Enhance documentation landing page with better UX

- Reorganize main guide page with progressive disclosure pattern
- Add context-based navigation (tabs for different user paths)
- Improve visual hierarchy with clear sections and formatting
- Add emoji icons for visual scanning
- Link to all guide pages prominently
- Include quick-start code and CLI examples on landing page
- Inspired by SQLModel-CRUD-Utilities documentation approach

Improves user experience by guiding visitors based on their needs
rather than forcing a linear read-through.

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>

Author: fsecada01

TextSpitter/guide/__init__.py

@@ -1,49 +1,147 @@
 """
-# TextSpitter — User Guide
+# TextSpitter Documentation
 
-Welcome to the TextSpitter documentation.
-TextSpitter extracts plain text from documents and source-code files with a
-single call, normalising every input type (file path, `BytesIO`, `SpooledTemporaryFile`,
-raw `bytes`) into a `str`.
+## Welcome to TextSpitter
+
+**Transforming documents into insights, effortlessly and efficiently.**
+
+TextSpitter extracts plain text from documents and source-code files with a single call.
+It normalises every input type — file paths, `BytesIO` streams, `SpooledTemporaryFile` objects,
+and raw `bytes` — into plain strings, making it ideal for LLM pipelines, search engines,
+and data-processing workflows.
 
 ---
 
-## Pages in this guide
+## 📚 Start Here
+
+Choose your path based on what you want to do:
+
+<details open>
+<summary><strong>⚡ I want to extract text right now</strong></summary>
+
+Start with **[Quick Start](quickstart.html)** to install and run your first extraction in under 2 minutes.
+
+```python
+from TextSpitter import TextSpitter
+
+text = TextSpitter(filename="report.pdf")
+print(text[:500])
+```
+
+</details>
+
+<details>
+<summary><strong>🎯 I need to understand how TextSpitter works</strong></summary>
+
+Read the **[Technical Overview](overview.html)** for architecture, module design, and implementation details.
+
+Covers: three-layer design, input resolution, PDF fallback chains, encoding strategy, and logging.
+
+</details>
+
+<details>
+<summary><strong>🔍 I want to learn by example</strong></summary>
+
+Follow the **[Tutorial](tutorial.html)** for a format-by-format walkthrough covering:
+- PDF extraction (with PyMuPDF + pypdf fallback)
+- DOCX extraction via FastAPI
+- TXT & CSV with encoding handling
+- Source code files (50+ extensions)
+- Direct `FileExtractor` and `WordLoader` usage
+
+</details>
+
+<details>
+<summary><strong>💼 I'm building a real application</strong></summary>
+
+Check **[Common Use Cases](usecases.html)** for production patterns:
+- Web APIs (FastAPI, Django/DRF)
+- Cloud storage (AWS S3)
+- LLM pipelines (LangChain, OpenAI embeddings)
+- Batch processing (directory trees, parallel extraction)
+- Logging strategies
+
+</details>
 
-| Page | Description |
-|------|-------------|
-| `TextSpitter.guide.overview` | Architecture and design decisions |
-| `TextSpitter.guide.quickstart` | Install and run your first extraction |
-| `TextSpitter.guide.tutorial` | Format-by-format walkthrough |
-| `TextSpitter.guide.usecases` | FastAPI, S3, LangChain, batch processing … |
-| `TextSpitter.guide.recipes` | Copy-paste snippets |
+<details>
+<summary><strong>📋 I need a code snippet</strong></summary>
+
+Browse **[Recipes](recipes.html)** for copy-paste snippets covering:
+- Input handling (BytesIO, SpooledTemporaryFile, raw bytes)
+- Format-specific extraction
+- Error and encoding handling
+- Testing patterns
+
+</details>
 
 ---
 
-## Supported formats
+## ✨ Supported Formats
 
-| Format | Reader | Notes |
+| Format | Method | Notes |
 |--------|--------|-------|
-| PDF | `pdf_file_read` | PyMuPDF → pypdf fallback |
-| DOCX | `docx_file_read` | python-docx paragraph extraction |
-| TXT | `text_file_read` | UTF-8 → latin-1 → UTF-8-replace |
-| CSV | `csv_file_read` | Same encoding cascade as TXT |
-| Source code | `code_file_read` | 50 + extensions |
+| **PDF** | `pdf_file_read()` | PyMuPDF → pypdf fallback |
+| **DOCX** | `docx_file_read()` | python-docx paragraph extraction |
+| **TXT** | `text_file_read()` | UTF-8 → latin-1 → UTF-8-replace |
+| **CSV** | `csv_file_read()` | Same encoding cascade as TXT |
+| **Source code** | `code_file_read()` | 50+ extensions (py, js, ts, go, rs, java, …) |
 
 ---
 
-## Quick example
+## 🚀 Quick Start
+
+### Install
+
+```sh
+pip install textspitter
+
+# With optional loguru logging
+pip install "textspitter[logging]"
+```
+
+### Extract
 
 ```python
 from TextSpitter import TextSpitter
 
+# From a file
 text = TextSpitter(filename="report.pdf")
-print(text[:200])
+
+# From a stream
+from io import BytesIO
+text = TextSpitter(file_obj=BytesIO(pdf_bytes), filename="report.pdf")
+
+# From raw bytes
+text = TextSpitter(file_obj=docx_bytes, filename="contract.docx")
 ```
 
-Install with optional loguru logging:
+### CLI
 
 ```sh
-pip install "textspitter[logging]"
+# Single file to stdout
+textspitter report.pdf
+
+# Multiple files to combined output
+textspitter chapter1.pdf chapter2.pdf -o book.txt
 ```
+
+---
+
+## 🔗 Navigation
+
+| Page | Purpose | Best for |
+|------|---------|----------|
+| [Overview](overview.html) | Architecture & design | Understanding the internals |
+| [Quick Start](quickstart.html) | Installation & first extraction | Getting started fast |
+| [Tutorial](tutorial.html) | Format-by-format guide | Learning by example |
+| [Use Cases](usecases.html) | Production patterns | Building real applications |
+| [Recipes](recipes.html) | Code snippets | Copy-paste solutions |
+
+---
+
+## 📖 Full API Reference
+
+For complete API documentation including class definitions, method signatures, and parameters,
+see the **TextSpitter module reference** in the sidebar.
+
 """