Implement Primary Topic Resolution in Path Logic

- Introduced `resolve_path_primary_topic` function to enhance the determination of primary topics from goal queries and semantic briefs, improving exercise relevance.
- Updated `_match_roadmap_slot` and `detect_off_topic_steps` functions to utilize the new primary topic resolution logic, ensuring accurate topic identification.
- Enhanced tests to validate the functionality of primary topic resolution and its impact on exercise selection and off-topic detection.
- Improved handling of primary topics in the `ExerciseProgressionPathBuilder` and related components for better integration with the overall path-building process.

backend/planning_exercise_path_builder.py

@@ -46,6 +46,7 @@ from planning_exercise_semantics import (
     enrich_brief_with_path_constraints,
     enrich_target_with_semantic_expectations,
     resolve_path_anti_patterns,
+    resolve_path_primary_topic,
     exercise_passes_path_semantic_gate,
     pick_best_path_hit,
     resolve_semantic_skill_weights,
@@ -631,9 +632,17 @@ def _match_roadmap_slot(
         extra_context=path_context_note,
     )
     stage_anti = list(dict.fromkeys([*(stage_spec.anti_patterns or []), *path_anti]))
-    path_primary = (semantic_brief.primary_topic or "").strip()
+    path_primary = (
+        resolve_path_primary_topic(
+            goal_query,
+            semantic_brief,
+            stage_learning_goal=stage_goal,
+            extra_context=path_context_note,
+        )
+        or ""
+    ).strip()
     path_tech_excludes = list(semantic_brief.exclude_phrases or [])
-    if semantic_brief.topic_type == "technique" and path_primary:
+    if path_primary:
         from planning_exercise_semantics import technique_sibling_excludes
 
         for item in technique_sibling_excludes(path_primary):

backend/planning_exercise_path_qa.py

@@ -25,6 +25,7 @@ from planning_exercise_semantics import (
     exercise_passes_stage_learning_goal_gate,
     exercise_passes_technique_path_scope,
     resolve_path_anti_patterns,
+    resolve_path_primary_topic,
     score_exercise_semantic_relevance,
     semantic_brief_for_stage,
     step_phase_for_index,
@@ -456,10 +457,17 @@ def detect_off_topic_steps(
                 )
             )
             continue
-        primary = (brief.primary_topic or "").strip()
-        if brief.topic_type == "technique" and primary:
-            siblings = technique_sibling_excludes(primary)
         stage_goal_pre = (step.get("roadmap_learning_goal") or "").strip()
+        primary = (
+            resolve_path_primary_topic(
+                goal_query or "",
+                brief,
+                stage_learning_goal=stage_goal_pre or None,
+            )
+            or ""
+        ).strip()
+        if primary:
+            siblings = technique_sibling_excludes(primary)
             if not exercise_passes_technique_path_scope(
                 primary_topic=primary,
                 title=bundle["title"],

backend/planning_exercise_semantics.py

@@ -180,6 +180,28 @@ def _find_technique_in_text(q_lower: str) -> Optional[Tuple[str, Tuple[str, ...]
     return None
 
 
+def resolve_path_primary_topic(
+    goal_query: str,
+    semantic_brief: Optional[PlanningSemanticBrief] = None,
+    *,
+    stage_learning_goal: Optional[str] = None,
+    extra_context: Optional[str] = None,
+) -> Optional[str]:
+    """
+    Haupttechnik aus Anfrage, Kontext oder Stufen-Lernziel — nicht nur aus goal_query.
+    """
+    if semantic_brief:
+        primary = (semantic_brief.primary_topic or "").strip()
+        if primary:
+            return primary
+    parts = [goal_query or "", extra_context or "", stage_learning_goal or ""]
+    combined = _normalize_phrase(" ".join(p for p in parts if p))
+    if not combined:
+        return None
+    hit = _find_technique_in_text(combined.lower())
+    return hit[0] if hit else None
+
+
 def technique_sibling_excludes(primary_topic: str) -> List[str]:
     """Andere Techniken derselben Familie (z. B. Mae/Yoko bei Mawashi) — aus Katalog."""
     topic = _normalize_phrase(primary_topic)
@@ -1038,13 +1060,22 @@ def exercise_passes_stage_fit(
         return False
 
     primary_path = (path_primary_topic or "").strip()
+    if not primary_path and lg:
+        hit = _find_technique_in_text(_normalize_phrase(lg))
+        if hit:
+            primary_path = hit[0]
+    tech_excludes = list(path_technique_excludes or [])
+    if primary_path:
+        for item in technique_sibling_excludes(primary_path):
+            if item not in tech_excludes:
+                tech_excludes.append(item)
     if primary_path and not exercise_passes_technique_path_scope(
         primary_topic=primary_path,
         title=title,
         summary=summary,
         goal=goal,
         learning_goal=lg,
-        sibling_excludes=path_technique_excludes,
+        sibling_excludes=tech_excludes,
         relaxed=relaxed,
     ):
         return False
@@ -1295,6 +1326,7 @@ __all__ = [
     "build_stage_match_brief",
     "enrich_brief_with_path_constraints",
     "exercise_passes_stage_fit",
+    "resolve_path_primary_topic",
     "resolve_path_anti_patterns",
     "exercise_passes_stage_learning_goal_gate",
     "merge_semantic_brief_llm",

backend/planning_progression_roadmap.py

@@ -1028,6 +1028,7 @@ def roadmap_context_from_override(
         goal_query=goal_query.strip(),
         max_steps=effective_max,
         semantic_brief=brief_to_summary_dict(semantic_brief),
+        resolved_structured=structured,
         goal_analysis=goal_analysis,
         roadmap=RoadmapArtifact(major_steps=majors),
         stage_specs=stage_specs,

backend/tests/test_planning_roadmap_stage_match.py

@@ -8,6 +8,7 @@ from planning_exercise_semantics import (
     exercise_passes_technique_path_scope,
     pick_best_path_hit,
     resolve_path_anti_patterns,
+    resolve_path_primary_topic,
     score_exercise_stage_fit,
     semantic_brief_for_stage,
     technique_sibling_excludes,
@@ -231,12 +232,13 @@ def test_pick_best_skips_kumite_for_mawashi_athletic_path():
             "id": 2,
             "title": "Sprungkraft Plyometrie",
             "summary": "Absprung und Landung",
-            "goal": "Sprungkraft für Tritttechnik",
+            "goal": "Sprungkraft für Mawashi Geri Vorbereitung",
             "score": 0.62,
             "semantic_score": 0.38,
             "stage_semantic_score": 0.38,
         },
     ]
+    primary = resolve_path_primary_topic(q, brief, stage_learning_goal=stage_goal)
     chosen = pick_best_path_hit(
         hits,
         set(),
@@ -244,6 +246,56 @@ def test_pick_best_skips_kumite_for_mawashi_athletic_path():
         stage_anti_patterns=path_anti,
         roadmap_stage_match=True,
         stage_match_brief=stage_brief,
+        path_primary_topic=primary,
+        path_technique_excludes=technique_sibling_excludes(primary or "mawashi geri"),
+    )
+    assert chosen is not None
+    assert int(chosen["id"]) == 2
+
+
+def test_resolve_path_primary_topic_from_stage_learning_goal():
+    brief = build_semantic_brief("Trainingsprogression gesprungener Tritt")
+    primary = resolve_path_primary_topic(
+        "Trainingsprogression gesprungener Tritt",
+        brief,
+        stage_learning_goal="Perfektionierung der statischen Mawashi Geri Technik",
+    )
+    assert primary and "mawashi" in primary
+
+
+def test_pick_rejects_kumite_when_primary_only_in_stage_goal():
+    brief = build_semantic_brief("Trainingsprogression")
+    stage_goal = "Perfektionierung der statischen Mawashi Geri Technik"
+    stage_brief = build_stage_match_brief(learning_goal=stage_goal)
+    primary = resolve_path_primary_topic("Trainingsprogression", brief, stage_learning_goal=stage_goal)
+    hits = [
+        {
+            "id": 4,
+            "title": "4 Kumite Reaktions Übungen",
+            "summary": "Partner",
+            "goal": "Kumite",
+            "score": 0.95,
+            "semantic_score": 0.4,
+            "stage_semantic_score": 0.35,
+        },
+        {
+            "id": 2,
+            "title": "Mawashi Geri Standtechnik",
+            "summary": "Rundtritt",
+            "goal": "Mawashi Geri Basis",
+            "score": 0.7,
+            "semantic_score": 0.5,
+            "stage_semantic_score": 0.48,
+        },
+    ]
+    chosen = pick_best_path_hit(
+        hits,
+        set(),
+        stage_learning_goal=stage_goal,
+        roadmap_stage_match=True,
+        stage_match_brief=stage_brief,
+        path_primary_topic=primary,
+        path_technique_excludes=technique_sibling_excludes(primary or "mawashi geri"),
     )
     assert chosen is not None
     assert int(chosen["id"]) == 2

frontend/src/components/ExerciseProgressionPathBuilder.jsx

@@ -142,8 +142,10 @@ function normalizeTitleKey(text) {
     .replace(/\s+/g, ' ')
 }
 
-function mergeGraphIntoPathSteps(pathRows, graphNodes) {
-  if (!Array.isArray(graphNodes) || !graphNodes.length || !pathRows.length) return pathRows
+function mergeGraphIntoPathSteps(pathRows, graphNodes, { skipGraphMerge = false } = {}) {
+  if (skipGraphMerge || !Array.isArray(graphNodes) || !graphNodes.length || !pathRows.length) {
+    return pathRows
+  }
   return pathRows.map((row, i) => {
     const node = graphNodes[i]
     if (!node?.exercise_id) return row
@@ -1019,14 +1021,14 @@ export default function ExerciseProgressionPathBuilder({
     }
   }
 
-  const applyPathMatchResponse = (res, q) => {
+  const applyPathMatchResponse = (res, q, { skipGraphMerge = true } = {}) => {
     const qa = res?.path_qa || null
     const rawRows = (Array.isArray(res?.steps) ? res.steps : []).map(mapApiStepToRow)
     const rows = applyOffTopicFlags(rawRows, qa)
+    const mergedRows = mergeGraphIntoPathSteps(rows, graphChainNodes, { skipGraphMerge })
     if (rows.length < 2) {
       throw new Error('Zu wenig Schritte im Vorschlag.')
     }
-    const mergedRows = mergeGraphIntoPathSteps(rows, graphChainNodes)
     const rawGaps = Array.isArray(res?.gap_fill_offers)
       ? res.gap_fill_offers
       : Array.isArray(qa?.gap_fill_offers)

frontend/src/utils/progressionGraphDraft.js

@@ -785,7 +785,7 @@ export function applyMatchStepsToSlots(draft, apiSteps) {
 }
 
 /** Lücken-Angebote in leere Slots legen; Panel nur für verbleibende Lücken. */
-export function applyGapOffersFromResponse(draft, res) {
+export function applyGapOffersFromResponse(draft, res, { replaceOffTopicSlots = false } = {}) {
   let next = draft
   if (res?.progression_roadmap) {
     next = syncSlotPhasesFromRoadmap(next, res.progression_roadmap)
@@ -798,8 +798,14 @@ export function applyGapOffersFromResponse(draft, res) {
     const idx = resolveOfferSlotIndex(next, offer)
     if (idx == null || idx < 0 || idx >= (next.slots?.length || 0)) continue
     const primary = next.slots[idx]?.primary
+    const isOffTopicReplace =
+      replaceOffTopicSlots &&
+      offer?.source === 'off_topic' &&
+      offer?.replace_step_index != null
+    if (!isOffTopicReplace) {
       if (primary?.kind === 'library' && primary.exerciseId != null) continue
       if (primary?.kind === 'proposal') continue
+    }
 
     next = applyGapOfferToSlot(next, idx, offer)
     if (offer?.offer_id) placedIds.add(offer.offer_id)
@@ -817,7 +823,7 @@ export function applyGapOffersFromResponse(draft, res) {
 }
 
 /** Match-Antwort: Schritte + Lücken-Angebote direkt in Slots (wie früher im Pfad-Wizard sichtbar). */
-export function applyMatchResponseToDraft(draft, res) {
+export function applyMatchResponseToDraft(draft, res, { replaceOffTopicSlots = true } = {}) {
   let next = applyMatchStepsToSlots(draft, res?.steps)
   if (res?.progression_roadmap) {
     next = {
@@ -825,7 +831,9 @@ export function applyMatchResponseToDraft(draft, res) {
       pathSkillExpectations: res?.path_skill_expectations || next.pathSkillExpectations,
     }
   }
-  const { draft: withOffers, remainingOffers } = applyGapOffersFromResponse(next, res)
+  const { draft: withOffers, remainingOffers } = applyGapOffersFromResponse(next, res, {
+    replaceOffTopicSlots,
+  })
   return { draft: withOffers, remainingOffers }
 }