Create Notebook Example to Showcase Library Usage

Issue Description:

To help users understand how to use graphrag-tagger, we need a well-documented Jupyter Notebook that demonstrates its core functionalities step by step. This will serve as a hands-on guide for users who want to integrate topic extraction and graph-based retrieval into their workflows.

Expected Content:

1. Installation & Setup

   • Install graphrag-tagger and required dependencies.
   • Load necessary libraries.

2. Basic Usage

   • Load a sample PDF document.
   • Extract text from the document.
   • Segment the text into meaningful chunks.

3. Topic Extraction & Refinement

   • Perform topic modeling using LDA or ktrain.
   • Use LLM-based refinement to clean and enhance topics.

4. Graph Construction & Visualization

   • Build a topic similarity graph.
   • Visualize the connections between extracted topics.

5. Real-World Application Example

   • Showcase how the extracted topics and graph can improve retrieval in a RAG/GraphRAG setup.

Deliverable:

A Jupyter Notebook (examples/graphrag_tagger_demo.ipynb) that provides a practical, easy-to-follow guide for new users.

Would love any feedback or additional suggestions! 🚀