docs: update chunking usage docs, minor reorg (#550)

Signed-off-by: Panos Vagenas <35837085+vagenas@users.noreply.github.com>

docs/concepts/architecture.md

@@ -10,7 +10,7 @@ For each document format, the *document converter* knows which format-specific *
 
 The *conversion result* contains the [*Docling document*](./docling_document.md), Docling's fundamental document representation.
 
-Some typical scenarios for using a Docling document include directly calling its *export methods*, such as for markdown, dictionary etc., or having it chunked by a *chunker*.
+Some typical scenarios for using a Docling document include directly calling its *export methods*, such as for markdown, dictionary etc., or having it chunked by a [*chunker*](./chunking.md).
 
 For more details on Docling's architecture, check out the [Docling Technical Report](https://arxiv.org/abs/2408.09869).
 

docs/reference/cli.md

@@ -1,4 +1,4 @@
-# CLI Reference
+# CLI reference
 
 This page provides documentation for our command line tools.
 

docs/usage.md

@@ -22,9 +22,7 @@ A simple example would look like this:
 docling https://arxiv.org/pdf/2206.01062
 ```
 
-To see all available options (export formats etc.) run `docling --help`. More details in the [CLI reference page](./cli.md).
-
-
+To see all available options (export formats etc.) run `docling --help`. More details in the [CLI reference page](./reference/cli.md).
 
 ### Advanced options
 
@@ -130,29 +128,37 @@ You can limit the CPU threads used by Docling by setting the environment variabl
 
 ## Chunking
 
-You can perform a hierarchy-aware chunking of a Docling document as follows:
+You can chunk a Docling document using a [chunker](concepts/chunking.md), such as a
+`HybridChunker`, as shown below (for more details check out
+[this example](examples/hybrid_chunking.ipynb)):
 
 ```python
 from docling.document_converter import DocumentConverter
-from docling_core.transforms.chunker import HierarchicalChunker
+from docling.chunking import HybridChunker
 
 conv_res = DocumentConverter().convert("https://arxiv.org/pdf/2206.01062")
 doc = conv_res.document
-chunks = list(HierarchicalChunker().chunk(doc))
 
-print(chunks[30])
+chunker = HybridChunker(tokenizer="BAAI/bge-small-en-v1.5")  # set tokenizer as needed
+chunk_iter = chunker.chunk(doc)
+```
+
+An example chunk would look like this:
+
+```python
+print(list(chunk_iter)[11])
 # {
-#   "text": "Lately, new types of ML models for document-layout analysis have emerged [...]",
+#   "text": "In this paper, we present the DocLayNet dataset. [...]",
 #   "meta": {
 #     "doc_items": [{
-#       "self_ref": "#/texts/40",
+#       "self_ref": "#/texts/28",
 #       "label": "text",
 #       "prov": [{
 #         "page_no": 2,
-#         "bbox": {"l": 317.06, "t": 325.81, "r": 559.18, "b": 239.97, ...},
-#       }]
-#     }],
-#     "headings": ["2 RELATED WORK"],
+#         "bbox": {"l": 53.29, "t": 287.14, "r": 295.56, "b": 212.37, ...},
+#       }], ...,
+#     }, ...],
+#     "headings": ["1 INTRODUCTION"],
 #   }
 # }
 ```

mkdocs.yml

@@ -56,7 +56,6 @@ nav:
     - "Docling": index.md
     - Installation: installation.md
     - Usage: usage.md
-    - CLI: cli.md
     - FAQ: faq.md
     - Docling v2: v2.md
   - Concepts:
@@ -76,15 +75,12 @@ nav:
       - "Table export": examples/export_tables.py
       - "Multimodal export": examples/export_multimodal.py
       - "Force full page OCR": examples/full_page_ocr.py
+    - Chunking:
+      - "Hybrid chunking": examples/hybrid_chunking.ipynb
     - RAG / QA:
       - "RAG with LlamaIndex 🦙": examples/rag_llamaindex.ipynb
       - "RAG with LangChain 🦜🔗": examples/rag_langchain.ipynb
       - "Hybrid RAG with Qdrant": examples/hybrid_rag_qdrant.ipynb
-    - Chunking:
-      - "Hybrid chunking": examples/hybrid_chunking.ipynb
-    #   - Chunking: examples/chunking.md
-    # - CLI:
-    #   - CLI: examples/cli.md
   - Integrations:
     - Integrations: integrations/index.md
     - "🐝 Bee": integrations/bee.md
@@ -99,10 +95,13 @@ nav:
     - "spaCy": integrations/spacy.md
     - "txtai": integrations/txtai.md
     # - "LangChain 🦜🔗": integrations/langchain.md
-  - API reference:
-    - Document Converter: api_reference/document_converter.md
-    - Pipeline options: api_reference/pipeline_options.md
-    - Docling Document: api_reference/docling_document.md
+  - Reference:
+    - Python API:
+      - Document Converter: reference/document_converter.md
+      - Pipeline options: reference/pipeline_options.md
+      - Docling Document: reference/docling_document.md
+    - CLI:
+      - CLI reference: reference/cli.md
 
 markdown_extensions:
   - pymdownx.superfences