Fetch Command Code models at startup
This commit is contained in:
Patrick Wozniak
@@ -6,17 +6,17 @@ A [pi](https://github.com/badlogic/pi-mono) custom provider that connects pi to
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> **Note:** This package only provides a model _provider_. It does **not** include an API key. You must bring your own Command Code API key or subscription.
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> 💰 **Current offer:** Command Code offers [4× usage of DeepSeek V4](https://commandcode.ai/docs/resources/pricing-limits#deepseek-v4-pro-4x-usage) (Pro and Flash) at no extra cost.
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> 💰 **Current offers:** Command Code offers [4× usage of DeepSeek V4 Pro](https://commandcode.ai/docs/resources/pricing-limits#deepseek-v4-pro-4x-usage) and [2× usage of Qwen 3.7 Max](https://commandcode.ai/docs/resources/pricing-limits#qwen-3.7-max-2x-usage).
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## Models
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18 models across premium and open-source providers:
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Models are fetched live from Command Code's Provider API at startup, so new models like Qwen 3.7 Max show up without a package release.
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| Category | Models |
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| --------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
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| **Anthropic** | Claude Opus 4.7, Claude Opus 4.6, Claude Sonnet 4.6, Claude Haiku 4.5 |
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| **OpenAI** | GPT-5.5, GPT-5.4, GPT-5.3 Codex, GPT-5.4 Mini |
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| **Open-source** | DeepSeek V4, DeepSeek V4 Pro, DeepSeek V4 Flash, Kimi K2.6, Kimi K2.5, GLM-5.1, GLM-5, MiniMax M2.7, MiniMax M2.5, Qwen 3.6 Max, Qwen 3.6 Plus |
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You can list the current Command Code models with:
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```sh
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pi -e index.ts --list-models
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```
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## Install
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@@ -88,40 +88,21 @@ After installing and setting your API key, select a Command Code model in pi:
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/model deepseek/deepseek-v4-flash
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```
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Any query will then use the Command Code API. You can list available models:
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```sh
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pi -e index.ts --list-models
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```
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Or within pi:
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Any query will then use the Command Code API. You can list available models within pi:
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```txt
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/models
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```
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## Update models
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## Model discovery
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The model list (`models.json`) is extracted from the [command-code](https://www.npmjs.com/package/command-code) npm package's dist file. When Command Code releases a new version with updated models, regenerate it:
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On startup, the provider fetches:
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```sh
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npm run extract-models
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```txt
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https://api.commandcode.ai/provider/v1/models
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```
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This runs `scripts/extract-models.ts`, which:
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1. Downloads the latest `command-code` tarball from npm (`npm pack command-code`)
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2. Parses the minified `dist/index.mjs` to extract provider definitions, model metadata, and pricing
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3. Fills in `contextWindow` and `maxOutputTokens` with sensible defaults where the CLI omits them
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4. Writes the result to `models.json`
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To use a specific version or local dist file:
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```sh
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npx tsx scripts/extract-models.ts /path/to/command-code/dist/index.mjs
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```
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`models.json` is committed to the repo and included in the npm package.
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For tests or local mocks, override it with `COMMANDCODE_MODELS_URL`.
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## Publish
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@@ -9,106 +9,32 @@
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* 3. Place API key in `~/.commandcode/auth.json` or `~/.pi/agent/auth.json`
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* as {"apiKey": "user_..."} or {"commandcode": "user_..."}
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*
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* Models are sourced from models.json, which is extracted from the command-code
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* npm package dist file. Run `npx tsx scripts/extract-models.ts` to refresh.
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* Models are fetched from Command Code's Provider API at startup.
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*/
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import { readFileSync } from "node:fs";
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import { calculateCost, createAssistantMessageEventStream } from "@mariozechner/pi-ai"
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import type { ExtensionAPI } from "@mariozechner/pi-coding-agent"
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import { calculateCost, createAssistantMessageEventStream } from "@mariozechner/pi-ai";
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import type { ExtensionAPI } from "@mariozechner/pi-coding-agent";
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import { createStreamCommandCode, DEFAULT_API_BASE } from "./src/core.ts"
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import { DEFAULT_MODELS_URL, fetchCommandCodeModels } from "./src/models.ts"
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import { getApiKey, login, refreshToken } from "./src/oauth.ts"
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import { createStreamCommandCode, DEFAULT_API_BASE } from "./src/core.ts";
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import { getApiKey, login, refreshToken } from "./src/oauth.ts";
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const API_BASE = process.env.COMMANDCODE_API_BASE ?? DEFAULT_API_BASE;
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// ---------------------------------------------------------------------------
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// Load model definitions from models.json
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// ---------------------------------------------------------------------------
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interface ModelsJson {
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providers: Record<string, string>;
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models: Array<{
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key: string;
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id: string;
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provider: string;
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spec: string;
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label: string;
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name: string;
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description: string;
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reasoning: boolean;
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reasoningEfforts: string[] | null;
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contextWindow: number;
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maxOutputTokens: number;
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vendorLabel: string | null;
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}>;
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pricing: Array<{
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provider: string;
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id: string;
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category: string;
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promptCost: number;
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completionCost: number;
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cacheWrite5mCost: number;
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cacheWrite1hCost: number;
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cacheHitCost: number;
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}>;
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}
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const modelsJson: ModelsJson = JSON.parse(
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readFileSync(new URL("./models.json", import.meta.url), "utf8"),
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);
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// ---------------------------------------------------------------------------
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// Build cost lookup (model id -> pricing)
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// ---------------------------------------------------------------------------
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const costByModelId = new Map<string, ModelsJson["pricing"][number]>();
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for (const p of modelsJson.pricing) {
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// Pricing id is like "anthropic:claude-sonnet-4-6"
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const colonIdx = p.id.indexOf(":");
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if (colonIdx > 0) {
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costByModelId.set(p.id.substring(colonIdx + 1), p);
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}
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costByModelId.set(p.id, p);
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}
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// ---------------------------------------------------------------------------
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// Build pi model list (all defaults come from models.json)
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// ---------------------------------------------------------------------------
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const MODELS = modelsJson.models.map((m) => {
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const cost = costByModelId.get(m.id);
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return {
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id: m.id,
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name: `${m.name} (CC)`,
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reasoning: m.reasoning,
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contextWindow: m.contextWindow,
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maxTokens: m.maxOutputTokens,
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cost: {
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input: cost?.promptCost ?? 0,
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output: cost?.completionCost ?? 0,
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cacheRead: cost?.cacheHitCost ?? 0,
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cacheWrite: Math.max(cost?.cacheWrite5mCost ?? 0, cost?.cacheWrite1hCost ?? 0),
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},
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};
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});
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// ---------------------------------------------------------------------------
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// Stream factory
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// ---------------------------------------------------------------------------
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const API_BASE = process.env.COMMANDCODE_API_BASE ?? DEFAULT_API_BASE
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const MODELS_URL = process.env.COMMANDCODE_MODELS_URL ?? DEFAULT_MODELS_URL
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const streamCommandCode = createStreamCommandCode({
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createStream: createAssistantMessageEventStream,
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calculateCost,
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apiBase: API_BASE,
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});
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})
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// ---------------------------------------------------------------------------
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// Extension entry point
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// ---------------------------------------------------------------------------
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export default function (pi: ExtensionAPI) {
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export default async function (pi: ExtensionAPI) {
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const models = await fetchCommandCodeModels({ url: MODELS_URL })
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pi.registerProvider("commandcode", {
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name: "Command Code",
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baseUrl: API_BASE,
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@@ -126,14 +52,14 @@ export default function (pi: ExtensionAPI) {
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refreshToken,
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getApiKey,
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},
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models: MODELS.map((model) => ({
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models: models.map((model) => ({
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id: model.id,
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name: model.name,
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reasoning: model.reasoning,
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input: ["text"] as const,
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cost: model.cost,
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
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contextWindow: model.contextWindow,
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maxTokens: model.maxTokens,
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})),
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});
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})
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}
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-545
@@ -1,545 +0,0 @@
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{
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"providers": {
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"ANTHROPIC": "anthropic",
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"OPENAI": "openai",
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"BASETEN": "baseten",
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"VERCEL_AI_GATEWAY": "vercel-ai-gateway",
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"CLOUDFLARE_AI_GATEWAY": "cloudflare-ai-gateway",
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"OPENROUTER": "openrouter"
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},
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"providerGroups": [
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{
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"id": "command-code",
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"label": "Command Code",
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"shortLabel": "cmd",
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"description": "recommended",
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"providers": [
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"anthropic",
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"openai",
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"baseten",
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"vercel-ai-gateway"
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]
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},
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{
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"id": "anthropic",
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"label": "Anthropic",
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"shortLabel": "anth",
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"description": "Claude Pro/Max",
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"providers": [
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"anthropic"
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]
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},
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{
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"id": "github-copilot",
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"label": "GitHub Copilot",
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"shortLabel": "copilot",
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"description": "Copilot subscription",
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"providers": [
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"anthropic",
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"openai"
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]
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},
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{
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"id": "codex",
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"label": "ChatGPT (Codex)",
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"shortLabel": "codex",
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"description": "ChatGPT Pro/Plus subscription",
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"providers": [
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"openai"
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]
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}
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],
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"models": [
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{
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"key": "SONNET_4_6",
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"id": "claude-sonnet-4-6",
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"provider": "anthropic",
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"spec": "chatComplete",
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"label": "Claude Sonnet 4.6",
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"name": "Claude Sonnet 4.6",
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"description": "best combo of speed & intelligence (recommended)",
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"reasoning": true,
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"reasoningEfforts": [
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"low",
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"medium",
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"high",
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"xhigh",
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"max"
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],
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"contextWindow": 1000000,
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"maxOutputTokens": 64000,
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"vendorLabel": null
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},
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{
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"key": "OPUS_4_7",
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"id": "claude-opus-4-7",
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"provider": "anthropic",
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"spec": "chatComplete",
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"label": "Claude Opus 4.7",
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"name": "Claude Opus 4.7",
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"description": "most intelligent for agents and coding",
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"reasoning": true,
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"reasoningEfforts": [
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"low",
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"medium",
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"high",
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"xhigh",
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"max"
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],
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"contextWindow": 1000000,
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"maxOutputTokens": 64000,
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"vendorLabel": null
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},
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{
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"key": "HAIKU_4_5",
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"id": "claude-haiku-4-5-20251001",
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"provider": "anthropic",
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"spec": "chatComplete",
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"label": "Claude Haiku 4.5",
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"name": "Claude Haiku 4.5",
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"description": "fastest & most compact, great for quick tasks",
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"reasoning": false,
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"reasoningEfforts": null,
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"contextWindow": 200000,
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"maxOutputTokens": 64000,
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"vendorLabel": null
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},
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{
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"key": "GPT_5_5",
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"id": "gpt-5.5",
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"provider": "openai",
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"spec": "responses",
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"label": "GPT-5.5",
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"name": "GPT-5.5",
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"description": "latest frontier model for general complex work",
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"reasoning": true,
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"reasoningEfforts": [
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"low",
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"medium",
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"high",
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"xhigh"
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],
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"contextWindow": 256000,
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"maxOutputTokens": 128000,
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"vendorLabel": null
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},
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{
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"key": "GPT_5_4",
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"id": "gpt-5.4",
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"provider": "openai",
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"spec": "responses",
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"label": "GPT-5.4",
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"name": "GPT-5.4",
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"description": "frontier model for general complex work",
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"reasoning": true,
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"reasoningEfforts": [
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"low",
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"medium",
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"high",
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"xhigh"
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],
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"contextWindow": 400000,
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"maxOutputTokens": 128000,
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"vendorLabel": null
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},
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{
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"key": "GPT_5_3_CODEX",
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"id": "gpt-5.3-codex",
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"provider": "openai",
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"spec": "responses",
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"label": "GPT-5.3 Codex",
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"name": "GPT-5.3 Codex",
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"description": "frontier coding model",
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"reasoning": true,
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"reasoningEfforts": [
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"low",
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"medium",
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"high",
|
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"xhigh"
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],
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"contextWindow": 400000,
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"maxOutputTokens": 128000,
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"vendorLabel": null
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},
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{
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"key": "GPT_5_4_MINI",
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"id": "gpt-5.4-mini",
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"provider": "openai",
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"spec": "responses",
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"label": "GPT-5.4 Mini",
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"name": "GPT-5.4 Mini",
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"description": "fast, cost-effective model for everyday tasks",
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"reasoning": true,
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"reasoningEfforts": [
|
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"low",
|
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"medium",
|
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"high"
|
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],
|
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"contextWindow": 400000,
|
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"maxOutputTokens": 128000,
|
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"vendorLabel": null
|
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},
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{
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"key": "KIMI_K2_6",
|
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"id": "moonshotai/Kimi-K2.6",
|
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"provider": "vercel-ai-gateway",
|
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"spec": "chatComplete",
|
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"label": "Kimi K2.6",
|
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"name": "Kimi K2.6",
|
||||
"description": "long-horizon coding with vision",
|
||||
"reasoning": false,
|
||||
"reasoningEfforts": null,
|
||||
"contextWindow": 256000,
|
||||
"maxOutputTokens": 65536,
|
||||
"vendorLabel": null
|
||||
},
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{
|
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"key": "KIMI_K2_5",
|
||||
"id": "moonshotai/Kimi-K2.5",
|
||||
"provider": "vercel-ai-gateway",
|
||||
"spec": "chatComplete",
|
||||
"label": "Kimi K2.5",
|
||||
"name": "Kimi K2.5",
|
||||
"description": "multimodal frontend coding",
|
||||
"reasoning": false,
|
||||
"reasoningEfforts": null,
|
||||
"contextWindow": 256000,
|
||||
"maxOutputTokens": 65536,
|
||||
"vendorLabel": null
|
||||
},
|
||||
{
|
||||
"key": "GLM_5_1",
|
||||
"id": "zai-org/GLM-5.1",
|
||||
"provider": "vercel-ai-gateway",
|
||||
"spec": "chatComplete",
|
||||
"label": "GLM-5.1",
|
||||
"name": "GLM-5.1",
|
||||
"description": "long-horizon autonomous coding agent",
|
||||
"reasoning": false,
|
||||
"reasoningEfforts": null,
|
||||
"contextWindow": 200000,
|
||||
"maxOutputTokens": 65536,
|
||||
"vendorLabel": null
|
||||
},
|
||||
{
|
||||
"key": "GLM_5",
|
||||
"id": "zai-org/GLM-5",
|
||||
"provider": "vercel-ai-gateway",
|
||||
"spec": "chatComplete",
|
||||
"label": "GLM-5",
|
||||
"name": "GLM-5",
|
||||
"description": "multi-mode thinking & long-range planning",
|
||||
"reasoning": false,
|
||||
"reasoningEfforts": null,
|
||||
"contextWindow": 200000,
|
||||
"maxOutputTokens": 65536,
|
||||
"vendorLabel": null
|
||||
},
|
||||
{
|
||||
"key": "MINIMAX_M2_7",
|
||||
"id": "MiniMaxAI/MiniMax-M2.7",
|
||||
"provider": "vercel-ai-gateway",
|
||||
"spec": "chatComplete",
|
||||
"label": "MiniMax M2.7",
|
||||
"name": "MiniMax M2.7",
|
||||
"description": "end-to-end software engineering agent",
|
||||
"reasoning": false,
|
||||
"reasoningEfforts": null,
|
||||
"contextWindow": 1048576,
|
||||
"maxOutputTokens": 65536,
|
||||
"vendorLabel": null
|
||||
},
|
||||
{
|
||||
"key": "MINIMAX_M2_5",
|
||||
"id": "MiniMaxAI/MiniMax-M2.5",
|
||||
"provider": "vercel-ai-gateway",
|
||||
"spec": "chatComplete",
|
||||
"label": "MiniMax M2.5",
|
||||
"name": "MiniMax M2.5",
|
||||
"description": "cross-platform full-stack agentic dev",
|
||||
"reasoning": false,
|
||||
"reasoningEfforts": null,
|
||||
"contextWindow": 200000,
|
||||
"maxOutputTokens": 65536,
|
||||
"vendorLabel": null
|
||||
},
|
||||
{
|
||||
"key": "DEEPSEEK_V4_PRO",
|
||||
"id": "deepseek/deepseek-v4-pro",
|
||||
"provider": "vercel-ai-gateway",
|
||||
"spec": "chatComplete",
|
||||
"label": "DeepSeek V4 Pro",
|
||||
"name": "DeepSeek V4 Pro",
|
||||
"description": "hybrid-attention long-context reasoning",
|
||||
"reasoning": true,
|
||||
"reasoningEfforts": [
|
||||
"high",
|
||||
"max"
|
||||
],
|
||||
"contextWindow": 1000000,
|
||||
"maxOutputTokens": 384000,
|
||||
"vendorLabel": null
|
||||
},
|
||||
{
|
||||
"key": "DEEPSEEK_V4_FLASH",
|
||||
"id": "deepseek/deepseek-v4-flash",
|
||||
"provider": "vercel-ai-gateway",
|
||||
"spec": "chatComplete",
|
||||
"label": "DeepSeek V4 Flash",
|
||||
"name": "DeepSeek V4 Flash",
|
||||
"description": "fast hybrid-attention reasoning",
|
||||
"reasoning": true,
|
||||
"reasoningEfforts": [
|
||||
"high",
|
||||
"max"
|
||||
],
|
||||
"contextWindow": 1000000,
|
||||
"maxOutputTokens": 384000,
|
||||
"vendorLabel": null
|
||||
},
|
||||
{
|
||||
"key": "QWEN_3_6_MAX_PREVIEW",
|
||||
"id": "Qwen/Qwen3.6-Max-Preview",
|
||||
"provider": "vercel-ai-gateway",
|
||||
"spec": "chatComplete",
|
||||
"label": "Qwen 3.6 Max Preview",
|
||||
"name": "Qwen 3.6 Max Preview",
|
||||
"description": "vibe coding & efficient agent execution",
|
||||
"reasoning": true,
|
||||
"reasoningEfforts": null,
|
||||
"contextWindow": 1000000,
|
||||
"maxOutputTokens": 65536,
|
||||
"vendorLabel": null
|
||||
},
|
||||
{
|
||||
"key": "QWEN_3_6_PLUS",
|
||||
"id": "Qwen/Qwen3.6-Plus",
|
||||
"provider": "vercel-ai-gateway",
|
||||
"spec": "chatComplete",
|
||||
"label": "Qwen 3.6 Plus",
|
||||
"name": "Qwen 3.6 Plus",
|
||||
"description": "agentic coding & reasoning",
|
||||
"reasoning": true,
|
||||
"reasoningEfforts": null,
|
||||
"contextWindow": 1000000,
|
||||
"maxOutputTokens": 65536,
|
||||
"vendorLabel": null
|
||||
},
|
||||
{
|
||||
"key": "QWEN_3_7_MAX",
|
||||
"id": "Qwen/Qwen3.7-Max",
|
||||
"provider": "vercel-ai-gateway",
|
||||
"spec": "chatComplete",
|
||||
"label": "Qwen 3.7 Max",
|
||||
"name": "Qwen 3.7 Max",
|
||||
"description": "frontier coding & long-horizon agent execution",
|
||||
"reasoning": true,
|
||||
"reasoningEfforts": null,
|
||||
"contextWindow": 1000000,
|
||||
"maxOutputTokens": 65536,
|
||||
"vendorLabel": null
|
||||
},
|
||||
{
|
||||
"key": "STEP_3_5_FLASH",
|
||||
"id": "stepfun/Step-3.5-Flash",
|
||||
"provider": "vercel-ai-gateway",
|
||||
"spec": "chatComplete",
|
||||
"label": "Step 3.5 Flash",
|
||||
"name": "Step 3.5 Flash",
|
||||
"description": "fast sparse-MoE agentic reasoning",
|
||||
"reasoning": true,
|
||||
"reasoningEfforts": null,
|
||||
"contextWindow": 1000000,
|
||||
"maxOutputTokens": 65536,
|
||||
"vendorLabel": null
|
||||
},
|
||||
{
|
||||
"key": "GEMINI_3_5_FLASH",
|
||||
"id": "google/gemini-3.5-flash",
|
||||
"provider": "vercel-ai-gateway",
|
||||
"spec": "chatComplete",
|
||||
"label": "Gemini 3.5 Flash",
|
||||
"name": "Gemini 3.5 Flash",
|
||||
"description": "Pro-level coding proficiency, parallel agentic execution",
|
||||
"reasoning": true,
|
||||
"reasoningEfforts": [
|
||||
"low",
|
||||
"medium",
|
||||
"high"
|
||||
],
|
||||
"contextWindow": 1000000,
|
||||
"maxOutputTokens": 65536,
|
||||
"vendorLabel": "Google"
|
||||
},
|
||||
{
|
||||
"key": "GEMINI_3_1_FLASH_LITE",
|
||||
"id": "google/gemini-3.1-flash-lite",
|
||||
"provider": "vercel-ai-gateway",
|
||||
"spec": "chatComplete",
|
||||
"label": "Gemini 3.1 Flash Lite",
|
||||
"name": "Gemini 3.1 Flash Lite",
|
||||
"description": "high-volume workhorse model with implicit caching",
|
||||
"reasoning": true,
|
||||
"reasoningEfforts": [
|
||||
"low",
|
||||
"medium",
|
||||
"high"
|
||||
],
|
||||
"contextWindow": 1000000,
|
||||
"maxOutputTokens": 65536,
|
||||
"vendorLabel": "Google"
|
||||
}
|
||||
],
|
||||
"pricing": [
|
||||
{
|
||||
"provider": "Anthropic",
|
||||
"id": "anthropic:claude-sonnet-4-20250514",
|
||||
"category": "premium",
|
||||
"promptCost": 3,
|
||||
"completionCost": 15,
|
||||
"cacheWrite5mCost": 3.75,
|
||||
"cacheWrite1hCost": 6,
|
||||
"cacheHitCost": 0.3
|
||||
},
|
||||
{
|
||||
"provider": "Anthropic",
|
||||
"id": "anthropic:claude-sonnet-4-5-20250929",
|
||||
"category": "premium",
|
||||
"promptCost": 3,
|
||||
"completionCost": 15,
|
||||
"cacheWrite5mCost": 3.75,
|
||||
"cacheWrite1hCost": 6,
|
||||
"cacheHitCost": 0.3
|
||||
},
|
||||
{
|
||||
"provider": "Anthropic",
|
||||
"id": "anthropic:claude-opus-4-5-20251101",
|
||||
"category": "premium",
|
||||
"promptCost": 5,
|
||||
"completionCost": 25,
|
||||
"cacheWrite5mCost": 6.25,
|
||||
"cacheWrite1hCost": 10,
|
||||
"cacheHitCost": 0.5
|
||||
},
|
||||
{
|
||||
"provider": "Anthropic",
|
||||
"id": "anthropic:claude-sonnet-4-6",
|
||||
"category": "premium",
|
||||
"promptCost": 3,
|
||||
"completionCost": 15,
|
||||
"cacheWrite5mCost": 3.75,
|
||||
"cacheWrite1hCost": 6,
|
||||
"cacheHitCost": 0.3
|
||||
},
|
||||
{
|
||||
"provider": "Anthropic",
|
||||
"id": "anthropic:claude-opus-4-7",
|
||||
"category": "premium",
|
||||
"promptCost": 5,
|
||||
"completionCost": 25,
|
||||
"cacheWrite5mCost": 6.25,
|
||||
"cacheWrite1hCost": 10,
|
||||
"cacheHitCost": 0.5
|
||||
},
|
||||
{
|
||||
"provider": "Anthropic",
|
||||
"id": "anthropic:claude-opus-4-6",
|
||||
"category": "premium",
|
||||
"promptCost": 5,
|
||||
"completionCost": 25,
|
||||
"cacheWrite5mCost": 6.25,
|
||||
"cacheWrite1hCost": 10,
|
||||
"cacheHitCost": 0.5
|
||||
},
|
||||
{
|
||||
"provider": "Anthropic",
|
||||
"id": "anthropic:claude-haiku-4-5-20251001",
|
||||
"category": "premium",
|
||||
"promptCost": 1,
|
||||
"completionCost": 5,
|
||||
"cacheWrite5mCost": 1.25,
|
||||
"cacheWrite1hCost": 2,
|
||||
"cacheHitCost": 0.1
|
||||
},
|
||||
{
|
||||
"provider": "OpenAI",
|
||||
"id": "openai:gpt-5.5",
|
||||
"category": "premium",
|
||||
"promptCost": 5,
|
||||
"completionCost": 30,
|
||||
"cacheWrite5mCost": 0,
|
||||
"cacheWrite1hCost": 0,
|
||||
"cacheHitCost": 0.5
|
||||
},
|
||||
{
|
||||
"provider": "OpenAI",
|
||||
"id": "openai:gpt-5.4",
|
||||
"category": "premium",
|
||||
"promptCost": 2.5,
|
||||
"completionCost": 15,
|
||||
"cacheWrite5mCost": 0,
|
||||
"cacheWrite1hCost": 0,
|
||||
"cacheHitCost": 0.25
|
||||
},
|
||||
{
|
||||
"provider": "OpenAI",
|
||||
"id": "openai:gpt-5.3-codex",
|
||||
"category": "premium",
|
||||
"promptCost": 2,
|
||||
"completionCost": 8,
|
||||
"cacheWrite5mCost": 0,
|
||||
"cacheWrite1hCost": 0,
|
||||
"cacheHitCost": 0.5
|
||||
},
|
||||
{
|
||||
"provider": "OpenAI",
|
||||
"id": "openai:gpt-5.4-mini",
|
||||
"category": "premium",
|
||||
"promptCost": 0.75,
|
||||
"completionCost": 4.5,
|
||||
"cacheWrite5mCost": 0,
|
||||
"cacheWrite1hCost": 0,
|
||||
"cacheHitCost": 0.075
|
||||
},
|
||||
{
|
||||
"provider": "Baseten",
|
||||
"id": "baseten:zai-org/GLM-5",
|
||||
"category": "opensource",
|
||||
"promptCost": 0.95,
|
||||
"completionCost": 3.15,
|
||||
"cacheWrite5mCost": 0,
|
||||
"cacheWrite1hCost": 0,
|
||||
"cacheHitCost": 0
|
||||
},
|
||||
{
|
||||
"provider": "Baseten",
|
||||
"id": "baseten:moonshotai/Kimi-K2.5",
|
||||
"category": "opensource",
|
||||
"promptCost": 0.6,
|
||||
"completionCost": 3,
|
||||
"cacheWrite5mCost": 0,
|
||||
"cacheWrite1hCost": 0,
|
||||
"cacheHitCost": 0
|
||||
},
|
||||
{
|
||||
"provider": "Baseten",
|
||||
"id": "baseten:moonshotai/Kimi-K2.6",
|
||||
"category": "opensource",
|
||||
"promptCost": 0.95,
|
||||
"completionCost": 4,
|
||||
"cacheWrite5mCost": 0,
|
||||
"cacheWrite1hCost": 0,
|
||||
"cacheHitCost": 0.16
|
||||
},
|
||||
{
|
||||
"provider": "Baseten",
|
||||
"id": "baseten:MiniMaxAI/MiniMax-M2.5",
|
||||
"category": "opensource",
|
||||
"promptCost": 0.5,
|
||||
"completionCost": 2,
|
||||
"cacheWrite5mCost": 0,
|
||||
"cacheWrite1hCost": 0,
|
||||
"cacheHitCost": 0
|
||||
}
|
||||
]
|
||||
}
|
||||
+1
-3
@@ -21,7 +21,6 @@
|
||||
"files": [
|
||||
"index.ts",
|
||||
"src/",
|
||||
"models.json",
|
||||
"README.md",
|
||||
"LICENSE"
|
||||
],
|
||||
@@ -35,8 +34,7 @@
|
||||
"test:abort": "tsx tests/test-abort.ts",
|
||||
"test:stream": "tsx tests/test-stream.ts",
|
||||
"test:pi-local": "node tests/test-pi-local.mjs",
|
||||
"test:smoke": "node tests/test-smoke.mjs",
|
||||
"extract-models": "tsx scripts/extract-models.ts"
|
||||
"test:smoke": "node tests/test-smoke.mjs"
|
||||
},
|
||||
"pi": {
|
||||
"extensions": [
|
||||
|
||||
@@ -1,252 +0,0 @@
|
||||
#!/usr/bin/env -S npx tsx
|
||||
|
||||
/**
|
||||
* Extract model & provider definitions from the command-code npm package dist file.
|
||||
*
|
||||
* Usage:
|
||||
* npx tsx scripts/extract-models.ts [path-to-dist/index.mjs]
|
||||
* npx tsx scripts/extract-models.ts (downloads latest from npm)
|
||||
*
|
||||
* Output: models.json
|
||||
* {
|
||||
* providers: { ... }, // provider key -> value map
|
||||
* providerGroups: { ... }, // provider-group key -> { id, label, providers[] }
|
||||
* models: [ ... ], // flattened model definitions
|
||||
* pricing: [ ... ] // pricing entries (per 1M tokens, USD)
|
||||
* }
|
||||
*/
|
||||
|
||||
import { execSync } from "node:child_process";
|
||||
import { existsSync, mkdirSync, readFileSync, writeFileSync } from "node:fs";
|
||||
import { join } from "node:path";
|
||||
|
||||
// ---------------------------------------------------------------------------
|
||||
// Helpers
|
||||
// ---------------------------------------------------------------------------
|
||||
|
||||
/** Evaluate a JS object literal string safely via Function constructor. */
|
||||
function parseObjectLiteral(code: string): Record<string, unknown> {
|
||||
const fn = new Function(`return (${code})`);
|
||||
return fn() as Record<string, unknown>;
|
||||
}
|
||||
|
||||
// ---------------------------------------------------------------------------
|
||||
// Step 1: get the dist file
|
||||
// ---------------------------------------------------------------------------
|
||||
|
||||
function ensureDist(srcPath?: string): string {
|
||||
if (srcPath) {
|
||||
if (!existsSync(srcPath)) throw new Error(`File not found: ${srcPath}`);
|
||||
return srcPath;
|
||||
}
|
||||
|
||||
// Download latest from npm
|
||||
const tmpDir = join(process.cwd(), ".extract-tmp");
|
||||
mkdirSync(tmpDir, { recursive: true });
|
||||
const tgz = execSync(`npm pack command-code --pack-destination "${tmpDir}"`, {
|
||||
encoding: "utf8",
|
||||
}).trim();
|
||||
const tgzPath = join(tmpDir, tgz);
|
||||
execSync(`tar xzf "${tgzPath}" -C "${tmpDir}"`, { encoding: "utf8" });
|
||||
return join(tmpDir, "package", "dist", "index.mjs");
|
||||
}
|
||||
|
||||
// ---------------------------------------------------------------------------
|
||||
// Step 2: extract
|
||||
// ---------------------------------------------------------------------------
|
||||
|
||||
interface ModelDef {
|
||||
key: string;
|
||||
id: string;
|
||||
provider: string;
|
||||
spec: string;
|
||||
label: string;
|
||||
name: string;
|
||||
description: string;
|
||||
reasoning: boolean;
|
||||
reasoningEfforts: string[] | null;
|
||||
contextWindow: number;
|
||||
maxOutputTokens: number;
|
||||
vendorLabel: string | null;
|
||||
}
|
||||
|
||||
interface PricingEntry {
|
||||
provider: string;
|
||||
id: string;
|
||||
category: string;
|
||||
promptCost: number;
|
||||
completionCost: number;
|
||||
cacheWrite5mCost: number;
|
||||
cacheWrite1hCost: number;
|
||||
cacheHitCost: number;
|
||||
}
|
||||
|
||||
interface ProviderGroup {
|
||||
id: string;
|
||||
label: string;
|
||||
shortLabel: string;
|
||||
description: string;
|
||||
providers: string[];
|
||||
}
|
||||
|
||||
function extract(code: string) {
|
||||
// --- Wt: provider constants ---
|
||||
const wtMatch = code.match(/Wt=\{([^}]+)\}/);
|
||||
if (!wtMatch) throw new Error("Cannot find Wt");
|
||||
const wtRaw = "{" + wtMatch[1] + "}";
|
||||
const wt: Record<string, string> = {};
|
||||
for (const m of wtRaw.matchAll(/(\w+):"(\w[-\w]*)"/g)) {
|
||||
wt[m[1]] = m[2];
|
||||
}
|
||||
console.log("Providers:", wt);
|
||||
|
||||
// --- an: model definitions ---
|
||||
// an={...}).SONNET
|
||||
const anIdx = code.indexOf("an={");
|
||||
if (anIdx < 0) throw new Error("Cannot find an");
|
||||
const anEndIdx = code.indexOf("}).SONNET", anIdx);
|
||||
if (anEndIdx < 0) throw new Error("Cannot find end of an");
|
||||
let anCode = code.substring(anIdx + 1, anEndIdx + 2); // "an={...})"
|
||||
anCode = anCode.replace(/^\(an=/, "").replace(/\)$/, "");
|
||||
|
||||
// Replace minified JS idioms
|
||||
anCode = anCode.replace(/\bQt\b/g, JSON.stringify("vercel-ai-gateway"));
|
||||
anCode = anCode.replace(/\bon\b/g, JSON.stringify("chatComplete"));
|
||||
anCode = anCode.replace(/\bsn\b/g, JSON.stringify("responses"));
|
||||
anCode = anCode.replace(/Wt\.([A-Z_]+)/g, (_, key: string) =>
|
||||
JSON.stringify(wt[key]),
|
||||
);
|
||||
anCode = anCode.replace(/!0/g, "true");
|
||||
anCode = anCode.replace(/!1/g, "false");
|
||||
|
||||
const an = parseObjectLiteral(anCode);
|
||||
|
||||
// --- Yt: pricing (provider -> model array) ---
|
||||
const ytIdx = code.indexOf("Yt={[");
|
||||
if (ytIdx < 0) throw new Error("Cannot find Yt");
|
||||
// Find the matching closing brace for Yt
|
||||
let depth = 1;
|
||||
let ytEndIdx = ytIdx + 4;
|
||||
while (depth > 0 && ytEndIdx < code.length) {
|
||||
if (code[ytEndIdx] === "{") depth++;
|
||||
else if (code[ytEndIdx] === "}") depth--;
|
||||
ytEndIdx++;
|
||||
}
|
||||
let ytCode = code.substring(ytIdx + 3, ytEndIdx); // "{ ... }"
|
||||
ytCode = ytCode.replace(/Wt\.([A-Z_]+)/g, (_, key: string) =>
|
||||
JSON.stringify(wt[key]),
|
||||
);
|
||||
ytCode = ytCode.replace(/!0/g, "true");
|
||||
ytCode = ytCode.replace(/!1/g, "false");
|
||||
const yt = parseObjectLiteral(ytCode);
|
||||
|
||||
// --- pn: provider groups ---
|
||||
const pnIdx = code.indexOf('pn={"command-code"');
|
||||
if (pnIdx < 0) throw new Error("Cannot find pn");
|
||||
const pnEndIdx = code.indexOf(",__name(buildModelGroups", pnIdx);
|
||||
if (pnEndIdx < 0) throw new Error("Cannot find end of pn");
|
||||
let pnCode = code.substring(pnIdx + 3, pnEndIdx);
|
||||
pnCode = pnCode.replace(/Wt\.([A-Z_]+)/g, (_, key: string) =>
|
||||
JSON.stringify(wt[key]),
|
||||
);
|
||||
pnCode = pnCode.replace(/!0/g, "true");
|
||||
pnCode = pnCode.replace(/!1/g, "false");
|
||||
pnCode = pnCode.replace(/,\s*$/, "");
|
||||
const pn = parseObjectLiteral(pnCode);
|
||||
|
||||
// --- Defaults for fields the CLI doesn't provide per-model ---
|
||||
// maxOutputTokens: use the minimum across all providers for each model.
|
||||
// Anthropic direct: 64k OpenAI direct: 128k
|
||||
// DeepSeek (gateway): 384k (known to work)
|
||||
// Other gateway models (Baseten/Vercel/Cloudflare/OpenRouter): 65536
|
||||
const CONTEXT_WINDOW_FALLBACKS: Record<string, number> = {
|
||||
"gpt-5.5": 256_000,
|
||||
"zai-org/GLM-5.1": 200_000,
|
||||
"MiniMaxAI/MiniMax-M2.7": 1_048_576,
|
||||
"Qwen/Qwen3.6-Max-Preview": 1_000_000,
|
||||
"Qwen/Qwen3.6-Plus": 1_000_000,
|
||||
};
|
||||
const DEFAULT_CONTEXT_WINDOW = 200_000;
|
||||
|
||||
function maxOutputTokensForModel(id: string, provider: string): number {
|
||||
if (provider === "anthropic") return 64_000;
|
||||
if (provider === "openai") return 128_000;
|
||||
if (id.startsWith("deepseek/")) return 384_000;
|
||||
// Gateway models — lowest common denominator across Baseten/Vercel/Cloudflare
|
||||
return 65_536;
|
||||
}
|
||||
|
||||
// --- Build output ---
|
||||
const models: ModelDef[] = [];
|
||||
for (const [key, obj] of Object.entries(an)) {
|
||||
const m = obj as Record<string, unknown>;
|
||||
const id = m.id as string;
|
||||
const provider = m.provider as string;
|
||||
models.push({
|
||||
key,
|
||||
id,
|
||||
provider,
|
||||
spec: (m.spec as string) || "chatComplete",
|
||||
label: m.label as string,
|
||||
name: m.name as string,
|
||||
description: m.description as string,
|
||||
reasoning: !!(
|
||||
m.reasoning ??
|
||||
((m.reasoningEfforts as string[])?.length ?? 0) > 0
|
||||
),
|
||||
reasoningEfforts: (m.reasoningEfforts as string[]) || null,
|
||||
contextWindow:
|
||||
(typeof m.contextWindow === "number" ? m.contextWindow : null) ??
|
||||
CONTEXT_WINDOW_FALLBACKS[id] ??
|
||||
DEFAULT_CONTEXT_WINDOW,
|
||||
maxOutputTokens:
|
||||
maxOutputTokensForModel(id, provider),
|
||||
vendorLabel: (m.vendorLabel as string) || null,
|
||||
});
|
||||
}
|
||||
|
||||
const pricing: PricingEntry[] = [];
|
||||
for (const [_provider, entries] of Object.entries(yt)) {
|
||||
for (const entry of entries as Array<Record<string, unknown>>) {
|
||||
pricing.push({
|
||||
provider: entry.provider as string,
|
||||
id: entry.id as string,
|
||||
category: entry.category as string,
|
||||
promptCost: entry.promptCost as number,
|
||||
completionCost: entry.completionCost as number,
|
||||
cacheWrite5mCost: (entry.cacheWrite5mCost as number) || 0,
|
||||
cacheWrite1hCost: (entry.cacheWrite1hCost as number) || 0,
|
||||
cacheHitCost: (entry.cacheHitCost as number) || 0,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
const providerGroups: ProviderGroup[] = [];
|
||||
for (const [key, obj] of Object.entries(pn)) {
|
||||
const g = obj as Record<string, unknown>;
|
||||
providerGroups.push({
|
||||
id: g.id as string,
|
||||
label: g.label as string,
|
||||
shortLabel: (g.shortLabel as string) || "",
|
||||
description: (g.description as string) || "",
|
||||
providers: (g.supportedModelProviders as string[]) || [],
|
||||
});
|
||||
}
|
||||
|
||||
return { providers: wt, providerGroups, models, pricing };
|
||||
}
|
||||
|
||||
// ---------------------------------------------------------------------------
|
||||
// main
|
||||
// ---------------------------------------------------------------------------
|
||||
|
||||
const distPath = ensureDist(process.argv[2]);
|
||||
console.log("Reading:", distPath);
|
||||
const code = readFileSync(distPath, "utf8");
|
||||
const result = extract(code);
|
||||
|
||||
const outPath = join(process.cwd(), "models.json");
|
||||
writeFileSync(outPath, JSON.stringify(result, null, 2), "utf8");
|
||||
console.log(
|
||||
`Wrote ${result.models.length} models + ${result.pricing.length} pricing entries to ${outPath}`,
|
||||
);
|
||||
@@ -0,0 +1,85 @@
|
||||
export const DEFAULT_MODELS_URL = "https://api.commandcode.ai/provider/v1/models"
|
||||
|
||||
const DEFAULT_MAX_OUTPUT_TOKENS = 65_536
|
||||
|
||||
interface ApiModel {
|
||||
id: string
|
||||
name: string
|
||||
contextLength: number
|
||||
}
|
||||
|
||||
export interface CommandCodeModel {
|
||||
id: string
|
||||
name: string
|
||||
reasoning: boolean
|
||||
contextWindow: number
|
||||
maxTokens: number
|
||||
}
|
||||
|
||||
interface FetchCommandCodeModelsOptions {
|
||||
url?: string
|
||||
fetchImpl?: typeof fetch
|
||||
}
|
||||
|
||||
function isRecord(value: unknown): value is Record<string, unknown> {
|
||||
return typeof value === "object" && value !== null
|
||||
}
|
||||
|
||||
function stringField(record: Record<string, unknown>, key: string): string {
|
||||
const value = record[key]
|
||||
if (typeof value !== "string") throw new Error(`Expected ${key} to be a string`)
|
||||
return value
|
||||
}
|
||||
|
||||
function numberField(record: Record<string, unknown>, key: string): number {
|
||||
const value = record[key]
|
||||
if (typeof value !== "number") throw new Error(`Expected ${key} to be a number`)
|
||||
return value
|
||||
}
|
||||
|
||||
function parseApiModel(value: unknown): ApiModel {
|
||||
if (!isRecord(value)) throw new Error("Expected model entry to be an object")
|
||||
|
||||
return {
|
||||
id: stringField(value, "id"),
|
||||
name: stringField(value, "name"),
|
||||
contextLength: numberField(value, "context_length"),
|
||||
}
|
||||
}
|
||||
|
||||
export function commandCodeModelsFromApiResponse(value: unknown): readonly CommandCodeModel[] {
|
||||
if (!isRecord(value)) throw new Error("Expected models response to be an object")
|
||||
if (value.object !== "list") throw new Error("Expected models response object to be 'list'")
|
||||
|
||||
const data = value.data
|
||||
if (!Array.isArray(data)) throw new Error("Expected models response data to be an array")
|
||||
|
||||
return data.map(parseApiModel).map((model) => ({
|
||||
id: model.id,
|
||||
name: `${model.name} (CC)`,
|
||||
reasoning: true,
|
||||
contextWindow: model.contextLength,
|
||||
maxTokens: Math.min(model.contextLength, DEFAULT_MAX_OUTPUT_TOKENS),
|
||||
}))
|
||||
}
|
||||
|
||||
export async function fetchCommandCodeModels(
|
||||
options: FetchCommandCodeModelsOptions = {},
|
||||
): Promise<readonly CommandCodeModel[]> {
|
||||
const url = options.url ?? DEFAULT_MODELS_URL
|
||||
const fetchImpl = options.fetchImpl ?? fetch
|
||||
const response = await fetchImpl(url, {
|
||||
headers: {
|
||||
accept: "application/json",
|
||||
},
|
||||
})
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(
|
||||
`Failed to fetch Command Code models: ${response.status} ${response.statusText}`,
|
||||
)
|
||||
}
|
||||
|
||||
const body: unknown = await response.json()
|
||||
return commandCodeModelsFromApiResponse(body)
|
||||
}
|
||||
Reference in New Issue
Block a user