open-notebook/docs/features/index.md

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Features

Open Notebook offers powerful features that set it apart from other AI research tools. This section provides deep dives into each capability, helping you master the advanced functionality that makes Open Notebook unique.

🤖 AI & Model Integration

🧠 AI Models

Complete guide to Open Notebook's multi-model AI support.

  • 15+ supported providers (OpenAI, Anthropic, Google, Ollama, and more)
  • Model selection strategies for cost and performance
  • Provider-specific setup and configuration
  • Advanced model switching and management
  • Cost optimization techniques

🎛️ Context Management

Master Open Notebook's granular context control system.

  • Three context levels: Not in Context, Summary Only, Full Content
  • Privacy-first configuration strategies
  • Performance optimization through context management
  • Integration with AI models for cost control
  • Advanced context features and automation

🔧 OpenAI-Compatible Providers

Use any OpenAI-compatible endpoint with Open Notebook.

  • LM Studio, Text Generation WebUI, vLLM support
  • Mode-specific configuration for different capabilities
  • Docker networking and remote server setup
  • Comprehensive troubleshooting and best practices
  • Works with local and cloud endpoints

🎙️ Local Text-to-Speech

Run text-to-speech completely locally using OpenAI-compatible TTS servers.

  • Zero ongoing costs after setup
  • Complete privacy - audio never leaves your machine
  • Multiple voice options and models
  • Perfect for podcast generation
  • Various local TTS solutions available

🦙 Ollama Setup

Configure local language models and embeddings with Ollama.

  • Free, privacy-focused AI models
  • Network configuration and Docker integration
  • Model recommendations and optimization
  • Troubleshooting and best practices

🔧 Content Processing

Transformations

Leverage Open Notebook's powerful content transformation system.

  • Built-in transformation types and examples
  • Custom transformation creation guide
  • Batch processing capabilities
  • Integration with notebooks and sources
  • Performance considerations and optimization

📝 Citations

Maintain research integrity with comprehensive citation support.

  • Automatic citation generation and formatting
  • Source attribution and accuracy verification
  • Integration with chat and notes
  • Export options with citation preservation
  • Best practices for academic research

🎵 Advanced Features

🎙️ Podcasts

Create professional multi-speaker podcasts from your research.

  • Advanced 1-4 speaker system (vs Google Notebook LM's 2-speaker limit)
  • Episode profiles and speaker configuration
  • Background processing and queue management
  • Audio quality settings and customization
  • Export and sharing capabilities

Feature Comparison

Feature Open Notebook Google Notebook LM Advantage
AI Providers 15+ providers Google only Complete flexibility
Context Control 3 granular levels All-or-nothing Privacy & performance
Podcast Speakers 1-4 speakers 2 speakers only Professional quality
Transformations Custom & built-in Limited Unlimited processing
Citations Comprehensive Basic Research integrity
Privacy Self-hosted Cloud-only Complete control

Integration Patterns

Research Workflow

SourcesTransformationsContext ManagementAI ModelsCitations

Content Creation

SourcesAI ModelsTransformationsPodcastsExport

Team Collaboration

Context ManagementCitationsTransformationsSharing

Best Practices

Getting Started

  1. Start with AI Models - Configure your preferred providers
  2. Master Context Management - Understand privacy and performance trade-offs
  3. Explore Transformations - Automate common research tasks
  4. Try Podcasts - Convert research into accessible audio content

Advanced Usage

  • Combine transformations for complex processing workflows
  • Use context management strategically for different research phases
  • Leverage citations for academic and professional credibility
  • Create custom episode profiles for consistent podcast quality

Performance Optimization

  • Context management reduces token usage and costs
  • Batch transformations for efficiency
  • Model selection based on task requirements
  • Background processing for time-intensive tasks

Next Steps

Need Help?


These features represent Open Notebook's core differentiators. Each one is designed to give you more control, better performance, and superior results compared to other AI research tools.