- description
- Extract text, tables, metadata, and images from 107 document formats (PDF, Office, images, HTML, email, archives, academic) using Xberg. Use when writing code that calls Xberg APIs in Python, Node.js/TypeScript, Rust, or CLI. Covers installation, extraction (sync/async), configuration (OCR, chunking, output format), batch processing, error handling, and plugins.
- license
- Elastic-2.0
- metadata
- {"author":"xberg-io","version":"0.1.0","repository":"https://github.com/xberg-io/xberg"}
- name
- xberg
<!--
AI-RULEZ :: GENERATED FILE — DO NOT EDIT
Content-Hash: blake3:5c39696cf46f9dabada4de547cf7b610394f57c4002ed5d2055fc83521fa3141
Source-Hash: blake3:662aa704cf97ad20f02258c9dcd1c73822213a426e27ec7ebc292d3f599fb7c2
Schema-Version: v1
-->
# Xberg Document Extraction
Xberg is a document intelligence library with a Rust core and bindings for Python, TypeScript/Node.js, Ruby, PHP, Go, Java, C#, Elixir, WebAssembly, Dart, Kotlin Android, Swift, Zig, and C. It extracts text, tables, metadata, and images from 107 formats across 140 unique file extensions and accepts 53 compatibility MIME aliases, including PDF, Office documents, images, HTML, email, archives, and academic formats.
Use this skill when writing code that:
- Extracts text or metadata from documents
- Performs OCR on scanned documents or images
- Batch-processes multiple files
- Configures extraction options (output format, chunking, OCR, language detection)
- Implements custom plugins (post-processors, validators, OCR backends)
> If the `xberg` MCP server is registered in this session, prefer its tools over shelling out to the CLI — they expose the same extraction surface with structured arguments and results.
## Installation
### Python
```bash
pip install xberg
```
### Node.js
```bash
npm install @xberg-io/xberg
```
### Rust
```bash
cargo add xberg
```
```toml
# Cargo.toml
[dependencies]
xberg = { version = "1.1.0", features = ["full"] }
tokio = { version = "1", features = ["full"] }
# feature flags: pdf, ocr, chunking, embeddings, language-detection, keywords, api, mcp
# (or "formats" / "full" aggregates); tokio-runtime is on by default
```
### CLI
```bash
brew install xberg-io/tap/xberg
# or run without a persistent install (the CLI proxy package self-installs the binary):
npx @xberg-io/xberg-cli@1.3.10 --help
uvx --from xberg-cli==1.3.8 xberg --help
# or download a prebuilt binary from the latest GitHub release:
# https://github.com/xberg-io/xberg/releases/latest
# or build from source:
cargo install xberg-cli
```
## Quick Start
The library entry points are `extract(input, config)` and `extract_batch(inputs, config)`. Both return an `ExtractionResult` **envelope** — the extracted document(s) live in `result.results`, and per-document data (`content`, `tables`, `metadata`, …) is on each `result.results[i]`. Python and Node are async-only.
### Python
```python
import asyncio
from xberg import ExtractInput, extract, ExtractionConfig
async def main() -> None:
result = await extract(ExtractInput(uri="document.pdf"), ExtractionConfig())
doc = result.results[0]
print(doc.content) # extracted text
print(doc.metadata) # document metadata
print(doc.tables) # extracted tables
asyncio.run(main())
```
### Node.js
```typescript
import { extract } from "@xberg-io/xberg";
const output = await extract({ kind: "uri", uri: "document.pdf" });
const doc = output.results[0];
console.log(doc.content);
console.log(doc.metadata);
console.log(doc.tables);
```
### Rust
```rust
use xberg::{extract, ExtractInput, ExtractionConfig};
#[tokio::main]
async fn main() -> xberg::Result<()> {
let output = extract(ExtractInput::from_uri("document.pdf"), &ExtractionConfig::default()).await?;
println!("{}", output.results[0].content);
Ok(())
}
```
### CLI
```bash
xberg extract document.pdf
xberg extract document.pdf --format json
xberg extract document.pdf --content-format markdown
```
## Configuration
All languages use the same configuration structure with language-appropriate naming conventions.
### Python (snake_case)
```python
from xberg import (
ExtractInput, extract,
ExtractionConfig, OcrConfig, TesseractConfig, PdfConfig, ChunkingConfig, OutputFormat,
)
config = ExtractionConfig(
ocr=OcrConfig(
backend="tesseract",
language=["eng"],
tesseract_config=TesseractConfig(psm=6, enable_table_detection=True),
),
pdf_options=PdfConfig(passwords=["secret123"]),
chunking=ChunkingConfig(max_characters=1000, overlap=200),
output_format=OutputFormat("markdown"),
)
result = await extract(ExtractInput(uri="document.pdf"), config)
```
### Node.js (camelCase)
```typescript
import { extract, type ExtractionConfig } from "@xberg-io/xberg";
const config: ExtractionConfig = {
ocr: { backend: "tesseract", language: ["eng"] },
pdfOptions: { passwords: ["secret123"] },
chunking: { maxCharacters: 1000, overlap: 200 },
outputFormat: "markdown",
};
const output = await extract({ kind: "uri", uri: "document.pdf" }, config);
```
### Rust (snake_case)
```rust
use xberg::{extract, ExtractInput, ExtractionConfig, OcrConfig, ChunkingConfig, OutputFormat};
let config = ExtractionConfig {
ocr: Some(OcrConfig {
backend: "tesseract".into(),
language: vec!["eng".to_string()],
..Default::default()
}),
chunking: Some(ChunkingConfig {
max_characters: 1000,
overlap: 200,
..Default::default()
}),
output_format: OutputFormat::Markdown,
..Default::default()
};
let output = extract(ExtractInput::from_uri("document.pdf"), &config).await?;
```
### Config File (TOML)
```toml
output_format = "markdown"
[ocr]
backend = "tesseract"
language = "eng"
[chunking]
max_characters = 1000
overlap = 200
[pdf_options]
passwords = ["secret123"]
```
```bash
# CLI: auto-discovers xberg.toml/yaml/yml/json in current/parent directories
xberg extract doc.pdf
# or explicit:
xberg extract doc.pdf --config xberg.toml
xberg extract doc.pdf --config-json '{"ocr":{"backend":"tesseract","language":"deu"}}'
```
## Batch Processing
`extract_batch` takes a list of `ExtractInput`s and returns one envelope whose `results` array holds documents in discovery order; one input may yield multiple documents. Per-input failures are reported in `result.errors` with an input index.
### Python
```python
from xberg import ExtractInput, extract_batch, ExtractionConfig
inputs = [
ExtractInput(uri="doc1.pdf"),
ExtractInput(uri="doc2.docx"),
ExtractInput(uri="doc3.xlsx"),
]
output = await extract_batch(inputs, ExtractionConfig())
for doc in output.results:
print(f"{len(doc.content)} chars extracted")
```
### Node.js
```typescript
import { extractBatch } from "@xberg-io/xberg";
const output = await extractBatch([
{ kind: "uri", uri: "doc1.pdf" },
{ kind: "uri", uri: "doc2.docx" },
]);
for (const doc of output.results) {
console.log(`${doc.content.length} chars`);
}
```
### Rust
```rust
use xberg::{extract_batch, ExtractInput, ExtractionConfig};
let config = ExtractionConfig::default();
let inputs = vec![ExtractInput::from_uri("doc1.pdf"), ExtractInput::from_uri("doc2.docx")];
let output = extract_batch(inputs, &config).await?;
```
### CLI
```bash
xberg batch *.pdf --format json
xberg batch docs/*.docx --content-format markdown
```
## OCR
OCR runs automatically for images and scanned PDFs. Tesseract is the default backend (native binding, no external install required).
### Backends
Select with `OcrConfig.backend`:
- **tesseract** (default): built-in native binding. All Tesseract languages supported.
- **paddleocr** (`"paddleocr"` / `"paddle-ocr"`): ONNX-based PaddleOCR.
- **vlm**: Vision-Language-Model OCR (configure via `OcrConfig.vlm_config`).
Custom backends can be registered in Python/Node via `register_ocr_backend` (see [Advanced Features](references/advanced-features.md)).
### Language Codes
```python
config = ExtractionConfig(ocr=OcrConfig(language=["eng"])) # English
config = ExtractionConfig(ocr=OcrConfig(language=["eng", "deu"])) # Multiple
# The single-string shorthand ("eng+deu") is only accepted in config files / --config-json,
# not in the OcrConfig constructor (Python takes a list, Node takes an array).
```
### Force OCR
```python
config = ExtractionConfig(force_ocr=True) # OCR even if text is extractable
```
## Result Envelope and Document Fields
`extract` / `extract_batch` return an `ExtractionResult` envelope: `results` (list of documents), `errors` (per-input failures), and `summary` (counts). Per-document fields live on each document in `results` — bind `doc = result.results[0]` (Python/Node) or `&output.results[0]` (Rust) first.
| Field | Python (`doc.`) | Node.js (`doc.`) | Rust (`document.`) | Description |
| ------------ | ---------------------- | --------------------- | ----------------------- | --------------------------------------------- |
| Text content | `content` | `content` | `content` | Extracted text (str/String) |
| MIME type | `mime_type` | `mimeType` | `mime_type` | Input document MIME type |
| Metadata | `metadata` | `metadata` | `metadata` | Document metadata (flat mapping) |
| Tables | `tables` | `tables` | `tables` | Extracted tables with cells + markdown |
| Languages | `detected_languages` | `detectedLanguages` | `detected_languages` | Detected languages (if enabled) |
| Chunks | `chunks` | `chunks` | `chunks` | Text chunks (if chunking enabled) |
| Images | `images` | `images` | `images` | Extracted images (if enabled) |
| Elements | `elements` | `elements` | `elements` | Semantic elements (if element_based format) |
| Pages | `pages` | `pages` | `pages` | Per-page content (if page extraction enabled) |
| Keywords | `extracted_keywords` | `extractedKeywords` | `extracted_keywords` | Extracted keywords (if enabled) |
## Error Handling
### Python
`extract` / `extract_batch` raise a plain `RuntimeError` on failure — the typed `XbergError` subclasses are not raised by these entry points, so catch `RuntimeError`. Per-input failures during `extract_batch` are reported non-fatally in `result.errors`.
```python
from xberg import ExtractInput, extract, ExtractionConfig
try:
result = await extract(ExtractInput(uri="file.pdf"), ExtractionConfig())
for err in result.errors:
print(f"Per-input error: {err}")
except RuntimeError as e:
print(f"Extraction failed: {e}")
```
### Node.js
The Node binding throws plain `Error` objects (it does not export typed error subclasses). Catch with `instanceof Error`, and inspect `output.errors` for non-fatal per-input failures.
```typescript
import { extract } from "@xberg-io/xberg";
try {
const output = await extract({ kind: "uri", uri: "file.pdf" });
if (output.errors.length > 0) {
console.error("Per-input errors:", output.errors);
}
} catch (e) {
if (e instanceof Error) {
console.error(`Extraction failed: ${e.message}`);
}
}
```
### Rust
```rust
use xberg::{extract, ExtractInput, ExtractionConfig, XbergError};
let config = ExtractionConfig::default();
View on GitHub