signalpilot 0.5.3

SignalPilot CLI - Your Trusted CoPilot for Data Analysis

SignalPilot Installer CLI

This installer CLI is a bootstrap installer that sets up the SignalPilot-AI Jupyter extension in one command.

**The CLI is NOT the product.** It's a convenience installer. The **SignalPilot Jupyter extension** (agentic harness) is the actual product.

What You're Installing

SignalPilot is a Jupyter-native AI agentic harness that investigates data by connecting to your organizational context:

Four core capabilities:

• 🔌 Multi-Source Context — Auto-connects to db warehouse, dbt lineage, query history, Slack threads, Jira tickets, and past investigations via MCP
• 🔄 Long-Running Agent Loop — Plans, executes, iterates until task complete with analyst-in-the-loop approval (not single-shot completions)
• 🧠 Multi-Session Memory — Remembers past hypotheses, validated assumptions, known data quirks across investigations
• 📚 Skills & Rules — Custom analysis patterns (skills) + team coding standards (rules) + business logic

Security: Zero data retention • Read-only access • Local-first execution • SOC 2 in progress

Quick Install

Prerequisites: macOS, Linux, or Windows (WSL) • Internet connection

Don't have uv? Install it first (takes 10 seconds):

curl -LsSf https://astral.sh/uv/install.sh | sh

Install SignalPilot:

uvx signalpilot

What happens:

• Creates ~/SignalPilotHome workspace with starter notebooks
• Installs isolated Python 3.12 + Jupyter Lab + SignalPilot extension
• Installs data packages (pandas, numpy, matplotlib, seaborn, plotly)
• Optimizes Jupyter cache for fast startup
• Launches Jupyter Lab at http://localhost:8888

Time: ~2 minutes

Why uv?

• 10-100x faster than pip/conda for package installation
• SignalPilot runs on it — native integration with kernel
• Modern Python package management with better dependency resolution

Launch Jupyter Lab Anytime

Once installed, start Jupyter Lab with:

uvx signalpilot lab

What this does:

• Opens Jupyter Lab in ~/SignalPilotHome (default workspace)
• Uses existing .venv (no reinstallation)
• SignalPilot extension pre-loaded
• Opens browser at http://localhost:8888

What Gets Installed

Python Packages:

• signalpilot-ai — AI agent integration (the actual product)
• jupyterlab — Modern Jupyter interface
• pandas, numpy — Data manipulation
• matplotlib, seaborn, plotly — Visualization
• python-dotenv, tomli — Configuration utilities

Directory Structure:

~/SignalPilotHome/
├── user-skills/       # Custom analysis patterns
├── user-rules/        # Team coding standards
├── team-workspace/    # Shared notebooks (git-tracked)
├── demo-project/      # Example notebooks
├── pyproject.toml     # Python project config
├── start-here.ipynb   # Quick start guide
└── .venv/             # Python environment

Working in Different Directories

By default, SignalPilot works in ~/SignalPilotHome. Use these flags to customize:

--here flag: Use current directory with default environment

cd ~/projects/my-analysis
uvx signalpilot lab --here

What this does:

• Opens Jupyter Lab in your current directory
• Uses default environment from ~/SignalPilotHome/.venv
• Perfect for quick exploration without setting up new environment

Use case: Analyzing data files in an existing project folder

--project flag: Use current directory with local environment

cd ~/projects/custom-analytics
uvx signalpilot lab --project

What this does:

• Opens Jupyter Lab in your current directory
• Uses local .venv in that directory
• Great for project-specific work with custom dependencies

Requirements:

• A .venv must exist in current directory
• Must have jupyterlab and signalpilot-ai installed

Create project environment:

mkdir ~/projects/custom-analytics && cd ~/projects/custom-analytics
uv venv --seed --python 3.12
source .venv/bin/activate
uv pip install jupyterlab signalpilot-ai pandas numpy matplotlib plotly
uvx signalpilot lab --project

Pass Jupyter Lab Arguments

You can pass any Jupyter Lab flags after the command:

# Custom port
uvx signalpilot lab --port=8888

# Disable browser auto-open
uvx signalpilot lab --no-browser

# Combine with directory flags
uvx signalpilot lab --here --port=8888

# Bind to all interfaces (remote access)
uvx signalpilot lab --ip=0.0.0.0 --port=9999

All standard jupyter lab arguments work.

Alternative Installation Methods

Option 1: Run with uvx (Recommended)

uvx signalpilot

No permanent installation needed. Perfect for most users.

Option 2: Install with uv tool

uv tool install signalpilot
sp init

Installs sp command globally. Use sp lab to launch later.

Option 3: Install with pip

pip install signalpilot
sp init

Works but slower than uv (10-100x). May have dependency conflicts.

Requirements

• Python 3.10 or higher
• uv package manager (recommended)

Links

• Homepage
• Full Documentation
• Installation Guide
• 5-Minute Quickstart
• GitHub

License

MIT License - See LICENSE file for details