frontend/src/app/data/mockData.ts

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,
  },
];