Cognitivess CLI

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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.

Two modes, one binary
  • Gateway mode (default) — routes your tool to Cognitivess-1 on the Cognitivess API. Needs a saved key.
  • Local mode (--local) — starts llama-server with a local .gguf file and points the tool at http://127.0.0.1:8080. Offline, no key, no billing. Prefer a browser over a CLI tool? Use cognitivess 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 | sh

This 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

claudeAnthropic protocol — Claude Code
openclawAnthropic protocol — OpenClaw
hermesOpenAI Chat — Hermes
codexOpenAI Responses — Codex

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 of claude, 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 .gguf path.
  • --port — local llama-server port (default 8080).
  • --host — local llama-server host (default 127.0.0.1).
  • --path — path to the tool's binary (overrides <TOOL>_BIN env / default).
  • --engine-path — path to the llama-server binary (default: auto-download, or LLAMA_SERVER_BIN env). --llama-path is kept as a deprecated alias.
  • -- ... — everything after -- is passed through to the tool (e.g. -c "continue", --resume).
Local mode key
When you run --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
Sharded models
Large quantized models on Hugging Face are sometimes split into shards (-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>.
Vision / multimodal models
Some models in the catalog are multimodal (vision). When you 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 .gguf path.
  • --engine-path — path to the llama-server binary (default: auto-download, or LLAMA_SERVER_BIN env). --llama-path is kept as a deprecated alias.
  • --no-engine — don't auto-install the engine; use one already in PATH.
  • --port — server port (default 8080).
  • --host — server host (default 127.0.0.1).
  • --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.
Branded web UI
In local mode the CLI overrides llama-server's built-in web UI with the Cognitivess theme — logo, colors and title — while keeping 100% of the built-in functionality. On first run it downloads a small theme pack from the gateway and extracts the matching 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 -y

cognitivess me

Check your saved key and current usage / spend over the last 30 days.

cognitivess me

Where things live

Config + key~/.config/cognitivess/config.json
Pulled models~/.config/cognitivess/models/<name>.gguf
llama-server engine~/.config/cognitivess/bin/<tag>/
Branded web UI~/.config/cognitivess/webui/
Download cache~/.config/cognitivess/cache/

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 .gguf is 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 override ANTHROPIC_API_KEY / OPENAI_API_KEY yourself.
  • Web UI at :8080 asks for a key — type local. 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-webui once you're back online.
  • --llama-path not working? — it's a deprecated alias. Use --engine-path instead (works on both launch and serve).