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Build AI-native applications in plain English. Data, UI, backend logic, and AI — all in one .ai file.

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Project description

namel3ss

Build AI-native applications in plain English — with explanations you can trust.

Try it in 60 seconds

The 10-minute demo (ClearOrders)

pip install namel3ss
n3 new demo
cd demo
n3 run

The first-run experience opens your browser to the ClearOrders app with orders, Ask AI, and Why? explanations ready to try.

  • Orders dataset
  • Ask AI + Answer
  • Why? explanation

Open Studio:

n3 app.ai studio

Why namel3ss

One .ai file describes your data, UI, backend logic, and AI behavior. Runs are deterministic in a clear execution environment, with AI as an explicit boundary. Explainability is built in so you can trust what happened and why. The first-run experience is designed to feel finished, not experimental.

What makes it different

  • One .ai file defines data, UI, backend logic, and AI.
  • Deterministic execution environment by default; AI is explicit and traced.
  • Built-in run summary and explanations for flows, tools, and UI.
  • File-first CLI and Studio for inspection and interaction.
  • First-run experience that opens the demo in a browser automatically.

Quickstart (non-demo)

n3 new starter my_app
cd my_app
n3 app.ai

Minimal UI example:

page "home":
  title is "Hello"
  text is "Welcome"

Optional AI example:

ai "assistant":
  provider is "mock"
  model is "mock-model"
  system_prompt is "You are a concise assistant."

flow "reply":
  ask ai "assistant" with input: input.message as reply
  return reply

Status

namel3ss is in v0.1.0a7 alpha. It is suitable for learning and experimentation, not production. Expect breaking changes between alpha revisions.

Start here (learning path)

Documentation index

Getting started

UI

Explainability

Tools & packs

Deployment & promotion

Trust, memory & governance

Memory in one minute: namel3ss memory is explicit, governed, and inspectable. It records what matters (preferences, decisions, facts, corrections) under clear policies, with deterministic recall and traceable writes — so AI behavior can be reviewed instead of guessed. You can inspect what was recalled or written through Studio and CLI explanations.

Stability & limitations

Community & support

Contributing

Read CONTRIBUTING.md and ECOSYSTEM.md.

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