// MongoDB Initialization Script for Trading Bot
// This script creates collections and indexes for sentiment and document storage

// Switch to the trading_documents database
db = db.getSiblingDB('trading_documents');

// Create collections with validation schemas

// Sentiment Analysis Collection
db.createCollection('sentiment_analysis', {
  validator: {
    $jsonSchema: {
      bsonType: 'object',
      required: ['symbol', 'source', 'timestamp', 'sentiment_score'],
      properties: {
        symbol: {
          bsonType: 'string',
          description: 'Stock symbol (e.g., AAPL, GOOGL)'
        },
        source: {
          bsonType: 'string',
          description: 'Data source (news, social, earnings_call, etc.)'
        },
        timestamp: {
          bsonType: 'date',
          description: 'When the sentiment was recorded'
        },
        sentiment_score: {
          bsonType: 'double',
          minimum: -1.0,
          maximum: 1.0,
          description: 'Sentiment score between -1 (negative) and 1 (positive)'
        },
        confidence: {
          bsonType: 'double',
          minimum: 0.0,
          maximum: 1.0,
          description: 'Confidence level of the sentiment analysis'
        },
        text_snippet: {
          bsonType: 'string',
          description: 'Original text that was analyzed'
        },
        metadata: {
          bsonType: 'object',
          description: 'Additional metadata about the sentiment source'
        }
      }
    }
  }
});

// Raw Documents Collection (for news articles, social media posts, etc.)
db.createCollection('raw_documents', {
  validator: {
    $jsonSchema: {
      bsonType: 'object',
      required: ['source', 'document_type', 'timestamp', 'content'],
      properties: {
        source: {
          bsonType: 'string',
          description: 'Document source (news_api, twitter, reddit, etc.)'
        },
        document_type: {
          bsonType: 'string',
          enum: ['news_article', 'social_post', 'earnings_transcript', 'research_report', 'press_release'],
          description: 'Type of document'
        },
        timestamp: {
          bsonType: 'date',
          description: 'When the document was created/published'
        },
        symbols: {
          bsonType: 'array',
          items: {
            bsonType: 'string'
          },
          description: 'Array of stock symbols mentioned in the document'
        },
        title: {
          bsonType: 'string',
          description: 'Document title or headline'
        },
        content: {
          bsonType: 'string',
          description: 'Full document content'
        },
        url: {
          bsonType: 'string',
          description: 'Original URL of the document'
        },
        author: {
          bsonType: 'string',
          description: 'Document author or source account'
        },
        processed: {
          bsonType: 'bool',
          description: 'Whether this document has been processed for sentiment'
        },
        metadata: {
          bsonType: 'object',
          description: 'Additional document metadata'
        }
      }
    }
  }
});

// Market Events Collection (for significant market events and their impact)
db.createCollection('market_events', {
  validator: {
    $jsonSchema: {
      bsonType: 'object',
      required: ['event_type', 'timestamp', 'description'],
      properties: {
        event_type: {
          bsonType: 'string',
          enum: ['earnings', 'merger', 'acquisition', 'ipo', 'dividend', 'split', 'regulatory', 'economic_indicator'],
          description: 'Type of market event'
        },
        timestamp: {
          bsonType: 'date',
          description: 'When the event occurred or was announced'
        },
        symbols: {
          bsonType: 'array',
          items: {
            bsonType: 'string'
          },
          description: 'Stock symbols affected by this event'
        },
        description: {
          bsonType: 'string',
          description: 'Event description'
        },
        impact_score: {
          bsonType: 'double',
          minimum: -5.0,
          maximum: 5.0,
          description: 'Expected market impact score'
        },
        source_documents: {
          bsonType: 'array',
          items: {
            bsonType: 'objectId'
          },
          description: 'References to raw_documents that reported this event'
        }
      }
    }
  }
});

// Create indexes for efficient querying

// Sentiment Analysis indexes
db.sentiment_analysis.createIndex({ symbol: 1, timestamp: -1 });
db.sentiment_analysis.createIndex({ source: 1, timestamp: -1 });
db.sentiment_analysis.createIndex({ timestamp: -1 });
db.sentiment_analysis.createIndex({ symbol: 1, source: 1, timestamp: -1 });

// Raw Documents indexes
db.raw_documents.createIndex({ symbols: 1, timestamp: -1 });
db.raw_documents.createIndex({ source: 1, timestamp: -1 });
db.raw_documents.createIndex({ document_type: 1, timestamp: -1 });
db.raw_documents.createIndex({ processed: 1, timestamp: -1 });
db.raw_documents.createIndex({ timestamp: -1 });

// Market Events indexes
db.market_events.createIndex({ symbols: 1, timestamp: -1 });
db.market_events.createIndex({ event_type: 1, timestamp: -1 });
db.market_events.createIndex({ timestamp: -1 });

// Insert some sample data for testing

// Sample sentiment data
db.sentiment_analysis.insertMany([
  {
    symbol: 'AAPL',
    source: 'news_analysis',
    timestamp: new Date(),
    sentiment_score: 0.75,
    confidence: 0.89,
    text_snippet: 'Apple reports strong quarterly earnings...',
    metadata: {
      article_id: 'news_001',
      provider: 'financial_news_api'
    }
  },
  {
    symbol: 'GOOGL',
    source: 'social_media',
    timestamp: new Date(),
    sentiment_score: -0.25,
    confidence: 0.67,
    text_snippet: 'Concerns about Google AI regulation...',
    metadata: {
      platform: 'twitter',
      engagement_score: 450
    }
  }
]);

// Sample raw document
db.raw_documents.insertOne({
  source: 'financial_news_api',
  document_type: 'news_article',
  timestamp: new Date(),
  symbols: ['AAPL', 'MSFT'],
  title: 'Tech Giants Show Strong Q4 Performance',
  content: 'Apple and Microsoft both reported better than expected earnings for Q4...',
  url: 'https://example.com/tech-earnings-q4',
  author: 'Financial Reporter',
  processed: true,
  metadata: {
    word_count: 850,
    readability_score: 0.75
  }
});

// Sample market event
db.market_events.insertOne({
  event_type: 'earnings',
  timestamp: new Date(),
  symbols: ['AAPL'],
  description: 'Apple Q4 2024 Earnings Report',
  impact_score: 2.5,
  source_documents: []
});

print('MongoDB initialization completed successfully!');
print('Created collections: sentiment_analysis, raw_documents, market_events');
print('Created indexes for efficient querying');
print('Inserted sample data for testing');