/**
 * Pi provider plugin for Inception Labs (Mercury).
 *
 * Registers an OpenAI-compatible provider against
 * https://api.inceptionlabs.ai/v1 using `openai-completions`.
 * Models are discovered at startup from GET /v1/models, with a static
 * fallback so the provider still loads when the discovery call fails
 * (offline, rate limited, no key yet).
 *
 * Auth: `Authorization: Bearer $INCEPTION_API_KEY` via `authHeader: true`.
 *
 * Usage:
 *   export INCEPTION_API_KEY="..."
 *   pi -e /path/to/pi-inception-provider
 *   # then /model -> inception/mercury-2
 */

import type { ExtensionAPI, ProviderModelConfig } from "@earendil-works/pi-coding-agent";

const PROVIDER_ID = "inception";
const BASE_URL = "https://api.inceptionlabs.ai/v1";
const MODELS_URL = `${BASE_URL}/models`;

/**
 * Static fallback used when /v1/models can't be reached.
 * Values mirror the public /v1/models response for mercury-2.
 */
const FALLBACK_MODELS: ProviderModelConfig[] = [
  {
    id: "mercury-2",
    name: "Inception Mercury 2",
    reasoning: false,
    input: ["text"],
    cost: { input: 0.25, output: 0.75, cacheRead: 0.025, cacheWrite: 0 },
    contextWindow: 128000,
    maxTokens: 50000,
    compat: {
      supportsDeveloperRole: false,
      maxTokensField: "max_tokens",
      supportsStore: false,
    },
  },
];

interface InceptionPricing {
  prompt?: string;
  completion?: string;
  input_cache_reads?: string;
  input_cache_writes?: string;
}

interface InceptionModel {
  id: string;
  name?: string;
  context_length?: number;
  max_output_length?: number;
  input_modalities?: string[];
  output_modalities?: string[];
  supported_features?: string[];
  pricing?: InceptionPricing;
}

/** Convert a per-token USD string (e.g. "0.00000025") to $/million tokens. */
function perTokenToPerMillion(value: string | undefined): number {
  const n = Number(value);
  if (!Number.isFinite(n)) return 0;
  return Math.round(n * 1_000_000 * 1_000_000) / 1_000_000; // round to micro-cent precision
}

function mapModel(m: InceptionModel): ProviderModelConfig {
  const input: ("text" | "image")[] = (m.input_modalities ?? ["text"])
    .filter((x): x is "text" | "image" => x === "text" || x === "image");
  if (input.length === 0) input.push("text");

  const pricing = m.pricing ?? {};

  return {
    id: m.id,
    name: m.name ?? m.id,
    // Mercury is marketed as a reasoning-capable dLLM, but the chat completions
    // endpoint does not expose extended-thinking controls (no thinking/reasoning
    // params in the API), so we don't advertise pi reasoning levels.
    reasoning: false,
    input,
    cost: {
      input: perTokenToPerMillion(pricing.prompt),
      output: perTokenToPerMillion(pricing.completion),
      cacheRead: perTokenToPerMillion(pricing.input_cache_reads),
      cacheWrite: perTokenToPerMillion(pricing.input_cache_writes),
    },
    contextWindow: m.context_length ?? 128000,
    maxTokens: m.max_output_length ?? 32768,
    compat: {
      supportsDeveloperRole: false,
      maxTokensField: "max_tokens",
      supportsStore: false,
    },
  };
}

export async function discoverModels(): Promise<ProviderModelConfig[]> {
  const response = await fetch(MODELS_URL, {
    headers: { Accept: "application/json" },
  });
  if (!response.ok) {
    throw new Error(`${response.status} ${response.statusText}`);
  }
  const payload = (await response.json()) as { data?: InceptionModel[] };
  const models = payload.data ?? [];
  if (models.length === 0) {
    throw new Error("models endpoint returned no data");
  }
  return models.map(mapModel);
}

export default async function (pi: ExtensionAPI) {
  let models: ProviderModelConfig[];
  try {
    models = await discoverModels();
  } catch (error) {
    const detail = error instanceof Error ? error.message : String(error);
    console.warn(
      `[pi-inception-provider] dynamic model discovery failed (${detail}); using static fallback.`,
    );
    models = FALLBACK_MODELS;
  }

  pi.registerProvider(PROVIDER_ID, {
    name: "Inception Labs",
    baseUrl: BASE_URL,
    apiKey: "$INCEPTION_API_KEY",
    authHeader: true,
    api: "openai-completions",
    models,
  });
}