ns = params_kw.copy() kb_id = ns.get('kb_id', '') env = request._run_ns rows = [] async with get_sor_context(env, 'rag') as sor: recs = await sor.sqlExe( "SELECT id, file_name, file_size, file_type, file_path, metadata, status, chunk_count " "FROM documents WHERE kb_id=${kb_id}$ AND metadata IS NOT NULL AND metadata != '' " "ORDER BY created_at DESC LIMIT 50", {"kb_id": kb_id}) rows = [dict(r) for r in recs] cards = [] import json as _json for r in rows: meta = {} try: meta = _json.loads(r['metadata'] or '{}') except: pass face_count = meta.get('face', meta.get('faces', 0)) or 0 speakers = meta.get('speakers', meta.get('voiceprint', 0)) or 0 # Build card for this document ext = (r['file_name'] or '').rsplit('.', 1)[-1].lower() if '.' in (r['file_name'] or '') else '' icon = '📄' if ext in ('mp4','avi','mov','mkv','webm'): icon = '🎬' elif ext in ('jpg','jpeg','png','gif','bmp','webp'): icon = '🖼' elif ext in ('mp3','wav','flac','ogg','m4a'): icon = '🎵' elif ext in ('pdf',): icon = '📕' elif ext in ('docx','doc'): icon = '📘' elif ext in ('pptx','ppt'): icon = '📙' elif ext in ('xlsx','xls'): icon = '📊' badges = [] if face_count > 0: badges.append('😀×' + str(int(face_count))) if speakers > 0: badges.append('🎤×' + str(int(speakers))) badge_text = ' '.join(badges) if badges else '暂无识别' cards.append({ "widgettype": "VBox", "options": {"width": "calc(50% - 8px)", "padding": "14px", "marginBottom": "12px", "border": "1px solid #e0e0e0", "borderRadius": "8px", "bgcolor": "#fff", "css": "card", "display": "inline-block", "verticalAlign": "top"}, "subwidgets": [ {"widgettype": "HBox", "options": {"alignItems": "center", "marginBottom": "8px"}, "subwidgets": [ {"widgettype": "Text", "options": {"text": icon + " " + (r['file_name'] or '')[:40], "cfontsize": 14, "fontWeight": "bold", "color": "#333", "cwidth": 0, "css": "filler"}} ]}, {"widgettype": "HBox", "options": {"spacing": "8px", "marginBottom": "10px"}, "subwidgets": [ {"widgettype": "Text", "options": {"text": badge_text, "cfontsize": 12, "bgcolor": "#e8f5e9" if face_count or speakers else "#f5f5f5", "color": "#2e7d32" if face_count or speakers else "#999", "padding": "4px 10px", "borderRadius": "12px"}} ]}, {"widgettype": "HBox", "options": {"spacing": "6px"}, "subwidgets": [ {"widgettype": "Text", "options": {"text": "😀 人脸: " + str(int(face_count)), "cfontsize": 12, "color": "#666"}}, {"widgettype": "Text", "options": {"text": "🎤 声纹: " + str(int(speakers)), "cfontsize": 12, "color": "#666", "marginLeft": "12px"}} ]}, {"widgettype": "Text", "options": {"text": "", "cheight": 0.3}}, {"widgettype": "Button", "options": { "label": "🏷 添加标签", "cfontsize": 12, "bgcolor": "#f0f0f0", "color": "#666", "css": "tag-btn", "padding": "4px 12px", "borderRadius": "16px", "border": "1px solid #ddd" }, "binds": [{ "wid": "self", "event": "click", "actiontype": "script", "target": "self", "script": "var doc_id='" + r['id'] + "';var tag=prompt('请输入标签:');if(!tag)return;var u='/rag/knowledge_bases_list/add_tag.dspy?doc_id='+encodeURIComponent(doc_id)+'&tag='+encodeURIComponent(tag)+'&kb_id=" + kb_id + "';fetch(u).then(function(r){return r.json()}).then(function(d){if(d.status==='SUCCEEDED'){alert('标签已添加');window.location.reload()}else{alert('失败:'+JSON.stringify(d))}})" }]} ] }) if not cards: return json.dumps({ "widgettype": "Text", "options": { "text": "暂无分析结果", "cfontsize": 14, "color": "#aaa", "halign": "center", "marginTop": "40px" } }, ensure_ascii=False) # Wrap cards in FlexBox-like container return json.dumps({ "widgettype": "VBox", "options": {"padding": "20px", "spacing": "8px"}, "subwidgets": [ {"widgettype": "Text", "options": {"text": "📊 文件分析结果", "cfontsize": 20, "fontWeight": "bold", "color": "#1a1a2e", "marginBottom": "16px"}}, {"widgettype": "Text", "options": {"text": "人脸检测 & 声纹识别 | 共 " + str(len(cards)) + " 个文件", "cfontsize": 13, "color": "#888", "marginBottom": "16px"}}, {"widgettype": "VBox", "options": {"width": "100%"}, "subwidgets": cards} ] }, ensure_ascii=False)