Add Chonkie to data management tools documentation

qdrant-landing/content/documentation/data-management/_index.md

@@ -10,6 +10,7 @@ partition: build
 | ------------------------------- | -------------------------------------------------------------------------------------------------- |
 | [Airbyte](/documentation/data-management/airbyte/)           | Data integration platform specialising in ELT pipelines.                                           |
 | [Airflow](/documentation/data-management/airflow/)           | Platform designed for developing, scheduling, and monitoring batch-oriented workflows.             |
+| [Chonkie](/documentation/data-management/chonkie/)           | No-nonsense, ultra-light and lightning fast RAG pipelines library.                                |
 | [CocoIndex](/documentation/data-management/cocoindex/)           | High performance ETL framework to transform data for AI, with real-time incremental processing     |
 | [Cognee](/documentation/data-management/cognee/)             | AI memory frameworks that allows loading from 30+ data sources to graph and vector stores          |
 | [Connect](/documentation/data-management/redpanda/)          | Declarative data-agnostic streaming service for efficient, stateless processing.                   |

qdrant-landing/content/documentation/data-management/chonkie.md

@@ -0,0 +1,101 @@
+---
+title: Chonkie
+---
+
+# Chonkie
+
+[Chonkie](https://github.com/chonkie-inc/chonkie) is a no-nonsense, ultra-light, and lightning-fast chunking library designed for RAG (Retrieval-Augmented Generation) applications.
+
+Chonkie integrates seamlessly with Qdrant through the **QdrantHandshake** class, allowing you to chunk, embed, and store text data without ever leaving the Chonkie SDK.
+
+## Setup
+
+Install Chonkie with Qdrant support:
+
+```bash
+pip install "chonkie[qdrant]"
+```
+
+## Basic Usage
+
+The `QdrantHandshake` provides a simple interface for storing and searching chunks:
+
+```python
+from chonkie import QdrantHandshake, SemanticChunker
+
+# Initialize handshake with custom embedding model
+handshake = QdrantHandshake(
+    url="http://localhost:6333",
+    collection_name="my_documents",
+    embedding_model="sentence-transformers/all-MiniLM-L6-v2"
+)
+
+# Create and write chunks
+chunker = SemanticChunker()
+chunks = chunker.chunk("Your text content here...")
+handshake.write(chunks)
+
+# Search using natural language
+results = handshake.search(query="your search query", limit=5)
+for result in results:
+    print(f"{result['score']}: {result['text']}")
+```
+
+### Qdrant Cloud
+
+```python
+handshake = QdrantHandshake(
+    url="https://your-cluster.qdrant.io",
+    api_key="your-api-key",
+    collection_name="my_collection",
+    embedding_model="BAAI/bge-small-en-v1.5"  # Change to your preferred model
+)
+```
+
+## Complete RAG Pipeline
+
+Build end-to-end RAG pipelines using Chonkie's fluent Pipeline API:
+
+```python
+from chonkie import Pipeline
+
+# Process documents and store in Qdrant with custom embedding model
+docs = (Pipeline()
+    .fetch_from("file", dir="./knowledge_base", ext=[".txt", ".md"])
+    .process_with("text")
+    .chunk_with("semantic", chunk_size=512)
+    .store_in("qdrant",
+              collection_name="knowledge",
+              url="http://localhost:6333",
+              embedding_model="sentence-transformers/all-MiniLM-L6-v2")
+    .run())
+
+print(f"Ingested {len(docs)} documents into Qdrant")
+```
+
+### Pipeline with Refinements
+
+```python
+from chonkie import Pipeline
+
+# Advanced pipeline with overlapping context and custom embeddings
+docs = (Pipeline()
+    .fetch_from("file", dir="./docs")
+    .process_with("text")
+    .chunk_with("semantic", threshold=0.8)
+    .refine_with("overlap", context_size=100)
+    .store_in("qdrant",
+              url="https://your-cluster.qdrant.io",
+              api_key="your-api-key",
+              collection_name="knowledge_base",
+              embedding_model="BAAI/bge-small-en-v1.5")
+    .run())
+```
+
+## Next steps
+
+- Chonkie [GitHub Repository](https://github.com/chonkie-inc/chonkie)
+- Chonkie [Documentation](https://chonkie.ai)
+- QdrantHandshake [API Reference](https://chonkie.ai/oss/handshakes/qdrant-handshake)
+- Chonkie [Chunking Strategies](https://chonkie.ai/oss/chunkers/overview)
+- Qdrant Python Client [Documentation](https://python-client.qdrant.tech/)