rckrdmrd
45e77e9a9c
DDL schemas for Trading Platform: - User management - Authentication - Payments - Education - ML predictions - Trading data Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
83 lines
3.4 KiB
SQL
83 lines
3.4 KiB
SQL
-- =====================================================
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-- LLM SCHEMA - USER MEMORY TABLE
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-- =====================================================
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-- Description: Persistent memory about users for personalization
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-- Schema: llm
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-- Author: Database Agent
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-- Date: 2025-12-06
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-- =====================================================
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CREATE TABLE llm.user_memory (
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id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
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user_id UUID NOT NULL REFERENCES auth.users(id) ON DELETE CASCADE,
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-- Tipo de memoria
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memory_type llm.memory_type NOT NULL,
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-- Contenido
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key VARCHAR(200) NOT NULL,
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value TEXT NOT NULL,
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-- Importancia
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importance_score DECIMAL(3,2) DEFAULT 0.50 CHECK (importance_score >= 0.00 AND importance_score <= 1.00),
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-- Fuente
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source_conversation_id UUID REFERENCES llm.conversations(id) ON DELETE SET NULL,
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extracted_from TEXT, -- Fragmento del que se extrajo la memoria
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extraction_method VARCHAR(50) DEFAULT 'llm', -- llm, manual, system
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-- Validez
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is_active BOOLEAN DEFAULT true,
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expires_at TIMESTAMPTZ,
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-- Confirmación (algunas memorias pueden requerir confirmación del usuario)
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requires_confirmation BOOLEAN DEFAULT false,
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confirmed_by_user BOOLEAN DEFAULT false,
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confirmed_at TIMESTAMPTZ,
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-- Metadata
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metadata JSONB,
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created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
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updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
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-- Constraints
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CONSTRAINT unique_user_memory_key UNIQUE(user_id, memory_type, key)
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);
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-- Índices
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CREATE INDEX idx_memory_user ON llm.user_memory(user_id);
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CREATE INDEX idx_memory_type ON llm.user_memory(memory_type);
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CREATE INDEX idx_memory_active ON llm.user_memory(is_active) WHERE is_active = true;
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CREATE INDEX idx_memory_importance ON llm.user_memory(importance_score DESC);
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CREATE INDEX idx_memory_conversation ON llm.user_memory(source_conversation_id);
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CREATE INDEX idx_memory_expires ON llm.user_memory(expires_at) WHERE expires_at IS NOT NULL;
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-- Comentarios
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COMMENT ON TABLE llm.user_memory IS 'Persistent memory about users for LLM personalization and context';
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COMMENT ON COLUMN llm.user_memory.memory_type IS 'Type of memory: fact, preference, context, goal, or constraint';
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COMMENT ON COLUMN llm.user_memory.key IS 'Memory identifier (e.g., "favorite_symbol", "trading_goal", "risk_limit")';
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COMMENT ON COLUMN llm.user_memory.value IS 'Memory content (e.g., "BTCUSDT", "save for house", "max 5% per trade")';
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COMMENT ON COLUMN llm.user_memory.importance_score IS 'Importance weight (0.00-1.00) for retrieval prioritization';
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COMMENT ON COLUMN llm.user_memory.extracted_from IS 'Original text from which memory was extracted';
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COMMENT ON COLUMN llm.user_memory.requires_confirmation IS 'Whether this memory needs explicit user confirmation';
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-- Ejemplos de memorias por tipo:
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COMMENT ON COLUMN llm.user_memory.memory_type IS
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'Memory type examples:
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- fact: "trading_since" = "2020", "max_loss_experienced" = "15%"
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- preference: "favorite_indicator" = "RSI", "avoids_margin_trading" = "true"
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- context: "recent_portfolio_loss" = "trying to recover", "learning_focus" = "risk management"
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- goal: "monthly_target" = "5% return", "learning_goal" = "master technical analysis"
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- constraint: "max_risk_per_trade" = "2%", "no_trading_during_work" = "9am-5pm"';
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-- Ejemplo de metadata JSONB:
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COMMENT ON COLUMN llm.user_memory.metadata IS
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'Example: {
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"confidence": 0.85,
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"last_mentioned": "2025-12-05T10:30:00Z",
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"mention_count": 5,
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"related_memories": ["mem_123", "mem_456"],
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"tags": ["trading_style", "risk_management"]
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}';
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