Core Concepts - Understand the Mental Model

Before diving into how to use Open Notebook, it's important to understand how it thinks. These core concepts explain the "why" behind the design.

The Five Mental Models

1. Notebooks, Sources, and Notes

How Open Notebook organizes your research. Understand the three-tier container structure and how information flows from raw materials to finished insights.

Key idea: A notebook is a scoped research container. Sources are inputs (PDFs, URLs, etc.). Notes are outputs (your insights, AI-generated summaries, captured responses).

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2. AI Context & RAG

How Open Notebook makes AI aware of your research - two different approaches.

Key idea: Chat sends entire selected sources to the LLM (full context, conversational). Ask uses RAG (retrieval-augmented generation) to automatically search and retrieve only relevant chunks. Different tools for different needs.

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3. Chat vs. Transformations

Why Open Notebook has different interaction modes and when to use each one.

Key idea: Chat is conversational exploration (you control context). Transformations are insight extractions. They reduced content to smaller bits of concentrated/dense information, which is much more suitable for an AI to use.

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4. Context Management

Your control panel for privacy and cost. Decide what data actually reaches AI.

Key idea: You choose three levels—not in context (private), summary only (condensed), or full content (complete access). This gives you fine-grained control.

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5. Podcasts Explained

Why Open Notebook can turn research into audio and why this matters.

Key idea: Podcasts transform your research into a different consumption format. Instead of reading, someone can listen and absorb your insights passively.

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Read This Section If:

• You're new to Open Notebook — Start here to understand how the system works conceptually before learning the features
• You're confused about Chat vs Ask — Section 2 explains the difference (full-content vs RAG)
• You're wondering when to use Chat vs Transformations — Section 3 clarifies the differences
• You want to understand privacy controls — Section 4 shows you what you can control
• You're curious about podcasts — Section 5 explains the architecture and why it's different from competitors

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The Big Picture

Open Notebook is built on a simple insight: Your research deserves to stay yours.

That means:

• Privacy by default — Your data doesn't leave your infrastructure unless you explicitly choose
• AI as a tool, not a gatekeeper — You decide which sources the AI sees, not the AI deciding for you
• Flexible consumption — Read, listen, search, chat, or transform your research however makes sense

These core concepts explain how that works.

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Next Steps

1. Just want to use it? → Go to User Guide
2. Want to understand it first? → Read the 5 sections above (15 min)
3. Setting up for the first time? → Go to Installation