feedforward-practice 0.1.0

Private practice feedback on drafts against an instructor rubric (.ffrubric) — the FeedForward Desktop sidecar engine

feedforward-practice

Private practice feedback on drafts against an instructor rubric — the engine and sidecar API behind FeedForward Desktop.

A student opens a .ffrubric file (exported by their instructor from FeedForward), pastes or opens a draft, points the app at a model endpoint they control, and gets rubric-aligned formative feedback rendered with FeedForward's qualitative levels (the dartboard: "Closing in", "On the board", …). Nothing is stored on a server; there are no accounts.

Model endpoints

One OpenAI-compatible client covers all supported setups:

Setup	Base URL	Key
Local Ollama (default)	http://localhost:11434/v1	none
Remote Ollama behind a proxy	your server's URL	bearer token
BYOK (OpenAI, Anthropic-compat, OpenRouter, Groq…)	provider URL	your key

Configure via arguments or FEEDFORWARD_PRACTICE_BASE_URL, FEEDFORWARD_PRACTICE_API_KEY, FEEDFORWARD_PRACTICE_MODEL.

Usage

pip install feedforward-practice            # engine + CLI
pip install "feedforward-practice[serve]"   # + the HTTP API for the desktop shell

feedforward-practice assess --rubric essay1.ffrubric --draft draft.md
feedforward-practice serve --port 8022

Contracts

The rubric format, level words, and prompt/JSON contract are vendored at build time from the FeedForward repo's shared/ directory — the single source of truth both the server and this package test against.

Part of the FeedForward project · MIT