Janady13/AI_Brain / daemon/seed_prophecy.cs

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Field	Recorded value
Source type	GitHub source
Original record	Janady13/AI_Brain / daemon/seed_prophecy.cs
Date	Not specified in source
Repository	Janady13/AI_Brain
Revision	6d0767aad08781eb5c4e1eb14a42ec92c437be78
Branch	copilot/convert-python-files-to-csharp
Path or archive member	daemon/seed_prophecy.cs
Original SHA-256	9ead73c293e6aa42e6b3f90661992909e3b4f4aa3ef105bb7cd6c8a7b4cb7808
Git blob SHA	f5ca02b93eb050684ad44ce719bee10ea0aaaa6a
Reading-copy SHA-256	9ead73c293e6aa42e6b3f90661992909e3b4f4aa3ef105bb7cd6c8a7b4cb7808

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// Generate 500 distinct prophecy module descriptions (forecasting modules)

using System;
using System.Collections.Generic;

namespace AIBrain.Daemon
{
    public static class SeedProphecy
    {
        public static IEnumerable<string> GenProphecy(int n)
        {
            var domains = new[]
            {
                "market volatility", "equity returns", "crypto price movement", "energy demand",
                "load forecasting", "weather extremes", "hurricane landfall", "wildfire risk",
                "epidemiology spread", "hospital admissions", "supply chain delays", "port congestion",
                "shipping times", "inventory replenishment", "customer churn", "lifetime value",
                "ad conversion", "marketing lift", "sales pipeline", "cash flow", "credit risk",
                "fraud detection", "cyber intrusion", "phishing campaigns", "patch urgency",
                "geopolitical risk", "election turnout", "policy passage", "legislative gridlock",
                "sports outcomes", "injury likelihood", "travel demand", "hotel occupancy",
                "traffic flow", "accident risk", "air quality index", "earthquake aftershocks",
                "product demand", "feature adoption", "release risk", "incident rate", "SLA breach",
                "compute capacity", "GPU queue time", "training time", "inference latency"
            };

            var methods = new[]
            {
                "Bayesian structural time series", "state-space model", "seasonal ARIMA",
                "prophet-style additive model", "Gaussian Process regression", "quantile regression",
                "gradient boosted trees", "random forest", "temporal convolution network",
                "transformer encoder", "graph temporal network", "survival analysis",
                "copula-based simulation", "Monte Carlo scenario generation", "change point detection",
                "extreme value theory", "hierarchical modeling", "spatio-temporal kriging"
            };

            var horizons = new[]
            {
                "nowcasting", "short-term (hours)", "near-term (days)", "mid-term (weeks)", "long-term (months)"
            };

            var constraints = new[]
            {
                "with uncertainty quantification", "with prediction intervals", "with conformal bands",
                "with causal adjustments", "with holidays and events", "with regime shifts",
                "with exogenous regressors", "with missing data imputation"
            };

            var seen = new HashSet<string>();
            int i = 0;

            foreach (var d in domains)
            {
                foreach (var m in methods)
                {
                    var phrase = $"Prophecy: {m} for {d}";
                    if (seen.Contains(phrase))
                        continue;

                    seen.Add(phrase);
                    yield return phrase;
                    i++;

                    if (i >= n)
                        yield break;
                }
            }

            if (i < n)
            {
                foreach (var d in domains)
                {
                    foreach (var h in horizons)
                    {
                        foreach (var c in constraints)
                        {
                            var phrase = $"Prophecy: {h} {d} {c}";
                            if (seen.Contains(phrase))
                                continue;

                            seen.Add(phrase);
                            yield return phrase;
                            i++;

                            if (i >= n)
                                yield break;
                        }
                    }
                }
            }
        }

        public static void Main(string[] args)
        {
            SeedCommon.RunSeed("prophecy", GenProphecy);
        }
    }
}