import type { ModelRosterConfig, Policy, PolicyCaps, PriceCatalog, PrivacyProfile, UltraConfig } from "../types.js";

export const ULTRAPI_VERSION = "1.0.0";
export const PI_VERSION = "0.84.1";
export const PI_AGENTS_VERSION = "0.13.2";
export const DEFAULT_ANALYTICS_RETENTION_DAYS = 365;

/**
 * Example rosters, not a policy. They are what a fresh install declares so that the
 * two reference setups work out of the box; any model id from any provider is
 * equally valid once it appears in `models.tiers`. Order is weakest to strongest.
 */
export const PRIVATE_MODELS = [
  "openai-codex/gpt-5.6-luna",
  "openai-codex/gpt-5.6-terra",
  "openai-codex/gpt-5.6-sol",
] as const;

export const FREE_ROLES = {
  scout: "opencode/big-pickle",
  normal: "opencode/deepseek-v4-flash-free",
  deep: "opencode/deepseek-v4-flash-free",
} as const;

export const FREE_MODELS = [...new Set(Object.values(FREE_ROLES))] as readonly string[];

export const DEFAULT_ROSTERS: Record<PrivacyProfile, ModelRosterConfig> = {
  private: { tiers: [...PRIVATE_MODELS] },
  free: { tiers: [...FREE_MODELS], nonCritical: [FREE_ROLES.scout] },
};

export function defaultRosterConfig(profile: PrivacyProfile): ModelRosterConfig {
  return structuredClone(DEFAULT_ROSTERS[profile]);
}

/**
 * The rate used to price a model the catalogue does not name, from what the provider charges for it.
 *
 * 125 is the highest credits-per-USD among the three models the shipped catalogue prices (luna 125,
 * terra 31.25, sol 25 — the catalogue is a capability-rank curve pinned to luna's dollar price, not
 * a dollar scale). Taking the highest is the conservative direction both ways this number is used:
 * a larger credit charge per dollar means the budget bites sooner, and a smaller USD ceiling comes
 * back out of `usdBudgetForCredits`. It is also the only value that keeps those two inverse — for a
 * purely derived roster `usdBudgetForCredits` returns exactly `credits / 125`, so the ceiling a
 * delegated run is handed and the charge it is billed cannot drift apart.
 */
export const DEFAULT_CREDITS_PER_USD = 125;

export const DEFAULT_PRICE_CATALOG: PriceCatalog = {
  version: "2026-08-09",
  currency: "credits",
  creditsPerUsd: DEFAULT_CREDITS_PER_USD,
  models: {
    "openai-codex/gpt-5.6-luna": { input: 25, cached: 2.5, output: 150 },
    "openai-codex/gpt-5.6-terra": { input: 62.5, cached: 6.25, output: 375 },
    "openai-codex/gpt-5.6-sol": { input: 125, cached: 12.5, output: 750 },
    // Declared zero, not unknown. The registry reports all-zero both for a model that is genuinely
    // free and for one whose provider declared no cost at all, and cannot tell them apart — so a
    // free price has to be written down here for it to be believed.
    [FREE_ROLES.scout]: { input: 0, cached: 0, output: 0 },
    [FREE_ROLES.normal]: { input: 0, cached: 0, output: 0 },
  },
};

export const POLICY_CAPS: Record<Policy, PolicyCaps> = {
  economy: { softCap: 4, internalStopTarget: 7, hardCap: 8, maxRepairCycles: 1, initialScouts: 1, maxParallel: 2, maxTotal: 4, maxWaves: 1 },
  balanced: { softCap: 10, internalStopTarget: 17, hardCap: 20, maxRepairCycles: 2, initialScouts: 2, maxParallel: 4, maxTotal: 8, maxWaves: 2 },
  quality: { softCap: 25, internalStopTarget: 43, hardCap: 50, maxRepairCycles: 3, initialScouts: 3, maxParallel: 6, maxTotal: 12, maxWaves: 2 },
  max: { softCap: 60, internalStopTarget: 100, hardCap: 120, maxRepairCycles: 4, initialScouts: 3, maxParallel: 8, maxTotal: 16, maxWaves: 3 },
};

export function defaultConfig(profile: UltraConfig["profile"] = "private"): UltraConfig {
  const free = profile === "free";
  return {
    schemaVersion: 1,
    configVersion: ULTRAPI_VERSION,
    policyVersion: ULTRAPI_VERSION,
    profile,
    mode: "auto",
    policy: "balanced",
    budgets: { acknowledged: false },
    models: defaultRosterConfig(profile),
    root: { model: free ? "opencode/deepseek-v4-flash-free" : "openai-codex/gpt-5.6-terra", thinking: "medium" },
    scout: { model: free ? "opencode/big-pickle" : "openai-codex/gpt-5.6-luna", thinking: "low", initial: 2, maxParallel: free ? 2 : 4, maxTotal: 8, maxTurns: 8, maxOutputTokens: 800 },
    boundedWriter: { model: free ? "opencode/deepseek-v4-flash-free" : "openai-codex/gpt-5.6-luna", thinking: "high", maxTurns: 20, maxOutputTokens: 1000 },
    repair: { model: free ? "opencode/deepseek-v4-flash-free" : "openai-codex/gpt-5.6-luna", thinking: "high", maxAttempts: 2, sameFingerprintEscalation: true },
    deep: { model: free ? "opencode/deepseek-v4-flash-free" : "openai-codex/gpt-5.6-sol", thinking: "high", maxTurns: 50 },
    arbitration: { model: free ? "opencode/deepseek-v4-flash-free" : "openai-codex/gpt-5.6-sol", thinking: "xhigh", maxTurns: 20 },
    warRoom: { autoEnabled: false, maxSpecialists: 2, maxRounds: 2, maxMessagesPerMember: 4 },
    piAgentsBudgets: { maxAgents: 8, maxParallelism: free ? 2 : 4, maxIterations: 2, maxDepth: 1, maxTurns: 30 },
    context: { envelopeTargetTokens: 5000, envelopeHardCapTokens: 8000, compactAtRatio: 0.68, blockWideSwarmAtRatio: 0.75 },
    telemetry: { rawVaultEnabled: true, rawRetentionDays: 30, analyticsRetentionDays: DEFAULT_ANALYTICS_RETENTION_DAYS },
    experiment: { challengerAllocation: 0.1, stopLossSuccessDrop: 0.05, stopLossCostIncrease: 0.2 },
    compatibility: { piVersion: PI_VERSION, piAgentsVersion: PI_AGENTS_VERSION },
  };
}