phase 14-15: docker build validation and helm deployment
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-- Stonks Oracle - Model Performance Metrics
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-- Tracks extraction success/failure rates, latency, retries, confidence,
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-- token usage estimates, and validation error distributions.
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-- Requirements: 5.2, 5.4, 12.1, 12.2
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CREATE TABLE model_performance_metrics (
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id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
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document_id UUID REFERENCES documents(id) ON DELETE SET NULL,
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ticker VARCHAR(20),
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model_name VARCHAR(200) NOT NULL,
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prompt_version VARCHAR(100),
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schema_version VARCHAR(50),
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success BOOLEAN NOT NULL,
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attempt_count INTEGER NOT NULL DEFAULT 1,
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total_duration_ms INTEGER NOT NULL DEFAULT 0,
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first_attempt_duration_ms INTEGER DEFAULT 0,
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final_attempt_duration_ms INTEGER DEFAULT 0,
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confidence FLOAT DEFAULT 0.0,
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validation_status VARCHAR(50) NOT NULL DEFAULT 'unknown',
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validation_error_count INTEGER DEFAULT 0,
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validation_warning_count INTEGER DEFAULT 0,
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validation_errors JSONB DEFAULT '[]',
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retry_count INTEGER DEFAULT 0,
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input_token_estimate INTEGER DEFAULT 0,
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output_token_estimate INTEGER DEFAULT 0,
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company_count INTEGER DEFAULT 0,
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recorded_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
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);
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-- Query by time range (dashboard primary access pattern)
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CREATE INDEX idx_model_perf_recorded ON model_performance_metrics(recorded_at DESC);
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-- Filter by model for per-model dashboards
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CREATE INDEX idx_model_perf_model ON model_performance_metrics(model_name, recorded_at DESC);
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-- Filter by success for failure analysis
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CREATE INDEX idx_model_perf_success ON model_performance_metrics(success, recorded_at DESC);
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-- Filter by validation status for schema failure dashboards
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CREATE INDEX idx_model_perf_validation ON model_performance_metrics(validation_status);
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