docs: add OpenDataLoader PDF Reader demo notebook

[hyunhee-jo]

Description

Add an example notebook for OpenDataLoader PDF Reader (opendataloader-pdf-llamaindex), an independently published LlamaIndex reader for fast, accurate, 100% local PDF extraction.

The reader is available on PyPI as opendataloader-pdf-llamaindex (v0.0.3). No new package is added to this repository — this PR is documentation only.

Notebook contents (44 cells, Colab-ready):

• Basic usage with per-page Document splitting
• All four output formats (text, Markdown, JSON, HTML)
• Advanced options (tagged PDFs, table detection, sanitization, page selection, image handling)
• Custom metadata via extra_info
• Multiple file loading
• SimpleDirectoryReader integration via file_extractor
• Hybrid AI mode (docling-fast backend)
• RAG pipeline with MarkdownNodeParser + VectorStoreIndex

Also adds a one-line entry to the data connectors module guide (modules.md).

New Package?

• Yes
• No

Version Bump?

• Yes
• No

Type of Change

• This change requires a documentation update

How Has This Been Tested?

• Ran all notebook cells end-to-end on Google Colab — all cells passed without errors
• Validated notebook JSON structure and cell source format
• Verified Colab badge URL resolves to the correct run-llama/llama_index path

Suggested Checklist:

• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• I have added Google Colab support for the newly added notebooks
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes
• I ran uv run make format; uv run make lint to appease the lint gods

Tests and lint checklist items are not applicable — this PR adds only a Jupyter notebook and a one-line markdown entry, with no Python package code.

AI Disclosure

This notebook was drafted with Claude Code assistance. All content was reviewed by the author, executed end-to-end on Google Colab, and revised through multiple code-review rounds before submission.

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