scripts/generate-model-data.mjs

import fs from "node:fs";
import path from "node:path";

const root = path.resolve(import.meta.dirname, "..");
const outputPath = path.join(root, "assets", "local-frontier-model-data.js");
const threshold = 100_000;
const hfBase = "https://huggingface.co";
const apiBase = `${hfBase}/api/models`;
const routerModelsApi = "https://router.huggingface.co/v1/models";
const requestHeaders = {
  "user-agent": "local-frontier-model-generator",
  ...(process.env.HF_TOKEN
    ? { authorization: `Bearer ${process.env.HF_TOKEN}` }
    : {}),
};
const cache = new Map();

const defaultCreators = [
  "CohereLabs",
  "EssentialAI",
  "MiniMaxAI",
  "Qwen",
  "Sao10K",
  "aisingapore",
  "allenai",
  "alpindale",
  "baidu",
  "deepcogito",
  "deepseek-ai",
  "google",
  "inclusionAI",
  "meta-llama",
  "moonshotai",
  "nvidia",
  "openai",
  "pearl-ai",
  "stepfun-ai",
  "swiss-ai",
  "utter-project",
  "zai-org",
];

const expandFields = [
  "author",
  "cardData",
  "createdAt",
  "downloads",
  "downloadsAllTime",
  "evalResults",
  "gated",
  "gguf",
  "inferenceProviderMapping",
  "lastModified",
  "library_name",
  "likes",
  "model-index",
  "pipeline_tag",
  "private",
  "safetensors",
  "sha",
  "siblings",
  "tags",
  "transformersInfo",
  "trendingScore",
];

const llmPipelines = new Set([
  "text-generation",
  "image-text-to-text",
  "video-text-to-text",
  "audio-text-to-text",
  "any-to-any",
  "text-to-audio",
]);

const excludedPipelines = new Set([
  "feature-extraction",
  "sentence-similarity",
  "text-ranking",
  "text-classification",
  "token-classification",
  "fill-mask",
  "automatic-speech-recognition",
  "text-to-speech",
  "voice-activity-detection",
  "image-classification",
  "image-segmentation",
  "object-detection",
  "zero-shot-image-classification",
  "zero-shot-object-detection",
  "image-text-to-image",
  "text-to-image",
  "image-to-image",
  "image-to-video",
  "text-to-video",
  "unconditional-image-generation",
  "image-to-3d",
  "text-to-3d",
  "robotics",
  "time-series-forecasting",
  "graph-ml",
]);

const textModelTerms = [
  "instruct",
  "chat",
  "assistant",
  "reasoning",
  "thinking",
  "coder",
  "code",
  "llm",
  "vlm",
  "omni",
  "gpt-oss",
  "kimi",
  "glm",
  "llama",
  "qwen",
  "gemma",
  "deepseek",
  "nemotron",
  "olmo",
  "apertus",
  "eurollm",
];

const excludedTerms = [
  "embedding",
  "embed",
  "reranker",
  "rerank",
  "whisper",
  "wav2vec",
  "speaker",
  "stable-diffusion",
  "diffusers",
  "flux",
  "sdxl",
  "clip",
  "siglip",
  "depth-anything",
  "ocr",
  "optical-character-recognition",
  "document-parse",
  "document-parser",
  "document-understanding",
  "pdf-parser",
  "receipt",
];

const excludedTokenTerms = new Set(["asr", "encoder"]);
const excludedAudioTokenTerms = new Set(["speech"]);
const globalArtifactSearchQueries = [
  "gguf",
  "awq",
  "gptq",
  "fp8",
  "fp4",
  "nvfp4",
  "quantized",
  "mlx",
  "llama.cpp",
];
const relatedArtifactSuffixes = [
  "gguf",
  "awq",
  "gptq",
  "fp8",
  "fp4",
  "nvfp4",
  "mlx",
];
const relatedVariantTokens = new Set([
  "base",
  "chat",
  "flash",
  "instruct",
  "it",
  "pro",
]);
const modelFamilyTokens = new Set([
  "apertus",
  "deepseek",
  "ernie",
  "gemma",
  "glm",
  "gpt",
  "kimi",
  "llama",
  "minimax",
  "mistral",
  "mixtral",
  "nemotron",
  "olmo",
  "phi",
  "qwen",
  "qwen2",
  "qwen3",
  "step",
]);
const codingModelNameRe =
  /(^|[-_/])(?:coder|coding|code)(?:$|[-_/])|(^|[-_/])(?:codellama|codeqwen|opencoder|starcoder)[a-z0-9.]*($|[-_/])/;

const assumptions = {
  default_overhead_gb: 8,
  default_l_alloc_tokens: 100000,
  default_l_read_tokens: 32000,
  default_r_star_toks: 20,
  default_rho: 1,
  unit: "decimal GB",
  hf_pipeline_filter:
    "leaderboard-compatible LLM and multimodal candidate filter",
  hf_llm_pipeline_tags: [...llmPipelines],
  min_hf_downloads: threshold,
  generated_by: "scripts/generate-model-data.mjs",
};

function sleep(ms) {
  return new Promise((resolve) => setTimeout(resolve, ms));
}

async function fetchJson(url, optional = false) {
  const { payload } = await fetchJsonWithHeaders(url, optional);
  return payload;
}

async function fetchJsonWithHeaders(url, optional = false) {
  for (let attempt = 1; attempt <= 3; attempt++) {
    const response = await fetch(url, { headers: requestHeaders });
    if (response.ok) {
      return { payload: await response.json(), headers: response.headers };
    }
    if (optional && [401, 403, 404].includes(response.status)) {
      return { payload: null, headers: response.headers };
    }
    if (response.status === 429 || response.status >= 500) {
      await sleep(500 * attempt);
      continue;
    }
    throw new Error(`${response.status} ${response.statusText}: ${url}`);
  }
  if (optional) return { payload: null, headers: new Headers() };
  throw new Error(`failed after retries: ${url}`);
}

function parseNextLink(link) {
  if (!link) return null;
  for (const part of link.split(",")) {
    const match = part.match(/<([^>]+)>;\s*rel="next"/);
    if (match) return match[1];
  }
  return null;
}

function apiUrl(params) {
  const search = new URLSearchParams();
  for (const [key, value] of params) {
    search.append(key, String(value));
  }
  return `${apiBase}?${search}`;
}

function detailApiUrl(id) {
  const search = new URLSearchParams();
  for (const field of expandFields) search.append("expand", field);
  return `${apiBase}/${encodeURIComponent(id).replace(/%2F/g, "/")}?${search}`;
}

async function modelInfo(id) {
  const key = `model:${id}`;
  if (!cache.has(key)) {
    cache.set(key, fetchJson(detailApiUrl(id), true));
  }
  return cache.get(key);
}

async function rawConfig(id) {
  const key = `config:${id}`;
  if (!cache.has(key)) {
    cache.set(
      key,
      fetchJson(`${hfBase}/${id}/raw/main/config.json`, true).catch(() => null),
    );
  }
  return cache.get(key);
}

function uniquePreserveOrder(values) {
  const seen = new Set();
  const result = [];
  for (const value of values) {
    if (!value || seen.has(value)) continue;
    seen.add(value);
    result.push(value);
  }
  return result;
}

function repoIdFrom(model) {
  const id = model?.id || model?.modelId;
  return typeof id === "string" ? id : "";
}

function downloadCount(model) {
  return Number.isInteger(model?.downloads) ? model.downloads : 0;
}

async function fetchRouterModels() {
  try {
    const payload = await fetchJson(routerModelsApi, true);
    const records = payload && Array.isArray(payload.data) ? payload.data : [];
    return records.filter(
      (record) => record && typeof record.id === "string" && record.id,
    );
  } catch (error) {
    console.error(`router model fetch failed: ${error.message}`);
    return [];
  }
}

function routerCreators(routerRecords) {
  return uniquePreserveOrder(
    routerRecords.map((record) => {
      if (typeof record.owned_by === "string" && record.owned_by) {
        return record.owned_by;
      }
      return record.id?.includes("/") ? record.id.split("/", 1)[0] : "";
    }),
  );
}

async function listCreatorModels(creator) {
  const params = [
    ["author", creator],
    ["limit", 100],
    ["sort", "downloads"],
    ["direction", -1],
    ...expandFields.map((field) => ["expand", field]),
  ];
  let url = apiUrl(params);
  const rows = [];
  while (url) {
    const { payload, headers } = await fetchJsonWithHeaders(url);
    if (!Array.isArray(payload)) {
      throw new Error(`expected model list for creator ${creator}`);
    }
    rows.push(...payload.filter((item) => item && typeof item === "object"));
    const minDownloads = Math.min(
      ...payload.map((model) => downloadCount(model)),
    );
    if (payload.length === 0 || minDownloads < threshold) break;
    url = parseNextLink(headers.get("link"));
  }
  return rows;
}

async function listSearchModels(query) {
  const params = [
    ["search", query],
    ["limit", 100],
    ["sort", "downloads"],
    ["direction", -1],
    ...expandFields.map((field) => ["expand", field]),
  ];
  let url = apiUrl(params);
  const rows = [];
  while (url && rows.length < 500) {
    const { payload, headers } = await fetchJsonWithHeaders(url);
    if (!Array.isArray(payload)) {
      throw new Error(`expected model list for search ${query}`);
    }
    let stop = false;
    for (const item of payload) {
      if (!item || typeof item !== "object") continue;
      if (downloadCount(item) < threshold) {
        stop = true;
        break;
      }
      rows.push(item);
      if (rows.length >= 500) break;
    }
    if (stop || rows.length >= 500) break;
    url = parseNextLink(headers.get("link"));
  }
  return rows;
}

function fileCounts(record) {
  const counts = new Map();
  for (const sibling of record.siblings || []) {
    const name = sibling?.rfilename;
    if (typeof name !== "string") continue;
    const lower = name.toLowerCase();
    for (const [key, suffix] of [
      ["safetensors", ".safetensors"],
      ["gguf", ".gguf"],
      ["bin", ".bin"],
    ]) {
      if (lower.endsWith(suffix)) {
        counts.set(key, (counts.get(key) || 0) + 1);
      }
    }
    if (
      lower.endsWith("tokenizer.json") ||
      lower.endsWith("tokenizer_config.json")
    ) {
      counts.set("tokenizer", (counts.get("tokenizer") || 0) + 1);
    }
    if (lower.endsWith("chat_template.jinja")) {
      counts.set("chat_template", (counts.get("chat_template") || 0) + 1);
    }
  }
  return counts;
}

function providerSummary(mapping) {
  const rows = Array.isArray(mapping) ? mapping : [];
  let supportsTools = false;
  let supportsStructured = false;
  for (const item of rows) {
    if (!item || typeof item !== "object") continue;
    supportsTools = supportsTools || item.features?.toolCalling === true;
    supportsStructured =
      supportsStructured || item.features?.structuredOutput === true;
  }
  return { supportsTools, supportsStructured };
}

function routerSummary(routerEntry) {
  const providers = Array.isArray(routerEntry?.providers)
    ? routerEntry.providers
    : [];
  return {
    routerServed: Boolean(routerEntry),
    supportsTools: providers.some((provider) => provider?.supports_tools),
    supportsStructured: providers.some(
      (provider) => provider?.supports_structured_output,
    ),
  };
}

function textTokens(text) {
  return new Set(
    text
      .toLowerCase()
      .split(/[^a-z0-9]+/)
      .filter(Boolean),
  );
}

function hasExcludedTerm(row) {
  const text = `${row.id} ${row.pipeline_tag} ${row.tags}`.toLowerCase();
  if (excludedTerms.some((term) => text.includes(term))) return true;
  const tokens = textTokens(text);
  if ([...excludedTokenTerms].some((token) => tokens.has(token))) return true;
  if (
    !llmPipelines.has(row.pipeline_tag) &&
    [...excludedAudioTokenTerms].some((token) => tokens.has(token))
  ) {
    return true;
  }
  return false;
}

function hasTextModelSignal(modelId) {
  if (codingModelNameRe.test(modelId)) return true;
  const boundaryTerms = new Set([
    "assistant",
    "chat",
    "code",
    "coder",
    "coding",
    "instruct",
    "reasoning",
    "thinking",
  ]);
  for (const term of textModelTerms) {
    if (boundaryTerms.has(term)) {
      const boundaryRe = new RegExp(`(^|[-_/])${term}($|[-_/])`);
      if (boundaryRe.test(modelId)) return true;
      continue;
    }
    if (modelId.includes(term)) return true;
  }
  return false;
}

function normalizeCandidateRecord(record, routerEntry = null) {
  const counts = fileCounts(record);
  const provider = providerSummary(record.inferenceProviderMapping);
  const router = routerSummary(routerEntry);
  const id = repoIdFrom(record);
  const tags = asArray(record.tags).filter((tag) => typeof tag === "string");
  return {
    id,
    downloads: downloadCount(record),
    pipeline_tag: record.pipeline_tag || "",
    private: record.private,
    tags: tags.join(","),
    has_chat_template: counts.get("chat_template") > 0,
    supports_tools_any: provider.supportsTools,
    supports_structured_output_any: provider.supportsStructured,
    router_supports_tools_any: router.supportsTools,
    router_supports_structured_output_any: router.supportsStructured,
    router_served: router.routerServed,
  };
}

function candidateDecision(row) {
  const modelId = row.id.toLowerCase();
  const text = `${row.id} ${row.pipeline_tag} ${row.tags}`.toLowerCase();
  if (row.private === true) return [false, "private"];
  if (excludedPipelines.has(row.pipeline_tag)) {
    return [false, `excluded pipeline: ${row.pipeline_tag}`];
  }
  if (hasExcludedTerm(row)) return [false, "excluded narrow/non-LLM term"];
  if (llmPipelines.has(row.pipeline_tag)) {
    return [true, `LLM pipeline: ${row.pipeline_tag}`];
  }
  if (row.has_chat_template) return [true, "chat template"];
  if (row.supports_tools_any || row.router_supports_tools_any) {
    return [true, "tool support"];
  }
  if (
    row.supports_structured_output_any ||
    row.router_supports_structured_output_any
  ) {
    return [true, "structured output support"];
  }
  if (text.includes("conversational")) return [true, "conversational tag"];
  if (hasTextModelSignal(modelId)) return [true, "model-name signal"];
  return [false, "no LLM signal"];
}

function normalizedRepoSlug(modelId) {
  return modelId
    .split("/")
    .at(-1)
    .toLowerCase()
    .replace(/[^a-z0-9]+/g, "-")
    .replace(/^-|-$/g, "");
}

function slugTokens(slug) {
  return slug.split("-").filter(Boolean);
}

function hasModelShape(slug) {
  const tokens = slugTokens(slug);
  return tokens.some((token) => modelFamilyTokens.has(token));
}

function slugDedupeKey(modelId) {
  let slug = normalizedRepoSlug(modelId);
  let previous = null;
  while (slug && slug !== previous) {
    previous = slug;
    slug = slug.replace(/-(?:gguf|awq|gptq|fp8|fp4|mxfp8|nvfp4)-v[0-9]+$/, "");
    slug = slug.replace(
      /-(?:gguf|awq|gptq|fp8|fp4|mxfp8|nvfp4|bf16|fp16|int2|int3|int4|int8|q[2-8](?:-(?:0|1|k|m|s|l))*|4bit|8bit|bnb|bitsandbytes|mlx|exl2|onnx|openvino|tensorrt|modelopt|qat|quantized|quant|compressed|safetensors|hf)$/,
      "",
    );
    slug = slug.replace(/-qat-w[0-9]+a[0-9]+-ct$/, "");
  }
  return slug || normalizedRepoSlug(modelId);
}

function shortenedVariantSlug(slug) {
  const tokens = slugTokens(slug);
  while (tokens.length > 2 && relatedVariantTokens.has(tokens.at(-1))) {
    tokens.pop();
  }
  return tokens.join("-");
}

function discoveryQueries(seedRows) {
  const queries = [...globalArtifactSearchQueries];
  const ordered = [...seedRows].sort(
    (a, b) => b.downloads - a.downloads || a.id.localeCompare(b.id),
  );
  for (const row of ordered.slice(0, 12)) {
    const slug = slugDedupeKey(row.id);
    if (!hasModelShape(slug)) continue;
    for (const candidateSlug of uniquePreserveOrder([
      slug,
      shortenedVariantSlug(slug),
    ])) {
      if (!candidateSlug || !hasModelShape(candidateSlug)) continue;
      for (const suffix of relatedArtifactSuffixes) {
        queries.push(`${candidateSlug}-${suffix}`);
      }
    }
  }
  return uniquePreserveOrder(queries);
}

async function discoverAdditionalModels(seedRows, existingIds) {
  const discovered = new Map();
  for (const query of discoveryQueries(seedRows)) {
    try {
      const rows = await listSearchModels(query);
      console.error(`discovery ${query}: ${rows.length}`);
      for (const row of rows) {
        const id = repoIdFrom(row);
        if (!id || existingIds.has(id)) continue;
        discovered.set(id, row);
      }
    } catch (error) {
      console.error(`discovery ${query} failed: ${error.message}`);
    }
  }
  return [...discovered.values()];
}

async function downloadedModels() {
  const routerRecords = await fetchRouterModels();
  const routerById = new Map(
    routerRecords.map((record) => [record.id, record]),
  );
  const creators = uniquePreserveOrder([
    ...defaultCreators,
    ...routerCreators(routerRecords),
  ]);
  const deduped = new Map();
  for (const creator of creators) {
    try {
      const rows = await listCreatorModels(creator);
      console.error(`creator ${creator}: ${rows.length}`);
      for (const row of rows) {
        const id = repoIdFrom(row);
        if (id) deduped.set(id, row);
      }
    } catch (error) {
      console.error(`creator ${creator} failed: ${error.message}`);
    }
  }
  for (const record of routerRecords) {
    if (deduped.has(record.id)) continue;
    const detail = await modelInfo(record.id);
    if (detail) deduped.set(record.id, detail);
  }
  const seedRows = [...deduped.values()]
    .map((row) =>
      normalizeCandidateRecord(row, routerById.get(repoIdFrom(row))),
    )
    .filter((row) => row.downloads >= threshold && candidateDecision(row)[0]);
  const discoveredRows = await discoverAdditionalModels(
    seedRows,
    new Set(deduped.keys()),
  );
  for (const row of discoveredRows) {
    const id = repoIdFrom(row);
    if (id) deduped.set(id, row);
  }
  return [...deduped.values()].filter((model) => {
    if (downloadCount(model) < threshold) return false;
    const row = normalizeCandidateRecord(
      model,
      routerById.get(repoIdFrom(model)),
    );
    return candidateDecision(row)[0];
  });
}

function asArray(value) {
  if (Array.isArray(value)) return value;
  return value === undefined || value === null ? [] : [value];
}

function licenseFrom(model) {
  return (
    model.cardData?.license ||
    model.tags?.find((tag) => tag.startsWith("license:"))?.slice(8) ||
    "unknown"
  );
}

function baseModelIds(model) {
  const ids = new Set();
  for (const value of asArray(model.cardData?.base_model)) {
    if (typeof value === "string" && value.includes("/")) ids.add(value);
  }
  for (const tag of model.tags || []) {
    if (!tag.startsWith("base_model:")) continue;
    const parts = tag.split(":");
    const id = parts.at(-1);
    if (id?.includes("/")) ids.add(id);
  }
  return [...ids].filter((id) => id !== model.id);
}

function numberFrom(...values) {
  for (const value of values) {
    const number = Number(value);
    if (Number.isFinite(number) && number > 0) return number;
  }
  return null;
}

function intFrom(...values) {
  const number = numberFrom(...values);
  return number === null ? null : Math.trunc(number);
}

function parseParamB(text) {
  const normalized = text.replace(/_/g, "-");
  const moe = normalized.match(
    /(?:^|[-/])(\d+(?:\.\d+)?)x(\d+(?:\.\d+)?)([bm])(?:$|[-/])/i,
  );
  if (moe) {
    const count = Number(moe[1]);
    const size = Number(moe[2]);
    return count * size * (moe[3].toLowerCase() === "m" ? 0.001 : 1);
  }
  const match = normalized.match(/(?:^|[-/])(\d+(?:\.\d+)?)([bm])(?:$|[-/])/i);
  if (!match) return null;
  return Number(match[1]) * (match[2].toLowerCase() === "m" ? 0.001 : 1);
}

function parseActiveParamB(text) {
  const match = text.match(/(?:^|[-_/])A(\d+(?:\.\d+)?)([BM])(?:$|[-_/])/);
  if (!match) return null;
  return Number(match[1]) * (match[2] === "M" ? 0.001 : 1);
}

function round(value, digits = 6) {
  return Number(value.toFixed(digits));
}

function paramCountB(model, baseInfo, id) {
  const totals = [
    model.safetensors?.total,
    baseInfo?.safetensors?.total,
    model.safetensors?.parameters?.F16,
    model.safetensors?.parameters?.BF16,
    model.safetensors?.parameters?.F32,
  ].filter((value) => Number.isFinite(value) && value > 0);
  if (totals.length) return round(Math.max(...totals) / 1e9, 4);
  const parsed = parseParamB(id) ?? parseParamB(baseInfo?.id ?? "");
  return round(parsed && parsed > 0 ? parsed : 0.1, 4);
}

function quantizationBits(config, model) {
  const quant = config?.quantization_config;
  const explicitBits = numberFrom(quant?.bits, quant?.nbits, quant?.num_bits);
  if (explicitBits) return explicitBits;
  const groupBits = Object.values(quant?.config_groups || {})
    .map((group) => numberFrom(group?.weights?.num_bits, group?.num_bits))
    .filter(Boolean);
  if (groupBits.length) return Math.min(...groupBits);
  const haystack = `${model.id} ${(model.tags || []).join(" ")}`.toLowerCase();
  if (haystack.includes("2-bit") || haystack.includes("q2")) return 2;
  if (
    haystack.includes("4-bit") ||
    haystack.includes("q4") ||
    haystack.includes("int4") ||
    haystack.includes("gptq") ||
    haystack.includes("awq") ||
    haystack.includes("mxfp4") ||
    haystack.includes("nvfp4") ||
    haystack.includes("fp4")
  ) {
    return 4;
  }
  if (
    haystack.includes("8-bit") ||
    haystack.includes("int8") ||
    haystack.includes("fp8") ||
    haystack.includes("q8")
  ) {
    return 8;
  }
  return null;
}

function dtypeBytes(model) {
  const parameters = model.safetensors?.parameters || {};
  const weighted = Object.entries(parameters)
    .map(([dtype, count]) => {
      const key = dtype.toUpperCase();
      const bytes =
        key.includes("F64") || key.includes("I64")
          ? 8
          : key.includes("F32") || key.includes("I32")
            ? 4
            : key.includes("F16") || key.includes("BF16") || key.includes("I16")
              ? 2
              : key.includes("I8")
                ? 1
                : null;
      return bytes ? { bytes, count: Number(count) } : null;
    })
    .filter(Boolean);
  const total = weighted.reduce((sum, row) => sum + row.count, 0);
  if (!total) return null;
  return weighted.reduce((sum, row) => sum + row.bytes * row.count, 0) / total;
}

function precision(config, model) {
  const bits = quantizationBits(config, model);
  const haystack = `${model.id} ${(model.tags || []).join(" ")}`.toLowerCase();
  if (haystack.includes("gguf")) return bits ? `GGUF ${bits}-bit` : "GGUF";
  if (haystack.includes("nvfp4")) return "NVFP4";
  if (haystack.includes("mxfp4")) return "MXFP4";
  if (haystack.includes("fp8")) return "FP8";
  if (bits) return `${bits}-bit`;
  const dtypes = Object.keys(model.safetensors?.parameters || {});
  if (dtypes.length) return dtypes.join("/");
  return "metadata-estimated";
}

function bytesPerParam(config, model) {
  const bits = quantizationBits(config, model);
  if (bits) return round(bits / 8, 4);
  return round(dtypeBytes(model) ?? 2, 4);
}

function contextTokens(config) {
  const rope = config?.rope_scaling || {};
  const value = numberFrom(
    config?.max_position_embeddings,
    config?.max_sequence_length,
    config?.max_seq_len,
    config?.seq_length,
    config?.n_positions,
    config?.n_ctx,
    rope?.original_max_position_embeddings,
  );
  if (value && value < 100_000_000) return Math.trunc(value);
  return 2048;
}

function effectiveConfig(config) {
  if (!config || typeof config !== "object") return {};
  for (const key of [
    "text_config",
    "language_config",
    "llm_config",
    "model_config",
  ]) {
    if (config[key] && typeof config[key] === "object") return config[key];
  }
  return config;
}

function architectureKind(config) {
  const modelType = String(config?.model_type || "").toLowerCase();
  if (
    modelType.includes("mamba") ||
    modelType.includes("rwkv") ||
    modelType.includes("recurrent")
  ) {
    return "recurrent";
  }
  if (
    config?.num_local_experts ||
    config?.num_experts ||
    config?.n_routed_experts ||
    config?.num_experts_per_tok ||
    modelType.includes("moe")
  ) {
    return "moe";
  }
  return "dense";
}

function architectureType(kind) {
  if (kind === "moe") return "MoE transformer";
  if (kind === "recurrent") return "Recurrent state-space model";
  return "Dense transformer";
}

function headDim(config, attentionHeads) {
  return intFrom(
    config?.head_dim,
    config?.hidden_size && attentionHeads
      ? Number(config.hidden_size) / attentionHeads
      : null,
    config?.n_embd && attentionHeads
      ? Number(config.n_embd) / attentionHeads
      : null,
  );
}

function kvGbPer1k(config, kind, layers, kvHeads, dim) {
  if (kind === "recurrent") return 0;
  if (!layers) return 0;
  const heads = kvHeads || intFrom(config?.num_attention_heads, config?.n_head);
  const width =
    dim ||
    (numberFrom(config?.hidden_size, config?.n_embd) && heads
      ? numberFrom(config?.hidden_size, config?.n_embd) / heads
      : null);
  if (!heads || !width) return 0;
  return round((layers * 2 * heads * width * 2 * 1000) / 1e9, 6);
}

function shortName(id) {
  return id
    .split("/")
    .at(-1)
    .replace(/[-_](Instruct|Chat|Base|HF|GGUF|AWQ|GPTQ)$/i, "")
    .replace(/[-_]/g, " ")
    .slice(0, 48);
}

function dataQuality(config, model, baseInfo) {
  const parts = [];
  parts.push(config ? "config" : "no-config");
  parts.push(
    model.safetensors?.total || baseInfo?.safetensors?.total
      ? "params"
      : "estimated-params",
  );
  if (baseInfo && baseInfo.id !== model.id) parts.push(`base:${baseInfo.id}`);
  return parts.join(", ");
}

async function buildModel(model) {
  const fullModel = (await modelInfo(model.id)) || model;
  model = {
    ...fullModel,
    downloads: model.downloads ?? fullModel.downloads,
    pipeline_tag: model.pipeline_tag ?? fullModel.pipeline_tag,
    tags: fullModel.tags || model.tags,
    cardData: fullModel.cardData || model.cardData,
  };
  const baseIds = baseModelIds(model);
  const baseInfo = baseIds.length ? await modelInfo(baseIds[0]) : null;
  const ownConfig = await rawConfig(model.id);
  const baseConfig =
    !ownConfig && baseInfo ? await rawConfig(baseInfo.id) : null;
  const apiConfig =
    model.config && Object.keys(model.config).length ? model.config : null;
  const rawConfigData =
    ownConfig || baseConfig || apiConfig || baseInfo?.config || {};
  const config = effectiveConfig(rawConfigData);
  const configSource = ownConfig
    ? model.id
    : baseConfig
      ? baseInfo.id
      : apiConfig
        ? model.id
        : baseInfo?.id;
  const kind = architectureKind(config);
  const totalParams = paramCountB(model, baseInfo, model.id);
  const activeFromName =
    parseActiveParamB(model.id) ?? parseActiveParamB(baseInfo?.id ?? "");
  const recordedExperts = intFrom(
    config?.num_local_experts,
    config?.num_experts,
    config?.n_routed_experts,
  );
  const recordedExpertsPerToken = intFrom(
    config?.num_experts_per_tok,
    config?.num_experts_per_token,
    config?.moe_top_k,
    config?.num_selected_experts,
  );
  const fallbackExperts =
    kind === "moe" && activeFromName && totalParams > activeFromName
      ? Math.max(1, Math.round(totalParams / activeFromName))
      : 1;
  const experts = kind === "moe" ? (recordedExperts ?? fallbackExperts) : null;
  const expertsPerToken =
    kind === "moe" ? (recordedExpertsPerToken ?? 1) : null;
  const activeParams =
    kind === "moe"
      ? round(
          activeFromName ??
            (experts && expertsPerToken
              ? Math.max(totalParams * (expertsPerToken / experts), 0.1)
              : totalParams),
          4,
        )
      : totalParams;
  const layers = intFrom(
    config?.num_hidden_layers,
    config?.n_layer,
    config?.num_layers,
    config?.decoder_layers,
  );
  const attentionHeads = intFrom(
    config?.num_attention_heads,
    config?.n_head,
    config?.num_heads,
  );
  const kvHeads = intFrom(
    config?.num_key_value_heads,
    config?.n_kv_heads,
    config?.multi_query_group_num,
  );
  const dim = headDim(config, attentionHeads);
  const bytes = bytesPerParam(config, model);
  const kvGb = kvGbPer1k(config, kind, layers, kvHeads, dim);
  const modelType = config?.model_type || model.config?.model_type || "unknown";
  const archName = asArray(config?.architectures || model.config?.architectures)
    .filter(Boolean)
    .join(", ");
  const quality = dataQuality(configSource ? config : null, model, baseInfo);
  const sources = [
    { label: "Hugging Face model card", url: `${hfBase}/${model.id}` },
  ];
  if (configSource) {
    sources.push({
      label: configSource === model.id ? "Model config" : "Base model config",
      url: `${hfBase}/${configSource}/raw/main/config.json`,
    });
  }
  if (baseInfo && baseInfo.id !== model.id) {
    sources.push({
      label: "Base model card",
      url: `${hfBase}/${baseInfo.id}`,
    });
  }
  return {
    id: model.id,
    name: `${model.id.split("/").at(-1)} ${precision(config, model)}`,
    short_name: shortName(model.id),
    license: licenseFrom(model),
    hf_pipeline_tag: model.pipeline_tag || "unknown",
    hf_downloads: model.downloads ?? 0,
    tags: (model.tags || []).filter((tag) => !tag.startsWith("region:")),
    architecture: {
      type: architectureType(kind),
      detail: `${modelType}${archName ? ` (${archName})` : ""}`,
      total_params_b: totalParams,
      active_params_b: activeParams,
      layers,
      attention_heads: attentionHeads,
      kv_heads: kvHeads,
      head_dim: dim,
      max_context_tokens: contextTokens(config),
      routed_experts: kind === "moe" ? experts : null,
      routed_experts_per_token: kind === "moe" ? expertsPerToken : null,
      shared_experts_per_token:
        kind === "moe" ? (intFrom(config?.n_shared_experts) ?? 0) : null,
    },
    adapter: {
      kind,
      weight_precision: precision(config, model),
      weight_bytes_per_param: bytes,
      resident_weight_gb: round(totalParams * bytes, 4),
      active_weight_gb: round(activeParams * bytes, 4),
      kv_alloc_gb_per_1k_tokens: kvGb,
      kv_read_gb_per_1k_tokens: kvGb,
      ...(kind === "recurrent"
        ? { kv_alloc_fixed_gb: 0.02, kv_read_fixed_gb: 0.002 }
        : {}),
      notes: `Generated from Hugging Face metadata on ${new Date().toISOString().slice(0, 10)}; downloads=${model.downloads ?? 0}; data quality: ${quality}. Bound weights use recorded repo precision when detectable, otherwise metadata-estimated precision.`,
    },
    sources,
  };
}

function escapeNonAscii(text) {
  return text.replace(
    /[^\x00-\x7F]/g,
    (char) => `\\u${char.charCodeAt(0).toString(16).padStart(4, "0")}`,
  );
}

async function main() {
  const candidates = await downloadedModels();
  console.error(
    `found ${candidates.length} leaderboard-compatible models >= ${threshold} downloads`,
  );
  const models = [];
  for (const [index, model] of candidates.entries()) {
    if (
      !/^[A-Za-z0-9][A-Za-z0-9._-]*\/[A-Za-z0-9][A-Za-z0-9._-]*$/.test(model.id)
    ) {
      console.error(`skipping unsupported repo id: ${model.id}`);
      continue;
    }
    try {
      models.push(await buildModel(model));
    } catch (error) {
      console.error(`failed ${model.id}: ${error.message}`);
    }
    if ((index + 1) % 25 === 0) {
      console.error(`processed ${index + 1}/${candidates.length}`);
    }
  }
  models.sort(
    (a, b) => b.hf_downloads - a.hf_downloads || a.id.localeCompare(b.id),
  );
  const data = {
    schema_version: "2",
    generated_at: new Date().toISOString(),
    assumptions,
    models,
  };
  const body = `window.LOCAL_FRONTIER_MODEL_DATA = ${JSON.stringify(data, null, 2)};\n`;
  fs.writeFileSync(outputPath, escapeNonAscii(body));
  console.error(`wrote ${models.length} models to ${outputPath}`);
}

await main();