GitHub Copilot - Unhide MiniMax Models

Injects MiniMax M2.5 models into GitHub Copilot model picker

You will need to install an extension such as Tampermonkey, Greasemonkey or Violentmonkey to install this script.

You will need to install an extension such as Tampermonkey to install this script.

You will need to install an extension such as Tampermonkey or Violentmonkey to install this script.

You will need to install an extension such as Tampermonkey or Userscripts to install this script.

You will need to install an extension such as Tampermonkey to install this script.

You will need to install a user script manager extension to install this script.

(Tôi đã có Trình quản lý tập lệnh người dùng, hãy cài đặt nó!)

You will need to install an extension such as Stylus to install this style.

You will need to install an extension such as Stylus to install this style.

You will need to install an extension such as Stylus to install this style.

You will need to install a user style manager extension to install this style.

You will need to install a user style manager extension to install this style.

You will need to install a user style manager extension to install this style.

(I already have a user style manager, let me install it!)

// ==UserScript==
// @name         GitHub Copilot - Unhide MiniMax Models
// @namespace    creos
// @version      1.3
// @description  Injects MiniMax M2.5 models into GitHub Copilot model picker
// @match        https://github.com/*
// @run-at       document-start
// @grant        none
// ==/UserScript==

(function () {
  'use strict';

  const script = document.createElement('script');
  script.textContent = `
(function () {
  const MINIMAX_MODELS = [
    {
      "id": "minimax-m2p5-fw",
      "name": "MiniMax M2.5",
      "object": "model",
      "vendor": "Fireworks",
      "version": "minimax-m2p5-fw",
      "preview": false,
      "model_picker_enabled": true,
      "model_picker_category": "powerful",
      "is_chat_default": false,
      "is_chat_fallback": false,
      "policy": { "state": "enabled", "terms": "" },
      "supported_endpoints": ["/chat/completions"],
      "capabilities": {
        "family": "minimax-m2p5-fw",
        "object": "model_capabilities",
        "type": "chat",
        "tokenizer": "o200k_base",
        "limits": {
          "max_context_window_tokens": 196608,
          "max_output_tokens": 32000,
          "max_prompt_tokens": 164000
        },
        "supports": {
          "streaming": true,
          "tool_calls": true,
          "parallel_tool_calls": true,
          "structured_outputs": true,
          "reasoning_effort": ["low", "medium", "high"]
        }
      },
      "billing": { "is_premium": false, "multiplier": 1 }
    },
    {
      "id": "minimax-m2p5-cb",
      "name": "MiniMax M2.5 (Fast)",
      "object": "model",
      "vendor": "Cerebras",
      "version": "minimax-m2p5-cb",
      "preview": false,
      "model_picker_enabled": true,
      "model_picker_category": "powerful",
      "is_chat_default": false,
      "is_chat_fallback": false,
      "policy": { "state": "enabled", "terms": "" },
      "supported_endpoints": ["/chat/completions"],
      "capabilities": {
        "family": "minimax-m2p5-cb",
        "object": "model_capabilities",
        "type": "chat",
        "tokenizer": "o200k_base",
        "limits": {
          "max_context_window_tokens": 196608,
          "max_output_tokens": 32000,
          "max_prompt_tokens": 164000
        },
        "supports": {
          "streaming": true,
          "tool_calls": true,
          "parallel_tool_calls": true,
          "structured_outputs": true,
          "reasoning_effort": ["low", "medium", "high"]
        }
      },
      "billing": { "is_premium": false, "multiplier": 1 }
    }
  ];

  function injectOrPatch(json) {
    const list = json?.data ?? (Array.isArray(json) ? json : null);
    if (!list) return null;

    // Patch existing MiniMax entries, or inject if missing
    const existingIds = new Set(list.map(m => m.id));
    const patched = list.map(m =>
      m.id?.includes('minimax') || m.id?.includes('m2p5')
        ? { ...m, model_picker_enabled: true, preview: false }
        : m
    );

    MINIMAX_MODELS.forEach(m => {
      if (!existingIds.has(m.id)) {
        console.log('[MiniMax Unhide] Injecting:', m.name);
        patched.push(m);
      }
    });

    return Array.isArray(json) ? patched : { ...json, data: patched };
  }

  const MODELS_URL = 'api.individual.githubcopilot.com/models';

  const _fetch = window.fetch;
  window.fetch = async function (...args) {
    const url = (typeof args[0] === 'string' ? args[0] : args[0]?.url) ?? '';
    const res = await _fetch.apply(this, args);

    if (url.includes(MODELS_URL)) {
      console.log('[MiniMax Unhide] Intercepted models API');
      try {
        const json = await res.clone().json();
        const result = injectOrPatch(json);
        if (result) {
          console.log('[MiniMax Unhide] Injected MiniMax models successfully');
          return new Response(JSON.stringify(result), {
            status: res.status,
            statusText: res.statusText,
            headers: res.headers,
          });
        }
      } catch (e) {
        console.error('[MiniMax Unhide] Error:', e);
      }
    }
    return res;
  };

  console.log('[MiniMax Unhide] v1.3 ready — watching for models API call');
})();
  `;

  (document.head || document.documentElement).appendChild(script);
  script.remove();
})();