Add Kreuzberg integration page (#425)

* Add Kreuzberg integration page

* Add Kreuzberg logo

Author: v-tan

integrations/kreuzberg.md

@@ -0,0 +1,118 @@
+---
+layout: integration
+name: Kreuzberg
+description: Locally convert 91+ document formats into Haystack Documents using Kreuzberg's Rust-core engine
+authors:
+    - name: deepset
+      socials:
+        github: deepset-ai
+        twitter: deepset_ai
+        linkedin: https://www.linkedin.com/company/deepset-ai/
+pypi: https://pypi.org/project/kreuzberg-haystack
+repo: https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/kreuzberg
+type: Data Ingestion
+report_issue: https://github.com/deepset-ai/haystack-core-integrations/issues
+logo: /logos/kreuzberg.png
+version: Haystack 2.0
+toc: true
+---
+
+### **Table of Contents**
+- [Overview](#overview)
+- [Installation](#installation)
+- [Usage](#usage)
+- [Additional Features](#additional-features)
+- [License](#license)
+
+## Overview
+
+[Kreuzberg](https://docs.kreuzberg.dev/) is a document intelligence framework with a Rust core that extracts text, tables, and metadata from 91+ file formats — entirely locally with no external API calls.
+
+This integration provides `KreuzbergConverter`, a Haystack component that converts files into Haystack `Document` objects with rich metadata. It supports parallel batch extraction using Rust's rayon thread pool for high throughput.
+
+**Supported format categories:**
+- **Documents**: PDF, DOCX, DOC, PPTX, PPT, XLSX, XLS, ODT, ODS, ODP, RTF, Pages, Keynote, Numbers, and more
+- **Images (via OCR)**: PNG, JPEG, TIFF, GIF, BMP, WebP, JPEG 2000, SVG
+- **Text/Markup**: Markdown, HTML, XML, LaTeX, Typst, JSON, YAML, reStructuredText, Jupyter notebooks
+- **Email**: EML, MSG (with attachment extraction)
+- **Archives**: ZIP, TAR, GZIP, 7Z (extracts and processes contents recursively)
+- **eBooks & Academic**: EPUB, BibTeX, DocBook, JATS
+
+## Installation
+
+```bash
+pip install kreuzberg-haystack
+```
+
+## Usage
+
+### Components
+
+This integration introduces one component:
+
+- **`KreuzbergConverter`**: Converts files and directories into Haystack `Document` objects. Accepts file paths, directory paths, and `ByteStream` objects as input.
+
+### Basic Usage
+
+```python
+from haystack_integrations.components.converters.kreuzberg import KreuzbergConverter
+
+converter = KreuzbergConverter()
+result = converter.run(sources=["report.pdf", "notes.docx"])
+documents = result["documents"]
+```
+
+### Markdown Output with OCR
+
+Use `ExtractionConfig` to customize output format, OCR backend, and other extraction settings:
+
+```python
+from haystack_integrations.components.converters.kreuzberg import KreuzbergConverter
+from kreuzberg import ExtractionConfig, OcrConfig
+
+converter = KreuzbergConverter(
+    config=ExtractionConfig(
+        output_format="markdown",
+        ocr=OcrConfig(backend="tesseract", language="eng"),
+    ),
+)
+result = converter.run(sources=["scanned_document.pdf"])
+documents = result["documents"]
+```
+
+### In a Pipeline
+
+```python
+from haystack import Pipeline
+from haystack.components.preprocessors import DocumentSplitter
+from haystack.components.writers import DocumentWriter
+from haystack.document_stores.in_memory import InMemoryDocumentStore
+from haystack_integrations.components.converters.kreuzberg import KreuzbergConverter
+
+document_store = InMemoryDocumentStore()
+
+pipeline = Pipeline()
+pipeline.add_component("converter", KreuzbergConverter())
+pipeline.add_component("splitter", DocumentSplitter(split_by="sentence", split_length=5))
+pipeline.add_component("writer", DocumentWriter(document_store=document_store))
+
+pipeline.connect("converter", "splitter")
+pipeline.connect("splitter", "writer")
+
+pipeline.run({"converter": {"sources": ["report.pdf", "presentation.pptx"]}})
+```
+
+## Additional Features
+
+- **Per-page extraction**: Create one `Document` per page using `PageConfig(extract_pages=True)`
+- **Chunking**: Split documents by token count with configurable overlap via `ChunkingConfig`
+- **Token reduction**: Reduce token count with modes from `"light"` to `"maximum"` via `TokenReductionConfig`
+- **Rich metadata**: Quality scores, detected languages, extracted keywords, table data, and PDF annotations
+- **Batch processing**: Parallel extraction enabled by default; set `batch=False` for sequential mode
+- **Config from file**: Load extraction settings from a TOML, YAML, or JSON file via `config_path`
+
+For the full configuration reference and format support matrix, see the [Kreuzberg documentation](https://docs.kreuzberg.dev/).
+
+### License
+
+`kreuzberg-haystack` is distributed under the terms of the [Apache-2.0](https://spdx.org/licenses/Apache-2.0.html) license.