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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