Skip to main content

SignalPilot Agent - Your Jupyter Notebook Assistant

Project description

SignalPilot Agent — The AI-Powered Assistant for Jupyter Notebooks

Logo


What is SignalPilot Agent?

SignalPilot is an AI-native notebook assistant that supercharges your existing Jupyter workflows.

Built by leading AI and quant researchers from YC, Harvard, MIT, and Goldman Sachs, SignalPilot brings real-time, context-aware assistance directly into JupyterLab.

Use natural language to clean data, write analysis code, debug errors, explore dataframes, and build models—faster and with fewer mistakes.

No hallucinated code. No context switching. Just faster insights.


Why Use SignalPilot Agent in Jupyter?

Whether you’re a quant, data scientist, or analyst living in notebooks, SignalPilot helps you:

✅ Clean and transform messy data in seconds

✅ Visualize trends, rollups, and anomalies from a prompt

✅ Connect your custom databases in one click and easily explore from notebooks

✅ Generate runnable Python or SQL that fits your current cell + variable context

✅ Auto-detect schema changes and debug downstream errors

✅ Stay private: run entirely local-first or in your own secure VPC

✅ Extend JupyterLab without changing how you work


Perfect For:

  • Data scientists cleaning huge CSVs
  • Quant researchers testing ML pipelines
  • Product and analytics teams tired of building dashboards and flaky notebooks
  • Anyone tired of LLM tools that break their code

Installation

📦 Requirements

  • JupyterLab >= 4.0.0
  • NodeJS (for development)

🧠 Install SignalPilot Agent:

pip install jupyterlab signalpilot_ai_internal

❌ Uninstall:

pip uninstall signalpilot_ai_internal

How to Get Started

To unlock full functionality, you’ll need SignalPilot API credentials.

👉 Request your API key or email us at fahim@signalpilot.ai


Why SignalPilot

  • ✅ Context-aware code gen: understands variables, dataframes, imports, and prior cells
  • ✅ AI that fixes schema issues and silent join bugs
  • ✅ Inline review + diffs before you run any code
  • ✅ Visualizations via natural language (matplotlib, plotly, seaborn supported)
  • ✅ BYO LLM: Anthropic, OpenAI, vLLM, Ollama, or HF endpoints
  • ✅ Built to run in air-gapped / enterprise environments

Local Development Instructions

To contribute or develop locally:

# Clone the repo and enter the directory
git clone https://github.com/sagebook/signalpilot_ai_internal.git
cd signalpilot_ai_internal

# Install in editable mode
pip install -e "."

# Link extension to JupyterLab
jupyter labextension develop . --overwrite

# Rebuild on changes
jlpm build

For auto-rebuild while editing:

# Watch source
jlpm watch

# Run JupyterLab in parallel
jupyter lab

Uninstall in Dev Mode

pip uninstall signalpilot_ai_internal
# Then manually remove labextension symlink from JupyterLab extensions dir.

Want to See SignalPilot in Action?

🎥 Try the demo notebook or explore at https://signalpilot.ai


Built for teams working with sensitive data:

  • Zero data retention by default
  • Optional BYO keys for Claude, OpenAI, or local models
  • Notebook-specific controls for what the model can “see”
  • Fine-grained telemetry settings

Contact

Questions? Ideas?

Email: fahim@signalpilot.ai

Website: https://signalpilot.ai


AI Jupyter Notebook, JupyterLab Extension, Jupyter Assistant, Data Science Assistant, Jupyter LLM, AI code generation, dataframe cleaning, Jupyter AI, SignalPilot, SignalPilot Agent, AI for dataframes, Jupyter SQL assistant, notebook extension

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

signalpilot_ai_internal-0.9.32.tar.gz (2.3 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

signalpilot_ai_internal-0.9.32-py3-none-any.whl (1.5 MB view details)

Uploaded Python 3

File details

Details for the file signalpilot_ai_internal-0.9.32.tar.gz.

File metadata

File hashes

Hashes for signalpilot_ai_internal-0.9.32.tar.gz
Algorithm Hash digest
SHA256 35562d6c4077ebb5bbb6b950f565819593b5385e705c5ccafdd819fcc85e4d35
MD5 e0bc937c104ad41057378d525e8d719d
BLAKE2b-256 978bb02c99a3e50c626d8c36d3531db678f7c2ab6cc4b202d45e71bc1f687194

See more details on using hashes here.

File details

Details for the file signalpilot_ai_internal-0.9.32-py3-none-any.whl.

File metadata

File hashes

Hashes for signalpilot_ai_internal-0.9.32-py3-none-any.whl
Algorithm Hash digest
SHA256 b7e5cc883c67371a004f557e17c960a776afe1f4b1a9fef6355074a4065947ad
MD5 aee931bb66570c0451087f5f8fca52ca
BLAKE2b-256 7f85ee340f7ac8d757f2824c4cabe4161e46c0e4d09c68074a636d88be1d5668

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page