A free, open-source AISC 360/341 steel-design agent that runs locally. Paste a design brief and watch the agent build an OpenSees model + a stamped-style HTML report + an interactive 3D viewer — bringing your own LLM (your API base-url + key, held in memory only, never written to disk).

browser ──▶ FastAPI app (localhost) ──▶ your LLM (key in app memory, never stored)
                 │  parses tool calls
                 ▼
           sandbox executor (run_python only) — Docker when available
                 │
           steel engine + OpenSees ─▶ report.html + viewer_3d.html

Not for construction. Every output is produced by your own AI model, may be incomplete or incorrect, and must be independently checked and sealed by a licensed professional engineer before any use for design, construction, or permitting. See DISCLAIMER.md.

With uv (recommended — no Python setup needed):

uv tool install --python 3.12 steltic
steltic                      # starts on http://127.0.0.1:8000 and opens your browser

The --python 3.12 matters: openseespy (the analysis engine) ships compiled binaries for Python 3.10–3.12 only, and uv ignores the package's upper Python bound — without the flag it may install onto a newer interpreter where the engine can't load (Steltic will tell you and refuse to start). uv downloads 3.12 automatically if you don't have it. Or with pipx (which respects the bound): pipx install --python 3.12 steltic. The install includes the full engine (openseespy/numpy/scipy/matplotlib, ~400MB) so designs run out of the box without Docker. Or from a checkout:

git clone <this repo> && cd steltic
python -m venv .venv && . .venv/bin/activate
pip install -e .
./run_local.sh               # http://localhost:8000

First run: open Settings, enter your provider's API base URL (any OpenAI-compatible endpoint — OpenRouter, vLLM, Together, Fireworks, OpenAI, Anthropic…), your API key, and a model id. Then paste a brief (stories, bays & spacings, loads, seismic, system) — or pick one of the 36 built-in example briefs — and click Design building.

Offline smoke test: set Model to MOCK — it drives the whole pipeline (sandbox, engine, OpenSees, report) with no LLM.

Windows note: if launching fails with "Application Control policy has blocked this file" or "os error 4551", Windows Smart App Control is blocking uv's downloaded (unsigned) Python. Fix: install the signed python.org build and point uv at it —

winget install Python.Python.3.12       # then open a new terminal
uv tool uninstall steltic
$env:UV_PYTHON_PREFERENCE = "only-system"
uv tool install --python 3.12 steltic

The agent's Python only ever executes in a sandbox. EXECUTOR (env / .env) picks the mode:

Steltic binds to 127.0.0.1 and has no authentication — don't expose the port. Designs are saved under your OS user-data dir (e.g. %LOCALAPPDATA%\Steltic, ~/.local/share/Steltic); override with DATA_DIR.

The hosted version of Steltic at stelticai.com grounds the agent with RAG vector databases of AISC 360, 341 and 358 (2022), the AISC Steel Construction Manual Design Examples (V16.0, 168 worked examples), an examples database of validated OpenSees models, and two databases of the OpenSees documentation. The specifications and design examples ground the LLM in the current procedures; the OpenSees databases help it build the model — and when OpenSees throws errors, resolve them. Steltic's performance has been validated with these databases and will likely reduce without them.

For copyright reasons the vector databases of AISC 360, 341 and 358 are not open-sourced in this project. The rest are freely downloadable from this repo's Releases page as portable .jsonl.gz dumps (pre-embedded; see rag_v2/README.md for loading them into your own Qdrant): steel_design_examples (168 original worked Q&A covering the AISC Design Examples scope), opensees_buildings_3d (40 validated 3D building models), opensees_building_templates, and the two OpenSees documentation sets.

Two options:

1. None (default — not recommended). Leave RAG_API_URL empty — the agent relies on its own cited AISC knowledge. Good models do respectably; grounded runs are better.
2. Bring your own server. Run any server exposing the small API described in rag_v2/README.md: load the downloadable OpenSees databases, and build the standards collections from your own licensed copies with the rag_v2/ chunking + ingestion starter kit. Then put the connection in the environment (or a .env next to where you launch): RAG_API_URL=http://your-server:8080/query and, if your server enforces one, RAG_API_TOKEN=....

The Nonlinear module can hand a re-design back through Continue once its Chapter 16 / pushover / DDM run is complete (see steltic_nonlinear/docs/README_feedback.md). Three things in this repository exist for that:

• cfg['drift_relief_16_1_2'] — the ASCE 7-22 §16.1.2 relief block SNL writes when a Chapter 16 analysis lets the §12.12.1 drift limits be relaxed (Risk Category I–III only). steel_engine/preflight.py and consistency.py accept a relaxed drift_limit only with a complete block, never for Risk Category IV, and never above the Chapter 16 limit; Chapter 8 of the report states the relief and that the design is provisional until Chapter 16 is re-run.
• POST /api/restore/<building>?archive=1 — moves an existing job aside as <building>__<timestamp> before the restore (what a fresh run already does), so a promoted candidate never silently overwrites a design of record; viewer_3d.html is now part of the restore whitelist.
• design/design_of_record.json — written by SNL when the user promotes a verified candidate; the report's Chapter 1 basis table shows it. The agent contract (contract/AGENT_START.md, Feedback from the Nonlinear module) says how the three loop briefs must be applied (capacity_design.SCWB.by_story, capacity_design.panel_zone.by_joint).

tests/test_drift_relief.py covers the rules (python -m pytest tests -q).

A provider behind OpenRouter validates the whole conversation on every request. If a turn is cut off in the middle of a tool call's arguments ({ and nothing more), a provider such as Together refuses the next request with 400 Invalid JSON in tool call arguments — a 400 the retry net does not retry, so the run ended, and the cut-off turn saved in conversation.json broke every Continue after it. The agent now keeps every tool call in the history parseable ({} stands in for arguments that did not parse), never runs such a call, answers it with an error that asks the model to repeat it with complete arguments, and heals a conversation saved by an older version when it is resumed. tests/test_tool_call_healing.py.

steltic/ FastAPI app + agent loop + sandbox executors · steel_engine/ OpenSees modelling, design pipeline, consistency checks, report + 3D viewer · contract/ the agent's working contract and references · frontend/ vanilla JS UI · sandbox_image/ Docker sandbox image · test_buildings/ 50+ example briefs (steel + CFS) with assessment rubrics · rag_v2/, rag_update/ build-your-own-RAG starter kit.

MIT — see LICENSE, NOTICE (third-party data notes) and DISCLAIMER.md (engineering disclaimer; also shown in-app at /terms).