Document Learning System

A complete system for reading documents, tracking progress across multiple sessions, and building long-term memory.

Quick Start

To start learning a document:

Please learn this document: [filename]

To resume from where you left off:

Resume learning [filename] from last position

To check current progress:

What's my progress on learning [filename]?

Core Features

1. Large File Support

• Handles PDF files up to hundreds of MBs
• Text-based documents (TXT, MD, LOG, etc.)
• Chunked processing to avoid memory issues
• Automatic encoding detection and recovery

2. Progress Tracking & Resume

• Bookmark system: Automatically tracks your position (chapter/page)
• Resume capability: Pick up exactly where you left off, even days later
• Progress visualization: See what's been learned vs remaining
• Manual control: Jump to specific chapters/pages if needed

3. Long-term Memory Integration

• Extracts key concepts automatically
• Stores learning summaries in MEMORY.md
• Creates session notes in memory/YYYY-MM-DD.md
• Builds a searchable knowledge base over time

How It Works

Session Flow

1. Start Learning

   • Upload or specify document path
   • System reads and extracts content
   • Creates initial progress entry

2. Track Progress

   • After each session, note where you stopped
   • Progress is saved automatically
   • Key points are extracted to memory files

3. Resume Later

   • Say "resume learning [document]"
   • System loads last position
   • Continues from there seamlessly

4. Build Knowledge Base

   • Over time, all learned content accumulates in MEMORY.md
   • Use memory_search to find specific topics later
   • Create comprehensive summaries periodically

Multi-Document Learning Support 📚🔄

You can now learn multiple PDFs simultaneously and switch between them!

How It Works

The system maintains a progress store that tracks ALL your learning documents:

• ✅ Track progress for Document A, B, C... all at once
• ✅ Learn Document A → Pause → Learn Document B → Pause → Resume Document A
• ✅ Each document remembers its exact position (chapter/page)
• ✅ Switch context seamlessly between different documents

Multi-Document Workflow Example

Day 1: Start learning PDF-A
User: Please learn this driver manual for me.
Assistant: Started tracking itop-3568-driver.pdf
   Progress: Page 0/450 (not started)

[Read some content]
User: Pause here, let's learn another document
Assistant: ✅ Saved progress for PDF-A at page 120/450
   Now learning PDF-B: user-guide.pdf

[Start PDF-B]
User: Please also learn this user guide
Assistant: Started tracking user-guide.pdf
   Progress: Page 0/80 (not started)

[Read some of PDF-B]
User: Pause, back to the driver manual
Assistant: ✅ Saved progress for PDF-B at page 35/80
   Switching context back to PDF-A...
   Resume from page 120/450

Day 2: Continue learning different documents
User: Let's continue with the user guide today
Assistant: Loading progress for user-guide.pdf...
   Last read: Page 35/80 (PDF-B)
   Continuing from where we left off...

[After reading PDF-B]
User: Show me status of all my learning documents
Assistant: 📚 Document Learning Status
   ==================================
   
   ✅ itop-3568-driver.pdf
      Progress: 120/450 pages (27%)
      Last updated: Today
   
   🔄 user-guide.pdf
      Progress: 50/80 pages (63%)
      Last updated: Just now

Day 3: Query specific document knowledge
User: What did I learn about the driver installation in PDF-A?
Assistant: [Searches memory and provides answer from PDF-A]
Based on my notes from itop-3568-driver.pdf...

Commands for Multi-Document Learning

Start a new document

Please learn this document: /path/to/document.pdf

Pause current, start another

Pause learning [current-doc], let's learn [new-doc]

Switch back to previous document

Resume learning [doc-name] from last position

Check all documents status

What's my progress on all my learning documents?
Show me the status of everything I'm learning

Key Benefits

1. No interference: Each document has independent progress tracking
2. Seamless switching: System automatically loads correct position for each doc
3. Complete history: All learning sessions are preserved and searchable
4. Flexible workflow: Learn at your own pace across multiple sources

Usage Patterns

Pattern 1: Learning a Technical Manual (e.g., PDF)

User: Here's a driver manual. Please learn it for me.
Assistant: I'll read the document, extract key points, and save progress. Let me start with Chapter 1...

[After reading first chapter]
Assistant: Progress update: Read chapters 1-2 of 15. Saved to memory. Ready to continue when you are!

[Days later - resume]
User: Resume learning the driver manual
Assistant: Loading last position (chapter 3)... Continuing from where we left off...

Pattern 2: Learning a Book/Text Document

User: I want to learn this book. Track my progress chapter by chapter.
Assistant: Got it! I'll read each chapter and save the summary after every session. Progress tracking enabled.

[After Chapter 1]
Assistant: ✅ Chapter 1 complete - Summary saved to memory/YYYY-MM-DD.md
📊 Progress: 1/24 chapters (4%)

[Next day]
User: Continue from last position
Assistant: Resuming at Chapter 2...

Pattern 3: Reference Learning (Look-up as needed)

User: I need to learn this specification document for reference.
Assistant: I'll read it and create a searchable knowledge base. You can later ask questions like "What does section 5 say about API limits?"

Later: What are the API rate limits mentioned in the spec?
Assistant: [Searches memory and provides answer from learned content]

Commands & Tools

Built-in Script

The skill includes scripts/read_large_document.py which handles:

• PDF reading with pdfplumber
• Text file encoding detection
• Progress saving/loading
• Key point extraction

Memory Integration Files

Read these for detailed integration patterns:

• references/memory_integration.md - How to integrate with MEMORY.md

Best Practices

1. Start small: Begin with one document at a time
2. Regular updates: Add progress notes after each session, even brief ones
3. Use summaries: Ask for chapter summaries to reinforce learning
4. Review periodically: Use memory_search to find what you've learned before
5. Be specific: When asking about content, mention the document name

Limitations & Notes

• PDFs must be text-based (not scanned images) for optimal reading
• Very large PDFs (>200MB) may take longer to process
• Progress tracking works best with structured documents (chapters/sections)
• For scanned PDFs, consider OCR tools first

Examples

Example 1: Learning a Driver Manual

User: Please learn this driver manual for me. It's in /workspace/linuxdriver/itop-3568-driver-v2.8.pdf
Assistant: I'll start reading the document now...

[Reads and extracts]
✅ Document loaded: itop-3568-driver-v2.8.pdf (120MB)
📑 Total pages: 450
🔑 Key concepts extracted: Hardware specs, Pinout details, Driver installation...

Progress saved! You can resume anytime with "Resume learning the driver manual"

Example 2: Resume After Days

User: Resume learning the driver manual from last position
Assistant: Loading progress... Last read: page 156 of 450 (Chapter 7)
Continuing from where we left off...

[Reads next section]
✅ Chapter 7 complete - Progress updated to page 234/450

Example 3: Query Learned Content

User: What did I learn about the pinout configuration?
Assistant: [Searches memory and provides answer from driver manual learning session]
Based on my notes from the itop-3568 driver manual (learned on April 6):
- GPIO pins are numbered X, Y, Z...
- Power supply requirements: 5V at 2A...

Ready to start learning? Just tell me which document you want to learn! 📚