dragon_feedback: Training data from chat feedback
In dragonfarm: Fine-Tune Small Language Models with LoRA from R

dragon_feedback

R Documentation

Training data from chat feedback

Description

Ratings and edits made in dragon_chat() or the app's Chat panel are saved under ⁠feedback/⁠ in the runs directory. This turns them into data for the next stage:

Usage

dragon_feedback(runs_dir = dragon_runs_dir(), label = NULL)

Arguments

`runs_dir`	Runs directory holding `feedback/feedback.jsonl`.
`label`	Optional filter: only feedback given to this run id or backend model.

Details

sft: a conversations dataset (dragon_conversations()) of replies the user liked or edited, each with the turns that led to it. Edited text replaces the model's reply.
pairs: a preference dataset (dragon_map_pairs()) for prompts that received both a liked (or edited) reply and a disliked one.

Both are written as JSONL under ⁠feedback/⁠ so runs trained on them stay reproducible through dragon_code().

Value

A list with records (a data frame of every feedback event), sft (dataset or NULL), and pairs (dataset or NULL).

Examples

if (interactive()) {
fb <- dragon_feedback()
fb$records
better <- dragon_train(fb$sft, dpo, wait = TRUE)       # continue from the run people chatted with
dpo2 <- dragon_prefer(fb$pairs, better, wait = TRUE)
}

dragonfarm documentation built on Oct. 12, 2026, 5:07 p.m.