b7e656a319
New front-end Launch Chat API Manage Sources Enable re-embedding of all contents Sources can be added without a notebook now Improved settings Enable model selector on all chats Background processing for better experience Dark mode Improved Notes Improved Docs: - Remove all Streamlit references from documentation - Update deployment guides with React frontend setup - Fix Docker environment variables format (SURREAL_URL, SURREAL_PASSWORD) - Update docker image tag from :latest to :v1-latest - Change navigation references (Settings → Models to just Models) - Update development setup to include frontend npm commands - Add MIGRATION.md guide for users upgrading from Streamlit - Update quick-start guide with correct environment variables - Add port 5055 documentation for API access - Update project structure to reflect frontend/ directory - Remove outdated source-chat documentation files
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# Frequently Asked Questions
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This document addresses common questions about Open Notebook usage, configuration, and best practices.
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## General Usage
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### What is Open Notebook?
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Open Notebook is an open-source, privacy-focused alternative to Google's Notebook LM. It allows you to:
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- Create and manage research notebooks
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- Chat with your documents using AI
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- Generate podcasts from your content
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- Search across all your sources with semantic search
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- Transform and analyze your content
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### How is Open Notebook different from Google Notebook LM?
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**Privacy**: Your data stays local by default. Only your chosen AI providers receive queries.
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**Flexibility**: Support for 15+ AI providers (OpenAI, Anthropic, Google, local models, etc.)
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**Customization**: Open source, so you can modify and extend functionality
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**Control**: You control your data, models, and processing
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### Do I need technical skills to use Open Notebook?
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**Basic usage**: No technical skills required. The Docker installation is designed for non-technical users.
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**Advanced features**: Some technical knowledge helpful for:
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- Custom model configurations
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- API integrations
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- Source code modifications
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### Can I use Open Notebook offline?
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**Partially**: The application runs locally, but requires internet for:
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- AI model API calls (unless using local models like Ollama)
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- Web content scraping
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- Some file processing features
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**Fully offline**: Possible with local models (Ollama) for basic functionality.
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### What file types does Open Notebook support?
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**Documents**:
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- PDF (text extraction)
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- Microsoft Word (DOC, DOCX)
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- Plain text (TXT)
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- Markdown (MD)
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**Web Content**:
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- URLs (automatic web scraping)
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- YouTube videos (transcript extraction)
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- Web articles and blog posts
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**Media**:
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- Images (PNG, JPG, GIF, WebP) with OCR
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- Audio files (MP3, WAV, M4A) with transcription
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- Video files (MP4, AVI, MOV) for transcript extraction
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**Other**:
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- Direct text input
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- CSV data
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- Code files (with syntax highlighting)
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### How much does it cost to run Open Notebook?
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**Software**: Free (open source)
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**AI API costs**: Pay-per-use to providers:
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- OpenAI: ~$0.50-5 per 1M tokens depending on model
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- Anthropic: ~$3-75 per 1M tokens depending on model
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- Google: Often free tier available
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- Local models: Free after initial setup
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**Typical monthly costs**: $5-50 for moderate usage, depending on chosen models.
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## AI Models and Providers
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### Which AI provider should I choose?
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**For beginners**: OpenAI (reliable, well-documented, good balance of cost/quality)
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**For advanced users**: Mix of providers based on specific needs
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**For privacy**: Local models (Ollama) or European providers (Mistral)
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**For cost optimization**: DeepSeek, Google (free tier), or OpenRouter
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### Can I use multiple AI providers simultaneously?
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**Yes**: Open Notebook supports multiple providers. You can configure different providers for different tasks:
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- OpenAI for chat
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- Google for embeddings
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- ElevenLabs for text-to-speech
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- Anthropic for complex reasoning
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### What are the best model combinations?
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**Budget-friendly**:
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- Language: `gpt-5-mini` (OpenAI) or `deepseek-chat` (DeepSeek)
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- Embedding: `text-embedding-3-small` (OpenAI)
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- TTS: `gpt-4o-mini-tts` (OpenAI)
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**High-quality**:
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- Language: `claude-3-7-sonnet` (Anthropic) or `gpt-4o` (OpenAI)
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- Embedding: `text-embedding-3-large` (OpenAI)
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- TTS: `eleven_turbo_v2_5` (ElevenLabs)
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**Privacy-focused**:
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- Language: Local Ollama models
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- Embedding: Local embedding models
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- TTS: Local TTS solutions
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### How do I set up local models with Ollama?
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1. **Install Ollama**: Download from https://ollama.ai
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2. **Start Ollama**: `ollama serve`
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3. **Download models**: `ollama pull llama2`
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4. **Configure Open Notebook**:
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```env
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OLLAMA_API_BASE=http://localhost:11434
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```
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5. **Select models**: In Models, choose Ollama models
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### Why are my AI requests failing?
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**Common causes**:
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- Invalid API keys
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- Insufficient credits/billing
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- Model not available for your account
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- Rate limiting
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- Network connectivity issues
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**Solutions**:
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1. Verify API keys in provider dashboard
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2. Check billing and usage limits
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3. Try different models
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4. Wait and retry for rate limits
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5. Check internet connection
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### How do I optimize AI costs?
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**Model selection**:
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- Use smaller models for simple tasks
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- Use larger models only for complex reasoning
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- Leverage free tiers when available
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**Usage optimization**:
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- Process documents in batches
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- Use shorter prompts
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- Cache results when possible
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- Use local models for frequent tasks
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**Provider diversity**:
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- Use OpenRouter for expensive models
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- Use free tier providers for testing
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- Mix providers based on strength
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## Data Management
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### Where is my data stored?
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**Local storage**: By default, all data is stored locally:
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- Database: SurrealDB files in `surreal_data/`
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- Uploads: Files in `notebook_data/`
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- No external data transmission (except to chosen AI providers)
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**Cloud storage**: Not implemented, but can be configured with external storage solutions.
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### How do I backup my data?
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**Manual backup**:
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```bash
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# Create backup
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tar -czf backup-$(date +%Y%m%d).tar.gz notebook_data/ surreal_data/
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# Restore backup
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tar -xzf backup-20240101.tar.gz
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```
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**Automated backup**: Set up cron jobs or use your preferred backup solution to backup the data directories.
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### Can I sync data between devices?
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**Currently**: No built-in sync functionality.
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**Workarounds**:
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- Use shared network storage for data directories
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- Manual backup/restore between devices
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- Database replication (advanced)
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### How do I migrate data between installations?
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1. **Stop services**: `make stop-all`
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2. **Copy data directories**:
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```bash
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cp -r surreal_data/ new_installation/
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cp -r notebook_data/ new_installation/
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```
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3. **Start new installation**
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4. **Verify data integrity**
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### What happens to my data if I delete a notebook?
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**Soft deletion**: Notebooks are marked as archived, not permanently deleted.
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**Hard deletion**: Currently not implemented in UI, but possible via API.
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**Recovery**: Archived notebooks can be restored from the database.
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### How do I clean up old data?
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**Manual cleanup**:
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- Delete unused notebooks through UI
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- Remove old files from `notebook_data/`
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- Clear browser cache
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**Database cleanup**: Advanced users can query the database directly to remove old records.
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## Best Practices
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### How should I organize my notebooks?
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**By topic**: Create separate notebooks for different research areas
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**By project**: One notebook per project or course
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**By source type**: Separate notebooks for different content types
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**By time period**: Monthly or quarterly notebooks
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### What's the optimal notebook size?
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**Recommended**: 20-100 sources per notebook
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**Performance**: Larger notebooks may have slower search
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**Organization**: Better to have focused notebooks than everything in one
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### How do I get the best search results?
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**Use descriptive queries**: Instead of "data", use "data analysis methods"
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**Combine keywords**: Use multiple related terms
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**Use natural language**: Ask questions as you would to a human
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**Refine iteratively**: Start broad, then get more specific
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### How can I improve chat responses?
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**Provide context**: Reference specific sources or topics
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**Be specific**: Ask detailed questions rather than general ones
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**Use follow-up questions**: Build on previous responses
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**Include examples**: Show what kind of response you want
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### What's the best way to process large documents?
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**Break into sections**: Split large documents into smaller parts
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**Use transformations**: Apply summarization before adding to notebook
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**Batch processing**: Process multiple documents at once
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**Use background jobs**: For heavy processing tasks
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### How do I handle multiple languages?
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**Model selection**: Choose models that support your languages
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**Language-specific providers**: Some providers are better for certain languages
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**Separate notebooks**: Consider separate notebooks for different languages
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**Encoding**: Ensure proper text encoding for non-English content
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### What are the security best practices?
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**API keys**: Never share API keys publicly
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**Password protection**: Use strong passwords for public deployments
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**Network security**: Use HTTPS for production deployments
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**Regular updates**: Keep Docker images updated
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**Backup encryption**: Encrypt backups if they contain sensitive data
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### How do I optimize performance?
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**Hardware**:
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- Use SSD storage for database
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- Allocate sufficient RAM (4GB+ recommended)
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- Use fast internet connection
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**Configuration**:
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- Choose appropriate models for your needs
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- Optimize embedding dimensions
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- Use efficient file formats
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**Usage patterns**:
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- Process documents in batches
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- Use background jobs for heavy tasks
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- Clear cache periodically
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## Technical Questions
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### Can I use Open Notebook programmatically?
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**Yes**: Open Notebook provides a comprehensive REST API:
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- Full API documentation at `/docs` endpoint
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- Support for all UI functionality
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- Authentication via API keys
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- Webhook support for notifications
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### How do I extend Open Notebook?
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**Plugin system**: Add custom transformations and processors
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**API integration**: Build custom applications using the API
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**Source code**: Modify the open-source codebase
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**Custom models**: Add support for new AI providers
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### Can I run Open Notebook in production?
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**Yes**: Designed for production use with:
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- Docker deployment
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- Horizontal scaling capability
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- Security features
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- Monitoring and logging
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**Considerations**:
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- Use production-grade database settings
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- Implement proper backup strategy
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- Configure monitoring and alerting
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- Use HTTPS and security best practices
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### How do I contribute to Open Notebook?
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**Ways to contribute**:
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- Report bugs and issues
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- Suggest new features
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- Contribute code improvements
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- Improve documentation
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- Help other users in the community
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**Getting started**:
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- Join Discord community
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- Check GitHub issues
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- Read contribution guidelines
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- Start with small improvements
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### What's the development roadmap?
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**Current focus**:
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- Stability and performance improvements
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- Additional AI provider support
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- Enhanced podcast generation
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- Better mobile experience
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**Future plans**:
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- Multi-user support
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- Advanced analytics
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- Integration with external tools
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- Cloud deployment options
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## Troubleshooting
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### My question isn't answered here. What should I do?
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1. **Check the troubleshooting guide**: [Common Issues](./common-issues.md)
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2. **Search existing issues**: GitHub repository issues
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3. **Ask the community**: Discord server
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4. **Create a GitHub issue**: For bugs or feature requests
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5. **Check the documentation**: Other documentation sections
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### How do I report a bug?
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**Include**:
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- Steps to reproduce
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- Expected vs actual behavior
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- Error messages and logs
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- System information
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- Configuration details (without API keys)
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**Submit to**: GitHub Issues with bug report template
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### How do I request a new feature?
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**Process**:
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1. Check if feature already exists or is planned
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2. Discuss in Discord to gauge interest
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3. Create detailed GitHub issue
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4. Consider contributing implementation
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### Where can I get help with installation?
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**Resources**:
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- [Installation Guide](../getting-started/installation.md)
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- [Docker Deployment Guide](../deployment/docker.md)
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- [ChatGPT Installation Assistant](https://chatgpt.com/g/g-68776e2765b48191bd1bae3f30212631-open-notebook-installation-assistant)
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- Discord community support
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### How do I stay updated with new releases?
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**Methods**:
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- Watch GitHub repository
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- Join Discord for announcements
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- Follow release notes
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- Enable automatic Docker updates
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---
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*This FAQ is updated regularly based on community questions and feedback. If you have a question that's not covered here, please ask in our Discord community or create a GitHub issue.* |