shinkan-jinkendo/frontend/src/components/ProgressionGraphEditor.jsx

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/**
* Integrierter Slot-Editor für Progressionsgraphen (Phase B).
*/
import React, { useCallback, useEffect, useMemo, useState } from 'react'
import { Link } from 'react-router-dom'
import api from '../utils/api'
import ExercisePickerModal from './ExercisePickerModal'
import ProgressionSlotCard from './ProgressionSlotCard'
import ProgressionFindingsPanel from './ProgressionFindingsPanel'
import {
applyGapOfferToSlot,
applyMatchStepsToSlots,
buildPlanningArtifactFromDraft,
hydrateProgressionGraphDraft,
librarySlotExercise,
majorStepsToOverridePayload,
reindexMajorSteps,
saveProgressionGraphDraft,
slotsToEvaluateSteps,
} from '../utils/progressionGraphDraft'
const ROADMAP_PHASES = ['einstieg', 'grundlage', 'vertiefung', 'anwendung', 'perfektion']
function roadmapStructuredPayload(startSituation, targetState, roadmapNotes) {
const body = {}
const start = (startSituation || '').trim()
const target = (targetState || '').trim()
const notes = (roadmapNotes || '').trim()
if (start) body.start_situation = start
if (target) body.target_state = target
if (notes) body.roadmap_notes = notes
return body
}
export default function ProgressionGraphEditor({ graphId }) {
const [graphMeta, setGraphMeta] = useState(null)
const [draft, setDraft] = useState(null)
const [busy, setBusy] = useState(false)
const [loadErr, setLoadErr] = useState('')
const [actionErr, setActionErr] = useState('')
const [pickContext, setPickContext] = useState(null)
const [pathQa, setPathQa] = useState(null)
const [gapFillOffers, setGapFillOffers] = useState([])
const [evaluating, setEvaluating] = useState(false)
const [matching, setMatching] = useState(false)
const [roadmapLoading, setRoadmapLoading] = useState(false)
const loadGraph = useCallback(async () => {
if (!graphId) return
setBusy(true)
setLoadErr('')
try {
const [graph, edges] = await Promise.all([
api.getExerciseProgressionGraph(Number(graphId)),
api.listExerciseProgressionEdges(Number(graphId)),
])
setGraphMeta(graph)
setDraft(
hydrateProgressionGraphDraft({
artifact: graph?.planning_roadmap,
edges: Array.isArray(edges) ? edges : [],
graphName: graph?.name,
}),
)
const findings = graph?.planning_roadmap?.last_findings
if (findings) setPathQa(findings)
} catch (e) {
setLoadErr(e.message || 'Graph konnte nicht geladen werden')
setDraft(null)
} finally {
setBusy(false)
}
}, [graphId])
useEffect(() => {
loadGraph()
}, [loadGraph])
const patchDraft = useCallback((patchFn) => {
setDraft((prev) => {
if (!prev) return prev
const next = patchFn(prev)
return { ...next, dirty: true }
})
}, [])
const handlePickExercise = async (exercise) => {
if (!pickContext || !exercise?.id) return
const { slotIndex, role } = pickContext
const entry = librarySlotExercise({
exerciseId: exercise.id,
exerciseTitle: exercise.title || `Übung #${exercise.id}`,
})
patchDraft((d) => {
const slots = d.slots.map((s, i) => {
if (i !== slotIndex) return s
if (role === 'primary') return { ...s, primary: entry }
const siblings = [...(s.siblings || [])]
if (!siblings.some((x) => x.exerciseId === entry.exerciseId)) siblings.push(entry)
return { ...s, siblings }
})
return { ...d, slots }
})
setPickContext(null)
}
const handlePatchLearningGoal = (slotIndex, value) => {
patchDraft((d) => {
const slots = d.slots.map((s, i) => (i === slotIndex ? { ...s, learning_goal: value } : s))
const majorSteps = reindexMajorSteps(
(d.majorSteps || []).map((m, i) => (i === slotIndex ? { ...m, learning_goal: value } : m)),
)
return { ...d, slots, majorSteps }
})
}
const handleClearPrimary = (slotIndex) => {
patchDraft((d) => {
const slots = d.slots.map((s, i) =>
i === slotIndex ? { ...s, primary: { kind: 'empty', exerciseId: null, variantId: null, exerciseTitle: '', variantName: null, proposalKey: null, aiSuggestion: null }, siblings: [] } : s,
)
return { ...d, slots }
})
}
const handleRemoveSibling = (slotIndex, sibIdx) => {
patchDraft((d) => {
const slots = d.slots.map((s, i) => {
if (i !== slotIndex) return s
return { ...s, siblings: s.siblings.filter((_, j) => j !== sibIdx) }
})
return { ...d, slots }
})
}
const handleAddSlot = () => {
patchDraft((d) => {
const idx = d.slots.length
const phase = ROADMAP_PHASES[Math.min(idx, ROADMAP_PHASES.length - 1)]
const slot = {
majorStepIndex: idx,
phase,
learning_goal: '',
consolidates: [],
rationale: '',
load_profile: [],
success_criteria: [],
anti_patterns: [],
exercise_type: '',
primary: { kind: 'empty', exerciseId: null, variantId: null, exerciseTitle: '', variantName: null, proposalKey: null, aiSuggestion: null },
siblings: [],
}
const major = {
index: idx,
phase,
learning_goal: '',
consolidates: [],
rationale: '',
load_profile: [],
success_criteria: [],
anti_patterns: [],
exercise_type: '',
}
return {
...d,
slots: [...d.slots, slot],
majorSteps: [...(d.majorSteps || []), major],
maxSteps: Math.max(d.maxSteps, idx + 1),
}
})
}
const validMajorSteps = useMemo(() => {
if (!draft?.slots) return []
return draft.slots.filter((s) => (s.learning_goal || '').trim().length >= 3)
}, [draft?.slots])
const runRoadmapGenerate = async () => {
const q = (draft?.goalQuery || '').trim()
if (q.length < 3) {
alert('Ziel-Anfrage: mindestens 3 Zeichen.')
return
}
setRoadmapLoading(true)
setActionErr('')
try {
const res = await api.suggestProgressionPath({
query: q,
max_steps: draft.maxSteps || 5,
include_llm_intent: true,
include_path_qa: false,
include_llm_path_qa: false,
include_path_reorder: false,
include_ai_gap_fill: false,
include_roadmap_preview: true,
include_llm_roadmap: true,
roadmap_only: true,
progression_graph_id: Number(graphId),
...roadmapStructuredPayload(draft.startSituation, draft.targetState, draft.roadmapNotes),
})
const roadmap = res?.progression_roadmap
if (!roadmap) throw new Error('Keine Roadmap in der Antwort')
const majors = (roadmap?.roadmap?.major_steps || []).map((s, i) => ({
index: i,
phase: s.phase || ROADMAP_PHASES[Math.min(i, ROADMAP_PHASES.length - 1)],
learning_goal: (s.learning_goal || '').trim(),
consolidates: Array.isArray(s.consolidates) ? s.consolidates : [],
rationale: s.rationale || '',
load_profile: [],
success_criteria: [],
anti_patterns: [],
exercise_type: '',
}))
const hydrated = hydrateProgressionGraphDraft({
artifact: {
...buildPlanningArtifactFromDraft({ ...draft, progressionRoadmap: roadmap }),
progression_roadmap: roadmap,
},
edges: [],
graphName: draft.graphName,
})
setDraft({ ...hydrated, goalQuery: q, dirty: true })
} catch (e) {
setActionErr(e.message || 'Roadmap-Generierung fehlgeschlagen')
} finally {
setRoadmapLoading(false)
}
}
const runMatch = async () => {
const q = (draft?.goalQuery || '').trim()
if (q.length < 3) {
alert('Ziel-Anfrage: mindestens 3 Zeichen.')
return
}
if (validMajorSteps.length < 2) {
alert('Mindestens zwei Slots mit Lernziel (je 3+ Zeichen) nötig.')
return
}
setMatching(true)
setActionErr('')
try {
const override = majorStepsToOverridePayload(draft.slots.map((s) => ({
index: s.majorStepIndex,
phase: s.phase,
learning_goal: s.learning_goal,
consolidates: s.consolidates,
rationale: s.rationale,
load_profile: s.load_profile,
success_criteria: s.success_criteria,
anti_patterns: s.anti_patterns,
exercise_type: s.exercise_type,
})))
const res = await api.suggestProgressionPath({
query: q,
max_steps: validMajorSteps.length,
include_llm_intent: true,
include_path_qa: true,
include_llm_path_qa: true,
include_path_reorder: false,
include_ai_gap_fill: true,
include_roadmap_preview: true,
include_llm_roadmap: false,
roadmap_first: true,
roadmap_override: override,
progression_graph_id: Number(graphId),
...roadmapStructuredPayload(draft.startSituation, draft.targetState, draft.roadmapNotes),
})
const next = applyMatchStepsToSlots(
{
...draft,
progressionRoadmap: res?.progression_roadmap || draft.progressionRoadmap,
pathSkillExpectations: res?.path_skill_expectations || draft.pathSkillExpectations,
},
res?.steps,
)
setDraft(next)
setPathQa(res?.path_qa || null)
setGapFillOffers(Array.isArray(res?.gap_fill_offers) ? res.gap_fill_offers : [])
} catch (e) {
setActionErr(e.message || 'Übungs-Match fehlgeschlagen')
} finally {
setMatching(false)
}
}
const runEvaluate = async () => {
const q = (draft?.goalQuery || '').trim()
if (q.length < 3) {
alert('Ziel-Anfrage: mindestens 3 Zeichen.')
return
}
setEvaluating(true)
setActionErr('')
try {
const override =
validMajorSteps.length >= 2
? majorStepsToOverridePayload(
draft.slots.map((s) => ({
index: s.majorStepIndex,
phase: s.phase,
learning_goal: s.learning_goal,
consolidates: s.consolidates,
rationale: s.rationale,
load_profile: s.load_profile,
success_criteria: s.success_criteria,
anti_patterns: s.anti_patterns,
exercise_type: s.exercise_type,
})),
)
: undefined
const res = await api.suggestProgressionPath({
query: q,
max_steps: draft.slots.length || draft.maxSteps || 5,
include_path_qa: true,
include_llm_path_qa: true,
include_ai_gap_fill: true,
include_path_reorder: false,
include_llm_intent: false,
evaluate_only: true,
evaluate_steps: slotsToEvaluateSteps(draft),
roadmap_override: override,
progression_graph_id: Number(graphId),
...roadmapStructuredPayload(draft.startSituation, draft.targetState, draft.roadmapNotes),
})
setPathQa(res?.path_qa || null)
setGapFillOffers(Array.isArray(res?.gap_fill_offers) ? res.gap_fill_offers : [])
setDraft((prev) => (prev ? { ...prev, lastFindings: res?.path_qa || null } : prev))
} catch (e) {
setActionErr(e.message || 'Bewertung fehlgeschlagen')
} finally {
setEvaluating(false)
}
}
const handleSave = async () => {
if (!draft || !graphId) return
setBusy(true)
setActionErr('')
try {
await saveProgressionGraphDraft(api, graphId, { ...draft, lastFindings: pathQa })
await loadGraph()
alert('Progressionsgraph gespeichert.')
} catch (e) {
setActionErr(e.message || 'Speichern fehlgeschlagen')
} finally {
setBusy(false)
}
}
const handleApplyGapOffer = (offer) => {
const idx =
offer?.roadmap_major_step_index != null ? Number(offer.roadmap_major_step_index) : null
if (idx == null || !Number.isFinite(idx)) {
alert('Angebot ohne Slot-Zuordnung — bitte manuell zuweisen.')
return
}
setDraft((prev) => applyGapOfferToSlot(prev, idx, offer))
}
if (loadErr) {
return (
<div className="card">
<p className="form-error">{loadErr}</p>
<Link to="/exercises" className="btn btn-secondary">
Zurück
</Link>
</div>
)
}
if (!draft) {
return (
<div style={{ display: 'flex', justifyContent: 'center', padding: '40px' }}>
<div className="spinner" />
</div>
)
}
return (
<div>
<div style={{ marginBottom: '12px', display: 'flex', justifyContent: 'space-between', alignItems: 'flex-start', flexWrap: 'wrap', gap: '8px' }}>
<div>
<h2 style={{ margin: 0, fontSize: '1.15rem' }}>
{graphMeta?.name || draft.graphName || `Graph #${graphId}`}
</h2>
<p style={{ margin: '4px 0 0', fontSize: '12px', color: 'var(--text3)' }}>
Slot-Editor · Roadmap = Struktur · ein Primärpfad + Schwestern
</p>
</div>
<Link to="/exercises" className="btn btn-secondary" style={{ fontSize: '12px' }}>
Zur Übersicht
</Link>
</div>
{actionErr ? (
<p className="form-error" style={{ marginTop: 0 }}>
{actionErr}
</p>
) : null}
<div
className="progression-graph-editor-grid"
style={{
display: 'grid',
gridTemplateColumns: 'minmax(0, 1fr) minmax(260px, 320px)',
gap: '14px',
alignItems: 'start',
}}
>
<div>
<div className="card" style={{ marginBottom: '12px' }}>
<h3 style={{ marginTop: 0, fontSize: '1rem' }}>Ziel & Roadmap</h3>
<div className="form-row">
<label className="form-label">Ziel-Anfrage</label>
<textarea
className="form-input"
rows={2}
value={draft.goalQuery}
disabled={busy}
onChange={(e) => patchDraft((d) => ({ ...d, goalQuery: e.target.value }))}
placeholder="z. B. Vom Anfänger zum sauberen Gerade-Tritt"
/>
</div>
<div className="form-row" style={{ display: 'grid', gridTemplateColumns: '1fr 1fr', gap: '10px' }}>
<div>
<label className="form-label">Start-Situation</label>
<input
className="form-input"
value={draft.startSituation}
disabled={busy}
onChange={(e) => patchDraft((d) => ({ ...d, startSituation: e.target.value }))}
/>
</div>
<div>
<label className="form-label">Ziel-Zustand</label>
<input
className="form-input"
value={draft.targetState}
disabled={busy}
onChange={(e) => patchDraft((d) => ({ ...d, targetState: e.target.value }))}
/>
</div>
</div>
<div style={{ display: 'flex', flexWrap: 'wrap', gap: '8px', marginTop: '8px' }}>
<button
type="button"
className="btn btn-secondary"
disabled={busy || roadmapLoading}
onClick={runRoadmapGenerate}
>
{roadmapLoading ? 'Roadmap…' : 'Roadmap generieren'}
</button>
<button
type="button"
className="btn btn-secondary"
disabled={busy || matching}
onClick={runMatch}
>
{matching ? 'Match…' : 'Übungen matchen'}
</button>
<button type="button" className="btn btn-primary" disabled={busy} onClick={handleSave}>
{busy ? 'Speichern…' : 'Graph speichern'}
</button>
</div>
{draft.dirty ? (
<p style={{ margin: '8px 0 0', fontSize: '11px', color: 'var(--accent-dark)' }}>
Ungespeicherte Änderungen
</p>
) : null}
</div>
<div style={{ display: 'flex', justifyContent: 'space-between', alignItems: 'center', marginBottom: '8px' }}>
<h3 style={{ margin: 0, fontSize: '1rem' }}>Slots ({draft.slots.length})</h3>
<button type="button" className="btn btn-secondary" style={{ fontSize: '12px' }} disabled={busy || draft.slots.length >= 10} onClick={handleAddSlot}>
Slot hinzufügen
</button>
</div>
{draft.slots.map((slot, idx) => (
<ProgressionSlotCard
key={`slot-${slot.majorStepIndex}-${idx}`}
slot={slot}
slotIndex={idx}
disabled={busy}
onPickPrimary={(i) => setPickContext({ slotIndex: i, role: 'primary' })}
onPickSibling={(i) => setPickContext({ slotIndex: i, role: 'sibling' })}
onClearPrimary={handleClearPrimary}
onRemoveSibling={handleRemoveSibling}
onPatchLearningGoal={handlePatchLearningGoal}
/>
))}
</div>
<ProgressionFindingsPanel
pathQa={pathQa}
gapFillOffers={gapFillOffers}
loading={evaluating}
error={evaluating ? '' : ''}
onEvaluate={runEvaluate}
onApplyGapOffer={handleApplyGapOffer}
evaluateDisabled={busy || !draft.goalQuery?.trim()}
/>
</div>
{pickContext ? (
<ExercisePickerModal
open
onClose={() => setPickContext(null)}
onSelectExercise={handlePickExercise}
/>
) : null}
<style>{`
@media (max-width: 900px) {
.progression-graph-editor-grid {
grid-template-columns: 1fr !important;
}
}
`}</style>
</div>
)
}