Overview
The cognitivess CLI is the fastest way to run Cognitivess-1 inside your coding tools — Claude Code, OpenClaw, Hermes and Codex — through one API key. It also runs any GGUF model fully offline on your own machine via llama.cpp, with no billing and no network calls.
- Gateway mode (default) — routes your tool to Cognitivess-1 on the Cognitivess API. Needs a saved key.
- Local mode (
--local) — startsllama-serverwith a local.gguffile and points the tool athttp://127.0.0.1:8080. Offline, no key, no billing. Prefer a browser over a CLI tool? Usecognitivess serve— same local model, web UI instead of a coding tool.
Installation
One-liner install (Linux / macOS / WSL — needs only Python 3):
curl -fsSL https://api.cognitivess.com/install | shThis downloads the cognitivess binary and puts it on your PATH. Verify it landed:
cognitivess --help
cognitivess login
Save your API key once. It is prompted securely (not echoed) and stored at ~/.config/cognitivess/config.json (locked to your account). You only do this for gateway mode — local mode needs no key.
cognitivess login # or pass it inline: cognitivess login --key "<YOUR_API_KEY>" # self-host / alternate gateway: cognitivess login --base-url https://api.cognitivess.com
Your key looks like ssh-ed25519 AAAA... — generate one in the
dashboard.
It is shown only once, so store it securely.
cognitivess launch <tool>
Launch a coding tool under Cognitivess-1. The CLI sets the right base_url + API key + model env vars for each tool, so the tool speaks to Cognitivess-1 as if it were the native backend.
Supported tools
Gateway mode (default)
# Run Claude Code under Cognitivess-1 cognitivess launch claude # Run Codex, passing tool-specific flags after "--" cognitivess launch codex -- -m Cognitivess-1 # Pin a model alias (c1, cognitivess-1, cognitivess) cognitivess launch claude --model c1
Local mode — run GGUF models offline
Add --local <name|path> to run a model on your own machine via llama-server. The CLI auto-installs the llama.cpp engine the first time, starts the server on 127.0.0.1:8080, and points the tool at it. No key needed, nothing leaves your machine.
# Run a pulled model by name (see `cognitivess pull` below) cognitivess launch claude --local qwen2.5-0.5b # Or point at a .gguf file directly (backward-compat) cognitivess launch claude --local ./my-model.gguf # Different port / host if 8080 is taken cognitivess launch hermes --local qwen2.5-0.5b --port 8081 # Use a custom llama-server binary cognitivess launch claude --local qwen2.5-0.5b --engine-path /usr/local/bin/llama-server
Flags
<tool>— one ofclaude,openclaw,hermes,codex.--model, -m— model name or alias (gateway mode only). Aliases:c1,cognitivess-1,cognitivess1,cognitivess.--local <MODEL.gguf>— run a local model offline via llama-server instead of the gateway. Accepts a catalog name (e.g.qwen2.5-0.5b) or a direct.ggufpath.--port— local llama-server port (default8080).--host— local llama-server host (default127.0.0.1).--path— path to the tool's binary (overrides<TOOL>_BINenv / default).--engine-path— path to thellama-serverbinary (default: auto-download, orLLAMA_SERVER_BINenv).--llama-pathis kept as a deprecated alias.-- ...— everything after--is passed through to the tool (e.g.-c "continue",--resume).
--local, the server uses the dummy API key local. It only has to match between llama-server and your tool — there is no validation and no billing. If you open the llama-server web UI at http://127.0.0.1:8080 and it asks for a key, type local (literally).cognitivess models
List available models — gateway models by default, or local GGUF models with --local.
# Gateway models (pricing, context, needs key) cognitivess models # Locally pulled .gguf models (offline storage, no key) cognitivess models --local
cognitivess pull <name>
Download a local .gguf model from Hugging Face into ~/.config/cognitivess/models/. Names come from the gateway catalog — run cognitivess pull with no argument to see them all, marked with ✓ pulled for what you already have.
# List the catalog cognitivess pull # Download a model cognitivess pull qwen2.5-0.5b # Re-download even if already pulled cognitivess pull qwen2.5-0.5b --force # Skip the llama-server engine install (model only) cognitivess pull qwen2.5-0.5b --no-engine # Then run it locally cognitivess launch claude --local qwen2.5-0.5b
-00001-of-00002.gguf, …). The CLI detects this automatically and downloads every shard in order into ~/.config/cognitivess/models/<name>/, with resume support per shard. The shards are kept separate (never concatenated — that would produce a corrupt file with two GGUF headers); llama-server loads them all from the directory on its own. You don't need to do anything special; just cognitivess pull <name>.pull one, the CLI also downloads its vision projector (mmproj-*.gguf) alongside the model. At launch (serve / launch --local), the projector is attached automatically with --mmproj — you get image, document (OCR) and video input in the web UI, no extra flags. The launcher prints Vision: enabled when it's active. Catalog entries with mmproj field: glm-ocr, qwen3.6-35b-a3b, qwythos-9b. If the projector download fails, the model still runs text-only (non-fatal).cognitivess serve <model>
Start the Cognitivess web UI server with a local model and keep it running until Ctrl+C. Unlike launch --local (which starts the same server and a coding tool on top of it), serve starts only the server — you interact with the model through your browser at http://127.0.0.1:8080, not via a CLI tool. Offline, no key, no billing.
# Serve a pulled model by name (browser opens automatically) cognitivess serve qwen2.5-0.5b # Or point at a .gguf file directly cognitivess serve ./path/to/model.gguf # Different port / host cognitivess serve qwen2.5-0.5b --port 8081 --host 0.0.0.0 # Use an engine already in PATH (skip the auto-install) cognitivess serve qwen2.5-0.5b --no-engine # Force a fresh install of the branded web UI cognitivess serve qwen2.5-0.5b --force-webui
Flags
<model>— model name from the catalog (e.g.qwen2.5-0.5b) or a direct.ggufpath.--engine-path— path to thellama-serverbinary (default: auto-download, orLLAMA_SERVER_BINenv).--llama-pathis kept as a deprecated alias.--no-engine— don't auto-install the engine; use one already inPATH.--port— server port (default8080).--host— server host (default127.0.0.1).--no-browser— don't auto-open the browser (the URL is still printed).--force-webui— re-install the branded web UI theme even if it's already cached.
bundle.js/bundle.css from your own engine (version-matched, so it always matches your llama.cpp release). Branding is best-effort and non-fatal: if the download fails, you fall back to the default llama-server UI. Cached in ~/.config/cognitivess/webui/.cognitivess rm <name>
Delete a locally pulled model (frees disk; also removes its sidecar .meta.json).
cognitivess rm qwen2.5-0.5b
# Skip the confirmation prompt
cognitivess rm qwen2.5-0.5b -ycognitivess me
Check your saved key and current usage / spend over the last 30 days.
cognitivess me
Where things live
Troubleshooting
- HTTP 404 on
pull— the catalog entry pointed at a file that moved on Hugging Face. The CLI now resolves case mismatches and sharded files automatically; if it still fails, check the repo's file list on HF. llama-server did not become ready— the model may be too large for your RAM, the port may be in use (try--port), or the.ggufis corrupt.- Tool says "invalid key" in local mode — you passed a real API key to a tool whose backend is the local server. In local mode the key is always
local; it's set automatically, so don't overrideANTHROPIC_API_KEY/OPENAI_API_KEYyourself. - Web UI at
:8080asks for a key — typelocal. That's the llama-server admin UI, not the gateway. - Branding (logo / colors) missing in the web UI — the theme pack couldn't be downloaded from the gateway (network/firewall), so the CLI fell back to the default llama-server UI. Re-run
cognitivess serve <model> --force-webuionce you're back online. --llama-pathnot working? — it's a deprecated alias. Use--engine-pathinstead (works on bothlaunchandserve).