import { KnowledgeSource, ChatMessage, RetrievedChunk } from '../types'; export const mockSources: KnowledgeSource[] = [ { id: '1', type: 'pdf', title: 'Machine Learning Research Paper 2024', language: 'EN', status: 'completed', chunkCount: 127, dateAdded: new Date('2024-02-15'), lastProcessed: new Date('2024-02-15'), metadata: { pageCount: 42, }, }, { id: '2', type: 'pdf', title: 'भारतीय संविधान और मौलिक अधिकार', language: 'HI', status: 'completed', chunkCount: 89, dateAdded: new Date('2024-02-10'), lastProcessed: new Date('2024-02-10'), metadata: { pageCount: 28, }, }, { id: '3', type: 'web', title: 'Introduction to React Server Components', language: 'EN', status: 'completed', chunkCount: 45, dateAdded: new Date('2024-02-20'), lastProcessed: new Date('2024-02-20'), metadata: { url: 'https://react.dev/blog/2023/03/22/react-labs-what-we-have-been-working-on-march-2023', domain: 'react.dev', }, }, { id: '4', type: 'web', title: 'తెలుగు సాహిత్య చరిత్ర', language: 'TE', status: 'completed', chunkCount: 67, dateAdded: new Date('2024-02-18'), lastProcessed: new Date('2024-02-18'), metadata: { url: 'https://example.te/literature', domain: 'example.te', }, }, { id: '5', type: 'youtube', title: 'Understanding Transformer Architecture', language: 'EN', status: 'completed', chunkCount: 156, dateAdded: new Date('2024-02-22'), lastProcessed: new Date('2024-02-22'), metadata: { videoId: 'dQw4w9WgXcQ', thumbnail: 'https://images.unsplash.com/photo-1611162617474-5b21e879e113?w=400', duration: '45:32', }, }, { id: '6', type: 'youtube', title: 'Deep Learning Fundamentals', language: 'EN', status: 'processing', chunkCount: 0, dateAdded: new Date('2024-03-07'), metadata: { videoId: 'abc123xyz', thumbnail: 'https://images.unsplash.com/photo-1526374965328-7f61d4dc18c5?w=400', duration: '1:12:45', }, }, { id: '7', type: 'pdf', title: 'Quantum Computing Basics', language: 'EN', status: 'completed', chunkCount: 98, dateAdded: new Date('2024-02-25'), lastProcessed: new Date('2024-02-25'), metadata: { pageCount: 35, }, }, ]; export const mockRetrievedChunks: RetrievedChunk[] = [ { id: 'chunk-1', sourceId: '1', sourceName: 'Machine Learning Research Paper 2024', sourceType: 'pdf', language: 'EN', text: 'Transformers have revolutionized natural language processing by introducing self-attention mechanisms that allow models to weigh the importance of different words in a sentence regardless of their positional distance. This breakthrough has led to significant improvements in tasks such as machine translation, text summarization, and question answering.', similarityScore: 0.94, metadata: { page: 5, }, }, { id: 'chunk-2', sourceId: '5', sourceName: 'Understanding Transformer Architecture', sourceType: 'youtube', language: 'EN', text: 'The key innovation of the transformer architecture is the multi-head attention mechanism. Unlike RNNs which process sequences sequentially, transformers can process all tokens in parallel, making them much more efficient for training on modern hardware.', similarityScore: 0.89, metadata: { timestamp: '12:34', }, }, { id: 'chunk-3', sourceId: '3', sourceName: 'Introduction to React Server Components', sourceType: 'web', language: 'EN', text: 'React Server Components allow developers to build applications that span the server and client, combining the rich interactivity of client-side apps with the improved performance of traditional server rendering.', similarityScore: 0.76, metadata: { url: 'https://react.dev/blog', }, }, { id: 'chunk-4', sourceId: '1', sourceName: 'Machine Learning Research Paper 2024', sourceType: 'pdf', language: 'EN', text: 'Attention mechanisms compute a weighted sum of values based on the similarity between a query and a set of keys. This allows the model to focus on the most relevant parts of the input when making predictions.', similarityScore: 0.72, metadata: { page: 7, }, }, ]; export const mockChatHistory: ChatMessage[] = [ { id: 'msg-1', role: 'user', content: 'What are transformers and how do they work in machine learning?', timestamp: new Date('2024-03-07T10:30:00'), }, { id: 'msg-2', role: 'assistant', content: 'Transformers are a revolutionary neural network architecture that have transformed natural language processing. According to the research, transformers introduced self-attention mechanisms that allow models to weigh the importance of different words in a sentence regardless of their positional distance. This breakthrough has led to significant improvements in tasks such as machine translation, text summarization, and question answering.\n\nThe key innovation is the multi-head attention mechanism. Unlike RNNs which process sequences sequentially, transformers can process all tokens in parallel, making them much more efficient for training on modern hardware. Attention mechanisms compute a weighted sum of values based on the similarity between a query and a set of keys, allowing the model to focus on the most relevant parts of the input when making predictions.', timestamp: new Date('2024-03-07T10:30:15'), citations: [ { sourceTitle: 'Machine Learning Research Paper 2024', sourceType: 'pdf', reference: 'Page 5', snippet: 'Transformers have revolutionized natural language processing by introducing self-attention mechanisms...', }, { sourceTitle: 'Understanding Transformer Architecture', sourceType: 'youtube', reference: '12:34', snippet: 'The key innovation of the transformer architecture is the multi-head attention mechanism...', }, { sourceTitle: 'Machine Learning Research Paper 2024', sourceType: 'pdf', reference: 'Page 7', snippet: 'Attention mechanisms compute a weighted sum of values based on the similarity...', }, ], retrievedChunks: mockRetrievedChunks, }, ];