Running against the localhost API. No WebGPU required. CV text is sent only to 127.0.0.1 on this machine.

Draft thematic CV sections on your computer

Turn a conventional CV into evidence for a Canadian Tri-Agency narrative CV. This desktop build keeps extract, verify, ranking, and draft in the browser UI while a Python process on localhost runs the language model (Ollama or llama-cpp-python).

Why desktop + local API?

No WebGPU requirement, easier model management, and stronger offline control. CV text is sent only to 127.0.0.1—never to a cloud model API.

What stays in the browser

CV parsing, evidence cards, gap audit, discipline ranking UI, and draft editing remain the same constrained workflow as the web prototype.

What Python owns

Model load, chat completions, and streaming drafts via Ollama (preferred) or GGUF files through llama-cpp-python.

How would you like to begin?

All three routes lead to the same evidence review. Choose the source that gives you the best factual starting point.

Requires the desktop app (or python -m localtcv_desktop) listening on localhost. WebGPU is not required.

Made in Canada 🇨🇦

Local preferences

Settings

Lists Ollama tags and GGUF files known to the desktop API.

Optional browser save

Opt-in only. CV text, verified evidence, selections, and drafts stay on this device in this browser’s site storage. This storage is not described as encrypted.

Browser saving is off.

Changing models takes effect the next time you start local AI.