345 lines
1.0 MiB
Plaintext
345 lines
1.0 MiB
Plaintext
<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<title>graphify - graphify-out/graph.html</title>
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<script src="https://unpkg.com/vis-network@9.1.6/standalone/umd/vis-network.min.js"
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integrity="sha384-Ux6phic9PEHJ38YtrijhkzyJ8yQlH8i/+buBR8s3mAZOJrP1gwyvAcIYl3GWtpX1"
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crossorigin="anonymous"></script>
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<style>
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* { box-sizing: border-box; margin: 0; padding: 0; }
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body { background: #0f0f1a; color: #e0e0e0; font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif; display: flex; height: 100vh; overflow: hidden; }
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#graph { flex: 1; }
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#sidebar { width: 280px; background: #1a1a2e; border-left: 1px solid #2a2a4e; display: flex; flex-direction: column; overflow: hidden; }
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#search-wrap { padding: 12px; border-bottom: 1px solid #2a2a4e; }
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#search { width: 100%; background: #0f0f1a; border: 1px solid #3a3a5e; color: #e0e0e0; padding: 7px 10px; border-radius: 6px; font-size: 13px; outline: none; }
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#search:focus { border-color: #4E79A7; }
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#search-results { max-height: 140px; overflow-y: auto; padding: 4px 12px; border-bottom: 1px solid #2a2a4e; display: none; }
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.search-item { padding: 4px 6px; cursor: pointer; border-radius: 4px; font-size: 12px; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
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.search-item:hover { background: #2a2a4e; }
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#info-panel { padding: 14px; border-bottom: 1px solid #2a2a4e; min-height: 140px; }
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#info-panel h3 { font-size: 13px; color: #aaa; margin-bottom: 8px; text-transform: uppercase; letter-spacing: 0.05em; }
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#info-content { font-size: 13px; color: #ccc; line-height: 1.6; }
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#info-content .field { margin-bottom: 5px; }
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#info-content .field b { color: #e0e0e0; }
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#info-content .empty { color: #555; font-style: italic; }
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.neighbor-link { display: block; padding: 2px 6px; margin: 2px 0; border-radius: 3px; cursor: pointer; font-size: 12px; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; border-left: 3px solid #333; }
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.neighbor-link:hover { background: #2a2a4e; }
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#neighbors-list { max-height: 160px; overflow-y: auto; margin-top: 4px; }
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#legend-wrap { flex: 1; overflow-y: auto; padding: 12px; }
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#legend-wrap h3 { font-size: 13px; color: #aaa; margin-bottom: 10px; text-transform: uppercase; letter-spacing: 0.05em; }
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.legend-item { display: flex; align-items: center; gap: 8px; padding: 4px 0; cursor: pointer; border-radius: 4px; font-size: 12px; }
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.legend-item:hover { background: #2a2a4e; padding-left: 4px; }
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.legend-item.dimmed { opacity: 0.35; }
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.legend-dot { width: 12px; height: 12px; border-radius: 50%; flex-shrink: 0; }
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.legend-label { flex: 1; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }
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.legend-count { color: #666; font-size: 11px; }
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#stats { padding: 10px 14px; border-top: 1px solid #2a2a4e; font-size: 11px; color: #555; }
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#legend-controls { display: flex; align-items: center; gap: 8px; margin-bottom: 8px; padding: 4px 0; }
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#legend-controls label { display: flex; align-items: center; gap: 6px; cursor: pointer; font-size: 12px; color: #aaa; user-select: none; }
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#legend-controls label:hover { color: #e0e0e0; }
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.legend-cb, #select-all-cb { appearance: none; -webkit-appearance: none; width: 14px; height: 14px; border: 1.5px solid #3a3a5e; border-radius: 3px; background: #0f0f1a; cursor: pointer; position: relative; flex-shrink: 0; }
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.legend-cb:checked, #select-all-cb:checked { background: #4E79A7; border-color: #4E79A7; }
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.legend-cb:checked::after, #select-all-cb:checked::after { content: ''; position: absolute; left: 3.5px; top: 1px; width: 4px; height: 7px; border: solid #fff; border-width: 0 2px 2px 0; transform: rotate(45deg); }
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#select-all-cb:indeterminate { background: #4E79A7; border-color: #4E79A7; }
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#select-all-cb:indeterminate::after { content: ''; position: absolute; left: 2px; top: 5px; width: 8px; height: 2px; background: #fff; border: none; transform: none; }
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</style>
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</head>
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<body>
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<div id="graph"></div>
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<div id="sidebar">
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<div id="search-wrap">
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<input id="search" type="text" placeholder="Search nodes..." autocomplete="off">
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<div id="search-results"></div>
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</div>
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<div id="info-panel">
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<h3>Node Info</h3>
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<div id="info-content"><span class="empty">Click a node to inspect it</span></div>
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</div>
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<div id="legend-wrap">
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<h3>Communities</h3>
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<div id="legend-controls">
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<label><input type="checkbox" id="select-all-cb" checked onchange="toggleAllCommunities(!this.checked)">Select All</label>
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</div>
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<div id="legend"></div>
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</div>
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<div id="stats">1235 nodes · 1548 edges · 131 communities</div>
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</div>
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<script>
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"border": "#BAB0AC"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "CT-006: Somente um candidato utiliz\u00e1vel -> Selecionar esse candidato.", "community": 119, "community_name": "select_article_extractor", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_203", "label": "CT-007: Nenhum utiliz\u00e1vel, mas existe candidato degradado -> Executar o\u2026", "color": {"background": "#BAB0AC", "border": "#BAB0AC", "highlight": {"background": "#ffffff", "border": "#BAB0AC"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "CT-007: Nenhum utiliz\u00e1vel, mas existe candidato degradado -> Executar o\u2026", "community": 119, "community_name": "select_article_extractor", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_215", "label": "CT-008: Todos os candidatos indispon\u00edveis -> Selecionar newspaper4k.", "color": {"background": "#BAB0AC", "border": "#BAB0AC", "highlight": {"background": "#ffffff", "border": "#BAB0AC"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "CT-008: Todos os candidatos indispon\u00edveis -> Selecionar newspaper4k.", "community": 119, "community_name": "select_article_extractor", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_227", "label": "CT-009: Readability retorna apenas um fragmento pequeno enquanto os outros\u2026", "color": {"background": "#BAB0AC", "border": "#BAB0AC", "highlight": {"background": "#ffffff", "border": "#BAB0AC"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "CT-009: Readability retorna apenas um fragmento pequeno enquanto os outros\u2026", "community": 119, "community_name": "select_article_extractor", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_244", "label": "CT-010: Um candidato cont\u00e9m o conte\u00fado comum e muito conte\u00fado excedente ->\u2026", "color": {"background": "#BAB0AC", "border": "#BAB0AC", "highlight": {"background": "#ffffff", "border": "#BAB0AC"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "CT-010: Um candidato cont\u00e9m o conte\u00fado comum e muito conte\u00fado excedente ->\u2026", "community": 119, "community_name": "select_article_extractor", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_260", "label": "CT-011: Um candidato cont\u00e9m somente parte do conte\u00fado comum -> Perde cobertura\u2026", "color": {"background": "#BAB0AC", "border": "#BAB0AC", "highlight": {"background": "#ffffff", "border": "#BAB0AC"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "CT-011: Um candidato cont\u00e9m somente parte do conte\u00fado comum -> Perde cobertura\u2026", "community": 119, "community_name": "select_article_extractor", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_273", "label": "CT-012: A entrada j\u00e1 cont\u00e9m selected_extractor -> Recalcular e substituir\u2026", "color": {"background": "#4E79A7", "border": "#4E79A7", "highlight": {"background": "#ffffff", "border": "#4E79A7"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "CT-012: A entrada j\u00e1 cont\u00e9m selected_extractor -> Recalcular e substituir\u2026", "community": 120, "community_name": "process_batch", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_299", "label": "CT-013: articles est\u00e1 vazio -> Gerar sa\u00edda v\u00e1lida com articles vazio.", "color": {"background": "#4E79A7", "border": "#4E79A7", "highlight": {"background": "#ffffff", "border": "#4E79A7"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "CT-013: articles est\u00e1 vazio -> Gerar sa\u00edda v\u00e1lida com articles vazio.", "community": 120, "community_name": "process_batch", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_318", "label": "CT-014: JSON inv\u00e1lido -> N\u00e3o gerar sa\u00edda.", "color": {"background": "#4E79A7", "border": "#4E79A7", "highlight": {"background": "#ffffff", "border": "#4E79A7"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "CT-014: JSON inv\u00e1lido -> N\u00e3o gerar sa\u00edda.", "community": 120, "community_name": "process_batch", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_335", "label": "Testa o processamento em lote completo sobre o arquivo real\u2026", "color": {"background": "#4E79A7", "border": "#4E79A7", "highlight": {"background": "#ffffff", "border": "#4E79A7"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Testa o processamento em lote completo sobre o arquivo real\u2026", "community": 120, "community_name": "process_batch", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_364", "label": "Teste de regress\u00e3o para o Artigo 1 (Los puntajes de River vs. Independiente\u2026", "color": {"background": "#BAB0AC", "border": "#BAB0AC", "highlight": {"background": "#ffffff", "border": "#BAB0AC"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Teste de regress\u00e3o para o Artigo 1 (Los puntajes de River vs. Independiente\u2026", "community": 119, "community_name": "select_article_extractor", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_398", "label": "Gera um lote de 100 artigos sint\u00e9ticos e verifica 100% de repetibilidade\u2026", "color": {"background": "#4E79A7", "border": "#4E79A7", "highlight": {"background": "#ffffff", "border": "#4E79A7"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Gera um lote de 100 artigos sint\u00e9ticos e verifica 100% de repetibilidade\u2026", "community": 120, "community_name": "process_batch", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_447", "label": "Testa a integra\u00e7\u00e3o end-to-end do pipeline downstream: L\u00ea o JSON enriquecido com\u2026", "color": {"background": "#4E79A7", "border": "#4E79A7", "highlight": {"background": "#ffffff", "border": "#4E79A7"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Testa a integra\u00e7\u00e3o end-to-end do pipeline downstream: L\u00ea o JSON enriquecido com\u2026", "community": 120, "community_name": "process_batch", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_484", "label": "E2E: Executa scripts/select_article_extractor.py como subprocesso real na linha\u2026", "color": {"background": "#4E79A7", "border": "#4E79A7", "highlight": {"background": "#ffffff", "border": "#4E79A7"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "E2E: Executa scripts/select_article_extractor.py como subprocesso real na linha\u2026", "community": 120, "community_name": "process_batch", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_521", "label": "E2E: Executa CLI sem a flag -o e valida cria\u00e7\u00e3o autom\u00e1tica de\u2026", "color": {"background": "#4E79A7", "border": "#4E79A7", "highlight": {"background": "#ffffff", "border": "#4E79A7"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "E2E: Executa CLI sem a flag -o e valida cria\u00e7\u00e3o autom\u00e1tica de\u2026", "community": 120, "community_name": "process_batch", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_549", "label": "E2E: Executa CLI com JSON inv\u00e1lido e valida c\u00f3digo de sa\u00edda e erro no stderr.", "color": {"background": "#4E79A7", "border": "#4E79A7", "highlight": {"background": "#ffffff", "border": "#4E79A7"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "E2E: Executa CLI com JSON inv\u00e1lido e valida c\u00f3digo de sa\u00edda e erro no stderr.", "community": 120, "community_name": "process_batch", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "tests_test_select_article_extractor_rationale_562", "label": "E2E: Executa CLI com arquivo inexistente e valida c\u00f3digo 1 e mensagem no stderr.", "color": {"background": "#4E79A7", "border": "#4E79A7", "highlight": {"background": "#ffffff", "border": "#4E79A7"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "E2E: Executa CLI com arquivo inexistente e valida c\u00f3digo 1 e mensagem no stderr.", "community": 120, "community_name": "process_batch", "source_file": "tests/test_select_article_extractor.py", "file_type": "rationale", "degree": 1}, {"id": "agents_rules_graphify", "label": "rules/graphify.md", "color": {"background": "#FF9DA7", "border": "#FF9DA7", "highlight": {"background": "#ffffff", "border": "#FF9DA7"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "rules/graphify.md", "community": 7, "community_name": "Graphify Rules", "source_file": ".agents/rules/graphify.md", "file_type": "document", "degree": 1}, {"id": "agents_rules_graphify_graphify", "label": "graphify", "color": {"background": "#FF9DA7", "border": "#FF9DA7", "highlight": {"background": "#ffffff", "border": "#FF9DA7"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "graphify", "community": 7, "community_name": "Graphify Rules", "source_file": ".agents/rules/graphify.md", "file_type": "document", "degree": 1}, {"id": "agents_skills_graphify_skill", "label": "graphify/SKILL.md", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "graphify/SKILL.md", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 1}, {"id": "agents_skills_graphify_skill_graphify", "label": "/graphify", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 16.8, "font": {"size": 12, "color": "#ffffff"}, "title": "/graphify", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 10}, {"id": "agents_skills_graphify_skill_usage", "label": "Usage", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Usage", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 1}, {"id": "agents_skills_graphify_skill_what_graphify_is_for", "label": "What graphify is for", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "What graphify is for", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 1}, {"id": "agents_skills_graphify_skill_what_you_must_do_when_invoked", "label": "What You Must Do When Invoked", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 18.2, "font": {"size": 12, "color": "#ffffff"}, "title": "What You Must Do When Invoked", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 12}, {"id": "agents_skills_graphify_skill_step_0_github_repos_and_multi_path_merge_only_if_a_url_or_several_paths", "label": "Step 0 - GitHub repos and multi-path merge (only if a URL or several paths)", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Step 0 - GitHub repos and multi-path merge (only if a URL or several paths)", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 1}, {"id": "agents_skills_graphify_skill_step_1_ensure_graphify_is_installed", "label": "Step 1 - Ensure graphify is installed", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Step 1 - Ensure graphify is installed", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 1}, {"id": "agents_skills_graphify_skill_step_2_detect_files", "label": "Step 2 - Detect files", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Step 2 - Detect files", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 1}, {"id": "agents_skills_graphify_skill_step_2_5_video_and_audio_only_if_video_files_detected", "label": "Step 2.5 - Video and audio (only if video files detected)", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Step 2.5 - Video and audio (only if video files detected)", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 1}, {"id": "agents_skills_graphify_skill_step_3_extract_entities_and_relationships", "label": "Step 3 - Extract entities and relationships", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 12.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Step 3 - Extract entities and relationships", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 4}, {"id": "agents_skills_graphify_skill_part_a_structural_extraction_for_code_files", "label": "Part A - Structural extraction for code files", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Part A - Structural extraction for code files", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 1}, {"id": "agents_skills_graphify_skill_part_b_semantic_extraction_parallel_subagents", "label": "Part B - Semantic extraction (parallel subagents)", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Part B - Semantic extraction (parallel subagents)", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 1}, {"id": "agents_skills_graphify_skill_part_c_merge_ast_semantic_into_final_extraction", "label": "Part C - Merge AST + semantic into final extraction", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Part C - Merge AST + semantic into final extraction", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 1}, {"id": "agents_skills_graphify_skill_step_4_build_graph_cluster_analyze_generate_outputs", "label": "Step 4 - Build graph, cluster, analyze, generate outputs", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Step 4 - Build graph, cluster, analyze, generate outputs", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 1}, {"id": "agents_skills_graphify_skill_step_4_5_graph_health_check_read_only_integrity_gate", "label": "Step 4.5 - Graph health check (read-only integrity gate)", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Step 4.5 - Graph health check (read-only integrity gate)", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 1}, {"id": "agents_skills_graphify_skill_step_5_label_communities", "label": "Step 5 - Label communities", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Step 5 - Label communities", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 1}, {"id": "agents_skills_graphify_skill_step_6_generate_obsidian_vault_opt_in_html", "label": "Step 6 - Generate Obsidian vault (opt-in) + HTML", "color": {"background": "#76B7B2", "border": "#76B7B2", "highlight": {"background": "#ffffff", "border": "#76B7B2"}}, "size": 10.7, "font": {"size": 0, "color": "#ffffff"}, "title": "Step 6 - Generate Obsidian vault (opt-in) + HTML", "community": 3, "community_name": "Graphify Commands", "source_file": ".agents/skills/graphify/SKILL.md", "file_type": "document", "degree": 1}, {"id": 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"color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "tests_fixtures_benchmark_24_fr_not_related", "to": "tests_fixtures_benchmark_24_fr_not_related_recette_traditionnelle_de_la_quiche_lorraine", "label": "contains", "title": "contains [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "tests_fixtures_benchmark_24_fr_tangential", "to": "tests_fixtures_benchmark_24_fr_tangential_promenade_dans_paris", "label": "contains", "title": "contains [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "tests_fixtures_benchmark_24_it_contextual", "to": "tests_fixtures_benchmark_24_it_contextual_innovazione_negli_impianti_frenanti", "label": "contains", "title": "contains [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "tests_fixtures_benchmark_24_it_direct", "to": "tests_fixtures_benchmark_24_it_direct_nuova_monoposto_a_maranello", "label": "contains", "title": "contains [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "tests_fixtures_benchmark_24_it_not_related", "to": "tests_fixtures_benchmark_24_it_not_related_ricetta_tradizionale_del_risotto", "label": "contains", "title": "contains [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "tests_fixtures_benchmark_24_it_tangential", "to": "tests_fixtures_benchmark_24_it_tangential_passeggiata_pomeridiana_a_modena", "label": "contains", "title": "contains [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "tests_fixtures_benchmark_24_pt_contextual", "to": "tests_fixtures_benchmark_24_pt_contextual_log\u00edstica_de_derivados", "label": "contains", "title": "contains [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "tests_fixtures_benchmark_24_pt_direct", "to": "tests_fixtures_benchmark_24_pt_direct_produ\u00e7\u00e3o_de_petr\u00f3leo_no_brasil", "label": "contains", "title": "contains [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "tests_fixtures_benchmark_24_pt_not_related", "to": "tests_fixtures_benchmark_24_pt_not_related_dicas_de_jardinagem", "label": "contains", "title": "contains [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "tests_fixtures_benchmark_24_pt_tangential", "to": "tests_fixtures_benchmark_24_pt_tangential_turismo_no_rio_de_janeiro", "label": "contains", "title": "contains [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}];
|
|
const LEGEND = [{"cid": 0, "color": "#4E79A7", "label": "Task Planning", "count": 27}, {"cid": 1, "color": "#F28E2B", "label": "Convergence Workflow", "count": 16}, {"cid": 2, "color": "#E15759", "label": "SpecKit Utilities", "count": 16}, {"cid": 3, "color": "#76B7B2", "label": "Graphify Commands", "count": 25}, {"cid": 4, "color": "#59A14F", "label": "speckit-analyze/SKILL.md", "count": 26}, {"cid": 5, "color": "#EDC948", "label": "Tasks: Multilingual NLP Entity Inherence Classifier (POC)", "count": 13}, {"cid": 6, "color": "#B07AA1", "label": "Feature Specification Template", "count": 13}, {"cid": 7, "color": "#FF9DA7", "label": "Graphify Rules", "count": 2}, {"cid": 8, "color": "#9C755F", "label": "Implementation Planning", "count": 11}, {"cid": 9, "color": "#BAB0AC", "label": "Feature Specification", "count": 11}, {"cid": 10, "color": "#4E79A7", "label": "Task Generation", "count": 11}, {"cid": 11, "color": "#F28E2B", "label": "Project Constitution", "count": 11}, {"cid": 12, "color": "#E15759", "label": "Constitution Template", "count": 11}, {"cid": 13, "color": "#76B7B2", "label": "Graphify Exports", "count": 9}, {"cid": 14, "color": "#59A14F", "label": "Ponytail Configuration", "count": 9}, {"cid": 15, "color": "#EDC948", "label": "Implementation Planning Template", "count": 9}, {"cid": 16, "color": "#B07AA1", "label": "Ponytail Help", "count": 8}, {"cid": 17, "color": "#FF9DA7", "label": "Checklist Generation", "count": 8}, {"cid": 18, "color": "#9C755F", "label": "Clarification Workflow", "count": 7}, {"cid": 19, "color": "#BAB0AC", "label": "Implementation Workflow", "count": 7}, {"cid": 20, "color": "#4E79A7", "label": "Graph Query", "count": 6}, {"cid": 21, "color": "#F28E2B", "label": "Constitution Workflow", "count": 6}, {"cid": 22, "color": "#E15759", "label": "Feature Branch Creation", "count": 6}, {"cid": 23, "color": "#76B7B2", "label": "Ponytail Audit", "count": 5}, {"cid": 24, "color": "#59A14F", "label": "Ponytail Metrics", "count": 5}, {"cid": 25, "color": "#EDC948", "label": "Ponytail Review", "count": 5}, {"cid": 26, "color": "#B07AA1", "label": "Task Issue Conversion", "count": 5}, {"cid": 27, "color": "#FF9DA7", "label": "Checklist Template", "count": 5}, {"cid": 28, "color": "#9C755F", "label": "Graphify Watch Mode", "count": 4}, {"cid": 29, "color": "#BAB0AC", "label": "Graphify Hooks", "count": 4}, {"cid": 30, "color": "#4E79A7", "label": "Graphify Updates", "count": 4}, {"cid": 31, "color": "#F28E2B", "label": "Ponytail Debt", "count": 4}, {"cid": 32, "color": "#E15759", "label": "Repository Merge", "count": 3}, {"cid": 33, "color": "#76B7B2", "label": "Media Transcription", "count": 3}, {"cid": 34, "color": "#59A14F", "label": "Extraction Specification", "count": 2}, {"cid": 35, "color": "#EDC948", "label": "Prerequisite Checks", "count": 1}, {"cid": 36, "color": "#B07AA1", "label": "Template Resolution", "count": 1}, {"cid": 37, "color": "#FF9DA7", "label": "Plan Setup", "count": 1}, {"cid": 38, "color": "#9C755F", "label": "Task Setup", "count": 1}, {"cid": 39, "color": "#BAB0AC", "label": "Graphify Workflows", "count": 2}, {"cid": 40, "color": "#4E79A7", "label": "main", "count": 17}, {"cid": 41, "color": "#F28E2B", "label": "1. Technical Decisions & Tradeoffs", "count": 9}, {"cid": 42, "color": "#E15759", "label": "1. Input Schemas", "count": 8}, {"cid": 43, "color": "#76B7B2", "label": "2. Basic CLI Usage Examples", "count": 8}, {"cid": 44, "color": "#59A14F", "label": "2. Standard Streams & Exit Codes", "count": 7}, {"cid": 45, "color": "#EDC948", "label": "ClassificationResult", "count": 21}, {"cid": 46, "color": "#B07AA1", "label": "InherenceClassifier", "count": 29}, {"cid": 47, "color": "#FF9DA7", "label": "classifier.py", "count": 36}, {"cid": 48, "color": "#9C755F", "label": "main", "count": 10}, {"cid": 49, "color": "#BAB0AC", "label": "content_northvolt_de.md", "count": 2}, {"cid": 50, "color": "#4E79A7", "label": "content_presal_pt.md", "count": 2}, {"cid": 51, "color": "#F28E2B", "label": "content_tangential_es.md", "count": 2}, {"cid": 52, "color": "#E15759", "label": "adapters/__init__.py", "count": 2}, {"cid": 53, "color": "#76B7B2", "label": "src/__init__.py", "count": 2}, {"cid": 54, "color": "#59A14F", "label": "de/contextual.md", "count": 2}, {"cid": 55, "color": "#EDC948", "label": "de/direct.md", "count": 2}, {"cid": 56, "color": "#B07AA1", "label": "de/not_related.md", "count": 2}, {"cid": 57, "color": "#FF9DA7", "label": "de/tangential.md", "count": 2}, {"cid": 58, "color": "#9C755F", "label": "en/contextual.md", "count": 2}, {"cid": 59, "color": "#BAB0AC", "label": "en/direct.md", "count": 2}, {"cid": 60, "color": "#4E79A7", "label": "en/not_related.md", "count": 2}, {"cid": 61, "color": "#F28E2B", "label": "en/tangential.md", "count": 2}, {"cid": 62, "color": "#E15759", "label": "es/contextual.md", "count": 2}, {"cid": 63, "color": "#76B7B2", "label": "es/direct.md", "count": 2}, {"cid": 64, "color": "#59A14F", "label": "es/not_related.md", "count": 2}, {"cid": 65, "color": "#EDC948", "label": "es/tangential.md", "count": 2}, {"cid": 66, "color": "#B07AA1", "label": "fr/contextual.md", "count": 2}, {"cid": 67, "color": "#FF9DA7", "label": "fr/direct.md", "count": 2}, {"cid": 68, "color": "#9C755F", "label": "fr/not_related.md", "count": 2}, {"cid": 69, "color": "#BAB0AC", "label": "fr/tangential.md", "count": 2}, {"cid": 70, "color": "#4E79A7", "label": "it/contextual.md", "count": 2}, {"cid": 71, "color": "#F28E2B", "label": "it/direct.md", "count": 2}, {"cid": 72, "color": "#E15759", "label": "it/not_related.md", "count": 2}, {"cid": 73, "color": "#76B7B2", "label": "it/tangential.md", "count": 2}, {"cid": 74, "color": "#59A14F", "label": "pt/contextual.md", "count": 2}, {"cid": 75, "color": "#EDC948", "label": "pt/direct.md", "count": 2}, {"cid": 76, "color": "#B07AA1", "label": "pt/not_related.md", "count": 2}, {"cid": 77, "color": "#FF9DA7", "label": "pt/tangential.md", "count": 2}, {"cid": 78, "color": "#9C755F", "label": "tests/__init__.py", "count": 2}, {"cid": 79, "color": "#BAB0AC", "label": "text-nlp-classifier", "count": 1}, {"cid": 80, "color": "#4E79A7", "label": "test_extract_article_contents.py", "count": 73}, {"cid": 81, "color": "#F28E2B", "label": "Extrator de Not\u00edcias do Google News \u2014 Guia Completo de Funcionamento", "count": 25}, {"cid": 82, "color": "#E15759", "label": "extract_google_news.py", "count": 19}, {"cid": 83, "color": "#76B7B2", "label": "ExtractionResult", "count": 7}, {"cid": 84, "color": "#59A14F", "label": "test_extract_google_news.py", "count": 16}, {"cid": 85, "color": "#EDC948", "label": "Implementation Tasks: Google News Headlines Extractor", "count": 14}, {"cid": 86, "color": "#B07AA1", "label": "Feature Specification: Google News Headlines Extractor", "count": 11}, {"cid": 87, "color": "#FF9DA7", "label": "2. Cen\u00e1rios Pr\u00e1ticos de Uso", "count": 10}, {"cid": 88, "color": "#9C755F", "label": "Implementation Plan: Google News Headlines Extractor", "count": 7}, {"cid": 89, "color": "#BAB0AC", "label": "scripts/__init__.py", "count": 2}, {"cid": 90, "color": "#4E79A7", "label": "SearchQuery", "count": 10}, {"cid": 91, "color": "#F28E2B", "label": "1. Technical Decisions & Tradeoffs", "count": 8}, {"cid": 92, "color": "#E15759", "label": "General Readiness Checklist: Google News Headlines Extractor", "count": 7}, {"cid": 93, "color": "#76B7B2", "label": "1. Entidades de Dom\u00ednio & DTOs", "count": 7}, {"cid": 94, "color": "#59A14F", "label": "Specification Quality Checklist: Google News Headlines Extractor", "count": 6}, {"cid": 95, "color": "#EDC948", "label": "CLI Contract: Google News Headlines Extractor", "count": 6}, {"cid": 96, "color": "#B07AA1", "label": "readiness.md", "count": 5}, {"cid": 97, "color": "#FF9DA7", "label": "\ud83e\udde0 TextNLPClassifierApp", "count": 36}, {"cid": 98, "color": "#9C755F", "label": "Extraction Pipeline Checklist: Article Content Multi-Engine Extractor", "count": 38}, {"cid": 99, "color": "#BAB0AC", "label": "sample_rss_xml", "count": 3}, {"cid": 100, "color": "#4E79A7", "label": "models.py", "count": 13}, {"cid": 101, "color": "#F28E2B", "label": "ECPSnapshot", "count": 17}, {"cid": 102, "color": "#E15759", "label": "Feature Specification: Multilingual NLP Entity Inherence Classifier (POC)", "count": 14}, {"cid": 103, "color": "#76B7B2", "label": "4. Requisitos Funcionais (FR)", "count": 21}, {"cid": 104, "color": "#59A14F", "label": "Tasks: Article Content Multi-Engine Extractor", "count": 19}, {"cid": 105, "color": "#EDC948", "label": "LocalEmbeddingsAdapter", "count": 14}, {"cid": 106, "color": "#B07AA1", "label": "Implementation Plan: Article Content Multi-Engine Extractor", "count": 12}, {"cid": 107, "color": "#FF9DA7", "label": "2. Cen\u00e1rios de Valida\u00e7\u00e3o", "count": 9}, {"cid": 108, "color": "#9C755F", "label": "1. Technical Decisions & Tradeoffs", "count": 9}, {"cid": 109, "color": "#BAB0AC", "label": "Implementation Plan: Multilingual NLP Entity Inherence Classifier (POC)", "count": 8}, {"cid": 110, "color": "#4E79A7", "label": "POC Readiness & Requirements Quality Checklist: Multilingual NLP Entity Inherence Classifier", "count": 7}, {"cid": 111, "color": "#F28E2B", "label": "Specification Quality Checklist: Multilingual NLP Entity Inherence Classifier", "count": 6}, {"cid": 112, "color": "#E15759", "label": "CLI Contract: Article Content Multi-Engine Extractor", "count": 6}, {"cid": 113, "color": "#76B7B2", "label": "001-multilingual-entity-classifier/spec.md", "count": 4}, {"cid": 114, "color": "#59A14F", "label": "JSON Schema Contract: Article Content Multi-Engine Extractor", "count": 4}, {"cid": 115, "color": "#EDC948", "label": "PRD \u2014 Sele\u00e7\u00e3o determin\u00edstica da biblioteca de extra\u00e7\u00e3o de conte\u00fado", "count": 30}, {"cid": 116, "color": "#B07AA1", "label": "select_article_extractor.py", "count": 18}, {"cid": 117, "color": "#FF9DA7", "label": "1. Text Normalization Pipeline", "count": 18}, {"cid": 118, "color": "#9C755F", "label": "Tasks: Deterministic Article Content Selection", "count": 18}, {"cid": 119, "color": "#BAB0AC", "label": "select_article_extractor", "count": 37}, {"cid": 120, "color": "#4E79A7", "label": "process_batch", "count": 26}, {"cid": 122, "color": "#E15759", "label": "test_select_article_extractor.py", "count": 15}, {"cid": 123, "color": "#76B7B2", "label": "Feature Specification: Deterministic Content Selection", "count": 12}, {"cid": 124, "color": "#59A14F", "label": "2. Entity Descriptions & Fields", "count": 11}, {"cid": 125, "color": "#EDC948", "label": "Implementation Plan: Deterministic Article Content Selection", "count": 11}, {"cid": 126, "color": "#B07AA1", "label": "Deterministic Content Selection Checklist: End-to-End Requirements Quality", "count": 8}, {"cid": 127, "color": "#FF9DA7", "label": "Quickstart: Deterministic Article Content Selection", "count": 7}, {"cid": 128, "color": "#9C755F", "label": "Specification Quality Checklist: Deterministic Content Selection", "count": 6}, {"cid": 129, "color": "#BAB0AC", "label": "CLI Interface Contract: Deterministic Article Content Selection", "count": 6}, {"cid": 130, "color": "#4E79A7", "label": "004-deterministic-content-selection/spec.md", "count": 6}, {"cid": 131, "color": "#F28E2B", "label": "JSON Schema Contract: Deterministic Article Content Selection", "count": 4}];
|
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|
|
// HTML-escape helper — prevents XSS when injecting graph data into innerHTML
|
|
function esc(s) {
|
|
return String(s).replace(/&/g,'&').replace(/</g,'<').replace(/>/g,'>').replace(/"/g,'"').replace(/'/g,''');
|
|
}
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|
|
|
// Build vis datasets
|
|
const nodesDS = new vis.DataSet(RAW_NODES.map(n => ({
|
|
id: n.id, label: n.label, color: n.color, size: n.size,
|
|
font: n.font, title: n.title,
|
|
_community: n.community, _community_name: n.community_name,
|
|
_source_file: n.source_file, _file_type: n.file_type, _degree: n.degree,
|
|
})));
|
|
|
|
const edgesDS = new vis.DataSet(RAW_EDGES.map((e, i) => ({
|
|
id: i, from: e.from, to: e.to,
|
|
label: '',
|
|
title: e.title,
|
|
dashes: e.dashes,
|
|
width: e.width,
|
|
color: e.color,
|
|
arrows: { to: { enabled: true, scaleFactor: 0.5 } },
|
|
})));
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|
|
|
const container = document.getElementById('graph');
|
|
const network = new vis.Network(container, { nodes: nodesDS, edges: edgesDS }, {
|
|
physics: {
|
|
enabled: true,
|
|
solver: 'forceAtlas2Based',
|
|
forceAtlas2Based: {
|
|
gravitationalConstant: -60,
|
|
centralGravity: 0.005,
|
|
springLength: 120,
|
|
springConstant: 0.08,
|
|
damping: 0.4,
|
|
avoidOverlap: 0.8,
|
|
},
|
|
stabilization: { iterations: 200, fit: true },
|
|
},
|
|
interaction: {
|
|
hover: true,
|
|
tooltipDelay: 100,
|
|
hideEdgesOnDrag: true,
|
|
navigationButtons: false,
|
|
keyboard: false,
|
|
},
|
|
nodes: { shape: 'dot', borderWidth: 1.5 },
|
|
edges: { smooth: { type: 'continuous', roundness: 0.2 }, selectionWidth: 3 },
|
|
});
|
|
|
|
network.once('stabilizationIterationsDone', () => {
|
|
network.setOptions({ physics: { enabled: false } });
|
|
});
|
|
|
|
function showInfo(nodeId) {
|
|
const n = nodesDS.get(nodeId);
|
|
if (!n) return;
|
|
const neighborIds = network.getConnectedNodes(nodeId);
|
|
const neighborItems = neighborIds.map(nid => {
|
|
const nb = nodesDS.get(nid);
|
|
const color = nb ? nb.color.background : '#555';
|
|
return `<span class="neighbor-link" style="border-left-color:${esc(color)}" data-nid="${esc(nid)}">${esc(nb ? nb.label : nid)}</span>`;
|
|
}).join('');
|
|
document.getElementById('info-content').innerHTML = `
|
|
<div class="field"><b>${esc(n.label)}</b></div>
|
|
<div class="field">Type: ${esc(n._file_type || 'unknown')}</div>
|
|
<div class="field">Community: ${esc(n._community_name)}</div>
|
|
<div class="field">Source: ${esc(n._source_file || '-')}</div>
|
|
<div class="field">Degree: ${n._degree}</div>
|
|
${neighborIds.length ? `<div class="field" style="margin-top:8px;color:#aaa;font-size:11px">Neighbors (${neighborIds.length})</div><div id="neighbors-list">${neighborItems}</div>` : ''}
|
|
`;
|
|
}
|
|
|
|
function focusNode(nodeId) {
|
|
network.focus(nodeId, { scale: 1.4, animation: true });
|
|
network.selectNodes([nodeId]);
|
|
showInfo(nodeId);
|
|
}
|
|
|
|
// Neighbor links use a data attribute + one delegated listener rather than an
|
|
// inline onclick. A node id/label sourced from a document or a scraped URL
|
|
// (graphify add) can contain a double-quote; dropping the stringified id
|
|
// unescaped into a quoted onclick both broke every link and allowed a hostile
|
|
// source to inject an event handler into the local report (stored XSS, #1838).
|
|
// esc() on data-nid keeps the value inside the attribute; the listener reads it
|
|
// back verbatim. Bound to document so it survives the innerHTML rebuild that
|
|
// recreates #neighbors-list on each showInfo().
|
|
document.addEventListener('click', e => {
|
|
const el = e.target.closest('.neighbor-link');
|
|
if (el && el.dataset.nid !== undefined) focusNode(el.dataset.nid);
|
|
});
|
|
|
|
// Track hovered node — hover detection is more reliable than click params
|
|
let hoveredNodeId = null;
|
|
network.on('hoverNode', params => {
|
|
hoveredNodeId = params.node;
|
|
container.style.cursor = 'pointer';
|
|
});
|
|
network.on('blurNode', () => {
|
|
hoveredNodeId = null;
|
|
container.style.cursor = 'default';
|
|
});
|
|
container.addEventListener('click', () => {
|
|
if (hoveredNodeId !== null) {
|
|
showInfo(hoveredNodeId);
|
|
network.selectNodes([hoveredNodeId]);
|
|
}
|
|
});
|
|
network.on('click', params => {
|
|
if (params.nodes.length > 0) {
|
|
showInfo(params.nodes[0]);
|
|
} else if (hoveredNodeId === null) {
|
|
document.getElementById('info-content').innerHTML = '<span class="empty">Click a node to inspect it</span>';
|
|
}
|
|
});
|
|
|
|
const searchInput = document.getElementById('search');
|
|
const searchResults = document.getElementById('search-results');
|
|
searchInput.addEventListener('input', () => {
|
|
const q = searchInput.value.toLowerCase().trim();
|
|
searchResults.innerHTML = '';
|
|
if (!q) { searchResults.style.display = 'none'; return; }
|
|
const matches = RAW_NODES.filter(n => n.label.toLowerCase().includes(q)).slice(0, 20);
|
|
if (!matches.length) { searchResults.style.display = 'none'; return; }
|
|
searchResults.style.display = 'block';
|
|
matches.forEach(n => {
|
|
const el = document.createElement('div');
|
|
el.className = 'search-item';
|
|
el.textContent = n.label;
|
|
el.style.borderLeft = `3px solid ${n.color.background}`;
|
|
el.style.paddingLeft = '8px';
|
|
el.onclick = () => {
|
|
network.focus(n.id, { scale: 1.5, animation: true });
|
|
network.selectNodes([n.id]);
|
|
showInfo(n.id);
|
|
searchResults.style.display = 'none';
|
|
searchInput.value = '';
|
|
};
|
|
searchResults.appendChild(el);
|
|
});
|
|
});
|
|
document.addEventListener('click', e => {
|
|
if (!searchResults.contains(e.target) && e.target !== searchInput)
|
|
searchResults.style.display = 'none';
|
|
});
|
|
|
|
const hiddenCommunities = new Set();
|
|
|
|
const selectAllCb = document.getElementById('select-all-cb');
|
|
|
|
function updateSelectAllState() {
|
|
const total = LEGEND.length;
|
|
const hidden = hiddenCommunities.size;
|
|
selectAllCb.checked = hidden === 0;
|
|
selectAllCb.indeterminate = hidden > 0 && hidden < total;
|
|
}
|
|
|
|
function toggleAllCommunities(hide) {
|
|
document.querySelectorAll('.legend-item').forEach(item => {
|
|
hide ? item.classList.add('dimmed') : item.classList.remove('dimmed');
|
|
});
|
|
document.querySelectorAll('.legend-cb').forEach(cb => {
|
|
cb.checked = !hide;
|
|
});
|
|
LEGEND.forEach(c => {
|
|
if (hide) hiddenCommunities.add(c.cid); else hiddenCommunities.delete(c.cid);
|
|
});
|
|
const updates = RAW_NODES.map(n => ({ id: n.id, hidden: hide }));
|
|
nodesDS.update(updates);
|
|
updateSelectAllState();
|
|
}
|
|
|
|
const legendEl = document.getElementById('legend');
|
|
LEGEND.forEach(c => {
|
|
const item = document.createElement('div');
|
|
item.className = 'legend-item';
|
|
const cb = document.createElement('input');
|
|
cb.type = 'checkbox';
|
|
cb.className = 'legend-cb';
|
|
cb.checked = true;
|
|
cb.addEventListener('change', (e) => {
|
|
e.stopPropagation();
|
|
if (cb.checked) {
|
|
hiddenCommunities.delete(c.cid);
|
|
item.classList.remove('dimmed');
|
|
} else {
|
|
hiddenCommunities.add(c.cid);
|
|
item.classList.add('dimmed');
|
|
}
|
|
const updates = RAW_NODES
|
|
.filter(n => n.community === c.cid)
|
|
.map(n => ({ id: n.id, hidden: !cb.checked }));
|
|
nodesDS.update(updates);
|
|
updateSelectAllState();
|
|
});
|
|
item.innerHTML = `<div class="legend-dot" style="background:${c.color}"></div>
|
|
<span class="legend-label">${c.label}</span>
|
|
<span class="legend-count">${c.count}</span>`;
|
|
item.prepend(cb);
|
|
item.onclick = (e) => {
|
|
if (e.target === cb) return;
|
|
cb.checked = !cb.checked;
|
|
cb.dispatchEvent(new Event('change'));
|
|
};
|
|
legendEl.appendChild(item);
|
|
});
|
|
</script>
|
|
<script>
|
|
// Render hyperedges as shaded regions
|
|
const hyperedges = [];
|
|
// afterDrawing passes ctx already transformed to network coordinate space.
|
|
// Draw node positions raw — no manual pan/zoom/DPR math needed.
|
|
|
|
// Andrew's monotone chain. Returns the hull in counter-clockwise order, which
|
|
// is what the perimeter must be traced in. Collinear and duplicate points
|
|
// collapse to the extremes, so degenerate member sets render as a segment
|
|
// rather than a zero-area crossed path.
|
|
function convexHull(pts) {
|
|
const p = pts.slice().sort((a, b) => (a.x - b.x) || (a.y - b.y));
|
|
if (p.length < 3) return p;
|
|
const cross = (o, a, b) => (a.x - o.x) * (b.y - o.y) - (a.y - o.y) * (b.x - o.x);
|
|
const build = seq => {
|
|
const out = [];
|
|
for (const q of seq) {
|
|
while (out.length >= 2 && cross(out[out.length - 2], out[out.length - 1], q) <= 0) out.pop();
|
|
out.push(q);
|
|
}
|
|
out.pop();
|
|
return out;
|
|
};
|
|
const hull = build(p).concat(build(p.slice().reverse()));
|
|
return hull.length >= 3 ? hull : p;
|
|
}
|
|
network.on('afterDrawing', function(ctx) {
|
|
hyperedges.forEach(h => {
|
|
const positions = h.nodes
|
|
.map(nid => network.getPositions([nid])[nid])
|
|
.filter(p => p !== undefined);
|
|
if (positions.length < 2) return;
|
|
ctx.save();
|
|
ctx.globalAlpha = 0.12;
|
|
ctx.fillStyle = '#6366f1';
|
|
ctx.strokeStyle = '#6366f1';
|
|
ctx.lineWidth = 2;
|
|
ctx.beginPath();
|
|
// Centroid and expanded hull in network coordinates.
|
|
// The perimeter must follow hull order, not h.nodes order: tracing the
|
|
// raw member order self-intersects whenever the layout does not happen
|
|
// to place members in angular order, filling as crossed wedges.
|
|
const cx = positions.reduce((s, p) => s + p.x, 0) / positions.length;
|
|
const cy = positions.reduce((s, p) => s + p.y, 0) / positions.length;
|
|
const hull = convexHull(positions);
|
|
const expanded = hull.map(p => ({
|
|
x: cx + (p.x - cx) * 1.15,
|
|
y: cy + (p.y - cy) * 1.15
|
|
}));
|
|
ctx.moveTo(expanded[0].x, expanded[0].y);
|
|
expanded.slice(1).forEach(p => ctx.lineTo(p.x, p.y));
|
|
ctx.closePath();
|
|
ctx.fill();
|
|
ctx.globalAlpha = 0.4;
|
|
ctx.stroke();
|
|
// Label
|
|
ctx.globalAlpha = 0.8;
|
|
ctx.fillStyle = '#4f46e5';
|
|
ctx.font = 'bold 11px sans-serif';
|
|
ctx.textAlign = 'center';
|
|
ctx.fillText(h.label, cx, cy - 5);
|
|
ctx.restore();
|
|
});
|
|
});
|
|
</script>
|
|
</body>
|
|
</html> |