Enhance exercise_ai and openrouter_chat modules with AI debugging and improved content handling

- Introduced detailed logging for AI operations in the `exercise_ai` and `openrouter_chat` modules, activated by the `SHINKAN_AI_DEBUG` environment variable, to aid in debugging and performance monitoring.
- Updated the `run_exercise_ai_suggestion` function to log prompt lengths, response sizes, and JSON parsing errors, enhancing transparency in AI interactions.
- Improved the `_flatten_message_content` function to handle nested content structures more effectively, ensuring compatibility with various AI response formats.
- Incremented the application version to 0.8.157 and updated the changelog to reflect these enhancements, including new logging features and content handling improvements.

backend/exercise_ai.py

@@ -8,7 +8,9 @@ from __future__ import annotations
 
 import copy
 import json
+import logging
 import math
+import os
 import re
 from typing import Any, Dict, List, Mapping, MutableMapping, Optional, Sequence, Tuple
 
@@ -16,6 +18,13 @@ from fastapi import HTTPException
 
 from openrouter_chat import OpenRouterError, normalize_openrouter_env, openrouter_chat_completion
 
+_LOGGER = logging.getLogger("shinkan.exercise_ai")
+
+
+def _ai_debug_on() -> bool:
+    return os.getenv("SHINKAN_AI_DEBUG", "").strip().lower() in ("1", "true", "yes", "full")
+
+
 _CANONICAL_SKILL_LEVELS = frozenset({"basis", "grundlagen", "aufbau", "fortgeschritten", "optimierung"})
 _LEGACY_SKILL_LEVEL_SLUG = {
     "einsteiger": "basis",
@@ -672,6 +681,20 @@ def run_exercise_ai_suggestion(
 
     result: Dict[str, Any] = {"model": model}
 
+    if _ai_debug_on():
+        fid_list = ",".join(str(x) for x in _ordered_focus_ids(focus_areas_context))
+        _LOGGER.warning(
+            "AI_DEBUG exercise_ai suggest want_summary=%s want_skills=%s title_chars=%s goal_plain_chars=%s "
+            "exec_plain_chars=%s focus_hint_chars=%s focus_ctx_ids=[%s]",
+            want_summary,
+            want_skills,
+            len(t_title),
+            len(g_plain),
+            len(e_plain),
+            len(focus),
+            fid_list,
+        )
+
     if want_summary:
         prow = _load_prompt_row(cur, "exercise_summary")
         if not prow:
@@ -683,10 +706,18 @@ def run_exercise_ai_suggestion(
             "exercise_execution": e_plain or "-",
         }
         prompt = _render_template(str(prow["template"]), ctx)
+        if _ai_debug_on():
+            _LOGGER.warning(
+                "AI_DEBUG exercise_ai summary prompt_slug=exercise_summary prompt_chars=%s unreplaced_mustache_pairs=%s",
+                len(prompt),
+                prompt.count("{{"),
+            )
         try:
             raw = openrouter_chat_completion(api_key=key, model=model, user_content=prompt)
         except OpenRouterError as e:
             raise HTTPException(status_code=502, detail=f"OpenRouter: {e}") from e
+        if _ai_debug_on():
+            _LOGGER.warning("AI_DEBUG exercise_ai summary response_chars=%s", len(raw or ""))
         text = (raw or "").strip()
         if not text:
             raise HTTPException(
@@ -720,6 +751,14 @@ def run_exercise_ai_suggestion(
             "skills_catalog": catalog,
         }
         prompt = _render_template(str(srow["template"]), ctx)
+        if _ai_debug_on():
+            _LOGGER.warning(
+                "AI_DEBUG exercise_ai skills prompt_slug=exercise_skill_suggestions catalog_chars=%s prompt_chars=%s "
+                "template_has_skills_placeholder=%s",
+                len(catalog),
+                len(prompt),
+                "{{skills_catalog}}" in str(srow.get("template") or ""),
+            )
         sys_hint = (
             "Du antwortest nur mit validem JSON (Array). Keine Kommentare, keine Erklaerungen ausserhalb des JSON."
         )
@@ -733,6 +772,8 @@ def run_exercise_ai_suggestion(
             )
         except OpenRouterError as e:
             raise HTTPException(status_code=502, detail=f"OpenRouter: {e}") from e
+        if _ai_debug_on():
+            _LOGGER.warning("AI_DEBUG exercise_ai skills response_chars=%s", len(raw or ""))
         body = (raw or "").strip()
         if not body:
             raise HTTPException(
@@ -745,11 +786,21 @@ def run_exercise_ai_suggestion(
         try:
             parsed = _extract_json_array(body)
         except (json.JSONDecodeError, ValueError) as e:
+            if _ai_debug_on():
+                _LOGGER.warning(
+                    "AI_DEBUG exercise_ai skills JSON parse_failed err=%s head=%s",
+                    e,
+                    (body.replace("\r", "").replace("\n", " ").strip())[:400],
+                )
             raise HTTPException(
                 status_code=502,
                 detail="KI lieferte kein verwertbares JSON fuer Skills.",
             ) from e
         skills = _sanitize_skill_entries(cur, parsed)
+        if _ai_debug_on():
+            cand_n = len(parsed) if isinstance(parsed, list) else -1
+            _LOGGER.warning("AI_DEBUG exercise_ai skills parsed_len=%s sanitized_kept=%s", cand_n, len(skills))
+
         result["skills"] = skills
 
     return result

backend/openrouter_chat.py

@@ -4,16 +4,53 @@ Minimal OpenRouter REST client (sync). Reads OPENROUTER_API_KEY / OPENROUTER_MOD
 from __future__ import annotations
 
 import json
+import logging
 import os
 from typing import Any, Dict, List, Optional
 
 import httpx
 
+_logger = logging.getLogger("shinkan.openrouter")
+
+_SKIP_ANTHROPIC_BLOCK_TYPES = frozenset(
+    {
+        "thinking",
+        "redacted_thinking",
+        "reasoning",
+        "tool_use",
+        "tool_calls",
+    }
+)
+
+
+def _shinkan_ai_debug() -> bool:
+    return os.getenv("SHINKAN_AI_DEBUG", "").strip().lower() in ("1", "true", "yes", "full")
+
+
+def _coerce_nested_text(val: Any) -> str:
+    if val is None:
+        return ""
+    if isinstance(val, str):
+        return val.strip()
+    if isinstance(val, bool) or isinstance(val, (int, float)):
+        return str(val).strip()
+    if isinstance(val, list):
+        return "".join(_coerce_nested_text(x) for x in val).strip()
+    if isinstance(val, dict):
+        # OpenRouter/Anthropic: verschachtelte text/content-Hüllen
+        for key in ("text", "content", "value"):
+            if key in val:
+                nested = _coerce_nested_text(val.get(key))
+                if nested:
+                    return nested
+        return ""
+    return str(val).strip()
+
 
 def _flatten_message_content(content: Any) -> str:
     """
-    OpenAI-kompatibles Chat-Completion kann `content` als String oder als Liste
-    strukturierter Blöcke liefern (z. B. Anthropic über OpenRouter/Bedrock).
+    Chat-Completion: `content` als String oder als Liste strukturierter Blöcke
+    (Anthropic Claude über OpenRouter/Bedrock, teils verschachtelt).
     """
     if content is None:
         return ""
@@ -23,25 +60,31 @@ def _flatten_message_content(content: Any) -> str:
         parts: List[str] = []
         for block in content:
             if isinstance(block, str):
-                parts.append(block)
+                bits = _coerce_nested_text(block)
+                if bits:
+                    parts.append(bits)
             elif isinstance(block, dict):
-                t = block.get("type")
-                txt = block.get("text")
-                if txt is None and t == "text":
-                    txt = block.get("content")
-                if isinstance(txt, str):
-                    parts.append(txt)
-                elif txt is not None:
-                    parts.append(str(txt))
+                t_raw = block.get("type")
+                ts = str(t_raw or "").strip().lower()
+                if ts and (ts in _SKIP_ANTHROPIC_BLOCK_TYPES or ts.endswith("_thinking")):
+                    continue
+                txt = None
+                if ts in ("text", "output_text", ""):
+                    txt = block.get("text")
+                    if txt is None:
+                        txt = block.get("content")
+                else:
+                    # unbekannten Typ weiter versuchen (Provider-Varianten), aber tool-use überspringen
+                    low = ts
+                    if "tool_use" in low or low.startswith("tool_"):
+                        continue
+                    txt = block.get("text") if block.get("text") is not None else block.get("content")
+                bits = _coerce_nested_text(txt)
+                if bits:
+                    parts.append(bits)
         return "".join(parts).strip()
     if isinstance(content, dict):
-        txt = content.get("text")
-        if txt is None:
-            txt = content.get("content")
-        if isinstance(txt, str):
-            return txt.strip()
-        if isinstance(txt, list):
-            return _flatten_message_content(txt)
+        return _coerce_nested_text(content)
     return str(content).strip()
 
 
@@ -118,18 +161,42 @@ def openrouter_chat_completion(
 
     msg0 = choices[0] if choices else {}
     inner = msg0.get("message") if isinstance(msg0, dict) else None
-    raw: Any = None
-    if isinstance(inner, dict):
-        raw = inner.get("content")
-        if raw is None and inner.get("refusal") is not None:
-            raw = inner.get("refusal")
-    elif isinstance(inner, str):
-        raw = inner
-    if raw is None and isinstance(msg0, dict):
-        raw = msg0.get("content")
 
-    content = _flatten_message_content(raw)
-    return content.strip()
+    blobs: List[Any] = []
+    if isinstance(inner, dict):
+        if inner.get("content") is not None:
+            blobs.append(inner.get("content"))
+        if inner.get("refusal") is not None:
+            blobs.append(inner.get("refusal"))
+    elif isinstance(inner, str):
+        blobs.append(inner)
+    if isinstance(msg0, dict) and msg0.get("content") is not None and msg0.get("content") not in blobs:
+        blobs.append(msg0.get("content"))
+
+    pieces = [_flatten_message_content(b).strip() for b in blobs if b is not None]
+    joined = ("\n".join(p for p in pieces if p)).strip()
+
+    if _shinkan_ai_debug():
+        fr = str(msg0.get("finish_reason") or "") if isinstance(msg0, dict) else ""
+        fu = data.get("usage") if isinstance(data.get("usage"), dict) else {}
+        pu = str(fu.get("prompt_tokens") or "")
+        pc = str(fu.get("completion_tokens") or "")
+        pt = str(fu.get("total_tokens") or "")
+        raw_cls = type(blobs[0]).__name__ if blobs else "none"
+        cc = str(len(joined))
+        _logger.warning(
+            "[AI_DEBUG/openrouter] model=%s finish_reason=%s usage_prompt=%s usage_completion=%s usage_total=%s "
+            "raw_content_cls=%s out_chars=%s",
+            model,
+            fr,
+            pu,
+            pc,
+            pt,
+            raw_cls,
+            cc,
+        )
+
+    return joined
 
 
 def normalize_openrouter_env() -> tuple[str, str]:

backend/version.py

@@ -1,6 +1,6 @@
 # Shinkan Jinkendo Version Information
 
-APP_VERSION = "0.8.156"
+APP_VERSION = "0.8.157"
 BUILD_DATE = "2026-05-22"
 DB_SCHEMA_VERSION = "20260529068"
 
@@ -23,7 +23,7 @@ MODULE_VERSIONS = {
     "skills": "0.1.1",  # DB 065 karate_relevance + relevance_level; CRUD unterstützt Felder
     "skill_profiles": "1.0.0",  # Phase 3: gewichtetes Fähigkeiten-Profil + skill-discovery/suggestions
     "methods": "0.1.0",
-    "exercises": "2.30.2",  # OpenRouter strukturierte content-Bloecke (Claude4/Bedrock); exercise_ai Robustheit + klare 502 wenn leeres Modell JSON; Retrieval-Admin Formular Gewichte/Unterkategorien
+    "exercises": "2.30.3",  # Frontend KI ohne Modal-Grausperre; Anthropic/OpenRouter verschachtelte Textbloecke; SHINKAN_AI_DEBUG Warn-Logs exercise_ai/OpenRouter
     "training_units": "0.4.0",  # POST .../publish-to-framework: Ablauf aus geplanter Einheit → Rahmen-Slot-Blueprint
     "training_programs": "0.1.0",
     "planning": "0.15.0",  # Vorlagen: Strukturvorschau, Bearbeiten inkl. Split-Sessions + Beschreibung
@@ -38,6 +38,15 @@ MODULE_VERSIONS = {
 }
 
 CHANGELOG = [
+    {
+        "version": "0.8.157",
+        "date": "2026-05-22",
+        "changes": [
+            "Übungsformular-KI: Buttons nur noch bei Busy deaktiviert; Vorschau wird vor neuem Aufruf geschlossen (kein Permanent-Grauschalter durch Modal-Zustand)",
+            "OpenRouter: verschachtelte Textbloecke/Content-Huellen fuer Anthropic; refusal optional mitgenommen",
+            "exercise_ai: SHINKAN_AI_DEBUG=1 — detaillierte WARN-Logs (Prompt-Laengen, parse-Fehler, Sanitize-Anzahl)",
+        ],
+    },
     {
         "version": "0.8.156",
         "date": "2026-05-22",

docs/HANDOVER.md

@@ -1,7 +1,7 @@
 # Shinkan Jinkendo – Entwicklungsstand & Handover
 
 **Stand:** 2026-05-29  
-**App-Version / DB-Schema:** App **`0.8.156`** (KI Retrieval-Admin Formular · OpenRouter Inhaltsbloecke Fix), DB-Schema **`20260529068`** — maßgeblich **`backend/version.py`**: `APP_VERSION`, `DB_SCHEMA_VERSION`
+**App-Version / DB-Schema:** App **`0.8.157`** (KI Übungen: UX-Flow + AI_DEBUG Logs), DB-Schema **`20260529068`** — maßgeblich **`backend/version.py`**: `APP_VERSION`, `DB_SCHEMA_VERSION`
 
 Diese Datei ist die **Einstiegs-Doku für neue Chat-Sessions**: Anforderungen im Detail stehen in `.claude/docs/` (siehe unten); hier der **implementierte Stand**, **Medien-Meilenstein** und **sinnvolle nächste Schritte**.
 
@@ -88,13 +88,14 @@ Das Schema ist gegenüber dem Code zurück: Migration **`022_skills_schema_compl
 - **Varianten:** Speichern in der **Aktionsleiste** persistiert zuerst geänderte Varianten (`persistPendingVariantChanges`), dann Übungs-Stammdaten; „Variante anlegen“ als `type="button"` ohne verschachteltes Formular (`createVariantFromDraft`)
 - **Governance (Übungen):** Owner = `created_by`; Bearbeiten = Ersteller, Plattform-Admin oder `can_plan_in_club` bei `visibility=club`; Löschen `club` = nur `club_admin`; Details **`FEATURES_DELIVERED_2026-Q2.md`** §16, **`EXERCISES_API_SPEC.md`** Permissions
 
-### 2.8 KI Assistenz Übungen & Skill-Katalog-Retrieval (Stand **0.8.156**)
+### 2.8 KI Assistenz Übungen & Skill-Katalog-Retrieval (Stand **0.8.157**)
 
 - **Doku:** Umsetzung `.claude/docs/working/AI_EXERCISE_IMPLEMENTATION_PLAN.md`; Profil-/JSON-Konzept `.claude/docs/working/AI_SKILL_RETRIEVAL_PROFILES_SPEC.md`; API-Felder **`KI_FEATURES_SPEC.md`** §5.2  
-- **DB:** Migration **`068`** – Tabelle **`ai_skill_retrieval_profiles`** (Konfig **`config`**) mit Seed „Standard“ + „Gewaltschutz“ (wenn Focus `Gewaltschutz` in `focus_areas` existiert)  
+- **DB:** Migration **`067`** **`ai_prompts`** (Slug **`exercise_summary`**, **`exercise_skill_suggestions`** — müssen **aktiv** sein); Migration **`068`** **`ai_skill_retrieval_profiles`** (Seed Standard + ggf. Gewaltschutz-Fokus)  
 - **`exercise_ai`:** Gewichtungen, Kategorie‑Anteil‑Caps (~Token), Keyword-Patches aus Ziel/Durchführung (z. B. Rollenspiel vs. Befreiung/Haltegriff)  
-- **API:** `POST /api/exercises/ai/suggest` optional **`focus_areas_context`**; **`POST …/ai/regenerate`** verwendet gespeicherte `exercise_focus_areas` automatisch für dieselbe Retrieval-Logik — **Pflege:** Superadmin **`GET/POST/PUT/DELETE /api/admin/ai-skill-retrieval-profiles*`** (`routers/ai_skill_retrieval_admin.py`)  
-- **Frontend:** `ExerciseFormPageRoot.jsx` übergibt `focus_areas_context` aus Einordnung; KI-Übernahmedialog nach API-Antwort — **Pflege:** **`AdminAiSkillRetrievalPage.jsx`**, Route **`/admin/ai-skill-retrieval`** (Nav „KI Retrieval“, nur Superadmin): **Gewichte pro Haupt- und Unterkategorie ohne JSON-Editor**; OpenRouter-Parser für Claude/Bedrock-Inhaltsbloecke in `openrouter_chat.py`
+- **API:** `POST /api/exercises/ai/suggest` optional **`focus_areas_context`**; **`POST …/ai/regenerate`** nutzt gespeicherte `exercise_focus_areas` — **Pflege:** Superadmin **`/api/admin/ai-skill-retrieval-profiles*`** (`routers/ai_skill_retrieval_admin.py`)  
+- **Diagnose bei leerem Dialog / Fehlern:** Umgebungsvariable **`SHINKAN_AI_DEBUG=1`** auf der API; in den Logs dann **`AI_DEBUG`** (`shinkan.exercise_ai`) und **`[AI_DEBUG/openrouter]`** (`shinkan.openrouter`) mit Prompt-Längen, Token-Zahlen und ggf. JSON-Parse-Anfang  
+- **Frontend:** **`ExerciseFormPageRoot.jsx`**: „KI:“-Schaltflächen nur bei laufender Anfrage deaktiviert; vor einem neuen Lauf wird die Vorschau geschlossen (**keine dauergraue UI** nur wegen eines alten Modal-Zustands). **Pflege:** **`AdminAiSkillRetrievalPage.jsx`**, Route **`/admin/ai-skill-retrieval`**  
 
 ---
 

frontend/src/components/exercises/ExerciseFormPageRoot.jsx

@@ -992,6 +992,8 @@ function ExerciseFormPageRoot() {
         return a.focus_area_id - b.focus_area_id
       })
 
+    /* Vor jedem neuen Aufruf: Vorschau schließen; sonst bleiben die KI-Buttons wegen Modal-Zustand dauerhaft deaktiviert. */
+    setAiSuggestionPreview(null)
     setAiSuggestBusy(true)
     try {
       const res = await api.suggestExerciseAi({
@@ -1541,7 +1543,7 @@ function ExerciseFormPageRoot() {
                 type="button"
                 className="btn btn-secondary"
                 style={{ fontSize: '12px' }}
-                disabled={aiSuggestBusy || !!aiSuggestionPreview}
+                disabled={aiSuggestBusy}
                 onClick={() => runExerciseAiSuggestion('summary')}
               >
                 KI: Kurzfassung
@@ -2216,7 +2218,7 @@ function ExerciseFormPageRoot() {
                 type="button"
                 className="btn btn-secondary"
                 style={{ fontSize: '12px' }}
-                disabled={aiSuggestBusy || !!aiSuggestionPreview}
+                disabled={aiSuggestBusy}
                 onClick={() => runExerciseAiSuggestion('skills')}
               >
                 KI: Fähigkeiten
@@ -2225,7 +2227,7 @@ function ExerciseFormPageRoot() {
                 type="button"
                 className="btn btn-secondary"
                 style={{ fontSize: '12px' }}
-                disabled={aiSuggestBusy || !!aiSuggestionPreview}
+                disabled={aiSuggestBusy}
                 onClick={() => runExerciseAiSuggestion('both')}
               >
                 KI: Kurzfassung und Fähigkeiten