229 lines
4.0 KiB
Markdown
229 lines
4.0 KiB
Markdown
# VAPORA Interactive Notebooks
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Interactive Marimo notebooks for exploring VAPORA capabilities.
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## What are Marimo Notebooks?
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Marimo is a modern Python notebook framework that's:
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- **Reactive**: Automatically updates when inputs change
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- **Git-friendly**: Pure Python files (not JSON)
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- **Interactive**: Widgets and dynamic visualizations
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- **Perfect for**: Learning, experimentation, demos
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## Installation
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### Prerequisites
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- Python 3.9+
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- VAPORA examples working
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### Setup
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```bash
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# Create virtual environment
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python3 -m venv venv
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source venv/bin/activate
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# Install dependencies
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pip install -r requirements.txt
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```
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## Available Notebooks
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### 1. Agent Basics
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**File**: `01-agent-basics.py`
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Interactive exploration of agent registration and selection.
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**Features**:
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- Agent role selector (dropdown)
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- Load slider (0-100%)
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- Capability matrix visualization
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- Scoring formula calculator
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**Run**:
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```bash
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marimo run 01-agent-basics.py
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```
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### 2. Budget Playground
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**File**: `03-budget-playground.py`
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Experiment with budget limits and cost optimization.
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**Features**:
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- Monthly budget slider ($0-$1000)
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- Task complexity selector
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- Provider cost comparison chart
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- Budget timeline visualization
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**Run**:
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```bash
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marimo run 03-budget-playground.py
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```
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### 3. Learning Curves
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**File**: `04-learning-curves.py`
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Visualize agent learning over time.
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**Features**:
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- Agent selector dropdown
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- Time window (7/14/30 days)
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- Learning curve plot (Plotly)
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- Success rate trend
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- Confidence intervals
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**Run**:
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```bash
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marimo run 04-learning-curves.py
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```
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### 4. Cost Analysis
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**File**: `06-cost-analysis.py`
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Analyze cost optimization strategies.
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**Features**:
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- Workload profile selector
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- Provider comparison chart
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- Cost efficiency analysis
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- ROI calculator
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**Run**:
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```bash
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marimo run 06-cost-analysis.py
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```
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## Using Notebooks
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### Launch Marimo Server
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```bash
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# Auto-open in browser
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marimo run 01-agent-basics.py
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# Manual: Open http://localhost:3000
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marimo server --port 3000
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```
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### Notebook Features
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**Reactive Updates**
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- Change a slider → instantly recalculate
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- Select dropdown → automatically visualize
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- All dependent cells update automatically
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**Widgets**
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```python
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# Create interactive input
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budget = mo.ui.slider(min=0, max=1000, value=500)
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mo.md(f"Budget: ${budget.value}")
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```
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**Visualizations**
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```python
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# Use Plotly for interactive charts
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import plotly.express as px
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fig = px.line(data, x='date', y='success_rate')
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mo.plot(fig)
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```
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**Running Shell Commands**
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```python
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import subprocess
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# Call Rust examples
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result = subprocess.run(
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["cargo", "run", "--example", "01-simple-agent"],
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capture_output=True,
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text=True
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)
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print(result.stdout)
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```
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## Common Patterns
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### Parameter Input
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```python
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agent_role = mo.ui.dropdown(
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["developer", "reviewer", "architect"],
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value="developer"
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)
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```
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### Visualization
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```python
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import plotly.graph_objects as go
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fig = go.Figure()
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fig.add_trace(go.Scatter(x=dates, y=values))
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mo.plot(fig)
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```
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### Data Display
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```python
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import pandas as pd
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df = pd.DataFrame({
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"Agent": ["alice", "bob"],
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"Expertise": [0.92, 0.78],
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})
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mo.ui.dataframe(df)
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```
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## Learning Workflow
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**Beginner**:
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1. Run 01-agent-basics.py
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2. Experiment with agent selection
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3. Understand scoring formula
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**Intermediate**:
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1. Run 03-budget-playground.py
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2. Test different budgets
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3. Observe cost implications
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**Advanced**:
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1. Run 04-learning-curves.py
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2. Analyze trends
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3. Predict future performance
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## Troubleshooting
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**"marimo command not found"**
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```bash
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pip install marimo
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marimo --version
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```
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**"Module not found: plotly"**
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```bash
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pip install -r requirements.txt
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```
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**"Port already in use"**
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```bash
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marimo server --port 3001 # Use different port
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```
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## Contributing Notebooks
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To create new notebook:
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1. Create `NN-description.py` in this directory
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2. Use provided template structure
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3. Add to `README.md`
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4. Test: `marimo run NN-description.py`
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## Resources
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- Marimo docs: https://marimo.io
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- Plotly docs: https://plotly.com/python
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- Interactive examples: https://marimo.io/examples
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---
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**Total notebooks**: 4
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Start with `01-agent-basics.py` →
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