{% extends "base.html" %}
{# Bot training: make and edit training bots (who they are, their rules,
   their scenarios), grade an answer, and run a scenario on a model. The
   bots are the desktop Training studio's own files. #}
{% block title %}Bot training{% endblock %}
{% block page_id %}training{% endblock %}
{% block head %}
<style>
  .tr-check { border: 1px solid var(--line); border-radius: 8px; padding: 8px; margin-bottom: 8px; background: var(--bg); }
  .tr-verdict { font-family: var(--mono); font-size: 13px; }
  .tr-verdict .ok { color: #7ee08c; }
  .tr-verdict .no { color: #ff9c95; }
  .tr-sticky { position: sticky; top: calc(var(--top-h) + 6px); z-index: 5; background: var(--bg-2); }
</style>
{% endblock %}
{% block content %}
<div class="a-page-head">
  <h1><i class="fa-solid fa-graduation-cap" aria-hidden="true"></i> Bot training</h1>
  {% if aida_is_owner %}<button class="a-btn a-btn--primary" type="button" id="tr-new"><i class="fa-solid fa-plus" aria-hidden="true"></i><span>New bot</span></button>{% endif %}
  <div class="a-sub">A training bot is who the model becomes: its name, its rules, and the scenarios it is graded on. Edit its mind and exam, bake it into an Ollama tag, and record compiler-judged Practice. Saved training jobs and chat datasets are shared with the desktop.</div>
</div>
<div class="a-split" id="tr-root"></div>
<section class="a-card"><h2>Chat datasets and fine-tuning</h2><p>Inspect imported chats before saving them. Fine-tuning checks the local GPU, libraries, data and matching model weights. It starts a real detached process; a failed check or missing service prevents training.</p>
<div class="a-grid a-grid-2"><label>Chat file<input class="a-input tr-work-control" id="tr-data-file" type="file" accept=".json,.jsonl,.csv,.tsv"></label><label>Dataset name<input class="a-input tr-work-control" id="tr-data-name"></label><label>System prompt for chats without one<textarea class="a-textarea tr-work-control" id="tr-data-system" rows="3"></textarea></label></div>
<button class="a-btn tr-work-control" id="tr-data-inspect">Inspect chat data</button><button class="a-btn tr-work-control" id="tr-data-apply">Save inspected chats</button><pre class="a-log" id="tr-data-report"></pre><div id="tr-datasets"></div><div id="tr-data-chats"></div>
<h3>New saved LoRA run on this PC</h3><div class="a-grid a-grid-2"><label>Chat dataset<select class="a-select tr-work-control" id="tr-ft-dataset"></select></label><label>Ollama base tag<input class="a-input tr-work-control" id="tr-ft-base"></label><label>HuggingFace weights or local weights directory<input class="a-input tr-work-control" id="tr-ft-hf"></label><label>New baked tag<input class="a-input tr-work-control" id="tr-ft-tag"></label><label>Epochs<input class="a-input tr-work-control" id="tr-ft-epochs" type="number" min="1" max="20" value="3"></label><label class="a-check"><input class="tr-work-control" id="tr-ft-4bit" type="checkbox" checked>Load in 4-bit</label></div><button class="a-btn tr-work-control" id="tr-ft-create">Create saved fine-tune run</button><button class="a-btn tr-work-control" id="tr-ft-save">Save settings to selected run</button><div id="tr-run"></div></section>
<section class="a-card"><h2>Desktop training catalog</h2><button class="a-btn tr-work-control" id="tr-catalog-refresh">Refresh saved catalog</button><div id="tr-catalog"></div></section>
<section class="a-card"><h2>Current operation</h2><button class="a-btn" id="tr-work-stop" disabled>Request Practice stop</button><pre class="a-log" id="tr-work-log" role="status" aria-live="polite"></pre></section>

{% endblock %}
{% block scripts %}
<script src="{{ aida_rel('static/js/training.js') }}"></script>
{% endblock %}