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https://huggingface.co/spaces/yangchenx/agentic-research-notebook-wizard/resolve/main/script.js
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hf download hf://spaces/yangchenx/agentic-research-notebook-wizard/script.js
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curl -L -o script.js https://huggingface.co/spaces/yangchenx/agentic-research-notebook-wizard/resolve/main/script.js
6.42 kB
| document.addEventListener('DOMContentLoaded', () => { | |
| const root = document.getElementById('root'); | |
| // Mock data for cells | |
| const initialCells = [ | |
| { | |
| id: 'cell-1', | |
| agentType: 'researcher', | |
| input: 'Find recent breakthroughs in quantum computing', | |
| output: { | |
| type: 'markdown', | |
| content: '## Quantum Computing Breakthroughs (2023)\n\n1. **IBM Quantum Heron Processor** - 133-qubit processor with improved error rates\n2. **Google Quantum Supremacy 2.0** - Demonstrated 70-qubit processor\n3. **Microsoft Topological Qubits** - More stable qubit design\n4. **Quantum Networking** - First multi-node quantum network demonstrated', | |
| tools_used: [ | |
| { name: 'arXiv Search', icon: 'search', status: 'success', latency: '420ms' }, | |
| { name: 'Research Summarizer', icon: 'file-text', status: 'success', latency: '320ms' } | |
| ], | |
| metadata: { | |
| version_hash: 'sha256:9f86d081884c7d659a2feaa0c55ad015a3bf4f1b2b0b822cd15d6c15b0f00a08', | |
| source_citations: [ | |
| { | |
| title: 'IBM Quantum Heron Processor Announcement', | |
| url: 'https://research.ibm.com/blog/quantum-heron-processor', | |
| description: 'Official announcement of the 133-qubit processor' | |
| }, | |
| { | |
| title: 'Nature: Quantum Computing Advances 2023', | |
| url: 'https://www.nature.com/quantum-2023', | |
| description: 'Comprehensive review of quantum computing milestones' | |
| } | |
| ], | |
| verification_score: 0.92, | |
| requires_human_check: true, | |
| human_check_status: 'approved' | |
| } | |
| }, | |
| status: 'success', | |
| timestamp: new Date(Date.now() - 3600000).toISOString() | |
| }, | |
| { | |
| id: 'cell-2', | |
| agentType: 'analyst', | |
| input: 'Summarize the key points from cell-1 into bullet points', | |
| output: { | |
| type: 'markdown', | |
| content: '- IBM released 133-qubit processor\n- Google demonstrated 70-qubit processor\n- Microsoft developed more stable qubit design\n- Multi-node quantum networks achieved', | |
| tools_used: [ | |
| { name: 'Text Summarizer', icon: 'align-left', status: 'success', latency: '210ms' } | |
| ], | |
| metadata: { | |
| version_hash: 'sha256:5e884898da28047151d0e56f8dc6292773603d0d6aabbdd62a11ef721d1542d8', | |
| source_citations: [], | |
| verification_score: 0.85, | |
| requires_human_check: false | |
| } | |
| }, | |
| status: 'success', | |
| timestamp: new Date(Date.now() - 1800000).toISOString() | |
| }, | |
| { | |
| id: 'cell-3', | |
| agentType: 'data-visualizer', | |
| input: 'Create a comparison table of quantum processors from cell-1', | |
| output: { | |
| type: 'table', | |
| content: { | |
| headers: ['Company', 'Qubits', 'Key Feature'], | |
| rows: [ | |
| ['IBM', '133', 'Improved error rates'], | |
| ['Google', '70', 'Supremacy 2.0'], | |
| ['Microsoft', 'N/A', 'Topological stability'] | |
| ] | |
| }, | |
| tools_used: [ | |
| { name: 'Table Generator', icon: 'grid', status: 'success', latency: '380ms' }, | |
| { name: 'Data Validator', icon: 'check-circle', status: 'success', latency: '290ms' } | |
| ], | |
| metadata: { | |
| version_hash: 'sha256:a591a6d40bf420404a011733cfb7b190d62c65bf0bcda32b57b277d9ad9f146e', | |
| source_citations: [], | |
| verification_score: 0.78, | |
| requires_human_check: true, | |
| human_check_status: 'pending' | |
| } | |
| }, | |
| status: 'success', | |
| timestamp: new Date(Date.now() - 900000).toISOString() | |
| } | |
| ]; | |
| // Create notebook with initial cells | |
| const notebook = document.createElement('agentic-notebook'); | |
| notebook.setAttribute('cells', JSON.stringify(initialCells)); | |
| root.appendChild(notebook); | |
| }); | |
| // Mock run function for cells | |
| function mockRunCell(cellId) { | |
| const cell = document.querySelector(`agentic-cell[id="${cellId}"]`); | |
| if (!cell) return; | |
| // Show loading state | |
| cell.setAttribute('status', 'loading'); | |
| // Simulate API call delay | |
| setTimeout(() => { | |
| // Update with mock response | |
| const randomSuccess = Math.random() > 0.1; // 90% success rate | |
| const timestamp = new Date().toISOString(); | |
| if (randomSuccess) { | |
| const agentType = cell.getAttribute('agent-type'); | |
| let output; | |
| if (agentType === 'researcher') { | |
| output = { | |
| type: 'markdown', | |
| content: '## Updated Research Results\n\nNew findings suggest quantum error correction is improving faster than expected.' | |
| }; | |
| } else if (agentType === 'analyst') { | |
| output = { | |
| type: 'markdown', | |
| content: '- Quantum error correction improving rapidly\n- New benchmarks show 2x improvement' | |
| }; | |
| } else if (agentType === 'data-visualizer') { | |
| output = { | |
| type: 'table', | |
| content: { | |
| headers: ['Metric', 'Improvement'], | |
| rows: [ | |
| ['Error Rate', '50% reduction'], | |
| ['Speed', '2x faster'], | |
| ['Stability', '3x more stable'] | |
| ] | |
| } | |
| }; | |
| } | |
| cell.setAttribute('output', JSON.stringify(output)); | |
| cell.setAttribute('status', 'success'); | |
| } else { | |
| cell.setAttribute('status', 'error'); | |
| } | |
| cell.setAttribute('timestamp', timestamp); | |
| }, 1500); | |
| } |