-4o", "anthropic/claude-sonnet-4-20250514").
source String The pipeline stage that triggered this LLM call (e.g. "vlm_ocr", "structured_extraction", "embeddings").
inputTokens Long? null Number of input/prompt tokens consumed.
outputTokens Long? null Number of output/completion tokens generated.
totalTokens Long? null Total tokens (input + output).
estimatedCost Double? null Estimated cost in USD based on the provider's published pricing.
finishReason String? null Why the model stopped generating (e.g. "stop", "length", "content_filter").

MetaSchema

Compiled meta-schema validator over preset.schema.json.

Methods
compile()

Compile the given JSON text as a Draft 2020-12 meta-schema.

Signature:

@Throws(LoadError::class)
@JvmStatic
fun compile(metaSchemaJson: String): MetaSchema

Example:

val result = MetaSchema.compile("value")

Parameters:

Name Type Required Description
metaSchemaJson String Yes The meta schema json

Returns: MetaSchema

Errors: Throws LoadError.

parsePreset()

Validate raw against the meta-schema and deserialize into a Preset, stamping the fingerprint over the canonical file bytes.

Signature:

@Throws(LoadError::class)
fun parsePreset(path: String, raw: ByteArray): Preset

Example:

val result = instance.parsePreset("value", "data".toByteArray())

Parameters:

Name Type Required Description
path String Yes Path to the file
raw ByteArray Yes The raw

Returns: Preset

Errors: Throws LoadError.


Metadata

Extraction result metadata.

Contains common fields applicable to all formats, format-specific metadata via a discriminated union, and additional custom fields from postprocessors.

Field Type Default Description
title String? null Document title
subject String? null Document subject or description
authors List<String>? \[\] Primary author(s) - always Vec for consistency
keywords List<String>? \[\] Keywords/tags - always Vec for consistency
language String? null Primary language (ISO 639 code)
createdAt String? null Creation timestamp (ISO 8601 format)
modifiedAt String? null Last modification timestamp (ISO 8601 format)
createdBy String? null User who created the document
modifiedBy String? null User who last modified the document
pages PageStructure? null Page/slide/sheet structure with boundaries
format FormatMetadata? null Format-specific metadata (discriminated union) Contains detailed metadata specific to the document format. Serialized as a nested "format" object with a format_type discriminator field.
imagePreprocessing ImagePreprocessingMetadata? null Image preprocessing metadata (when OCR preprocessing was applied)
jsonSchema Any? null JSON schema (for structured data extraction)
error ErrorMetadata? null Error metadata (for batch operations)
extractionDurationMs Long? null Extraction duration in milliseconds (for benchmarking). This field is populated by batch extraction to provide per-file timing information. It's null for single-file extraction (which uses external timing).
category String? null Document category (from frontmatter or classification).
tags List<String>? \[\] Document tags (from frontmatter).
documentVersion String? null Document version string (from frontmatter).
abstractText String? null Abstract or summary text (from frontmatter).
outputFormat String? null Output format identifier (e.g., "markdown", "html", "text"). Set by the output format pipeline stage when format conversion is applied. Previously stored in metadata.additional\["output_format"\].
ocrUsed Boolean Whether OCR was used during extraction. Set to true whenever the extraction pipeline ran an OCR backend (Tesseract, PaddleOCR, VLM, etc.) and used that output as the primary or fallback text. false means native text extraction was used exclusively.
additional Map<String, Any> {} Additional custom fields from postprocessors. Serialized as a nested "additional" object (not flattened at root level). Uses Cow<'static, str> keys so static string keys avoid allocation.
Methods
isEmpty()

Returns true when no metadata fields, format-specific metadata, or additional postprocessor fields are populated.

Signature:

fun isEmpty(): Boolean

Example:

val result = instance.isEmpty()

Returns: Boolean


ModelPaths

Combined paths to all models needed for OCR (backward compatibility).

Field Type Default Description
detModel Path Path to the detection model directory.
clsModel Path Path to the classification model directory.
recModel Path Path to the recognition model directory.
dictFile Path Path to the character dictionary file.

MultidocInput

Input signals for multi-document boundary detection.

Field Type Default Description
pageCount Int Total number of pages in the PDF.
pages List<PageSignals> Per-page signals extracted from the PDF.

MultidocThresholds

Thresholds for multi-document boundary detection.

All fields are public; callers override any subset via struct-update syntax.

Field Type Default Description
densityShiftThreshold Float 0.3 Text density difference threshold for DensityShift detection. Default: 0.3.
bigramOverlapMin Float 0.1 Minimum bigram-overlap ratio below which a density shift is promoted to a DensityShift boundary. Default: 0.1 (10 % overlap).
Methods
default()

Signature:

@JvmStatic
fun default(): MultidocThresholds

Example:

val result = MultidocThresholds.default()

Returns: MultidocThresholds


NerConfig

Since: v5.0

Configuration for the NER post-processor.

Field Type Default Description
backend NerBackendKind NerBackendKind.Onnx Backend that runs the entity detection.
categories List<EntityCategory> \[\] Entity categories to detect. Defaults to a sensible PERSON/ORG/LOCATION/EMAIL set when empty.
model String? null Override the default model — only used by NerBackendKind.Onnx. null lets the backend pick its pinned default (urchade/gliner_multi-v2.1 for gline-rs).
llm LlmConfig? null Optional LLM configuration — only used by NerBackendKind.Llm. Token usage for LLM backends is recorded in ExtractionResult.llm_usage.
customLabels List<String> \[\] Arbitrary user-supplied entity labels for zero-shot detection. gline-rs natively supports zero-shot inference over caller-supplied labels — this is the primary value of GLiNER. The LLM backend also honours these labels by including them in the structured-output schema. Custom labels surface as EntityCategory.Custom in the resulting Entity stream. Use this when you need domain-specific entity types (e.g. "Treatment", "Product", "Vessel") without forking GLiNER's taxonomy.

OcrBackend

Trait for OCR backend plugins.

Implement this trait to add custom OCR capabilities. OCR backends can be:

  • Native Rust implementations (like Tesseract)
  • FFI bridges to Python libraries (like EasyOCR, PaddleOCR)
  • Cloud-based OCR services (Google Vision, AWS Textract, etc.)
Thread Safety

OCR backends must be thread-safe (Send + Sync) to support concurrent processing.

Methods
processImage()

Process an image and extract text via OCR.

Returns:

An ExtractionResult containing the extracted text and metadata.

Errors:

  • KreuzbergError.Ocr - OCR processing failed
  • KreuzbergError.Validation - Invalid image format or configuration
  • KreuzbergError.Io - I/O errors (these always bubble up)
Reading backend_options

Backends that support runtime tuning can read config.backend_options and deserialize only the keys they care about. Unknown keys are silently ignored, so multiple backends can coexist in a pipeline without key conflicts.

Signature:

@Throws(Error::class)
fun processImage(imageBytes: ByteArray, config: OcrConfig): ExtractionResult

Example:

val result = instance.processImage("data".toByteArray(), OcrConfig())

Parameters:

Name Type Required Description
imageBytes ByteArray Yes Raw image data (JPEG, PNG, TIFF, etc.)
config OcrConfig Yes OCR configuration (language, PSM mode, etc.)

Returns: ExtractionResult

Errors: Throws Error.

processImageFile()

Process a file and extract text via OCR.

Default implementation reads the file and calls process_image. Override for custom file handling or optimizations.

Errors:

Same as process_image, plus file I/O errors.

Signature:

@Throws(Error::class)
fun processImageFile(path: Path, config: OcrConfig): ExtractionResult

Example:

val result = instance.processImageFile("value", OcrConfig())

Parameters:

Name Type Required Description
path Path Yes Path to the image file
config OcrConfig Yes OCR configuration

Returns: ExtractionResult

Errors: Throws Error.

supportsLanguage()

Check if this backend supports a given language code.

Returns:

true if the language is supported, false otherwise.

Signature:

fun supportsLanguage(lang: String): Boolean

Example:

val result = instance.supportsLanguage("value")

Parameters:

Name Type Required Description
lang String Yes ISO 639-⅔ language code (e.g., "eng", "deu", "fra")

Returns: Boolean

backendType()

Get the backend type identifier.

Returns:

The backend type enum value.

Signature:

fun backendType(): OcrBackendType

Example:

val result = instance.backendType()

Returns: OcrBackendType

supportedLanguages()

Optional: Get a list of all supported languages.

Defaults to empty list. Override to provide comprehensive language support info.

Signature:

fun supportedLanguages(): List<String>

Example:

val result = instance.supportedLanguages()

Returns: List<String>

supportsTableDetection()

Optional: Check if the backend supports table detection.

Defaults to false. Override if your backend can detect and extract tables.

Signature:

fun supportsTableDetection(): Boolean

Example:

val result = instance.supportsTableDetection()

Returns: Boolean

supportsDocumentProcessing()

Check if the backend supports direct document-level processing (e.g. for PDFs).

Defaults to false. Override if the backend has optimized document processing.

Signature:

fun supportsDocumentProcessing(): Boolean

Example:

val result = instance.supportsDocumentProcessing()

Returns: Boolean

emitsStructuredMarkdown()

Declare that this backend emits structured markdown directly (tables, headings, lists) and downstream layout reconstruction should be skipped.

Defaults to false — classical OCR backends (Tesseract, PaddleOCR classical) return plain text per detected region. End-to-end VLM backends (PaddleOCR-VL, GOT-OCR 2.0) emit markdown in one forward pass and should override this to true.

Signature:

fun emitsStructuredMarkdown(): Boolean

Example:

val result = instance.emitsStructuredMarkdown()

Returns: Boolean

processDocument()

Process a document file directly via OCR.

Only called if supports_document_processing returns true.

Signature:

@Throws(Error::class)
fun processDocument(path: Path, config: OcrConfig): ExtractionResult

Example:

val result = instance.processDocument("value", OcrConfig())

Parameters:

Name Type Required Description
path Path Yes The path
config OcrConfig Yes The ocr config

Returns: ExtractionResult

Errors: Throws Error.


OcrConfidence

Confidence scores for an OCR element.

Separates detection confidence (how confident that text exists at this location) from recognition confidence (how confident about the actual text content).

Field Type Default Description
detection Double? null Detection confidence: how confident the OCR engine is that text exists here. PaddleOCR provides this as box_score, Tesseract doesn't have a direct equivalent. Range: 0.0 to 1.0 (or None if not available).
recognition Double Recognition confidence: how confident about the text content. Range: 0.0 to 1.0.

OcrConfig

OCR configuration.

Field Type Default Description
enabled Boolean true Whether OCR is enabled. Setting enabled: false is a shorthand for disable_ocr: true on the parent ExtractionConfig. Images return metadata only; PDFs use native text extraction without OCR fallback. Defaults to true. When false, all other OCR settings are ignored.
backend String OCR backend: tesseract, easyocr, paddleocr
language List<String> \[\] Language code(s) for OCR recognition. Accepts either a single language code ("eng") or a list (["eng", "deu"]). Defaults to ["eng"]. For Tesseract, languages are joined with "+".
tesseractConfig TesseractConfig? null Tesseract-specific configuration (optional)
outputFormat OutputFormat? null Output format for OCR results (optional, for format conversion)
paddleOcrConfig Any? null PaddleOCR-specific configuration (optional, JSON passthrough)
backendOptions Any? null Arbitrary per-call options passed through to the backend unchanged. Custom OCR backends and built-in backends that support runtime tuning can read this value and deserialize the keys they care about. Keys unknown to the backend are silently ignored. This is the recommended extension point for per-call parameters that are not covered by the typed fields above (e.g. mode switching, preprocessing flags, inference batch size). Scope: when pipeline is null, this value is propagated to the primary stage of the auto-constructed pipeline. When pipeline is explicitly set, this field has no effect — the caller must set OcrPipelineStage.backend_options directly on the relevant stage(s) instead. Example: json { "mode": "fast", "enable_layout": true, "timeout_ms": 5000 }
elementConfig OcrElementConfig? null OCR element extraction configuration
qualityThresholds OcrQualityThresholds? null Quality thresholds for the native-text-to-OCR fallback decision. When None, uses compiled defaults (matching previous hardcoded behavior).
pipeline OcrPipelineConfig? null Multi-backend OCR pipeline configuration. When set, enables weighted fallback across multiple OCR backends based on output quality. When None, uses the single backend field (same as today).
autoRotate Boolean false Enable automatic page rotation based on orientation detection. When enabled, uses Tesseract's DetectOrientationScript() to detect page orientation (0/90/180/270 degrees) before OCR. If the page is rotated with high confidence, the image is corrected before recognition. This is critical for handling rotated scanned documents.
vlmFallback VlmFallbackPolicy VlmFallbackPolicy.Disabled Ergonomic VLM fallback policy. When set to anything other than VlmFallbackPolicy.Disabled and OcrConfig.pipeline is null, a multi-stage pipeline is synthesised automatically: - VlmFallbackPolicy.OnLowQuality\[classical_stage, vlm_stage\] with the quality_threshold mapped onto OcrQualityThresholds.pipeline_min_quality. - VlmFallbackPolicy.Always\[vlm_stage\] only. Requires OcrConfig.vlm_config to be Some when not Disabled. When OcrConfig.pipeline is explicitly set, this field is ignored.
vlmConfig LlmConfig? null VLM (Vision Language Model) OCR configuration. Required when backend is "vlm" or when vlm_fallback is not VlmFallbackPolicy.Disabled. Uses liter-llm to send page images to a vision model for text extraction.
vlmPrompt String? null Custom Jinja2 prompt template for VLM OCR. When null, uses the default template. Available variables: - {{ language }} — The document language code (e.g., "eng", "deu").
acceleration AccelerationConfig? null Hardware acceleration for ONNX Runtime models (e.g. PaddleOCR, layout detection). Not user-configurable via config files — injected at runtime from ExtractionConfig.acceleration before each process_image call.
tessdataBytes Map<String, ByteArray>? null Caller-supplied Tesseract traineddata bytes per language code. Primary use case is the WASM build, which has no filesystem and cannot download tessdata at runtime. Native builds typically rely on TessdataManager and ignore this field. When present, the WASM Tesseract backend prefers these bytes over its compile-time-bundled English data. Skipped by serde to keep config files small — supply via the typed API at runtime.
tessdataPath Path? null Runtime override for tessdata directory path. When set, uses this path as the highest-priority tessdata location, bypassing environment variables and cache directories. Useful for embedding pre-installed tessdata in applications. When null, uses the standard resolution chain: TESSDATA_PREFIX env, cache dir, system paths.
Methods
default()

Signature:

@JvmStatic
fun default(): OcrConfig

Example:

val result = OcrConfig.default()

Returns: OcrConfig


OcrElement

A unified OCR element representing detected text with full metadata.

This is the primary type for structured OCR output, preserving all information from both Tesseract and PaddleOCR backends.

Field Type Default Description
text String The recognized text content.
geometry OcrBoundingGeometry OcrBoundingGeometry.Rectangle Bounding geometry (rectangle or quadrilateral).
confidence OcrConfidence Confidence scores for detection and recognition.
level OcrElementLevel OcrElementLevel.Line Hierarchical level (word, line, block, page).
rotation OcrRotation? null Rotation information (if detected).
pageNumber Int Page number (1-indexed).
parentId String? null Parent element ID for hierarchical relationships. Only used for Tesseract output which has word -> line -> block hierarchy.
backendMetadata Map<String, Any> {} Backend-specific metadata that doesn't fit the unified schema.

OcrElementConfig

Configuration for OCR element extraction.

Controls how OCR elements are extracted and filtered.

Field Type Default Description
includeElements Boolean Whether to include OCR elements in the extraction result. When true, the ocr_elements field in ExtractionResult will be populated.
minLevel OcrElementLevel OcrElementLevel.Line Minimum hierarchical level to include. Elements below this level (e.g., words when min_level is Line) will be excluded.
minConfidence Double Minimum recognition confidence threshold (0.0-1.0). Elements with confidence below this threshold will be filtered out.
buildHierarchy Boolean Whether to build hierarchical relationships between elements. When true, parent_id fields will be populated based on spatial containment. Only meaningful for Tesseract output.

OcrExtractionResult

OCR extraction result.

Result of performing OCR on an image or scanned document, including recognized text and detected tables.

Field Type Default Description
content String Recognized text content
mimeType String Original MIME type of the processed image
metadata Map<String, Any> OCR processing metadata (confidence scores, language, etc.)
tables List<OcrTable> Tables detected and extracted via OCR
ocrElements List<OcrElement>? /* serde(default) */ Structured OCR elements with bounding boxes and confidence scores. Available when TSV output is requested or table detection is enabled.

OcrMetadata

OCR processing metadata.

Captures information about OCR processing configuration and results.

Field Type Default Description
language String OCR language code(s) used
psm Int Tesseract Page Segmentation Mode (PSM)
outputFormat String Output format (e.g., "text", "hocr")
tableCount Int Number of tables detected
tableRows Int? null Number of rows in the detected table (if a single table was found).
tableCols Int? null Number of columns in the detected table (if a single table was found).

OcrPipelineConfig

Multi-backend OCR pipeline with quality-based fallback.

Backends are tried in priority order (highest first). After each backend produces output, quality is evaluated. If it meets quality_thresholds.pipeline_min_quality, the result is accepted. Otherwise the next backend is tried.

Field Type Default Description
stages List<OcrPipelineStage> Ordered list of backends to try. Sorted by priority (descending) at runtime.
qualityThresholds OcrQualityThresholds /* serde(default) */ Quality thresholds for deciding whether to accept a result or try the next backend.

OcrPipelineStage

A single backend stage in the OCR pipeline.

Field Type Default Description
backend String Backend name: "tesseract", "paddleocr", "easyocr", or a custom registered name.
priority Int serde(default = "default_priority") Priority weight (higher = tried first). Stages are sorted by priority descending.
language List<String>? /* serde(default) */ Language override for this stage (None = use parent OcrConfig.language). Accepts either a single language code ("eng") or a list (["eng", "deu"]).
tesseractConfig TesseractConfig? /* serde(default) */ Tesseract-specific config override for this stage.
paddleOcrConfig Any? /* serde(default) */ PaddleOCR-specific config for this stage.
vlmConfig LlmConfig? /* serde(default) */ VLM config override for this pipeline stage.
backendOptions Any? /* serde(default) */ Arbitrary per-call options passed through to the backend unchanged. Backends that support runtime tuning (mode switching, preprocessing flags, inference parameters, etc.) read this value and deserialize the keys they care about. Keys unknown to the backend are silently ignored, so options from different backends can coexist in the same config without conflict. Example (custom backend): json { "mode": "fast", "enable_layout": true }

OcrQualityThresholds

Quality thresholds for OCR fallback decisions and pipeline quality gating.

All fields default to the values that match the previous hardcoded behavior, so OcrQualityThresholds.default() preserves existing semantics exactly.

Field Type Default Description
minTotalNonWhitespace Long 64 Minimum total non-whitespace characters to consider text substantive.
minNonWhitespacePerPage Double 32 Minimum non-whitespace characters per page on average.
minMeaningfulWordLen Long 4 Minimum character count for a word to be "meaningful".
minMeaningfulWords Long 3 Minimum count of meaningful words before text is accepted.
minAlnumRatio Double 0.3 Minimum alphanumeric ratio (non-whitespace chars that are alphanumeric).
minGarbageChars Long 5 Minimum Unicode replacement characters (U+FFFD) to trigger OCR fallback.
maxFragmentedWordRatio Double 0.6 Maximum fraction of short (1-2 char) words before text is considered fragmented.
criticalFragmentedWordRatio Double 0.8 Critical fragmentation threshold — triggers OCR regardless of meaningful words. Normal English text has ~20-30% short words. 80%+ is definitive garbage.
minAvgWordLength Double 2 Minimum average word length. Below this with enough words indicates garbled extraction.
minWordsForAvgLengthCheck Long 50 Minimum word count before average word length check applies.
minConsecutiveRepeatRatio Double 0.08 Minimum consecutive word repetition ratio to detect column scrambling.
minWordsForRepeatCheck Long 50 Minimum word count before consecutive repetition check is applied.
substantiveMinChars Long 100 Minimum character count for "substantive markdown" OCR skip gate.
nonTextMinChars Long 20 Minimum character count for "non-text content" OCR skip gate.
alnumWsRatioThreshold Double 0.4 Alphanumeric+whitespace ratio threshold for skip decisions.
pipelineMinQuality Double 0.5 Minimum quality score (0.0-1.0) for a pipeline stage result to be accepted. If the result from a backend scores below this, try the next backend.
Methods
default()

Signature:

@JvmStatic
fun default(): OcrQualityThresholds

Example:

val result = OcrQualityThresholds.default()

Returns: OcrQualityThresholds


OcrRotation

Rotation information for an OCR element.

Field Type Default Description
angleDegrees Double Rotation angle in degrees (0, 90, 180, 270 for PaddleOCR).
confidence Double? null Confidence score for the rotation detection.

OcrTable

Table detected via OCR.

Represents a table structure recognized during OCR processing.

Field Type Default Description
cells List<List<String>> Table cells as a 2D vector (rows × columns)
markdown String Markdown representation of the table
pageNumber Int Page number where the table was found (1-indexed)
boundingBox OcrTableBoundingBox? /* serde(default) */ Bounding box of the table in pixel coordinates (from OCR word positions).

OcrTableBoundingBox

Bounding box for an OCR-detected table in pixel coordinates.

Field Type Default Description
left Int Left x-coordinate (pixels)
top Int Top y-coordinate (pixels)
right Int Right x-coordinate (pixels)
bottom Int Bottom y-coordinate (pixels)

OrientationResult

Document orientation detection result.

Field Type Default Description
degrees Int Detected orientation in degrees (0, 90, 180, or 270).
confidence Float Confidence score (0.0-1.0).

PaddleOcrConfig

Configuration for PaddleOCR backend.

Configures PaddleOCR text detection and recognition with multi-language support. Uses a builder pattern for convenient configuration.

Field Type Default Description
language String Language code (e.g., "en", "ch", "jpn", "kor", "deu", "fra")
cacheDir Path? null Optional custom cache directory for model files
useAngleCls Boolean Enable angle classification for rotated text (default: false). Can misfire on short text regions, rotating crops incorrectly before recognition.
enableTableDetection Boolean Enable table structure detection (default: false)
detDbThresh Float Database threshold for text detection (default: 0.3) Range: 0.0-1.0, higher values require more confident detections
detDbBoxThresh Float Box threshold for text bounding box refinement (default: 0.5) Range: 0.0-1.0
detDbUnclipRatio Float Unclip ratio for expanding text bounding boxes (default: 1.6) Controls the expansion of detected text regions
detLimitSideLen Int Maximum side length for detection image (default: 960) Larger images may be resized to this limit for faster inference
recBatchNum Int Batch size for recognition inference (default: 6) Number of text regions to process simultaneously
padding Int Padding in pixels added around the image before detection (default: 10). Large values can include surrounding content like table gridlines.
dropScore Float Minimum recognition confidence score for text lines (default: 0.5). Text regions with recognition confidence below this threshold are discarded. Matches PaddleOCR Python's drop_score parameter. Range: 0.0-1.0
modelTier String Model tier controlling detection/recognition model size and accuracy trade-off. - "mobile" (default): Lightweight models (~4.5MB detection, ~16.5MB recognition), fast download and inference - "server": Large, high-accuracy models (~88MB detection, ~84MB recognition), best for GPU or complex documents
Methods
withCacheDir()

Sets a custom cache directory for model files.

Signature:

fun withCacheDir(path: Path): PaddleOcrConfig

Example:

val result = instance.withCacheDir("value")

Parameters:

Name Type Required Description
path Path Yes Path to cache directory

Returns: PaddleOcrConfig

withTableDetection()

Enables or disables table structure detection.

Signature:

fun withTableDetection(enable: Boolean): PaddleOcrConfig

Example:

val result = instance.withTableDetection(true)

Parameters:

Name Type Required Description
enable Boolean Yes Whether to enable table detection

Returns: PaddleOcrConfig

withAngleCls()

Enables or disables angle classification for rotated text.

Signature:

fun withAngleCls(enable: Boolean): PaddleOcrConfig

Example:

val result = instance.withAngleCls(true)

Parameters:

Name Type Required Description
enable Boolean Yes Whether to enable angle classification

Returns: PaddleOcrConfig

withDetDbThresh()

Sets the database threshold for text detection.

Signature:

fun withDetDbThresh(threshold: Float): PaddleOcrConfig

Example:

val result = instance.withDetDbThresh(0.5)

Parameters:

Name Type Required Description
threshold Float Yes Detection threshold (0.0-1.0)

Returns: PaddleOcrConfig

withDetDbBoxThresh()

Sets the box threshold for text bounding box refinement.

Signature:

fun withDetDbBoxThresh(threshold: Float): PaddleOcrConfig

Example:

val result = instance.withDetDbBoxThresh(0.5)

Parameters:

Name Type Required Description
threshold Float Yes Box threshold (0.0-1.0)

Returns: PaddleOcrConfig

withDetDbUnclipRatio()

Sets the unclip ratio for expanding text bounding boxes.

Signature:

fun withDetDbUnclipRatio(ratio: Float): PaddleOcrConfig

Example:

val result = instance.withDetDbUnclipRatio(0.5)

Parameters:

Name Type Required Description
ratio Float Yes Unclip ratio (typically 1.5-2.0)

Returns: PaddleOcrConfig

withDetLimitSideLen()

Sets the maximum side length for detection images.

Signature:

fun withDetLimitSideLen(length: Int): PaddleOcrConfig

Example:

val result = instance.withDetLimitSideLen(42)

Parameters:

Name Type Required Description
length Int Yes Maximum side length in pixels

Returns: PaddleOcrConfig

withRecBatchNum()

Sets the batch size for recognition inference.

Signature:

fun withRecBatchNum(batchSize: Int): PaddleOcrConfig

Example:

val result = instance.withRecBatchNum(42)

Parameters:

Name Type Required Description
batchSize Int Yes Number of text regions to process simultaneously

Returns: PaddleOcrConfig

withDropScore()

Sets the minimum recognition confidence threshold.

Signature:

fun withDropScore(score: Float): PaddleOcrConfig

Example:

val result = instance.withDropScore(0.5)

Parameters:

Name Type Required Description
score Float Yes Minimum confidence (0.0-1.0), text below this is dropped

Returns: PaddleOcrConfig

withPadding()

Sets padding in pixels added around images before detection.

Signature:

fun withPadding(padding: Int): PaddleOcrConfig

Example:

val result = instance.withPadding(42)

Parameters:

Name Type Required Description
padding Int Yes Padding in pixels (0-100)

Returns: PaddleOcrConfig

withModelTier()

Sets the model tier controlling detection/recognition model size.

Signature:

fun withModelTier(tier: String): PaddleOcrConfig

Example:

val result = instance.withModelTier("value")

Parameters:

Name Type Required Description
tier String Yes "mobile" (default, lightweight, faster) or "server" (high accuracy, GPU/complex documents)

Returns: PaddleOcrConfig

default()

Creates a default configuration with English language support.

Signature:

@JvmStatic
fun default(): PaddleOcrConfig

Example:

val result = PaddleOcrConfig.default()

Returns: PaddleOcrConfig


PageBoundary

Byte offset boundary for a page.

Tracks where a specific page's content starts and ends in the main content string, enabling mapping from byte positions to page numbers. Offsets are guaranteed to be at valid UTF-8 character boundaries when using standard String methods (push_str, push, etc.).

Field Type Default Description
byteStart Long Byte offset where this page starts in the content string (UTF-8 valid boundary, inclusive)
byteEnd Long Byte offset where this page ends in the content string (UTF-8 valid boundary, exclusive)
pageNumber Int Page number (1-indexed)

PageClassification

Classification result for a single page.

Field Type Default Description
pageNumber Int 1-indexed page number this classification belongs to.
labels List<ClassificationLabel> Labels assigned to the page. Single-label classification yields exactly one entry; multi-label classification yields any subset of the configured label set.

PageClassificationConfig

Since: v5.0

Configuration for the page-classification post-processor.

Field Type Default Description
promptTemplate String? null Minijinja prompt template. Receives {{ labels }} (joined list), {{ page_text }} and {{ multi_label }} variables. null lets the backend pick a sensible default.
labels List<String> The set of labels the classifier may emit. Must contain at least one entry.
multiLabel Boolean /* serde(default) */ Allow multiple labels per page. Single-label mode returns at most one label.
llm LlmConfig LLM configuration used for classification.

PageConfig

Page extraction and tracking configuration.

Controls how pages are extracted, tracked, and represented in the extraction results. When null, page tracking is disabled.

Page range tracking in chunk metadata (first_page/last_page) is automatically enabled when page boundaries are available and chunking is configured.

Field Type Default Description
extractPages Boolean false Extract pages as separate array (ExtractionResult.pages)
insertPageMarkers Boolean false Insert page markers in main content string
markerFormat String "<!-- PAGE {page_num} -->" Page marker format (use {page_num} placeholder) Default: "\n\n\n\n"
Methods
default()

Signature:

@JvmStatic
fun default(): PageConfig

Example:

val result = PageConfig.default()

Returns: PageConfig


PageContent

Content for a single page/slide.

When page extraction is enabled, documents are split into per-page content with associated tables and images mapped to each page.

Performance

Uses shared tables and images for memory efficiency:

  • List<Table> enables zero-copy sharing of table data
  • List<ExtractedImage> enables zero-copy sharing of image data
  • Maintains exact JSON compatibility via custom Serialize/Deserialize

This reduces memory overhead for documents with shared tables/images by avoiding redundant copies during serialization.

Field Type Default Description
pageNumber Int Page number (1-indexed)
content String Text content for this page
tables List<Table> /* serde(default) */ Tables found on this page (uses Arc for memory efficiency) Serializes as List for JSON compatibility while maintaining shared in-memory ownership for zero-copy sharing.
imageIndices List<Int> /* serde(default) */ Indices into ExtractionResult.images for images found on this page. Each value is a zero-based index into the top-level images collection. Only populated when extract_images = true in the extraction config.
hierarchy PageHierarchy? null Hierarchy information for the page (when hierarchy extraction is enabled) Contains text hierarchy levels (H1-H6) extracted from the page content.
isBlank Boolean? null Whether this page is blank (no meaningful text content) Determined during extraction based on text content analysis. A page is blank if it has fewer than 3 non-whitespace characters and contains no tables or images.
layoutRegions List<LayoutRegion>? null Layout detection regions for this page (when layout detection is enabled). Contains detected layout regions with class, confidence, bounding box, and area fraction. Only populated when layout detection is configured.
speakerNotes String? null Speaker notes for this slide (PPTX only). Contains the text from the slide's notes pane (ppt/notesSlides/notesSlide{N}.xml). Only populated when the source is a PPTX file and notes are present.
sectionName String? null Section name this slide belongs to (PPTX only). PowerPoint sections group slides into logical chapters (<p:sectionLst> in ppt/presentation.xml). Only populated when the source is a PPTX file and the slide belongs to a named section.
sheetName String? null Sheet name for this page (XLSX/ODS only). Each spreadsheet sheet maps to one PageContent entry. This field carries the sheet's display name as it appears in the workbook. null for all non-spreadsheet formats and for sheets with an empty name.

PageHierarchy

Page hierarchy structure containing heading levels and block information.

Used when PDF text hierarchy extraction is enabled. Contains hierarchical blocks with heading levels (H1-H6) for semantic document structure.

Field Type Default Description
blockCount Int Number of hierarchy blocks on this page
blocks List<HierarchicalBlock> /* serde(default) */ Hierarchical blocks with heading levels

PageInfo

Metadata for individual page/slide/sheet.

Captures per-page information including dimensions, content counts, and visibility state (for presentations).

Field Type Default Description
number Int Page number (1-indexed)
title String? null Page title (usually for presentations)
imageCount Int? null Number of images on this page
tableCount Int? null Number of tables on this page
hidden Boolean? null Whether this page is hidden (e.g., in presentations)
isBlank Boolean? null Whether this page is blank (no meaningful text, no images, no tables) A page is considered blank if it has fewer than 3 non-whitespace characters and contains no tables or images. This is useful for filtering out empty pages in scanned documents or PDFs with blank separator pages.
hasVectorGraphics Boolean /* serde(default) */ Whether this page contains non-trivial vector graphics (paths, shapes, curves) Indicates the presence of vector-drawn content such as charts, diagrams, or geometric shapes (e.g., from Adobe InDesign, LaTeX TikZ). These are invisible to ExtractionResult.images since they are not embedded as raster XObjects. Set to true when path count exceeds a heuristic threshold, signaling that downstream consumers may want to rasterize the page to capture this content. Only populated for PDFs; null for other document types.

PageRange

Page range for a chunk (0-indexed, inclusive).

Field Type Default Description
start Int Start page (0-indexed, inclusive).
end Int End page (0-indexed, inclusive).
Methods
pageCount()

Get the number of pages in this range.

Signature:

fun pageCount(): Int

Example:

val result = instance.pageCount()

Returns: Int


PageSignals

Per-page signals extracted from PDF content.

Field Type Default Description
pageNumber Int 1-indexed page number.
textExcerpt String First ~500 characters of extracted text.
startsWithLetterheadLike Boolean true if page starts with letterhead-like content (ALL CAPS line in first 5 lines or a logo-image bbox at top).
hasPageNumberOneMarker Boolean true if text contains "Page 1" or "1 of N" pattern.
hasSignatureBlock Boolean true if text contains signature indicators ("Sincerely", "Signed") or a signature image bbox.
layoutTextDensity Float Text density: characters per page area, normalised to \[0.0, 1.0\].
Methods
fromPageText()

Derive signals from raw page text.

Callers that already have structured per-page data (e.g. from a PDF extractor) can set individual fields directly. This constructor is for callers that only have the plain-text content of a page (e.g. from PageContent).

when unknown (disables density-shift detection for this page).

Heuristics

All signal derivations are conservative starting points. Each is documented inline. They err on the side of fewer false positives; tune thresholds via MultidocThresholds rather than by changing these heuristics.

Signature:

@JvmStatic
fun fromPageText(pageNumber: Int, text: String, layoutTextDensity: Float): PageSignals

Example:

val result = PageSignals.fromPageText(42, "value", 0.5)

Parameters:

Name Type Required Description
pageNumber Int Yes The page number
text String Yes The text
layoutTextDensity Float Yes The layout text density

Returns: PageSignals


PageStructure

Unified page structure for documents.

Supports different page types (PDF pages, PPTX slides, Excel sheets) with character offset boundaries for chunk-to-page mapping.

Field Type Default Description
totalCount Int Total number of pages/slides/sheets
unitType PageUnitType Type of paginated unit
boundaries List<PageBoundary>? null Character offset boundaries for each page Maps character ranges in the extracted content to page numbers. Used for chunk page range calculation.
pages List<PageInfo>? null Detailed per-page metadata (optional, only when needed)

PatternMatch

One detected PII span in the input text.

Field Type Default Description
start Long Inclusive byte-offset start of the match in the source text.
end Long Exclusive byte-offset end of the match.
category PiiCategory Category the match belongs to.
text String Matched substring (owned copy — pattern engine returns owned data so the caller can free the original text if needed before replacement).

PdfAnnotation

A PDF annotation extracted from a document page.

Field Type Default Description
annotationType PdfAnnotationType The type of annotation.
content String? null Text content of the annotation (e.g., comment text, link URL).
pageNumber Int Page number where the annotation appears (1-indexed).
boundingBox BoundingBox? null Bounding box of the annotation on the page.

PdfConfig

PDF-specific configuration.

Field Type Default Description
extractImages Boolean false Extract images from PDF
extractTables Boolean true Extract tables from PDF. When true (default), runs pdf_oxide's native grid detector and, if it finds nothing, falls back to the heuristic text-layer reconstruction in pdf.oxide.table.extract_tables_heuristic. Set to false to skip both passes — tables will then be empty in the result.
passwords List<String>? null List of passwords to try when opening encrypted PDFs
extractMetadata Boolean true Extract PDF metadata
hierarchy HierarchyConfig? null Hierarchy extraction configuration (None = hierarchy extraction disabled)
extractAnnotations Boolean false Extract PDF annotations (text notes, highlights, links, stamps). Default: false
topMarginFraction Float? null Top margin fraction (0.0–1.0) of page height to exclude headers/running heads. Default: 0.06 (6%)
bottomMarginFraction Float? null Bottom margin fraction (0.0–1.0) of page height to exclude footers/page numbers. Default: 0.05 (5%)
allowSingleColumnTables Boolean false Allow single-column pseudo tables in extraction results. By default, tables with fewer than 2 columns (layout-guided) or 3 columns (heuristic) are rejected. When true, the minimum column count is relaxed to 1, allowing single-column structured data (glossaries, itemized lists) to be emitted as tables. Other quality filters (density, sparsity, prose detection) still apply.
ocrInlineImages Boolean false Perform OCR on inline images extracted from PDF pages and attach the recognized text to each ExtractedImage.ocr_result. Requires Tesseract to be available; if ExtractionConfig.ocr is null the extractor falls back to TesseractConfig.default(). Per-image failures degrade gracefully (the image is returned without OCR text rather than failing the whole extraction). Default: false.
extractFormFields Boolean true Extract AcroForm and XFA form fields into ExtractionResult.form_fields. When true (default), reads the document's interactive form structure (field names, types, values, widget geometry). Cheap and strictly additive — non-form PDFs simply yield an empty list. Set to false to skip the form pass entirely.
readingOrder Boolean false Reorder extracted text by layout-detected reading order. When true, projects text spans onto layout-detected regions, performs column detection, and emits spans in natural reading order (important for multi-column academic PDFs). Requires the layout-detection feature; has no effect without it. Defaults to false.
Methods
default()

Signature:

@JvmStatic
fun default(): PdfConfig

Example:

val result = PdfConfig.default()

Returns: PdfConfig


PdfFormField

A form field extracted from a PDF's AcroForm or XFA structure.

Populated by the PDF extractor when PdfConfig.extract_form_fields is enabled and the document is a fillable form. Supports both AcroForm (standard) and XFA (XML Forms Architecture) layers. When both are present, AcroForm fields take priority (canonical fallback per PDF spec), and XFA-only fields are appended. The collection is empty for non-form PDFs and for non-PDF formats.

PdfConfig.extract_form_fields: crate.core.config.PdfConfig.extract_form_fields

Field Type Default Description
name String Partial field name (the leaf name within the field hierarchy).
fullName String Fully-qualified field name (dotted path from the form root).
fieldType FormFieldType Classified field type.
value String? /* serde(default) */ Current field value, if any.
defaultValue String? /* serde(default) */ Default field value, if any.
flags Int /* serde(default) */ Raw field-flags bitmask (read-only, required, multiline, …).
page Int? /* serde(default) */ 1-indexed page the field's widget appears on. Currently always null for AcroForm fields; page assignment is a deferred enhancement requiring spatial analysis of widget annotations per page.
bbox BoundingBox? /* serde(default) */ Widget bounding box on its page, if known.
maxLength Int? /* serde(default) */ Maximum input length for text fields, if specified.
tooltip String? /* serde(default) */ Tooltip / alternate field description, if present.

PdfMetadata

PDF-specific metadata.

Contains metadata fields specific to PDF documents that are not in the common Metadata structure. Common fields like title, authors, keywords, and dates are at the Metadata level.

Field Type Default Description
pdfVersion String? null PDF version (e.g., "1.7", "2.0")
producer String? null PDF producer (application that created the PDF)
isEncrypted Boolean? null Whether the PDF is encrypted/password-protected
width Long? null First page width in points (1/72 inch)
height Long? null First page height in points (1/72 inch)
pageCount Int? null Total number of pages in the PDF document

Plugin

Base trait that all plugins must implement.

This trait provides common functionality for plugin lifecycle management, identification, and metadata.

Thread Safety

All plugins must be Send + Sync to support concurrent usage across threads.

Methods
name()

Returns the unique name/identifier for this plugin.

The name should be:

  • Unique across all plugins
  • Lowercase with hyphens (e.g., "my-custom-plugin")
  • URL-safe characters only

Signature:

fun name(): String

Example:

val result = instance.name()

Returns: String

version()

Returns the semantic version of this plugin.

Should follow semver format: MAJOR.MINOR.PATCH

Defaults to the kreuzberg crate version.

Signature:

fun version(): String

Example:

val result = instance.version()

Returns: String

initialize()

Initialize the plugin.

Called once when the plugin is registered. Use this to:

  • Load configuration
  • Initialize resources (connections, caches, etc.)
  • Validate dependencies
Thread Safety

This method takes &self instead of &mut self to work with Arc<dyn Plugin>. Plugins needing mutable state during initialization should use interior mutability patterns (Mutex, RwLock, OnceCell, etc.).

Errors:

Should return an error if initialization fails. The plugin will not be registered if this method returns an error.

Defaults to a no-op for stateless plugins.

Signature:

@Throws(Error::class)
fun initialize()

Example:

instance.initialize()

Returns: No return value.

Errors: Throws Error.

shutdown()

Shutdown the plugin.

Called when the plugin is being unregistered or the application is shutting down. Use this to:

  • Close connections
  • Flush caches
  • Release resources
Thread Safety

This method takes &self instead of &mut self to work with Arc<dyn Plugin>. Plugins needing mutable state during shutdown should use interior mutability patterns (Mutex, RwLock, etc.).

Errors:

Errors during shutdown are logged but don't prevent the shutdown process.

Defaults to a no-op for stateless plugins.

Signature:

@Throws(Error::class)
fun shutdown()

Example:

instance.shutdown()

Returns: No return value.

Errors: Throws Error.

description()

Optional plugin description for debugging and logging.

Defaults to empty string if not overridden.

Signature:

fun description(): String

Example:

val result = instance.description()

Returns: String

author()

Optional plugin author information.

Defaults to empty string if not overridden.

Signature:

fun author(): String

Example:

val result = instance.author()

Returns: String


PostProcessor

Trait for post-processor plugins.

Post-processors transform or enrich extraction results after the initial extraction is complete. They can:

  • Clean and normalize text
  • Add metadata (language, keywords, entities)
  • Split content into chunks
  • Score quality
  • Apply custom transformations
Processing Order

Post-processors are executed in stage order:

  1. Early - Language detection, entity extraction
  2. Middle - Keyword extraction, token reduction
  3. Late - Custom hooks, final validation

Within each stage, processors are executed in registration order.

Error Handling

Post-processor errors are non-fatal by default - they're captured in metadata and execution continues. To make errors fatal, return an error from process().

Thread Safety

Post-processors must be thread-safe (Send + Sync).

Methods
process()

Process an extraction result.

Transform or enrich the extraction result. Can modify:

  • content - The extracted text
  • metadata - Add or update metadata fields
  • tables - Modify or enhance table data

Returns:

Ok(()) if processing succeeded, Err(...) for fatal failures.

Errors:

Return errors for fatal processing failures. Non-fatal errors should be captured in metadata directly on the result.

Performance

This signature avoids unnecessary cloning of large extraction results by taking a mutable reference instead of ownership. Processors modify the result in place.

Example - Language Detection
Example - Text Cleaning

Signature:

@Throws(Error::class)
fun process(result: ExtractionResult, config: ExtractionConfig)

Example:

instance.process(ExtractionResult(), ExtractionConfig())

Parameters:

Name Type Required Description
result ExtractionResult Yes Mutable reference to the extraction result to process
config ExtractionConfig Yes Extraction configuration

Returns: No return value.

Errors: Throws Error.

processingStage()

Get the processing stage for this post-processor.

Determines when this processor runs in the pipeline.

Returns:

The ProcessingStage (Early, Middle, or Late).

Signature:

fun processingStage(): ProcessingStage

Example:

val result = instance.processingStage()

Returns: ProcessingStage

shouldProcess()

Optional: Check if this processor should run for a given result.

Allows conditional processing based on MIME type, metadata, or content. Defaults to true (always run).

Returns:

true if the processor should run, false to skip.

Signature:

fun shouldProcess(result: ExtractionResult, config: ExtractionConfig): Boolean

Example:

val result = instance.shouldProcess(ExtractionResult(), ExtractionConfig())

Parameters:

Name Type Required Description
result ExtractionResult Yes The extraction result
config ExtractionConfig Yes The extraction config

Returns: Boolean

estimatedDurationMs()

Optional: Estimate processing time in milliseconds.

Used for logging and debugging. Defaults to 0 (unknown).

Returns:

Estimated processing time in milliseconds.

Signature:

fun estimatedDurationMs(result: ExtractionResult): Long

Example:

val result = instance.estimatedDurationMs(ExtractionResult())

Parameters:

Name Type Required Description
result ExtractionResult Yes The extraction result

Returns: Long

priority()

Execution priority within the processing stage.

Higher values run first within the same ProcessingStage. Defaults to 50. Use 0-49 for fallback processors, 50 for normal processors, and 51-255 for high-priority processors that should run early in their stage.

Signature:

fun priority(): Int

Example:

val result = instance.priority()

Returns: Int


PostProcessorConfig

Post-processor configuration.

Field Type Default Description
enabled Boolean true Enable post-processors
enabledProcessors List<String>? null Whitelist of processor names to run (None = all enabled)
disabledProcessors List<String>? null Blacklist of processor names to skip (None = none disabled)
enabledSet List<String>? null Pre-computed AHashSet for O(1) enabled processor lookup
disabledSet List<String>? null Pre-computed AHashSet for O(1) disabled processor lookup
Methods
default()

Signature:

@JvmStatic
fun default(): PostProcessorConfig

Example:

val result = PostProcessorConfig.default()

Returns: PostProcessorConfig


PptxAppProperties

Application properties from docProps/app.xml for PPTX

Contains PowerPoint-specific document metadata.

Field Type Default Description
application String? null Application name (e.g., "Microsoft Office PowerPoint")
appVersion String? null Application version
totalTime Int? null Total editing time in minutes
company String? null Company name
docSecurity Int? null Document security level
scaleCrop Boolean? null Scale crop flag
linksUpToDate Boolean? null Links up to date flag
sharedDoc Boolean? null Shared document flag
hyperlinksChanged Boolean? null Hyperlinks changed flag
slides Int? null Number of slides
notes Int? null Number of notes
hiddenSlides Int? null Number of hidden slides
multimediaClips Int? null Number of multimedia clips
presentationFormat String? null Presentation format (e.g., "Widescreen", "Standard")
slideTitles List<String> \[\] Slide titles

PptxExtractionResult

PowerPoint (PPTX) extraction result.

Contains extracted slide content, metadata, and embedded images/tables.

Field Type Default Description
content String Extracted text content from all slides
metadata PptxMetadata Presentation metadata
slideCount Long Total number of slides
imageCount Long Total number of embedded images
tableCount Long Total number of tables
images List<ExtractedImage> Extracted images from the presentation
pageStructure PageStructure? null Slide structure with boundaries (when page tracking is enabled)
pageContents List<PageContent>? null Per-slide content (when page tracking is enabled)
document DocumentStructure? null Structured document representation
officeMetadata Map<String, String> /* serde(default) */ Office metadata extracted from docProps/core.xml and docProps/app.xml. Contains keys like "title", "author", "created_by", "subject", "keywords", "modified_by", "created_at", "modified_at", etc.
revisions List<DocumentRevision>? /* serde(default) */ Slide comments as revisions. Each <p:cm> element in ppt/comments/comment{N}.xml becomes a DocumentRevision { kind: Comment } with author (resolved from ppt/commentAuthors.xml), ISO-8601 timestamp, and RevisionAnchor.Slide { index }. null when no comment XML parts exist.

PptxMetadata

PowerPoint presentation metadata.

Extracted from PPTX files containing slide counts and presentation details.

Field Type Default Description
slideCount Int Total number of slides in the presentation
slideNames List<String> \[\] Names of slides (if available)
imageCount Int? null Number of embedded images
tableCount Int? null Number of tables

Preset

A curated structured-extraction preset loaded from the embedded library.

Each preset is a JSON file under src/presets/library/<id>/v1.json that validates against the meta-schema in src/presets/preset.schema.json.

The curated catalog is downstream (kreuzberg-cloud) and injects presets via extend_from_dir. The embedded OSS library ships only the generic_document toy preset.

Field Type Default Description
id String Stable, URL-safe preset identifier (lowercase snake_case).
version String Monotonic version string (e.g. v1).
schemaName String Human-readable schema name forwarded to the LLM as the response/tool name.
description String One-line preset description shown in the registry UI.
category PresetCategory Top-level category for grouping in the playground.
tags List<String> /* serde(default) */ Free-form tags used for search/filtering. May be empty.
schema Any JSON Schema (Draft 2020-12) describing the structured output shape.
systemPrompt String Instruction primer sent to the model.
contextTemplate String? /* serde(default) */ Optional mustache-style template merged with caller-supplied context.
mergeMode MergeMode Strategy for merging per-batch outputs across paginated calls.
preferredCallMode CallMode Default call mode suggested for this preset; heuristics may override.
emitCitations Boolean When true, the prompt asks the model to wrap each field as {value, page, bbox, confidence} for downstream citation overlays.
sample PresetSample? /* serde(default) */ Optional bundled sample (input file + reference output) for preview.
fingerprint String /* serde(default) */ Stable sha256 fingerprint of the canonical preset file contents. Populated at registry load — not present in the on-disk JSON files. Used as a cache-invalidation token by the worker pipeline.

PresetSample

Pointer to a sample input + its reference output bundled with the preset.

Field Type Default Description
inputPath String Path to the sample input file, relative to the preset directory.
outputPath String Path to the reference structured output, relative to the preset directory.

PresetSummary

Lightweight projection of Preset used by the registry list endpoint (omits the full schema and prompt to keep the payload small).

Field Type Default Description
id String Preset identifier matching Preset.id.
version String Preset version matching Preset.version.
schemaName String Schema name matching Preset.schema_name.
description String One-line preset description.
category PresetCategory Top-level category.
tags List<String> Free-form tags.
preferredCallMode CallMode Default call mode.
emitCitations Boolean Whether the preset prompts the model for citations.
fingerprint String Stable fingerprint matching Preset.fingerprint.

ProcessingWarning

A non-fatal warning from a processing pipeline stage.

Captures errors from optional features that don't prevent extraction but may indicate degraded results.

Field Type Default Description
source String The pipeline stage or feature that produced this warning (e.g., "embedding", "chunking", "language_detection", "output_format").
message String Human-readable description of what went wrong.

PstMetadata

Outlook PST archive metadata.

Field Type Default Description
messageCount Long Total number of email messages found in the PST archive.

QrBoundingBox

Pixel-space bounding box of a QR code inside its source image.

Field Type Default Description
x Int Horizontal pixel offset of the bounding box top-left corner.
y Int Vertical pixel offset of the bounding box top-left corner.
width Int Width of the bounding box in pixels.
height Int Height of the bounding box in pixels.

QrCode

One QR code decoded from an extracted image.

Field Type Default Description
payload String Decoded payload (text, URL, vCard string, …).
confidence Float? null Detector-reported confidence in \[0.0, 1.0\]. null when the decoder does not expose confidence (the default rqrr backend always reports Some because successful decode implies high confidence).
bbox QrBoundingBox? null Bounding box of the QR code inside the source image, in pixel coordinates (x, y of the top-left corner; width, height of the rectangle). null if the decoder did not report a bounding box.

RakeParams

RAKE-specific parameters.

Field Type Default Description
minWordLength Long 1 Minimum word length to consider (default: 1).
maxWordsPerPhrase Long 3 Maximum words in a keyword phrase (default: 3).
Methods
default()

Signature:

@JvmStatic
fun default(): RakeParams

Example:

val result = RakeParams.default()

Returns: RakeParams


RecognizedTable

Pre-computed table markdown for a table detection region.

Produced by the TATR-based table structure recognizer and surfaced as part of layout-aware OCR results. The struct lives here (under layout-types, pure-Rust) so that consumers who do not enable layout-detection (ORT) can still reference the type in their own code.

Field Type Default Description
detectionBbox BBox Detection bbox that this table corresponds to (for matching).
cells List<List<String>> Table cells as a 2D vector (rows × columns).
markdown String Rendered markdown table.

RedactionConfig

Since: v5.0

Configuration for the redaction post-processor.

Field Type Default Description
categories List<PiiCategory> \[\] Categories to redact. Empty means "every category supported by the engine."
strategy RedactionStrategy RedactionStrategy.Mask Strategy applied to every match.
ner NerConfig? null Optional NER backend — required to redact PERSON / ORGANIZATION / LOCATION categories (the pure-Rust pattern engine only covers regex-detectable PII).
preserveOffsets Boolean true When true, chunk byte ranges are kept consistent with the rewritten content by adjusting byte_start / byte_end after replacement. When false, chunk byte ranges still refer to the original content offsets — useful when downstream consumers want to map findings back to the original document.
customTerms List<RedactionTerm> \[\] Arbitrary user-supplied literal terms to redact. Each term is treated as a regex hit against the document, surfacing as PiiCategory.Custom(label) in RedactionFinding where label is the per-term label (defaulting to the literal value itself). Case-insensitive by default; set RedactionTerm.case_sensitive for exact match. Use this when you need to redact tenant-specific tokens (employee IDs, project codes, internal product names) without writing a custom plugin.
customPatterns List<RedactionPattern> \[\] Arbitrary user-supplied regex patterns to redact. Same surfacing semantics as custom_terms: each hit becomes a PiiCategory.Custom(label) finding. Patterns are validated at config-construction time via RedactionConfig.validate.
Methods
default()

Signature:

@JvmStatic
fun default(): RedactionConfig

Example:

val result = RedactionConfig.default()

Returns: RedactionConfig

validate()

Validate user-supplied terms and patterns at config-construction time.

Compiles every RedactionPattern.pattern (with the case-insensitive inline flag where applicable) and returns the first compilation error so the caller can reject the config before the redaction pipeline runs. Pure terms (regex-escaped) cannot fail to compile, but the function still rejects empty values to avoid degenerate zero-length matches.

Signature:

@Throws(Error::class)
fun validate()

Example:

instance.validate()

Returns: No return value.

Errors: Throws Error.


RedactionFinding

One redaction event: which span was rewritten, why, and with what.

Field Type Default Description
start Int Byte-offset start in the original (pre-redaction) ExtractionResult.content.
end Int Byte-offset end (exclusive) in the original ExtractionResult.content.
category PiiCategory PII category that fired this redaction.
strategy RedactionStrategy Strategy applied to this finding (mask, hash, token-replace, drop).
replacementToken String String that replaced the original mention. Always present; for Drop the replacement is the empty string.

RedactionPattern

One user-supplied regex pattern to redact.

The pattern is compiled with the Rust regex crate (no look-around). Case sensitivity is encoded in the pattern via the (?i) inline flag when Self.case_sensitive is false.

Field Type Default Description
label String Custom category label surfaced in RedactionFinding.category.
pattern String Regex pattern (Rust regex crate dialect — no look-around).
caseSensitive Boolean serde(default = "default_case_sensitive") When true, match case-sensitively; otherwise prepend (?i) to the regex.
Methods
labeled()

Build a pattern with the given label (case-insensitive by default).

Signature:

@JvmStatic
fun labeled(label: String, pattern: String): RedactionPattern

Example:

val result = RedactionPattern.labeled("value", "value")

Parameters:

Name Type Required Description
label String Yes The label
pattern String Yes The pattern

Returns: RedactionPattern


RedactionReport

Audit report describing what the redaction processor found and how it replaced it.

The redactor returns this alongside the rewritten content so compliance, replay, and audit-log consumers can see exactly what fired. Offsets are relative to the original pre-redaction content and are intended for audit reconstruction only — the original bytes are dropped at the end of the pipeline.

Field Type Default Description
findings List<RedactionFinding> Individual redaction findings in original-source byte order.
totalRedacted Int Total number of redactions applied across the document.

RedactionTerm

One user-supplied literal term to redact.

Matched as a regex-escaped substring (so callers do not need to escape metacharacters themselves). Case-insensitive by default — set Self.case_sensitive to true for exact byte-match semantics.

Field Type Default Description
label String Custom category label surfaced in RedactionFinding.category.
value String Literal value to match. Regex metacharacters are escaped automatically.
caseSensitive Boolean serde(default = "default_case_sensitive") When true, match the value as-is; otherwise match ASCII-case-insensitively.
Methods
literal()

Build a term whose label is the literal value itself (case-insensitive).

Signature:

@JvmStatic
fun literal(value: String): RedactionTerm

Example:

val result = RedactionTerm.literal("value")

Parameters:

Name Type Required Description
value String Yes The value

Returns: RedactionTerm

labeled()

Build a term with a custom label.

Signature:

@JvmStatic
fun labeled(label: String, value: String): RedactionTerm

Example:

val result = RedactionTerm.labeled("value", "value")

Parameters:

Name Type Required Description
label String Yes The label
value String Yes The value

Returns: RedactionTerm


Registry

Sorted map of preset id → Preset.

Methods
loadEmbedded()

Build the registry from preset files embedded at compile time under src/presets/library/. Validates every file against the meta-schema.

Signature:

@Throws(LoadError::class)
@JvmStatic
fun loadEmbedded(): Registry

Example:

val result = Registry.loadEmbedded()

Returns: Registry

Errors: Throws LoadError.

global()

Return the global registry, loading it on first access.

Panics:

Panics if any embedded preset is malformed. The build-time validation test ensures this cannot happen for the embedded presets; a panic here indicates a build artifact problem, not a runtime error.

Signature:

@JvmStatic
fun global(): Registry

Example:

val result = Registry.global()

Returns: Registry

get()

Look up a preset by its identifier.

Signature:

fun get(id: String): Preset?

Example:

val result = instance.get("value")

Parameters:

Name Type Required Description
id String Yes The id

Returns: Preset?

summaries()

Materialize a PresetSummary list for the public registry endpoint.

Signature:

fun summaries(): List<PresetSummary>

Example:

val result = instance.summaries()

Returns: List<PresetSummary>

len()

Number of presets currently loaded.

Signature:

fun len(): Long

Example:

val result = instance.len()

Returns: Long

isEmpty()

Whether the registry contains zero presets.

Signature:

fun isEmpty(): Boolean

Example:

val result = instance.isEmpty()

Returns: Boolean

sampleBytes()

Read raw sample bytes for <preset_id> from library/<id>/samples/<name>. Returns null when the file is absent.

Signature:

fun sampleBytes(presetId: String, name: String): ByteArray?

Example:

val result = instance.sampleBytes("value", "value")

Parameters:

Name Type Required Description
presetId String Yes The preset id
name String Yes The name

Returns: ByteArray?

extendFromDir()

Load additional preset files from a runtime directory and insert them into this registry.

Reads every *.json file directly under dir (non-recursive), validates each against the meta-schema, and inserts it. Files that fail validation are rejected — the error is returned immediately and the registry is left in a partially-updated state. Existing entries with the same id are overwritten.

Returns the number of presets successfully loaded from dir.

Use case

This is the injection point for downstream catalogs: kreuzberg-cloud calls this once at startup to add its 20+ curated presets on top of the single embedded OSS preset.

Signature:

@Throws(LoadError::class)
fun extendFromDir(dir: Path): Long

Example:

val result = instance.extendFromDir("value")

Parameters:

Name Type Required Description
dir Path Yes The dir

Returns: Long

Errors: Throws LoadError.


Renderer

Trait for document renderers that convert InternalDocument to output strings.

Renderers are typically stateless converters that transform the internal document representation into a specific output format (Markdown, HTML, Djot, plain text, etc.). They participate in the standard Plugin lifecycle so custom renderers can be registered from any supported binding language.

The format name is exposed via Plugin.name. For stateless renderers the Plugin lifecycle methods (version, initialize, shutdown) all take no-op defaults and need not be overridden.

Thread Safety

Renderers must be Send + Sync (inherited from Plugin).

Methods
render()

Render an InternalDocument to the output format.

Returns:

The rendered output as a string.

Errors:

Returns an error if rendering fails.

Signature:

@Throws(Error::class)
fun render(doc: InternalDocument): String

Example:

val result = instance.render(InternalDocument())

Parameters:

Name Type Required Description
doc InternalDocument Yes The internal document to render

Returns: String

Errors: Throws Error.


RerankedDocument

A single document returned by the reranker, with its position in the input and score.

index maps back to the caller's original document list, so metadata arrays (e.g. IDs, paths) can be reordered without passing them through the reranker.

Since v5.0.

Field Type Default Description
index Long Position of this document in the original input documents slice.
score Float Relevance score in \[0, 1\]. Higher means more relevant to the query.
document String The document text.

RerankerBackend

Trait for in-process reranker backend plugins.

Cross-encoders score (query, document) pairs jointly and return a raw logit per document. The dispatcher in rerank applies sigmoid to convert logits to [0, 1] scores, sorts descending by score, and truncates to top_k.

Async to match the convention used by EmbeddingBackend and other plugin traits. Host-language bridges wrap their synchronous host callables in spawn_blocking or the equivalent.

Thread safety

Backends must be Send + Sync + 'static. They are stored in Arc<dyn RerankerBackend> and may be called concurrently from kreuzberg's dispatcher. If the backend's underlying model is not thread-safe, the backend itself must serialize access internally (e.g. via Mutex<Inner>).

Contract
  • rerank(query, documents) MUST return exactly documents.len() scores. The dispatcher validates this before sorting and returning to callers; a non-conforming backend surfaces as a KreuzbergError.Validation, not a panic.

  • Scores are raw logits in any range — callers must NOT assume [0, 1]. The dispatcher applies sigmoid before sorting.

  • rerank may be called from any thread. Its future must be Send (enforced by async_trait when #[async_trait] is used on non-WASM targets).

  • shutdown() (inherited from Plugin) may be invoked concurrently with an in-flight rerank() call. Implementations must tolerate this — letting in-flight calls finish via the Arc reference and only releasing shared state that isn't needed by rerank.

Runtime

The synchronous rerank entry uses tokio.task.block_in_place to await the trait's async rerank, which requires a multi-thread tokio runtime. Callers running inside a current_thread runtime must use rerank_async instead.

Since v5.0.

Methods
rerank()

Score a list of documents against a query.

Returns one raw logit per document in the same order as the input. The dispatcher applies sigmoid to convert to [0, 1] scores.

Errors:

Implementations should return Plugin for backend-specific failures. The dispatcher validates the returned length against documents.len() before sorting.

Signature:

@Throws(Error::class)
fun rerank(query: String, documents: List<String>): List<Float>

Example:

val result = instance.rerank("value", [])

Parameters:

Name Type Required Description
query String Yes The query
documents List<String> Yes The documents

Returns: List<Float>

Errors: Throws Error.


RerankerConfig

Configuration for the reranking pipeline.

Controls which model to use, how many results to return, and download/cache behavior for local ONNX models.

Since v5.0.

Field Type Default Description
model RerankerModelType RerankerModelType.Preset The reranker model to use (defaults to "balanced" preset if not specified).
topK Long? null Return at most this many documents. null returns all. Applied after sorting by score, so the highest-scoring documents are kept.
batchSize Long 32 Batch size for local ONNX cross-encoder inference.
showDownloadProgress Boolean false Show model download progress (local ONNX path only).
cacheDir Path? null Custom cache directory for model files. Defaults to ~/.cache/kreuzberg/rerankers/ if not specified.
acceleration AccelerationConfig? null Hardware acceleration for the reranker ONNX model. Controls which execution provider (CPU, CUDA, CoreML, TensorRT) is used for local inference. Defaults to null (auto-select per platform).
maxRerankDurationSecs Long? null Maximum wall-clock duration (in seconds) for a single rerank() call when using RerankerModelType.Plugin. Applies only to the in-process plugin path — protects against hung host-language backends. On timeout, the dispatcher returns Plugin instead of blocking forever. null disables the timeout. The default (60 seconds) is conservative for common in-process inference; increase for large document sets on slow hardware.
Methods
default()

Signature:

@JvmStatic
fun default(): RerankerConfig

Example:

val result = RerankerConfig.default()

Returns: RerankerConfig


RerankerPreset

Metadata for a bundled reranker preset.

All string fields are owned String for FFI compatibility — instances are safe to clone and pass across language boundaries.

Since v5.0.

Field Type Default Description
name String Short identifier (catalog name, e.g. "bge-reranker-base").
modelRepo String HuggingFace repository name for the model.
modelFile String Path to the ONNX model file within the repo.
additionalFiles List<String> /* serde(default) */ Sibling files that must be downloaded alongside model_file. Empty for most presets. Used by repos that split the weight blob — e.g. rozgo/bge-reranker-v2-m3 ships the model in model.onnx plus a co-located model.onnx.data payload.
maxLength Long Maximum token sequence length the model supports.
description String Human-readable description of the preset's intended use case.

ResolvedPreset

A preset merged with caller-supplied overrides (custom schema, prompt suffix, context map). Output is what the pipeline orchestrator consumes.

Field Type Default Description
id String Source preset identifier.
version String Source preset version.
fingerprint String Fingerprint of the source preset file, used as a cache token.
schemaName String Schema name forwarded to the LLM.
schema Any Effective JSON Schema (caller override or the preset's own).
systemPrompt String System prompt with rendered context appended.
mergeMode MergeMode Merge strategy for paginated outputs.
preferredCallMode CallMode Preferred call mode.
emitCitations Boolean Whether the prompt asks for per-field citations.

RevisionDelta

The content changes that make up a single revision.

For insertions and deletions the content field carries the added/removed lines as DiffLine.Added / DiffLine.Removed entries. For format changes, content is empty — the property diff is left as a TODO for a later enrichment pass.

Field Type Default Description
content List<DiffLine> \[\] Line-level content changes for this revision.
tableChanges List<CellChange> \[\] Cell-level table changes for this revision.

SecurityLimits

Configuration for security limits across extractors.

All limits are intentionally conservative to prevent DoS attacks while still supporting legitimate documents.

Field Type Default Description
maxArchiveSize Long 524288000 Maximum uncompressed size for archives (500 MB)
maxCompressionRatio Long 100 Maximum compression ratio before flagging as potential bomb (100:1)
maxFilesInArchive Long 10000 Maximum number of files in archive (10,000)
maxNestingDepth Long 1024 Maximum nesting depth for structures (100)
maxEntityLength Long 1048576 Maximum length of any single XML entity / attribute / token (1 MiB). This is a per-token cap, NOT a total cap — billion-laughs class attacks where a single entity expands to hundreds of MB are caught here, while normal long text content (a paragraph, a CDATA block) is caught by max_content_size instead.
maxContentSize Long 104857600 Maximum string growth per document (100 MB)
maxIterations Long 10000000 Maximum iterations per operation
maxXmlDepth Long 1024 Maximum XML depth (100 levels)
maxTableCells Long 100000 Maximum cells per table (100,000)
Methods
default()

Signature:

@JvmStatic
fun default(): SecurityLimits

Example:

val result = SecurityLimits.default()

Returns: SecurityLimits


ServerConfig

API server configuration.

This struct holds all configuration options for the Kreuzberg API server, including host/port settings, CORS configuration, and upload limits.

Defaults
  • host: "127.0.0.1" (localhost only)
  • port: 8000
  • cors_origins: empty listtor (allows all origins)
  • max_request_body_bytes: 104_857_600 (100 MB)
  • max_multipart_field_bytes: 104_857_600 (100 MB)
Field Type Default Description
host String Server host address (e.g., "127.0.0.1", "0.0.0.0")
port Short Server port number
corsOrigins List<String> \[\] CORS allowed origins. Empty vector means allow all origins. If this is an empty listtor, the server will accept requests from any origin. If populated with specific origins (e.g., "<https://example.com">), only those origins will be allowed.
maxRequestBodyBytes Long Maximum size of request body in bytes (default: 100 MB)
maxMultipartFieldBytes Long Maximum size of multipart fields in bytes (default: 100 MB)
Methods
default()

Signature:

@JvmStatic
fun default(): ServerConfig

Example:

val result = ServerConfig.default()

Returns: ServerConfig

listenAddr()

Get the server listen address (host:port).

Signature:

fun listenAddr(): String

Example:

val result = instance.listenAddr()

Returns: String

corsAllowsAll()

Check if CORS allows all origins.

Returns true if the cors_origins vector is empty, meaning all origins are allowed. Returns false if specific origins are configured.

Signature:

fun corsAllowsAll(): Boolean

Example:

val result = instance.corsAllowsAll()

Returns: Boolean

isOriginAllowed()

Check if a given origin is allowed by CORS configuration.

Returns true if:

  • CORS allows all origins (empty origins list), or
  • The given origin is in the allowed origins list

Signature:

fun isOriginAllowed(origin: String): Boolean

Example:

val result = instance.isOriginAllowed("value")

Parameters:

Name Type Required Description
origin String Yes The origin to check (e.g., "https://example.com")

Returns: Boolean

maxRequestBodyMb()

Get maximum request body size in megabytes (rounded up).

Signature:

fun maxRequestBodyMb(): Long

Example:

val result = instance.maxRequestBodyMb()

Returns: Long

maxMultipartFieldMb()

Get maximum multipart field size in megabytes (rounded up).

Signature:

fun maxMultipartFieldMb(): Long

Example:

val result = instance.maxMultipartFieldMb()

Returns: Long


StructuredData

Structured data (Schema.org, microdata, RDFa) block.

Field Type Default Description
dataType StructuredDataType Type of structured data
rawJson String Raw JSON string representation
schemaType String? null Schema type if detectable (e.g., "Article", "Event", "Product")

StructuredDataResult

Result of parsing a structured data file (JSON, JSONL, YAML, or TOML).

Field Type Default Description
content String The extracted text content, formatted for readability.
format String The source format identifier (e.g. "json", "yaml", "toml").
metadata Map<String, String> Key-value metadata extracted from recognized text fields.
textFields List<String> JSON paths of fields that were classified as text-bearing.

StructuredExtractionConfig

Configuration for LLM-based structured data extraction.

Sends extracted document content to a VLM with a JSON schema, returning structured data that conforms to the schema.

Field Type Default Description
schema Any JSON Schema defining the desired output structure.
schemaName String serde(default = "default_schema_name") Schema name passed to the LLM's structured output mode.
schemaDescription String? /* serde(default) */ Optional schema description for the LLM.
strict Boolean /* serde(default) */ Enable strict mode — output must exactly match the schema.
prompt String? /* serde(default) */ Custom Jinja2 extraction prompt template. When null, a default template is used. Available template variables: - {{ content }} — The extracted document text. - {{ schema }} — The JSON schema as a formatted string. - {{ schema_name }} — The schema name. - {{ schema_description }} — The schema description (may be empty).
llm LlmConfig LLM configuration for the extraction.

StructuredInput

Signals consumed by the call-mode heuristic.

All fields derive from a prior kreuzberg extraction — no double-work. This is a plain DTO; it intentionally has no dependency on internal kreuzberg extraction types so it can be constructed from any source.

Field Type Default Description
mimeType String MIME type, canonicalised to lowercase by the caller.
pageCount Int Number of pages in the document.
textCoverage Double Fraction of pages with a real text layer (0.0..=1.0).
avgCharsPerPage Double Average extracted characters per page.
embeddedImageCount Int Count of embedded images (figures, photos, signatures) discovered.
userForceVision Boolean When true, promote the result to at least StructuredCallMode.TextPlusVision.

StructuredThresholds

Thresholds for the structured-extraction call-mode heuristic.

All defaults are conservative starting points. Deployments should measure their own document corpus and override via their own config; these values are chosen to be safe-by-default, not to be optimal for any particular workload.

Construct custom thresholds with struct-update syntax:

Field Type Default Description
scanMaxCoverage Double 0.1 PDFs with text_coverage strictly below this are treated as scanned. Conservative default: 0.10 — deployments override via their own config after measuring their document corpus.
digitalMinCoverage Double 0.9 PDFs with text_coverage at or above this AND zero embedded images route to StructuredCallMode.TextOnly. Conservative default: 0.90 — deployments override via their own config after measuring their document corpus.
docxTextMinDensity Double 200 DOCX / HTML / text documents with avg_chars_per_page above this route to StructuredCallMode.TextOnly. Conservative default: 200.0 — deployments override via their own config after measuring their document corpus.
enableVisionFallback Boolean false When true, emit StructuredCallMode.TextOnlyWithVisionFallback instead of StructuredCallMode.TextOnly so the orchestrator can escalate to vision on low confidence. Conservative default: false — must be explicitly enabled per deployment after bench validation; deployments override via their own config.
Methods
default()

Signature:

@JvmStatic
fun default(): StructuredThresholds

Example:

val result = StructuredThresholds.default()

Returns: StructuredThresholds


SummarizationConfig

Since: v5.0

Configuration for the summarisation post-processor.

Field Type Default Description
strategy SummaryStrategy SummaryStrategy.Extractive Summarisation strategy.
maxTokens Int? null Maximum summary length in tokens. null lets the backend pick a default.
llm LlmConfig? null LLM configuration for the abstractive backend. Ignored when strategy = Extractive. Required when strategy = Abstractive.

SupportedFormat

A supported document format entry.

Represents a file extension and its corresponding MIME type that Kreuzberg can process.

Field Type Default Description
extension String File extension (without leading dot), e.g., "pdf", "docx"
mimeType String MIME type string, e.g., "application/pdf"

SvgOptions

SVG-specific configuration for the image-encode pipeline.

Applies when the source image is SVG or when the output format is set to ImageOutputFormat.Svg. Available when the svg feature is active.

Used via ImageExtractionConfig.svg.

Field Type Default Description
sanitize Boolean true Run SVG bytes through usvg sanitization (strips external href attributes, JavaScript event handlers, and foreignObject elements) even when the output format is Native. Defaults to true.
renderDpi Float 96 Target DPI when rasterizing SVG to a pixel-based format (PNG, JPEG, WebP, HEIF). The tree's viewBox is scaled by render_dpi / 96.0 before the pixel buffer is allocated. Defaults to 96.0 (1× CSS pixel density).
Methods
default()

Signature:

@JvmStatic
fun default(): SvgOptions

Example:

val result = SvgOptions.default()

Returns: SvgOptions


Table

Extracted table structure.

Represents a table detected and extracted from a document (PDF, image, etc.). Tables are converted to both structured cell data and Markdown format.

Field Type Default Description
cells List<List<String>> \[\] Table cells as a 2D vector (rows × columns)
markdown String Markdown representation of the table
pageNumber Int Page number where the table was found (1-indexed)
boundingBox BoundingBox? null Bounding box of the table on the page (PDF coordinates: x0=left, y0=bottom, x1=right, y1=top). Only populated for PDF-extracted tables when position data is available.

TableCell

Individual table cell with content and optional styling.

Future extension point for rich table support with cell-level metadata.

Field Type Default Description
content String Cell content as text
rowSpan Int Row span (number of rows this cell spans)
colSpan Int Column span (number of columns this cell spans)
isHeader Boolean Whether this is a header cell

TableDiff

Cell-level changes for a pair of tables that share the same index.

Field Type Default Description
fromIndex Long Zero-based index of the table in both a.tables and b.tables.
toIndex Long Zero-based index in b.tables (equal to from_index for same-dimension tables).
cellChanges List<CellChange> Cell-level changes within the table.

TableGrid

Structured table grid with cell-level metadata.

Stores row/column dimensions and a flat list of cells with position info.

Field Type Default Description
rows Int Number of rows in the table.
cols Int Number of columns in the table.
cells List<GridCell> \[\] All cells in row-major order.

TesseractConfig

Tesseract OCR configuration.

Provides fine-grained control over Tesseract OCR engine parameters. Most users can use the defaults, but these settings allow optimization for specific document types (invoices, handwriting, etc.).

Field Type Default Description
language List<String> \[\] Language code(s) for OCR recognition. Accepts either a single language code ("eng") or a list (["eng", "deu"]). For Tesseract backend, languages are joined with "+".
psm Int 3 Page Segmentation Mode (0-13). Common values: - 3: Fully automatic page segmentation (native default) - 6: Assume a single uniform block of text (WASM default — avoids layout-analysis hang) - 11: Sparse text with no particular order
outputFormat String "markdown" Output format ("text" or "markdown")
oem Int 3 OCR Engine Mode (0-3). - 0: Legacy engine only - 1: Neural nets (LSTM) only (usually best) - 2: Legacy + LSTM - 3: Default (based on what's available)
minConfidence Double 0 Minimum confidence threshold (0.0-100.0). Words with confidence below this threshold may be rejected or flagged.
preprocessing ImagePreprocessingConfig? null Image preprocessing configuration. Controls how images are preprocessed before OCR. Can significantly improve quality for scanned documents or low-quality images.
enableTableDetection Boolean true Enable automatic table detection and reconstruction
tableMinConfidence Double 0 Minimum confidence threshold for table detection (0.0-1.0)
tableColumnThreshold Int 50 Column threshold for table detection (pixels)
tableRowThresholdRatio Double 0.5 Row threshold ratio for table detection (0.0-1.0)
useCache Boolean true Enable OCR result caching
classifyUsePreAdaptedTemplates Boolean true Use pre-adapted templates for character classification
languageModelNgramOn Boolean false Enable N-gram language model
tesseditDontBlkrejGoodWds Boolean true Don't reject good words during block-level processing
tesseditDontRowrejGoodWds Boolean true Don't reject good words during row-level processing
tesseditEnableDictCorrection Boolean true Enable dictionary correction
tesseditCharWhitelist String "" Whitelist of allowed characters (empty = all allowed)
tesseditCharBlacklist String "" Blacklist of forbidden characters (empty = none forbidden)
tesseditUsePrimaryParamsModel Boolean true Use primary language params model
textordSpaceSizeIsVariable Boolean true Variable-width space detection
thresholdingMethod Boolean false Use adaptive thresholding method
Methods
default()

Signature:

@JvmStatic
fun default(): TesseractConfig

Example:

val result = TesseractConfig.default()

Returns: TesseractConfig


TextAnnotation

Inline text annotation — byte-range based formatting and links.

Annotations reference byte offsets into the node's text content, enabling precise identification of formatted regions.

Field Type Default Description
start Int Start byte offset in the node's text content (inclusive).
end Int End byte offset in the node's text content (exclusive).
kind AnnotationKind Annotation type.

TextExtractionResult

Plain text and Markdown extraction result.

Contains the extracted text along with statistics and, for Markdown files, structural elements like headers and links.

Field Type Default Description
content String Extracted text content
lineCount Long Number of lines
wordCount Long Number of words
characterCount Long Number of characters
headers List<String>? null Markdown headers (text only, Markdown files only)

TextMetadata

Text/Markdown metadata.

Extracted from plain text and Markdown files. Includes word counts and, for Markdown, structural elements like headers and links.

Field Type Default Description
lineCount Int Number of lines in the document
wordCount Int Number of words
characterCount Int Number of characters
headers List<String>? \[\] Markdown headers (headings text only, for Markdown files)

TokenCounter

Per-category running counter for RedactionStrategy.TokenReplace.

Methods
new()

Create a fresh counter with no previous state.

Signature:

@JvmStatic
fun new(): TokenCounter

Example:

val result = TokenCounter.new()

Returns: TokenCounter


TokenReductionConfig

Configuration for the token-reduction pipeline.

Field Type Default Description
level ReductionLevel ReductionLevel.Moderate Reduction intensity level.
languageHint String? null ISO 639-1 language code hint for stopword selection (e.g. "en", "de").
preserveMarkdown Boolean false Preserve Markdown formatting tokens during reduction.
preserveCode Boolean true Preserve code block contents unchanged.
semanticThreshold Float 0.3 Cosine similarity threshold below which sentences are considered dissimilar.
enableParallel Boolean true Use Rayon parallel iterators for multi-core processing.
useSimd Boolean true Use SIMD-optimized text scanning where available.
customStopwords Map<String, List<String>>? null Per-language custom stopword lists (language_code → stopword_list).
preservePatterns List<String> \[\] Regex patterns whose matched text is always preserved unchanged.
targetReduction Float? null Target fraction of text to retain (0.0–1.0); null = no fixed target.
enableSemanticClustering Boolean false Group semantically similar sentences and emit only one per cluster.
Methods
default()

Signature:

@JvmStatic
fun default(): TokenReductionConfig

Example:

val result = TokenReductionConfig.default()

Returns: TokenReductionConfig


TokenReductionOptions

Token reduction configuration.

Field Type Default Description
mode String Reduction mode: "off", "light", "moderate", "aggressive", "maximum"
preserveImportantWords Boolean true Preserve important words (capitalized, technical terms)
Methods
default()

Signature:

@JvmStatic
fun default(): TokenReductionOptions

Example:

val result = TokenReductionOptions.default()

Returns: TokenReductionOptions


TranscriptionConfig

Configuration for audio/video transcription (speech-to-text).

When present and enabled, Kreuzberg will route audio and video files (mp3, mp4, m4a, wav, webm, etc.) through the transcription pipeline.

The heavy dependencies (ORT, hf-hub, symphonia) are only pulled when the transcription feature is enabled. The config struct itself is available under transcription-types so that ExtractionConfig round-trips on all targets.

All fields have sensible defaults. The recommended starting point is:

[extraction.transcription]
enabled = true
model = "tiny"
Field Type Default Description
enabled Boolean true Master switch. When false the block is ignored and audio files fall back to the normal "unsupported format" path.
model WhisperModel WhisperModel.Tiny Whisper model size to use. Smaller = faster + lower memory. tiny is the pragmatic default for first-time users and CI.
language String? null Optional language hint (ISO-639-1 code, e.g. "en", "de"). When null (default), the current engine falls back to English. For deterministic production output, always set this explicitly.
timestamps Boolean false Whether to request segment-level timestamps. Accepted for forward compatibility. The current engine always uses <\|notimestamps\|> and does not emit segment metadata yet.
maxDurationMs Long? null Hard safety limit on input duration (milliseconds). Files longer than this are rejected after decode, before model work. Default: 30 minutes. Set to null to disable (not recommended for untrusted input).
maxBytes Long? null Hard safety limit on input size (bytes). Default: 512 MiB. Protects against pathological or malicious uploads.
timeoutMs Long? null Wall-clock timeout for the entire transcription operation (ms). Default: 10 minutes. Reserved for timeout enforcement; the current extractor does not enforce this field yet.
modelCacheDir Path? null Override the directory used for Whisper model cache. When null, uses the centralized resolver: KREUZBERG_CACHE_DIR/whisper or the platform default (~/.cache/kreuzberg/whisper on Linux, etc.).
allowNetwork Boolean true Allow network access to download models from Hugging Face Hub. When false, only previously cached models may be used. Useful for air-gapped or fully offline deployments.
verifyHash Boolean true Request SHA256 verification of downloaded model files. Reserved for the checksum table follow-up. The current resolver logs a warning and treats this as a no-op.
Methods
default()

Signature:

@JvmStatic
fun default(): TranscriptionConfig

Example:

val result = TranscriptionConfig.default()

Returns: TranscriptionConfig


Translation

Translation of the extracted content.

Holds the translated rendition of ExtractionResult.content and (when preserve_markup was requested) the translated formatted_content. Chunks are translated in place inside ExtractionResult.chunks[*].content rather than duplicated here.

Field Type Default Description
targetLang String BCP-47 language tag the translation was produced into (e.g. "de", "fr-CA").
sourceLang String? null BCP-47 source language. null when the translation backend was asked to detect.
content String Translated plain-text body. Matches the shape of ExtractionResult.content.
formattedContent String? null Translated markup body (Markdown / HTML / etc.) when preserve_markup was enabled on the config. null otherwise.

TranslationConfig

Since: v5.0

Configuration for the translation post-processor.

Field Type Default Description
targetLang String BCP-47 language tag for the target language (e.g. "de", "fr-CA").
sourceLang String? null Optional explicit source language. null asks the backend to auto-detect.
preserveMarkup Boolean /* serde(default) */ Translate the formatted (Markdown/HTML) rendition alongside plain text when formatted_content is present.
llm LlmConfig LLM configuration used for translation.

TreeSitterConfig

Configuration for tree-sitter language pack integration.

Controls grammar download behavior and code analysis options.

Example (TOML)
[tree_sitter]
languages = ["python", "rust"]
groups = ["web"]

[tree_sitter.process]
structure = true
comments = true
docstrings = true
Field Type Default Description
enabled Boolean true Enable code intelligence processing (default: true). When false, tree-sitter analysis is completely skipped even if the config section is present.
cacheDir Path? null Custom cache directory for downloaded grammars. When null, uses the default: ~/.cache/tree-sitter-language-pack/v{version}/libs/.
languages List<String>? null Languages to pre-download on init (e.g., \["python", "rust"\]).
groups List<String>? null Language groups to pre-download (e.g., \["web", "systems", "scripting"\]).
process TreeSitterProcessConfig Processing options for code analysis.
Methods
default()

Signature:

@JvmStatic
fun default(): TreeSitterConfig

Example:

val result = TreeSitterConfig.default()

Returns: TreeSitterConfig


TreeSitterProcessConfig

Processing options for tree-sitter code analysis.

Controls which analysis features are enabled when extracting code files.

Field Type Default Description
structure Boolean true Extract structural items (functions, classes, structs, etc.). Default: true.
imports Boolean true Extract import statements. Default: true.
exports Boolean true Extract export statements. Default: true.
comments Boolean false Extract comments. Default: false.
docstrings Boolean false Extract docstrings. Default: false.
symbols Boolean false Extract symbol definitions. Default: false.
diagnostics Boolean false Include parse diagnostics. Default: false.
chunkMaxSize Long? null Maximum chunk size in bytes. null disables chunking.
contentMode CodeContentMode CodeContentMode.Chunks Content rendering mode for code extraction.
Methods
default()

Signature:

@JvmStatic
fun default(): TreeSitterProcessConfig

Example:

val result = TreeSitterProcessConfig.default()

Returns: TreeSitterProcessConfig


UserChunkConfig

User-provided chunk configuration.

Field Type Default Description
pageRanges List<PageRange>? \[\] User-specified page ranges (overrides automatic chunking).
pagesPerChunk Int? null User-specified pages per chunk (overrides automatic calculation).
forceChunking Boolean Force chunking even for small documents.
disableChunking Boolean Disable chunking even for large documents.

Validator

Trait for validator plugins.

Validators check extraction results for quality, completeness, or correctness. Unlike post-processors, validator errors fail fast - if a validator returns an error, the extraction fails immediately.

Use Cases
  • Quality Gates: Ensure extracted content meets minimum quality standards
  • Compliance: Verify content meets regulatory requirements
  • Content Filtering: Reject documents containing unwanted content
  • Format Validation: Verify extracted content structure
  • Security Checks: Scan for malicious content
Error Handling

Validator errors are fatal - they cause the extraction to fail and bubble up to the caller. Use validators for hard requirements that must be met.

For non-fatal checks, use post-processors instead.

Thread Safety

Validators must be thread-safe (Send + Sync).

Methods
validate()

Validate an extraction result.

Check the extraction result and return Ok(()) if valid, or an error if validation fails.

Returns:

  • Ok(()) if validation passes
  • Err(...) if validation fails (extraction will fail)

Errors:

  • KreuzbergError.Validation - Validation failed
  • Any other error type appropriate for the failure
Example - Content Length Validation
Example - Quality Score Validation
Example - Security Validation

Signature:

@Throws(Error::class)
fun validate(result: ExtractionResult, config: ExtractionConfig)

Example:

instance.validate(ExtractionResult(), ExtractionConfig())

Parameters:

Name Type Required Description
result ExtractionResult Yes The extraction result to validate
config ExtractionConfig Yes Extraction configuration

Returns: No return value.

Errors: Throws Error.

shouldValidate()

Optional: Check if this validator should run for a given result.

Allows conditional validation based on MIME type, metadata, or content. Defaults to true (always run).

Returns:

true if the validator should run, false to skip.

Signature:

fun shouldValidate(result: ExtractionResult, config: ExtractionConfig): Boolean

Example:

val result = instance.shouldValidate(ExtractionResult(), ExtractionConfig())

Parameters:

Name Type Required Description
result ExtractionResult Yes The extraction result
config ExtractionConfig Yes The extraction config

Returns: Boolean

priority()

Optional: Get the validation priority.

Higher priority validators run first. Useful for ordering validation checks (e.g., run cheap validations before expensive ones).

Default priority is 50.

Returns:

Priority value (higher = runs earlier).

Signature:

fun priority(): Int

Example:

val result = instance.priority()

Returns: Int


XlsxAppProperties

Application properties from docProps/app.xml for XLSX

Contains Excel-specific document metadata.

Field Type Default Description
application String? null Application name (e.g., "Microsoft Excel")
appVersion String? null Application version
docSecurity Int? null Document security level
scaleCrop Boolean? null Scale crop flag
linksUpToDate Boolean? null Links up to date flag
sharedDoc Boolean? null Shared document flag
hyperlinksChanged Boolean? null Hyperlinks changed flag
company String? null Company name
worksheetNames List<String> \[\] Worksheet names

XmlExtractionResult

XML extraction result.

Contains extracted text content from XML files along with structural statistics about the XML document.

Field Type Default Description
content String Extracted text content (XML structure filtered out)
elementCount Long Total number of XML elements processed
uniqueElements List<String> List of unique element names found (sorted)

XmlMetadata

XML metadata extracted during XML parsing.

Provides statistics about XML document structure.

Field Type Default Description
elementCount Int Total number of XML elements processed
uniqueElements List<String> \[\] List of unique element tag names (sorted)

YakeParams

YAKE-specific parameters.

Field Type Default Description
windowSize Long 2 Window size for co-occurrence analysis (default: 2). Controls the context window for computing co-occurrence statistics.
Methods
default()

Signature:

@JvmStatic
fun default(): YakeParams

Example:

val result = YakeParams.default()

Returns: YakeParams


YearRange

Year range for bibliographic metadata.

Field Type Default Description
min Int? null Earliest (minimum) year in the range.
max Int? null Latest (maximum) year in the range.
years List<Int> /* serde(default) */ All individual years present in the collection.

Enums

ExecutionProviderType

ONNX Runtime execution provider type.

Determines which hardware backend is used for model inference. Auto (default) selects the best available provider per platform.

Value Description
Auto Auto-select: CoreML on macOS, CUDA on Linux, CPU elsewhere.
Cpu CPU execution provider (always available).
CoreMl Apple CoreML (macOS/iOS Neural Engine + GPU).
Cuda NVIDIA CUDA GPU acceleration.
TensorRt NVIDIA TensorRT (optimized CUDA inference).

ImageOutputFormat

Target format for re-encoding extracted images.

Controls whether and how extracted images are normalised to a uniform container format before being returned in ExtractionResult.images. The default (Native) preserves the format produced by each extractor without any additional encode pass.

Callers that need uniform output — e.g. cloud pipelines that always store WebP thumbnails — set this once on ImageExtractionConfig.output_format rather than re-encoding downstream.

Serde shape

Uses a tagged enum: {"type": "native"}, {"type": "png"}, {"type": "jpeg", "quality": 90}, etc.

Value Description
Native Preserve whatever format the extractor produced (default). No re-encode pass is performed. ExtractedImage.format reflects the source format: JPEG for embedded PDF images, PNG for rasterised content, or the native container format from office documents.
Png Re-encode all extracted images as PNG (lossless).
Jpeg Re-encode all extracted images as JPEG at the given quality level. quality must be in 1..=100. Values outside this range are clamped and a warning is emitted. Higher values produce larger files with less artefacting; 85 is a reasonable default. — Fields: quality: Byte
Webp Re-encode all extracted images as WebP at the given quality level. quality must be in 1..=100. Values outside this range are clamped and a warning is emitted. 80 is a reasonable default. — Fields: quality: Byte
Heif Re-encode all extracted images as HEIF/HEIC at the given quality level. Requires the heic feature. quality must be in 1..=100. Values outside this range are clamped and a warning is emitted. 80 is a reasonable default. — Fields: quality: Byte
Svg Output pure-vector SVG. Lossless. Raster sources are not re-encoded (a warning is emitted and the image bytes are left untouched). When the source is already SVG, the bytes are passed through the usvg sanitizer (strips external hrefs, JS event handlers, and foreignObject elements) when SvgOptions.sanitize is true. Requires the svg feature.

OutputFormat

Output format for extraction results.

Controls the format of the content field in ExtractionResult. When set to Markdown, Djot, or Html, the output uses that format. Plain returns the raw extracted text. Structured returns JSON with full OCR element data including bounding boxes and confidence scores.

Value Description
Plain Plain text content only (default)
Markdown Markdown format
Djot Djot markup format
Html HTML format
Json JSON tree format with heading-driven sections.
Structured Structured JSON format with full OCR element metadata.
Custom Custom renderer registered via the RendererRegistry. The string is the renderer name (e.g., "docx", "latex"). — Fields: 0: String

HtmlTheme

Built-in HTML theme selection.

Value Description
Default Sensible defaults: system font stack, neutral colours, readable line measure. CSS custom properties (--kb-*) are all defined so user CSS can override individual values.
GitHub GitHub Markdown-inspired palette and spacing.
Dark Dark background, light text.
Light Minimal light theme with generous whitespace.
Unstyled No built-in stylesheet emitted. CSS custom properties are still defined on :root so user stylesheets can reference var(--kb-*) tokens.

TableModel

Which table structure recognition model to use.

Controls the model used for table cell detection within layout-detected table regions. Wire format is snake_case in all serializers (JSON, TOML, YAML).

Value Description
Tatr TATR (Table Transformer) -- default, 30MB, DETR-based row/column detection.
SlanetWired SLANeXT wired variant -- 365MB, optimized for bordered tables.
SlanetWireless SLANeXT wireless variant -- 365MB, optimized for borderless tables.
SlanetPlus SLANet-plus -- 7.78MB, lightweight general-purpose.
SlanetAuto Classifier-routed SLANeXT: auto-select wired/wireless per table. Uses PP-LCNet classifier (6.78MB) + both SLANeXT variants (730MB total).
Disabled Disable table structure model inference entirely; use heuristic path only.

CallMode

How a structured-extraction preset is dispatched to the model.

This is the preset-facing call mode (the preferred_call_mode field of a Preset). The richer runtime decision enum used by the structured pipeline — which adds Skip and TextOnlyWithVisionFallback — lives in crate.heuristics.structured.StructuredCallMode; this 3-variant type is the stable, serializable surface presets and bindings depend on.

Value Description
TextOnly Use the extracted text only.
VisionOnly Use rasterized page images only.
TextPlusVision Provide both extracted text and page images to the model.

MergeMode

How partial results from multiple model calls (e.g. per page batch) are combined.

Canonical home for the merge strategy referenced by presets and by the structured pipeline's post-processing. There is intentionally only one merge type across the crate — do not introduce a second.

Value Description
ObjectMerge Deep-merge JSON objects field by field (later calls fill missing fields).
ArrayConcat Concatenate top-level arrays across calls.
ObjectFirst Keep the first non-empty result; ignore subsequent calls.

NerBackendKind

NER backend selector.

Value Description
Onnx gline-rs ONNX inference. Requires ner-onnx feature. Models download lazily from HuggingFace via model_download.hf_download.
Llm liter-llm zero-shot NER via structured-output prompts. Requires ner-llm feature. Useful when domain-specific categories outstrip the ONNX taxonomy.

VlmFallbackPolicy

Policy controlling when VLM (Vision Language Model) OCR is used as a fallback.

This knob is syntactic sugar over the explicit OcrPipelineConfig stage ordering. When vlm_fallback is set and pipeline is null, an equivalent pipeline is synthesised at extraction time:

  • VlmFallbackPolicy.Disabled — no synthesis; single-backend mode (default).
  • VlmFallbackPolicy.OnLowQuality — tries the classical backend first; if the result scores below quality_threshold, tries VLM.

  • VlmFallbackPolicy.Always — skips the classical backend and sends every page to the VLM.

When OcrConfig.pipeline is explicitly set, vlm_fallback is ignored — the explicit pipeline takes precedence.

Errors:

Both OnLowQuality and Always require OcrConfig.vlm_config to be Some. Constructing an OcrConfig with one of these policies but no vlm_config is detected by OcrConfig.validate and will surface as a Validation error at extraction time, not a panic.

Value Description
Disabled No VLM fallback (default). Behaves identically to the pre-policy single-backend mode.
OnLowQuality Try the classical OCR backend first. If the quality score is below quality_threshold, send the page to the VLM. quality_threshold is in the \[0.0, 1.0\] range produced by calculate_quality_score. A value of 0.5 is a reasonable starting point; calibrate with the Stage 0 benchmark harness. — Fields: qualityThreshold: Double
Always Skip the classical OCR backend entirely. Every page is sent to the VLM.

TableChunkingMode

Controls how markdown tables are handled when they exceed the chunk size limit.

Only applies when chunker_type is Markdown.

Variants

  • Split - Default behavior: tables are split at row boundaries like any other block element. Continuation chunks contain only data rows without the header, which can break downstream consumers that need column context.

  • RepeatHeader - Prepend the table header (header row + separator row) to every continuation chunk that contains data rows from the same table. Adds a small amount of duplicate text but ensures each chunk is self-contained for extraction, search, and LLM consumption.

Value Description
Split Split tables at row boundaries (default). Continuation chunks have no header.
RepeatHeader Prepend the table header to every chunk that continues a split table.

ChunkerType

Type of text chunker to use.

Variants

  • Text - Generic text splitter, splits on whitespace and punctuation
  • Markdown - Markdown-aware splitter, preserves formatting and structure
  • Yaml - YAML-aware splitter, creates one chunk per top-level key
  • Semantic - Topic-aware chunker. With an EmbeddingConfig, splits at embedding-based topic shifts tuned by topic_threshold (default 0.75, lower = more splits). Without an embedding, falls back to a structural-boundary heuristic (ALL-CAPS headers, numbered sections, blank-line paragraphs) and merges groups into chunks capped at max_characters (default 1000). topic_threshold has no effect in the fallback path. For best results, pair with an embedding model.
Value Description
Text Generic whitespace- and punctuation-aware text splitter (default).
Markdown Markdown-aware splitter that preserves heading and code-block boundaries.
Yaml YAML-aware splitter that creates one chunk per top-level key.
Semantic Topic-aware chunker that splits at embedding-based topic shifts.

ChunkSizing

How chunk size is measured.

Defaults to Characters (Unicode character count). When using token-based sizing, chunks are sized by token count according to the specified tokenizer.

Token-based sizing uses HuggingFace tokenizers loaded at runtime. Any tokenizer available on HuggingFace Hub can be used, including OpenAI-compatible tokenizers (e.g., Xenova/gpt-4o, Xenova/cl100k_base).

Value Description
Characters Size measured in Unicode characters (default).
Tokenizer Size measured in tokens from a HuggingFace tokenizer. — Fields: model: String, cacheDir: Path

EmbeddingModelType

Embedding model types supported by Kreuzberg.

Value Description
Preset Use a preset model configuration (recommended) — Fields: name: String
Custom Use a custom ONNX model from HuggingFace — Fields: modelId: String, dimensions: Long
Llm Provider-hosted embedding model via liter-llm. Uses the model specified in the nested LlmConfig (e.g., "openai/text-embedding-3-small"). — Fields: llm: LlmConfig
Plugin In-process embedding backend registered via the plugin system. The caller registers an EmbeddingBackend once (e.g. a wrapper around an already-loaded llama-cpp-python, sentence-transformers, or tuned ONNX model), then references it by name in config. Kreuzberg calls back into the registered backend during chunking and standalone embed requests — no HuggingFace download, no ONNX Runtime requirement, no HTTP sidecar. When this variant is selected, only the following EmbeddingConfig fields apply: normalize (post-call L2 normalization) and max_embed_duration_secs (dispatcher timeout). Model-loading fields (batch_size, cache_dir, show_download_progress, acceleration) are ignored — the host owns the model lifecycle. Semantic chunking falls back to ChunkingConfig.max_characters when this variant is used, since there is no preset to look a chunk-size ceiling up against — size your context window via max_characters directly. See register_embedding_backend. — Fields: name: String

RerankerModelType

Reranker model types supported by Kreuzberg.

Since v5.0.

Value Description
Preset Use a preset cross-encoder model (recommended). — Fields: name: String
Custom Use a custom ONNX cross-encoder from HuggingFace. — Fields: modelId: String, modelFile: String, additionalFiles: List<String>, maxLength: Long
Llm Provider-hosted reranker via liter-llm (e.g. Cohere, Jina, Voyage). The model in the nested LlmConfig must be a rerank-capable model ID (e.g. "cohere/rerank-english-v3.0"). — Fields: llm: LlmConfig
Plugin In-process reranker registered via the plugin system. The caller registers a RerankerBackend once (e.g. a wrapper around a sentence-transformers cross-encoder or a provider client), then references it by name in config. Kreuzberg calls back into the registered backend — no HuggingFace download, no ONNX Runtime requirement. When this variant is selected, only max_rerank_duration_secs applies. Model-loading fields (batch_size, cache_dir, show_download_progress, acceleration) are ignored — the host owns the model lifecycle. See register_reranker_backend. — Fields: name: String

WhisperModel

Supported Whisper model sizes.

These map to published ONNX exports on Hugging Face (onnx-community or similar orgs). The actual filenames and repos are resolved inside the transcription engine.

Value Description
Tiny Smallest, fastest, lowest quality. Good default for development and CI.
Base Reasonable quality/speed tradeoff.
Small Better accuracy with higher memory and cache use.
Medium High quality; slower and more memory-intensive.
LargeV3 Best quality (large-v3). Use only when latency and memory use are acceptable.

CodeContentMode

Content rendering mode for code extraction.

Controls how extracted code content is represented in the content field of ExtractionResult.

Value Description
Chunks Use TSLP semantic chunks as content (default).
Raw Use raw source code as content.
Structure Emit function/class headings + docstrings (no code bodies).

ListType

Type of list detection.

Value Description
Bullet Bullet points (-, *, •, etc.)
Numbered Numbered lists (1., 2., etc.)
Lettered Lettered lists (a., b., A., B., etc.)
Indented Indented items

OcrBackendType

OCR backend types.

Value Description
Tesseract Tesseract OCR (native Rust binding)
EasyOcr EasyOCR (Python-based, via FFI)
PaddleOcr PaddleOCR (Python-based, via FFI)
Candle Candle-based VLM OCR (TrOCR, PaddleOCR-VL).
Custom Custom/third-party OCR backend

ProcessingStage

Processing stages for post-processors.

Post-processors are executed in stage order (Early → Middle → Late). Use stages to control the order of post-processing operations.

Value Description
Early Early stage - foundational processing. Use for: - Language detection - Character encoding normalization - Entity extraction (NER) - Text quality scoring
Middle Middle stage - content transformation. Use for: - Keyword extraction - Token reduction - Text summarization - Semantic analysis
Late Late stage - final enrichment. Use for: - Custom user hooks - Analytics/logging - Final validation - Output formatting

ReductionLevel

Intensity level for the token-reduction pipeline.

Value Description
Off No reduction applied; text is returned as-is.
Light Remove only the most common stopwords.
Moderate Balanced stopword removal and redundancy filtering.
Aggressive Aggressive filtering; may remove less common content words.
Maximum Maximum compression; prioritizes brevity over completeness.

PdfAnnotationType

Type of PDF annotation.

Value Description
Text Sticky note / text annotation
Highlight Highlighted text region
Link Hyperlink annotation
Stamp Rubber stamp annotation
Underline Underline text markup
StrikeOut Strikeout text markup
Other Any other annotation type

BlockType

Types of block-level elements in Djot.

Value Description
Paragraph Standard prose paragraph.
Heading Section heading (level stored in FormattedBlock.level).
Blockquote Block quotation container.
CodeBlock Fenced or indented code block.
ListItem Individual item within a list.
OrderedList Numbered (ordered) list container.
BulletList Unnumbered (bullet) list container.
TaskList Task / checkbox list container.
DefinitionList Definition list container.
DefinitionTerm Term part of a definition list entry.
DefinitionDescription Description / definition part of a definition list entry.
Div Generic div container with optional attributes.
Section Logical section container, often associated with a heading.
ThematicBreak Horizontal rule / thematic break.
RawBlock Raw content block in a specified format (e.g. HTML, LaTeX).
MathDisplay Display-mode mathematical expression.

InlineType

Types of inline elements in Djot.

Value Description
Text Plain text run.
Strong Bold / strong emphasis.
Emphasis Italic / regular emphasis.
Highlight Highlighted text (marker pen).
Subscript Subscript text.
Superscript Superscript text.
Insert Inserted text (tracked change).
Delete Deleted text (tracked change).
Code Inline code span.
Link Hyperlink with URL.
Image Inline image reference.
Span Generic inline span with optional attributes.
Math Inline mathematical expression.
RawInline Raw inline content in a specified format.
FootnoteRef Footnote reference marker.
Symbol Named symbol or emoji shortcode.

RelationshipKind

Semantic kind of a relationship between document elements.

Value Description
FootnoteReference Footnote marker -> footnote definition.
CitationReference Citation marker -> bibliography entry.
InternalLink Internal anchor link (#id) -> target heading/element.
Caption Caption paragraph -> figure/table it describes.
Label Label -> labeled element (HTML <label for>, LaTeX \label{}).
TocEntry TOC entry -> target section.
CrossReference Cross-reference (LaTeX \ref{}, DOCX cross-reference field).

ContentLayer

Content layer classification for document nodes.

Replaces separate body/furniture arrays with per-node granularity.

Value Description
Body Main document body content.
Header Page/section header (running header).
Footer Page/section footer (running footer).
Footnote Footnote content.

NodeContent

Tagged enum for node content. Each variant carries only type-specific data.

Uses #[serde(tag = "node_type")] to avoid "type" keyword collision in Go/Java/TypeScript bindings.

Value Description
Title Document title. — Fields: text: String
Heading Section heading with level (1-6). — Fields: level: Byte, text: String
Paragraph Body text paragraph. — Fields: text: String
List List container — children are ListItem nodes. — Fields: ordered: Boolean
ListItem Individual list item. — Fields: text: String
Table Table with structured cell grid. — Fields: grid: TableGrid
Image Image reference. — Fields: description: String, imageIndex: Int, src: String
Code Code block. — Fields: text: String, language: String
Quote Block quote — container, children carry the quoted content.
Formula Mathematical formula / equation. — Fields: text: String
Footnote Footnote reference content. — Fields: text: String
Group Logical grouping container (section, key-value area). heading_level + heading_text capture the section heading directly rather than relying on a first-child positional convention. — Fields: label: String, headingLevel: Byte, headingText: String
PageBreak Page break marker.
Slide Presentation slide container — children are the slide's content nodes. — Fields: number: Int, title: String
DefinitionList Definition list container — children are DefinitionItem nodes.
DefinitionItem Individual definition list entry with term and definition. — Fields: term: String, definition: String
Citation Citation or bibliographic reference. — Fields: key: String, text: String
Admonition Admonition / callout container (note, warning, tip, etc.). Children carry the admonition body content. — Fields: kind: String, title: String
RawBlock Raw block preserved verbatim from the source format. Used for content that cannot be mapped to a semantic node type (e.g. JSX in MDX, raw LaTeX in markdown, embedded HTML). — Fields: format: String, content: String
MetadataBlock Structured metadata block (email headers, YAML frontmatter, etc.).

AnnotationKind

Types of inline text annotations.

Value Description
Bold Bold (strong) text formatting.
Italic Italic (emphasis) text formatting.
Underline Underlined text.
Strikethrough Strikethrough text.
Code Inline code span.
Subscript Subscript text.
Superscript Superscript text.
Link Hyperlink annotation. — Fields: url: String, title: String
Highlight Highlighted text (PDF highlights, HTML <mark>).
Color Text color (CSS-compatible value, e.g. "#ff0000", "red"). — Fields: value: String
FontSize Font size with units (e.g. "12pt", "1.2em", "16px"). — Fields: value: String
Custom Extensible annotation for format-specific styling. — Fields: name: String, value: String

EntityCategory

Standard entity categories produced by built-in NER backends.

The Custom(String) variant lets caller-supplied categories (e.g. LLM schemas) flow through without losing fidelity to the consumer.

Value Description
Person A person's name.
Organization A company, institution, or organisation name.
Location A geographic location (city, country, address).
Date A calendar date.
Time A time of day or duration.
Money A monetary amount with optional currency.
Percent A percentage value.
Email An email address.
Phone A phone number.
Url A URL or URI.
Custom A caller-supplied custom category label. — Fields: 0: String

ExtractionMethod

How the extracted text was produced.

Value Description
Native Text extracted directly from the document's native format (no OCR).
Ocr All text was obtained via OCR (e.g. scanned image-only PDF).
Mixed Text came from a combination of native extraction and OCR.

ChunkType

Semantic structural classification of a text chunk.

Assigned by the heuristic classifier in chunking.classifier. Defaults to Unknown when no rule matches. Designed to be extended in future versions without breaking changes.

Value Description
Heading Section heading or document title.
PartyList Party list: names, addresses, and signatories.
Definitions Definition clause ("X means…", "X shall mean…").
OperativeClause Operative clause containing legal/contractual action verbs.
SignatureBlock Signature block with signatures, names, and dates.
Schedule Schedule, annex, appendix, or exhibit section.
TableLike Table-like content with aligned columns or repeated patterns.
Formula Mathematical formula or equation.
CodeBlock Code block or preformatted content.
Image Embedded or referenced image content.
OrgChart Organizational chart or hierarchy diagram.
Diagram Diagram, figure, or visual illustration.
Unknown Unclassified or mixed content.

ImageKind

Heuristic classification of what an image likely depicts.

Value Description
Photograph Photographic image (natural scene, photograph)
Diagram Technical or schematic diagram
Chart Chart, graph, or plot
Drawing Freehand or technical drawing
TextBlock Text-heavy image (scanned text, document)
Decoration Decorative element or border
Logo Logo or brand mark
Icon Small icon
TileFragment Fragment of a larger tiled image (tile of a technical drawing)
Mask Mask or transparency map
PageRaster Full-page render produced during OCR preprocessing; used as a citation thumbnail.
Unknown Could not classify with reasonable confidence

ResultFormat

Result-shape selection for extraction results.

Distinct from OutputFormat (which controls rendering — Plain, Markdown, HTML, etc.). ResultFormat controls the shape of the result: a unified content blob vs. an element-based decomposition.

Value Description
Unified Unified format with all content in content field
ElementBased Element-based format with semantic element extraction

ElementType

Semantic element type classification.

Categorizes text content into semantic units for downstream processing. Supports the element types commonly found in Unstructured documents.

Value Description
Title Document title
NarrativeText Main narrative text body
Heading Section heading
ListItem List item (bullet, numbered, etc.)
Table Table element
Image Image element
PageBreak Page break marker
CodeBlock Code block
BlockQuote Block quote
Footer Footer text
Header Header text

FormFieldType

Kind of a PDF form field.

Mirrors pdf_oxide's widget field taxonomy without leaking the upstream type across the binding surface.

Value Description
Text Single- or multi-line text input.
Checkbox Checkbox (on/off toggle).
Radio Radio-button group member.
Choice Choice field (dropdown or list box).
Signature Digital-signature field.
Button Push button.
Unknown Field type that could not be classified.

FormatMetadata

Format-specific metadata (discriminated union).

Only one format type can exist per extraction result. This provides type-safe, clean metadata without nested optionals.

Value Description
Pdf Metadata extracted from a PDF document. — Fields: 0: PdfMetadata
Docx Metadata extracted from a DOCX Word document. — Fields: 0: DocxMetadata
Excel Metadata extracted from an Excel spreadsheet. — Fields: 0: ExcelMetadata
Email Metadata extracted from an email message (EML/MSG). — Fields: 0: EmailMetadata
Pptx Metadata extracted from a PowerPoint presentation. — Fields: 0: PptxMetadata
Archive Metadata extracted from an archive (ZIP, TAR, 7Z, etc.). — Fields: 0: ArchiveMetadata
Image Metadata extracted from a raster or vector image. — Fields: 0: ImageMetadata
Xml Metadata extracted from an XML document. — Fields: 0: XmlMetadata
Text Metadata extracted from a plain-text file. — Fields: 0: TextMetadata
Html Metadata extracted from an HTML document. — Fields: 0: HtmlMetadata
Ocr Metadata produced by an OCR pipeline. — Fields: 0: OcrMetadata
Csv Metadata extracted from a CSV or TSV file. — Fields: 0: CsvMetadata
Bibtex Metadata extracted from a BibTeX bibliography file. — Fields: 0: BibtexMetadata
Citation Metadata extracted from a citation file (RIS, PubMed, EndNote). — Fields: 0: CitationMetadata
FictionBook Metadata extracted from a FictionBook (FB2) e-book. — Fields: 0: FictionBookMetadata
Dbf Metadata extracted from a dBASE (DBF) database file. — Fields: 0: DbfMetadata
Jats Metadata extracted from a JATS (Journal Article Tag Suite) XML file. — Fields: 0: JatsMetadata
Epub Metadata extracted from an EPUB e-book. — Fields: 0: EpubMetadata
Pst Metadata extracted from an Outlook PST archive. — Fields: 0: PstMetadata
Audio Metadata extracted from an audio or video file. — Fields: 0: AudioMetadata
Code Code (tree-sitter analyzable source). The structured analysis result is exposed via ExtractionResult.code_intelligence; this variant only tags the format.

TextDirection

Text direction enumeration for HTML documents.

Value Description
LeftToRight Left-to-right text direction
RightToLeft Right-to-left text direction
Auto Automatic text direction detection

LinkType

Link type classification.

Value Description
Anchor Anchor link (#section)
Internal Internal link (same domain)
External External link (different domain)
Email Email link (mailto:)
Phone Phone link (tel:)
Other Other link type

ImageType

Image type classification.

Value Description
DataUri Data URI image
InlineSvg Inline SVG
External External image URL
Relative Relative path image

StructuredDataType

Structured data type classification.

Value Description
JsonLd JSON-LD structured data
Microdata Microdata
RDFa RDFa

OcrBoundingGeometry

Bounding geometry for an OCR element.

Supports both axis-aligned rectangles (from Tesseract) and 4-point quadrilaterals (from PaddleOCR and rotated text detection).

Value Description
Rectangle Axis-aligned bounding box (typical for Tesseract output). — Fields: left: Int, top: Int, width: Int, height: Int
Quadrilateral 4-point quadrilateral for rotated/skewed text (PaddleOCR). Points are in clockwise order starting from top-left: \[top_left, top_right, bottom_right, bottom_left\]

OcrElementLevel

Hierarchical level of an OCR element.

Maps to Tesseract's page segmentation hierarchy and provides equivalent semantics for PaddleOCR.

Value Description
Word Individual word
Line Line of text (default for PaddleOCR)
Block Paragraph or text block
Page Page-level element

PageUnitType

Type of paginated unit in a document.

Distinguishes between different types of "pages" (PDF pages, presentation slides, spreadsheet sheets).

Value Description
Page Standard document pages (PDF, DOCX, images)
Slide Presentation slides (PPTX, ODP)
Sheet Spreadsheet sheets (XLSX, ODS)

RedactionStrategy

Strategy applied when a PII match is rewritten.

Value Description
Mask Replace the matched span with a fixed mask token (default "\[REDACTED\]").
Hash Replace with a SHA-256 hash of the original value (truncated to 16 hex chars). Lets downstream consumers do equality joins without recovering the source.
TokenReplace Replace with a per-category running token ("\[PERSON_1\]", "\[PERSON_2\]", …) so the same person referenced twice gets the same token within the document.
Drop Delete the matched span entirely.

PiiCategory

PII categories the pattern engine recognises.

Value Description
Email Email address (e.g. user@example.com).
Phone Phone number in any common format.
Ssn US Social Security Number.
CreditCard Payment card number (Visa, Mastercard, Amex, etc.).
PostalCode Postal / ZIP code.
IpAddress IPv4 or IPv6 address.
Iban International Bank Account Number.
SwiftBic SWIFT / BIC bank identifier code.
DateOfBirth Date of birth.
Person Person name, surfaced by the optional NER backend.
Organization Organization name, surfaced by the optional NER backend.
Location Location, surfaced by the optional NER backend.
Custom Caller-supplied custom category (e.g. internal employee IDs). Surfaced by the redaction engine when a hit comes from RedactionConfig.custom_terms or RedactionConfig.custom_patterns. The string is the label passed alongside the term/pattern. Use those fields rather than constructing Custom directly via the categories filter — the pattern engine cannot detect arbitrary text from a category name alone. — Fields: 0: String

DiffLine

A single line in a unified-diff hunk.

Defined here (rather than only in crate.diff) so RevisionDelta can reference it unconditionally, without requiring the diff Cargo feature. crate.diff re-exports this type verbatim.

Value Description
Context Unchanged context line. — Fields: 0: String
Added Line added in the "after" version. — Fields: 0: String
Removed Line removed from the "before" version. — Fields: 0: String

RevisionKind

Semantic classification of a tracked change.

Value Description
Insertion Text or content was inserted.
Deletion Text or content was deleted.
FormatChange Run-level formatting (font, size, colour, …) was changed.
Comment A reviewer comment or annotation.

RevisionAnchor

Best-effort document location for a revision.

Value Description
Paragraph Body paragraph, identified by its zero-based index in the document flow. — Fields: index: Long
TableCell Cell inside a table. — Fields: row: Long, col: Long, tableIndex: Long
Page Page, identified by its zero-based index. — Fields: index: Long
Slide Presentation slide, identified by its zero-based index. — Fields: index: Long
Sheet Spreadsheet cell or range, identified by sheet index and optional name. — Fields: index: Long, name: String

SummaryStrategy

Summarisation strategy.

Value Description
Extractive Pure-Rust extractive summary (TextRank over the chunk graph). Deterministic, fast, no external service required.
Abstractive Abstractive summary produced by liter-llm. Requires liter-llm feature and a configured LlmConfig. Token usage is captured in ExtractionResult.llm_usage.

UriKind

Semantic classification of an extracted URI.

Value Description
Hyperlink A clickable hyperlink (web URL, file link).
Image An image or media resource reference.
Anchor An internal anchor or cross-reference target.
Citation A citation or bibliographic reference (DOI, academic ref).
Reference A general reference (e.g. \ref{} in LaTeX, :ref: in RST).
Email An email address (mailto: link or bare email).

RegionKind

Classification of a detected layout region that warrants VLM extraction.

Each variant maps to a specific prompt optimised for that content type. The mapping is intentionally narrow — only region kinds for which VLM extraction provides a clear quality benefit over classical suppression.

Value Description
Figure A figure, diagram, chart, or image region. VLM prompt: describe the diagram / chart, including axis labels, legend entries, and any embedded text.
DenseTable A densely formatted or complex table that classical extraction garbles. VLM prompt: extract the table as GitHub-Flavoured Markdown.
ComplexLayout A region whose layout the classical pipeline cannot handle (multi-column insets, heavily annotated forms, mixed text+diagram). VLM prompt: extract all text and structure as markdown, preserving reading order.
Caption A standalone image to be captioned (not extracted as figure markdown). VLM prompt: produce a single-sentence alt-text-style caption suitable for accessibility tooling and downstream indexing. Used by the captioning post-processor to populate ExtractedImage.caption.

KeywordAlgorithm

Keyword algorithm selection.

Value Description
Yake YAKE (Yet Another Keyword Extractor) - statistical approach
Rake RAKE (Rapid Automatic Keyword Extraction) - co-occurrence based

EnrichStatus

Async lifecycle status for an enrichment job.

Intended for use with any polling or event-driven pipeline that needs to track whether enrichment has completed, succeeded, or failed.

Serialisation

Uses an internally-tagged "status" field with snake_case variants:

{ "status": "pending" }
{ "status": "completed", "result": { ... } }
{ "status": "failed", "error": "text too large" }
Value Description
Pending Job submitted; processing has not yet started or is in progress.
Completed Processing completed successfully. — Fields: result: EnrichResult
Failed Processing failed. — Fields: error: String

SchemaCompliance

Schema-validation outcome surfaced as one of three buckets.

Fold into the combined confidence score without leaking internal validation error types.

Value Description
AllValid Every batch validated against the schema.
PartialValid At least one batch validated; at least one did not.
AllInvalid No batch validated.

ChunkingDecision

The chunking decision made by the analyzer.

Value Description
NoChunking Process without chunking (small file, text layer detected, etc.) — Fields: reason: NoChunkingReason
Chunk Chunk according to plan. — Fields: 0: ChunkPlan
UseOverrides Use user-provided chunk overrides. — Fields: userChunks: List<PageRange>

NoChunkingReason

Reason for not chunking a document.

Value Description
SmallFile File is below size threshold. — Fields: sizeBytes: Long, thresholdBytes: Long
FewPages Document has fewer pages than threshold. — Fields: pageCount: Int, threshold: Int
TextLayerDetected PDF has substantial text layer (OCR not needed). — Fields: textCoverage: Float, avgCharsPerPage: Int
FormatNotChunkable Document format does not support chunking. — Fields: mimeType: String
ChunkingDisabled Chunking is disabled by configuration.
FastTextExtraction Force OCR is disabled and text extraction is fast.

ChunkingReason

Reason for chunking a document.

Value Description
LargeFile File exceeds size threshold. — Fields: sizeBytes: Long, thresholdBytes: Long
ManyPages Document has many pages. — Fields: pageCount: Int, threshold: Int
OcrRequired PDF requires OCR and is large. — Fields: pageCount: Int, forceOcr: Boolean
LargeAndManyPages Both size and page count exceed thresholds. — Fields: sizeBytes: Long, pageCount: Int

BoundaryReason

Reason for boundary detection.

Value Description
Start Start of PDF.
PageOneMarker Page-one marker ("Page 1", "1 of N") detected.
LetterheadReset Letterhead reset after signature block.
DensityShift Text density shift with low bigram overlap.
End End of PDF.

StructuredCallMode

Outcome of the structured-extraction call-mode heuristic.

Distinct from crate.core.config.CallMode which has three variants and governs extraction-engine behaviour. This enum governs whether and how an already-extracted document is sent to an LLM structured-extraction pipeline.

Value Description
Skip Document is unsupported or not worth invoking the pipeline.
TextOnly Send extracted text only; no vision model call.
VisionOnly Send page rasters only; no extracted text payload.
TextPlusVision Fuse extracted text with page rasters in a single multimodal call.
TextOnlyWithVisionFallback Try text-only first; escalate to vision on low confidence score.

PresetCategory

High-level category used to group presets in the registry UI.

Value Description
Finance Invoices, receipts, statements, purchase orders, W-9.
Identity Passports, drivers licenses, insurance cards.
Legal Contracts, NDAs, agreements.
Logistics Bills of lading, customs declarations, packing lists.
Medical Clinical records, lab reports.
Hr Pay stubs, resumes, employment offers.
Other Catch-all for documents that don't fit the other categories.

PsmMode

Page Segmentation Mode for Tesseract OCR.

Value Description
OsdOnly Orientation and script detection only.
AutoOsd Automatic page segmentation with OSD.
AutoOnly Automatic page segmentation without OSD or OCR.
Auto Fully automatic page segmentation with no OSD (default).
SingleColumn Assume a single column of text of variable sizes.
SingleBlockVertical Assume a single uniform block of vertically aligned text.
SingleBlock Assume a single uniform block of text.
SingleLine Treat the image as a single text line.
SingleWord Treat the image as a single word.
CircleWord Treat the image as a single word in a circle.
SingleChar Treat the image as a single character.

PaddleLanguage

Supported languages in PaddleOCR.

Maps user-friendly language codes to paddle-ocr-rs language identifiers.

Value Description
English English
Chinese Simplified Chinese
Japanese Japanese
Korean Korean
German German
French French
Latin Latin script (covers most European languages)
Cyrillic Cyrillic (Russian and related)
TraditionalChinese Traditional Chinese
Thai Thai
Greek Greek
EastSlavic East Slavic (Russian, Ukrainian, Belarusian)
Arabic Arabic (Arabic, Persian, Urdu)
Devanagari Devanagari (Hindi, Marathi, Sanskrit, Nepali)
Tamil Tamil
Telugu Telugu

LayoutClass

The 18 canonical document layout classes.

All model backends (RT-DETR, YOLO, etc.) map their native class IDs to this shared set. Models with fewer classes (DocLayNet: 11, PubLayNet: 5) map to the closest equivalent.

Wire format is snake_case in all serializers (JSON, TOML, YAML).

Value Description
Caption Figure or table caption text.
Chart Chart or graph visualization.
Footnote Footnote or endnote text.
Formula Mathematical formula or equation.
ListItem A single item in a bulleted or numbered list.
PageFooter Running footer at the bottom of a page.
PageHeader Running header at the top of a page.
Picture Image, chart, or other graphical element.
SectionHeader Section heading.
Table Data table.
Text Body text paragraph.
Title Document or chapter title.
DocumentIndex Table of contents or index.
Code Source code block.
CheckboxSelected Checkbox in selected state.
CheckboxUnselected Checkbox in unselected state.
Form Form field or form element.
KeyValueRegion Key-value pair region (e.g. label + value in a form).

Errors

KreuzbergError

Main error type for all Kreuzberg operations.

All errors in Kreuzberg use this enum, which preserves error chains and provides context for debugging.

Variants

  • Io - File system and I/O errors (always bubble up)
  • Parsing - Document parsing errors (corrupt files, unsupported features)
  • Ocr - OCR processing errors
  • Validation - Input validation errors (invalid paths, config, parameters)
  • Cache - Cache operation errors (non-fatal, can be ignored)
  • ImageProcessing - Image manipulation errors
  • Serialization - JSON/MessagePack serialization errors
  • MissingDependency - Missing optional dependencies (tesseract, etc.)
  • Plugin - Plugin-specific errors
  • LockPoisoned - Mutex/RwLock poisoning (should not happen in normal operation)
  • UnsupportedFormat - Unsupported MIME type or file format
  • Other - Catch-all for uncommon errors
Variant Description
Io A file system or I/O operation failed. These errors always bubble up unchanged.
Parsing Document parsing failed (e.g. corrupt file, unsupported format feature).
Ocr An OCR engine returned an error or produced unusable output.
Validation Invalid configuration or input parameters were supplied.
Cache A cache read or write operation failed.
ImageProcessing An image manipulation operation (resize, decode, DPI conversion) failed.
Serialization JSON or MessagePack serialization/deserialization failed.
MissingDependency A required optional system dependency (e.g. tesseract) was not found.
Plugin A registered plugin returned an error during extraction.
LockPoisoned An internal Mutex or RwLock was found in a poisoned state.
UnsupportedFormat The document's MIME type is not supported by any registered extractor.
Embedding The embedding model or embedding pipeline returned an error.
Reranking The reranker model or reranking pipeline returned an error. Since v5.0.
Transcription Audio/video transcription failed.
Timeout The extraction operation exceeded the configured time limit.
Cancelled The extraction was cancelled via a CancellationToken.
Security A security policy was violated (e.g. zip bomb, oversized archive).
Other A catch-all for uncommon errors that do not fit another variant.

HeuristicsError

Errors that can occur during heuristics analysis.

Variant Description
ConfigError Invalid configuration value.
PdfAnalysisError PDF analysis step failed (only when heuristics-pdf feature is active).

LoadError

Errors produced while loading or validating a preset file.

Variant Description
Parse The file is not valid JSON.
SchemaValidation The file parses as JSON but does not validate against the meta-schema.
Deserialize The file validates but cannot be deserialized into Preset.
IdMismatch The preset's declared id does not match its file-system location.
BadMetaSchema The meta-schema itself failed to compile.
Io A filesystem I/O error occurred while reading a preset directory.

ResolveError

Errors produced while resolving a preset against caller overrides.

Variant Description
SchemaNotObject A custom schema override was supplied but is not a JSON object.

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