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Introduction

Chanterelle is a lightweight desktop application for data scientists and ML engineers to test, present, and share models and findings — without deploying anything to the cloud.

Project files are plain JSON and Python, so they live alongside your code in version control and open instantly in Chanterelle.

Project Types​

TypeWhat you writeWhat Chanterelle gives you
🧠Modelmodel_meta.json + handler_io.pyA generated UI form wired to your Python model
📊Analyticsanalytics.jsonA rich static dashboard with charts, tables, and images
💬Interactiveinteractive.json + handler_io.pyA multi-turn conversational agent with dynamic forms

Which should I use?​

  • Model — You have a trained ML model and want to test it interactively, or hand it off to a stakeholder without building a full UI.
  • Analytics — You have plots, tables, and KPI numbers you want to package into a shareable report. No live Python required.
  • Interactive — You want a back-and-forth conversation interface: a SQL assistant, a reporting workflow, an LLM wrapper, or similar.

How It Works​

Model Projects​

Three components, all in your project folder:

1. model_meta.json — defines inputs, outputs, presets, and UI settings.
➡️ Model Metadata reference

2. handler_io.py — Python functions that load, transform, and run your model.
➡️ Handler functions reference

3. model_findings.json (optional) — a dedicated insights page with charts, confusion matrices, KPIs, and more.
➡️ Model Findings reference

Analytics Projects​

Write an analytics.json with sections and visualizations. Chanterelle renders it as a navigable report with a table of contents sidebar. No Python runtime required.
➡️ Analytics reference

Interactive Projects​

Write an interactive.json and a handler_io.py with initialize() and on_input() functions. The Python process stays alive across turns so you can maintain state and stream responses.
➡️ Interactive reference


Using an AI Coding Assistant?

Chanterelle includes a built-in skill that teaches GitHub Copilot, Cursor, Windsurf, and others how to scaffold valid project files from natural language descriptions.

➡️ Learn more