Release 2.9.4: PPTX wizard figure analysis + skill model trigger fix

- pptx-wizard: add "🔍 이미지 분석" button in Step 2 image panel
  * calls /api/pptx/analyze-image per figure via mistral vision
  * shows per-image progress (1/10, 2/10...)
  * "제외" caption → dimmed card + filtered from outline prompt
  * captions shown below each thumbnail in the grid
- server: POST /api/pptx/analyze-image endpoint
  * resolves /api/files/ path to workspace file, thumbnails if >300KB
  * calls orchestration.secondary vision model (mistral-large-3:675b-cloud)
  * caches results in project/.image-captions.json (skips on re-analysis)
- pptx-wizard: generateOutline() includes captions in imgList
  * "제외" images filtered out before sending to LLM
  * format: "/api/files/... (figure_p2_1) — 카플란-마이어 생존곡선 3그룹"
- skills-manager: fix getModelOverrideForUser() trigger filtering
  * was returning skill model for ALL messages regardless of trigger keywords
  * now only overrides when message matches skill triggers (same logic as buildPromptContext)
  * presenter model (mistral) now only applies for 발표/pptx/슬라이드 keywords

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

src/gateway/server-v2.ts

@@ -6510,7 +6510,7 @@ RULES:
       // Model priority: explicit request > vision fallback > skill override > config default
       const effectiveModel = String(modelOverride || '').trim()
         || _visionFallbackModel
-        || skillsManager.getModelOverrideForUser(username ? getUserWorkspace(username) : null)
+        || skillsManager.getModelOverrideForUser(username ? getUserWorkspace(username) : null, message)
         || undefined;
       // Always use streaming so text tokens appear in real-time. The streaming
       // handler collects tool_calls from chunks and returns them in the final
@@ -9942,6 +9942,85 @@ app.post('/api/pptx/extract-images', requireGatewayAuth, async (req: express.Req
   }
 });
 
+// POST /api/pptx/analyze-image — vision-model caption for a single extracted figure
+// Caches results in workspace/pptx/<project>/.image-captions.json
+app.post('/api/pptx/analyze-image', requireGatewayAuth, async (req: express.Request, res: express.Response) => {
+  try {
+    const session = getSessionUser(req);
+    const username = (session as any)?.username;
+    const workspacePath = username ? getUserWorkspace(username) : getConfig().getWorkspacePath();
+
+    const imgUrl   = String(req.body?.url   || '').trim();
+    const project  = pptxProjectSlug(String(req.body?.project || ''));
+    if (!imgUrl) { res.status(400).json({ error: 'url required' }); return; }
+
+    // Load cache
+    const cacheFile = project
+      ? path.join(workspacePath, PPTX_BASE, project, '.image-captions.json')
+      : null;
+    let cached: Record<string, string> = {};
+    if (cacheFile && fs.existsSync(cacheFile)) {
+      try { cached = JSON.parse(fs.readFileSync(cacheFile, 'utf-8')); } catch {}
+    }
+    if (cached[imgUrl]) {
+      res.json({ success: true, url: imgUrl, caption: cached[imgUrl], fromCache: true });
+      return;
+    }
+
+    // Resolve file path
+    const relParts = imgUrl.replace(/^\/api\/files\//, '').split('/').map(decodeURIComponent);
+    const filePath = path.resolve(workspacePath, ...relParts);
+    if (!fs.existsSync(filePath)) {
+      res.json({ success: false, url: imgUrl, caption: '' });
+      return;
+    }
+
+    // Read + thumbnail if large
+    let buf: Buffer | null = null;
+    const stat = fs.statSync(filePath);
+    if (stat.size <= 300_000) {
+      buf = fs.readFileSync(filePath);
+    } else {
+      try {
+        const { execSync } = await import('child_process');
+        const script = `from PIL import Image; import sys; img=Image.open(sys.argv[1]); img.thumbnail((600,600)); img.save(sys.stdout.buffer,'JPEG',quality=80)`;
+        buf = execSync(`python3 -c "${script}" "${filePath}"`, { maxBuffer: 5 * 1024 * 1024 });
+      } catch { buf = null; }
+    }
+    if (!buf) { res.json({ success: false, url: imgUrl, caption: '' }); return; }
+
+    const ext  = path.extname(filePath).toLowerCase();
+    const mime = ext === '.png' ? 'image/png' : ext === '.webp' ? 'image/webp' : 'image/jpeg';
+    const b64  = `data:${mime};base64,${buf.toString('base64')}`;
+
+    // Call vision model
+    const ollama2 = getOllamaClient();
+    const rawCfg2 = getConfig().getConfig() as any;
+    const sec2 = rawCfg2.orchestration?.secondary;
+    const visionModel = (sec2?.model && sec2?.vision === true) ? sec2.model : 'mistral-large-3:675b-cloud';
+
+    const result = await ollama2.chatWithThinking([{
+      role: 'user' as const,
+      content: [
+        { type: 'text'      as const, text: '이 그림을 한 줄(30자 이내)로 설명하세요. 그래프/차트/다이어그램 종류와 핵심 내용 위주로. 슬라이드에 쓰기 부적합한 그림(흐릿함·텍스트만 있는 표·빈 이미지)이면 "제외"라고만 답하세요.' },
+        { type: 'image_url' as const, image_url: { url: b64 } },
+      ],
+    }], 'executor', { model: visionModel, num_predict: 80 });
+
+    const caption = String(result.message?.content || '').trim().replace(/\n/g, ' ').slice(0, 80);
+    cached[imgUrl] = caption;
+    if (cacheFile) {
+      try {
+        fs.mkdirSync(path.dirname(cacheFile), { recursive: true });
+        fs.writeFileSync(cacheFile, JSON.stringify(cached, null, 2), 'utf-8');
+      } catch {}
+    }
+    res.json({ success: true, url: imgUrl, caption });
+  } catch (err) {
+    res.status(500).json({ error: String(err) });
+  }
+});
+
 // GET /api/pptx/project-pdfs?project=<slug> — list PDF files in project folder
 // Also returns companion .txt / .ko.txt paths if they exist.
 app.get('/api/pptx/project-pdfs', requireGatewayAuth, async (req: express.Request, res: express.Response) => {

src/gateway/skills-manager.ts

@@ -286,8 +286,9 @@ export class SkillsManager {
     return parts.join('\n');
   }
 
-  /** Return the model override from the first enabled skill that specifies one, or undefined. */
+  /** Return the model override from the first triggered+enabled skill that specifies one, or undefined. */
-  getModelOverrideForUser(userDir: string | null): string | undefined {
+  getModelOverrideForUser(userDir: string | null, userMessage = ''): string | undefined {
+    const msgLower = userMessage.toLowerCase();
     const userState = userDir ? this.getUserState(userDir) : null;
     const enabled = this.getAll().filter(s => {
       if (this.GLOBAL_ONLY_SKILLS.has(s.id)) return s.enabled;
@@ -295,7 +296,12 @@ export class SkillsManager {
       return s.enabled;
     });
     for (const skill of enabled) {
-      if (skill.model) return skill.model;
+      if (!skill.model) continue;
+      // Only apply model override when the skill is triggered (or has no triggers)
+      if (skill.triggers && skill.triggers.length > 0) {
+        if (!skill.triggers.some(t => msgLower.includes(t.toLowerCase()))) continue;
+      }
+      return skill.model;
     }
     return undefined;
   }

web-ui/pptx-wizard.html

@@ -343,6 +343,7 @@ body{background:var(--bg);color:var(--text);font-family:'Segoe UI',system-ui,san
       <div style="flex:2;min-width:0">
         <div style="display:flex;align-items:center;gap:8px;margin-bottom:6px">
           <span style="font-size:10px;color:var(--muted);font-weight:600;text-transform:uppercase;letter-spacing:.04em">캡처 이미지 <span id="imgcnt"></span></span>
+          <button id="btn-analyze-imgs" onclick="analyzeImages()" style="font-size:11px;color:#10b981;background:rgba(16,185,129,.1);border:1px solid #10b981;border-radius:5px;padding:2px 8px;cursor:pointer;flex-shrink:0" title="AI(mistral vision)가 각 이미지 내용 분석 — 아웃라인 생성 시 정확한 슬라이드 배치에 활용">🔍 이미지 분석</button>
           <label style="display:flex;align-items:center;gap:4px;font-size:11px;color:var(--brand2);background:rgba(99,102,241,.1);border:1px solid var(--brand);border-radius:5px;padding:2px 8px;cursor:pointer;flex-shrink:0" title="이미지 파일 업로드">
             <input type="file" id="img-upload-input" accept="image/*" multiple style="display:none" onchange="handleImgUpload(this.files)">
             ＋ 이미지 업로드
@@ -762,7 +763,7 @@ function updSrcState(){
   const checks=[...document.querySelectorAll('.src-chk input')];
   if(checks.every(c=>!c.checked)) checks[0].checked=true;
 }
-let extractedImages = [], paperTexts = {};
+let extractedImages = [], paperTexts = {}, imageCaptions = {};
 let prepLog = {}, outline = null, outlineEdits = {}, currentProcessingKey = null;
 let pptxRelPath = null, previewImages = [];
 let currentStep = 1, abTabMode = 'en', modalSlide = -1;
@@ -854,7 +855,7 @@ async function savePapersToProject() {
 function newProject(){
   papers=[]; selected=new Set(); paperMeta={};
   paperTexts={}; paperTranslations={}; txlStatus={};
-  prepLog={}; extractedImages={}; abPaper=null;
+  prepLog={}; extractedImages={}; imageCaptions={}; abPaper=null;
   outline=null; outlineEdits={}; pptxRelPath=null; previewImages=[];
   document.querySelectorAll('.preview-card[data-edited]').forEach(c=>delete c.dataset.edited);
   const sel=document.getElementById('cfg-open-proj'); if(sel) sel.value='';
@@ -907,7 +908,7 @@ async function onOpenProjChange(relPath){
   document.querySelectorAll('.preview-card[data-edited]').forEach(c=>delete c.dataset.edited);
   papers=[]; selected=new Set(); paperMeta={};
   paperTexts={}; paperTranslations={}; txlStatus={};
-  prepLog={}; extractedImages=[]; abPaper=null;
+  prepLog={}; extractedImages=[]; imageCaptions={}; abPaper=null;
 
   // PPTX 없는 프로젝트 — step 1로 이동해서 논문 목록 확인
   if(!hasPptx){
@@ -2071,12 +2072,42 @@ function renderImgGrid(){
   const g=document.getElementById('imgrid'); if(!g)return;
   document.getElementById('imgcnt').textContent='('+extractedImages.length+')';
   if(!extractedImages.length){g.innerHTML='<div style="color:var(--muted);font-size:11px">없음</div>';return;}
-  g.innerHTML=extractedImages.map((img,i)=>
+  g.innerHTML=extractedImages.map((img,i)=>{
-    `<div class="icard" title="${esc(img.label)}" style="position:relative" onmouseenter="this.querySelector('.icard-del').style.opacity=1" onmouseleave="this.querySelector('.icard-del').style.opacity=0">
+    const cap=imageCaptions[img.url]||'';
+    const excluded=cap==='제외';
+    const capHtml=cap?`<div style="font-size:8px;padding:1px 4px;line-height:1.3;color:${excluded?'#f87171':'#34d399'};overflow:hidden;text-overflow:ellipsis;white-space:nowrap" title="${esc(cap)}">${excluded?'⛔ 제외':cap}</div>`:'';
+    return `<div class="icard" title="${esc(img.label)}" style="position:relative;opacity:${excluded?.5:1}" onmouseenter="this.querySelector('.icard-del').style.opacity=1" onmouseleave="this.querySelector('.icard-del').style.opacity=0">
        <img src="${esc(img.url)}" loading="lazy" onerror="this.style.display='none'" onclick="showImgPreview('${esc(img.url)}','${esc(img.label)}')" style="cursor:zoom-in;width:100%;height:100%;object-fit:cover">
        <button class="icard-del" onclick="event.stopPropagation();deleteImg(${i})" style="position:absolute;top:4px;right:4px;opacity:0;transition:.15s;background:rgba(220,38,38,.85);border:none;color:#fff;border-radius:4px;width:22px;height:22px;font-size:13px;cursor:pointer;display:flex;align-items:center;justify-content:center;line-height:1" title="삭제">✕</button>
        <div class="ilabel" style="overflow:hidden;text-overflow:ellipsis;white-space:nowrap;font-size:9px;padding:2px 5px">${esc(img.label)}</div>
-     </div>`).join('');
+       ${capHtml}
+     </div>`;
+  }).join('');
+}
+
+async function analyzeImages(){
+  if(!extractedImages.length){setMsg(2,'분석할 이미지가 없습니다.','var(--yellow)');return;}
+  const btn=document.getElementById('btn-analyze-imgs');
+  btn.disabled=true;
+  const project=resolveProjectSlug();
+  const total=extractedImages.length;
+  let done=0;
+  for(const img of extractedImages){
+    btn.textContent=`🔍 ${done}/${total}`;
+    if(!imageCaptions[img.url]){
+      try{
+        const r=await fetch('/api/pptx/analyze-image',{...jh(),method:'POST',body:JSON.stringify({url:img.url,label:img.label,project})});
+        const d=await r.json();
+        if(d.caption) imageCaptions[img.url]=d.caption;
+      }catch(e){console.warn('[analyzeImages]',e);}
+    }
+    done++;
+    renderImgGrid();
+  }
+  btn.disabled=false;
+  btn.textContent='🔍 이미지 분석';
+  const excluded=Object.values(imageCaptions).filter(c=>c==='제외').length;
+  setMsg(2,`이미지 분석 완료 (${total}장${excluded?', 제외 '+excluded+'장':''})`, 'var(--green)');
 }
 
 async function deleteImg(i){
@@ -2194,7 +2225,11 @@ async function generateOutline() {
     contentBlocks.push(block);
   }
 
-  const imgList=extractedImages.slice(0,30).map((img,i)=>`${i+1}. ${img.url} (${img.label})`).join('\n');
+  const imgList=extractedImages
+    .filter(img=>(imageCaptions[img.url]||'')!=='제외')
+    .slice(0,30)
+    .map((img,i)=>{const cap=imageCaptions[img.url]?` — ${imageCaptions[img.url]}`:'';return `${i+1}. ${img.url} (${img.label})${cap}`;})
+    .join('\n');
 
   const prompt=`[PPTX 워크플로 시작]\n요청: ${topic}\nPMCIDs: ${pmcids}\n템플릿: ${tmpl}${skin?'\n배경 스킨: '+skin:''}\n슬라이드 수: ${slides}장\n\n=== 논문 내용 ===\n${contentBlocks.join('\n\n---\n')}\n\n=== 추출된 이미지 ===\n${imgList||'없음'}\n\n위 논문 내용과 이미지를 활용해 슬라이드 아웃라인을 \`\`\`pptx-outline 블록으로 출력해주세요. create_presentation은 아직 호출하지 마세요.`;