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Notebook Agent Guide

The Notebook agent manages Jupyter notebook operations, enabling programmatic creation, editing, and execution of notebook cells.

Overview

  • NotebookAgent - AI-powered Jupyter notebook manipulation and execution

NotebookAgent

The NotebookAgent understands: - Notebook structure and cells - Code execution order - Markdown documentation - Output handling and display

Basic Usage

from louieai.notebook import lui

# Create new notebook
lui("Create a new notebook for data analysis", agent="NotebookAgent")

# Add cells
lui("Add a code cell that imports pandas and numpy", agent="NotebookAgent")

# Execute notebook
lui("Run all cells in the current notebook", agent="NotebookAgent")

Notebook Creation

# Data science notebook
lui("""
Create a data science notebook with:
- Title and description markdown cell
- Import statements cell
- Data loading cell
- Analysis cells
- Visualization cells
""", agent="NotebookAgent")

# Tutorial notebook
lui("""
Create a tutorial notebook explaining:
- Concept introduction (markdown)
- Code example
- Exercise for the reader
- Solution (hidden initially)
""", agent="NotebookAgent")

# Report notebook
lui("""
Generate a report notebook containing:
- Executive summary
- Data analysis with code
- Visualizations
- Conclusions and recommendations
""", agent="NotebookAgent")

Cell Management

# Add cells
lui("""
Add a new cell after the current one that:
- Loads data from CSV
- Shows first 5 rows
- Displays basic statistics
""", agent="NotebookAgent")

# Edit cells
lui("""
Update the visualization cell to:
- Use seaborn instead of matplotlib
- Add proper labels and title
- Save the figure
""", agent="NotebookAgent")

# Organize cells
lui("""
Reorganize notebook:
- Group import cells at top
- Move utility functions together
- Place visualizations at end
""", agent="NotebookAgent")

Code Execution

# Run specific cells
lui("""
Execute:
- All data loading cells
- Skip visualization cells
- Clear previous outputs first
""", agent="NotebookAgent")

# Parameterized execution
lui("""
Run notebook with parameters:
- date_range = "2024-01-01 to 2024-12-31"
- output_format = "pdf"
- include_details = True
""", agent="NotebookAgent")

# Error handling
lui("""
Run notebook and:
- Continue on errors
- Log failed cells
- Mark problematic cells
""", agent="NotebookAgent")

Documentation

# Add documentation
lui("""
Document this notebook:
- Add overview at the top
- Explain each code section
- Include example outputs
- Add references
""", agent="NotebookAgent")

# Convert to documentation
lui("""
Convert notebook to:
- Clean documentation
- Remove debug code
- Format for publication
- Include only key outputs
""", agent="NotebookAgent")

# Add interactivity
lui("""
Make notebook interactive:
- Add widgets for parameters
- Create dropdown for options
- Add sliders for thresholds
- Include run button
""", agent="NotebookAgent")

Common Patterns

Data Analysis Workflow

# Complete analysis notebook
lui("""
Create a complete analysis notebook:
1. Data loading and validation
2. Exploratory data analysis
3. Feature engineering
4. Statistical analysis
5. Visualizations
6. Export results
""", agent="NotebookAgent")

# Reproducible research
lui("""
Set up reproducible notebook:
- Environment setup cell
- Random seed setting
- Data versioning
- Results checksums
""", agent="NotebookAgent")

Machine Learning Pipeline

# ML notebook template
lui("""
Create ML pipeline notebook:
1. Data preprocessing
2. Train/test split
3. Model training
4. Evaluation metrics
5. Hyperparameter tuning
6. Final predictions
""", agent="NotebookAgent")

# Experiment tracking
lui("""
Add experiment tracking:
- Log parameters
- Track metrics
- Save model artifacts
- Compare runs
""", agent="NotebookAgent")

Reporting and Dashboards

# Automated reports
lui("""
Generate weekly report notebook:
- Pull latest data
- Run standard analyses
- Create visualizations
- Format for email
""", agent="NotebookAgent")

# Interactive dashboards
lui("""
Create dashboard notebook with:
- Parameter cells
- Dynamic queries
- Interactive plots
- Real-time updates
""", agent="NotebookAgent")

Advanced Features

Template Management

# Create templates
lui("""
Save this notebook as template for:
- Data quality checks
- Remove specific values
- Keep structure and code
- Mark customizable sections
""", agent="NotebookAgent")

# Apply templates
lui("""
Create new notebook from template:
- Use analysis template
- Fill in project parameters
- Update data sources
- Customize visualizations
""", agent="NotebookAgent")

Notebook Conversion

# Export formats
lui("""
Convert notebook to:
- Python script (.py)
- Markdown document
- HTML presentation
- PDF report
""", agent="NotebookAgent")

# Clean outputs
lui("""
Prepare notebook for sharing:
- Clear all outputs
- Remove sensitive data
- Check for credentials
- Add license header
""", agent="NotebookAgent")

Collaboration Features

# Version control
lui("""
Prepare notebook for git:
- Clear outputs
- Consistent cell IDs
- Add cell tags
- Include requirements
""", agent="NotebookAgent")

# Review preparation
lui("""
Prepare for code review:
- Add docstrings
- Include type hints
- Add unit tests cells
- Document assumptions
""", agent="NotebookAgent")

Integration with Other Agents

# Generate analysis code
lui("Write code to analyze customer churn", agent="CodeAgent")

# Create notebook from code
lui("""
Create a notebook from this analysis:
- Split into logical cells
- Add markdown explanations
- Include visualizations
- Make it runnable
""", agent="NotebookAgent")

# Query data
lui("Get customer data for analysis", agent="PostgresAgent")

# Document findings
lui("Add conclusions based on the analysis", agent="TextAgent")

Best Practices

Cell Organization

# Logical structure
lui("""
Organize notebook with:
- Clear section headers
- One concept per cell
- Imports at the top
- Helper functions grouped
- Main analysis flow
- Results at the end
""", agent="NotebookAgent")

Performance

# Optimize execution
lui("""
Optimize notebook performance:
- Cache expensive operations
- Use efficient data structures
- Limit output size
- Add progress indicators
""", agent="NotebookAgent")

Maintainability

# Future-proof notebooks
lui("""
Make notebook maintainable:
- Pin dependency versions
- Use configuration files
- Parameterize paths
- Add error handling
- Include tests
""", agent="NotebookAgent")

Notebook Automation

# Scheduled execution
lui("""
Set up notebook to run:
- Daily at 6 AM
- With latest data
- Email results
- Archive outputs
""", agent="NotebookAgent")

# CI/CD integration
lui("""
Integrate notebook with CI/CD:
- Run on pull requests
- Check for errors
- Validate outputs
- Generate artifacts
""", agent="NotebookAgent")

Next Steps