Skip to main content

AI-native programming language for deterministic, inspectable applications.

This project has been archived.

The maintainers of this project have marked this project as archived. No new releases are expected.

Project description

namel3ss

AI-native programming language for deterministic, inspectable applications. Deterministic execution with explicit AI boundaries and governed runtime.

namel3ss: one .ai file defining data, flows, explicit AI, and deterministic UI

One .ai file defines records, deterministic flows, explicit AI boundaries, and UI — with inspectable state changes.

license: MIT tests


Start here

Try it in 60 seconds: docs/quickstart.md.

Run modes

  • n3 run app.ai runs in production mode and renders only user-facing UI.
  • n3 run studio app.ai (or n3 run --studio app.ai) runs the same app with Studio instrumentation in the manifest.
  • n3 studio app.ai remains available as the dedicated Studio inspector command.
  • UI blocks can be marked with debug_only metadata so they render only in Studio mode.
  • Custom UI components are opt-in via use plugin "name" and require custom_ui in capabilities.

What you can run today

RAG support (deterministic)

namel3ss supports production-grade retrieval-augmented generation as a first-class pattern:

  • Deterministic ingestion and retrieval
  • Answering with mandatory citations
  • PDF page preview and exact source highlighting
  • Explain mode for auditable selection
  • Optional embeddings (runtime config only, no grammar changes)

See the canonical overview: docs/rag/overview.md

Core stable

Core stable is the graduation gate for the language surface, compiler determinism, and safety guards. See the authoritative definition in docs/graduation/core_stable.md.

Get started

Develop from source

Use this for development and testing.

python3 -m venv .venv && . .venv/bin/activate
python3 -m pip install --upgrade pip && python3 -m pip install -e ".[dev]"
python3 -m namel3ss --help

Run with Docker (isolated runtime)

Use this for a clean, repeatable runtime.

docker build -t namel3ss:local .
docker run --rm namel3ss:local n3 --help

Learn / explore (docs & templates)

Use the local Docker image to open Studio for a bundled demo.

docker run -d --name namel3ss_studio -p 7340:7340 \
  -v "$PWD:/workspace" -w /workspace \
  namel3ss:local n3 app/app.ai studio --host 0.0.0.0 --port 7340
docker logs namel3ss_studio
docker rm -f namel3ss_studio

See docs/install-and-run.md for complete install and Studio instructions.

Installation (summary)

Supported paths:

  • Install from source (development)
  • Docker (local) for an isolated runtime

Full guide: docs/install-and-run.md

Docker quick check:

docker build -t namel3ss:local .
docker run --rm namel3ss:local n3 --help

Install + Verify

Install (source, editable):

python3 -m pip install --upgrade pip
python3 -m pip install -e ".[dev]"

Verify CLI and package:

n3 --version
n3 doc
python3 tools/package_verify.py

Verify embedding (C example, requires C toolchain + cargo):

python3 -m pytest -q tests/embed/test_embed_c_example.py

Browser Protocol

Browser Protocol is defined in docs/runtime/browser-protocol.md.

Docker & CI guarantees

  • Docker builds install from local source, not PyPI.
  • Docker builds are validated in CI.
  • CLI smoke tests are enforced automatically.
  • Wheel installs are smoke-tested in release automation.

References:

Release & governance

Release invariants (enforced):

  • VERSION is metadata.
  • Docker builds do not depend on PyPI.
  • Publish is gated by CI and guards.
  • Canonical sequence: VERSION bump → tests → tag → PyPI publish → docker image → release notes.

References:

How it works (high level)

Design guarantees:

  • Deterministic execution
  • Explicit AI boundary
  • Inspectable state and traces
  • Governed memory

Runtime guarantees:

  • Stable CLI surface
  • Deterministic manifests and outputs
  • Read-only diagnostics and explain output
  • Safe cleanup of runtime artifacts

See docs/trust-and-governance.md.

UX as a Contract

UX behavior is deterministic and explainable through stable manifests and n3 see output.

Guarantees:

  • Uploads (progress, preview metadata, async errors)
  • Conditional UI (state-gated visibility)
  • Reusable UI patterns (compile-time expansion)
  • Accessibility by default (roles, labels, keyboard, contrast)

Detailed UX contracts: docs/ui/overview.md

Language Contracts

Language Contracts are defined here:

Reserved identifiers

If you must use reserved identifiers, escape them with backticks and use n3 reserved to list them. The reserved words list is in docs/language/reserved-words.md.

Documentation index

Getting started:

Language & grammar:

Runtime & backend:

UI & Studio:

Governance & releases:

Discussions & Design Conversations

GitHub Discussions is the canonical place for architectural and language design conversations. Use Discussions for design questions, trade-offs, and long-form proposals; use Issues for bugs and actionable feature requests.

Reference discussion: https://github.com/namel3ss-Ai/namel3ss/discussions/2

Contributing

See CONTRIBUTING.md.

Summary:

  • Clone the repo.
  • Create and activate a virtual environment.
  • Install editable + run tests (python3 -m pytest -q).

Troubleshooting

Project details


Download files

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

Source Distribution

namel3ss-0.1.0a20.tar.gz (2.0 MB view details)

Uploaded Source

Built Distribution

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

namel3ss-0.1.0a20-py3-none-any.whl (3.1 MB view details)

Uploaded Python 3

File details

Details for the file namel3ss-0.1.0a20.tar.gz.

File metadata

  • Download URL: namel3ss-0.1.0a20.tar.gz
  • Upload date:
  • Size: 2.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.10

File hashes

Hashes for namel3ss-0.1.0a20.tar.gz
Algorithm Hash digest
SHA256 900f2968bc23d4f4d842c3c41cd4ea760d2b16d54340a12f7630845e0e806d6e
MD5 1cb9c6d29c9c5f513469597ea10b1021
BLAKE2b-256 bc36045e4659bfd2045c3c1e921d9be40a72c011a9ebf3ae5501c6954cc66647

See more details on using hashes here.

File details

Details for the file namel3ss-0.1.0a20-py3-none-any.whl.

File metadata

  • Download URL: namel3ss-0.1.0a20-py3-none-any.whl
  • Upload date:
  • Size: 3.1 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.10

File hashes

Hashes for namel3ss-0.1.0a20-py3-none-any.whl
Algorithm Hash digest
SHA256 26ab7f8990452f6dfc43e79795416004cde18f7e2362b13da6bcd4132f44e2fc
MD5 1804cf057288df5b2fd1698eddea0bc8
BLAKE2b-256 00a8416f670d67b076fa4b03500209e978928d25f1372c5fe4f5fa945aca2807

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