Branch-length batch covering tooling, the model layer, the Web App and the public surfaces. Highlights: - Changelog: a per-release `changelog/<version>/` tree, grouped by the surface each change touches, with a root CHANGELOG.md holding one line per release. - Dev startup: `scripts/dev-prebuild.mjs` serializes the skills+core prebuild behind a lock and keeps `pnpm install` current; `pnpm dev` runs server+web together. - AgentHub 0.3.3 -> 0.4.0: OmniMessage complete payloads carry one opaque `fidelity` object in place of item-level `signature`/`phase`, threaded verbatim through Trace, replay and resume; malformed classification adapted to the new error types. - Model layer: a model is always referenced by an explicit `(provider, model_id)` pair. The provider is never inferred, guessed or defaulted -- both the catalog inference and the unique-match config resolution are gone, and CLI, SDK, server routes and run_subagent all require the complete pair. Catalog gains the Qwen Token Plan, Qwen Pay-As-You-Go and Fireworks AI gateways, plus an expanded OpenRouter group. - Web App: catalog preset sync and per-group speed test on the Models page, positional slash commands, a markdown renderer, skill-library update reminders, and a vertically centred draft page whose upward menus size themselves to the room available. - Public surfaces: restructured READMEs, the penguin.ooo landing site and blog, refreshed benchmark results for both suites, and the demo videos playing on the landing page. Includes the fixes from a full review of the branch: 23 confirmed findings, among them a provider-inference bug that could send one vendor's API key to another vendor's endpoint, and an Escape handler that destroyed the composer's contents unrecoverably. Verified on the branch head: pnpm test (1127 passing, 7 packages), pnpm typecheck and pnpm format:check clean, Playwright e2e 14/14.
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title, date, category, excerpt
| title | date | category | excerpt |
|---|---|---|---|
| 携手 AMD 开发者计划:免费领取 $50 Fireworks 额度,直连 PenguinHarness | 2026-07-20 | news | 我们很高兴与 AMD AI Developer Program 合作,为大家带来 Fireworks 的免费兑换码——按本文申请 $50 Credits,再在 PenguinHarness 里三步用起来。 |
我们很高兴与 AMD AI Developer Program(AMD 开发者计划)合作,为大家带来 Fireworks 的免费兑换码:加入计划并通过审核,即可获得可兑换 $50 Fireworks AI Credits 的 Coupon Code。PenguinHarness 内置 Fireworks AI 网关分组——OpenAI 协议、预置 base URL 与五个模型,额度到手即刻可用。
页面内容、Credits 金额与有效期可能调整,请以申请时的页面及审批邮件为准。
第一步:加入 AMD AI Developer Program
访问官方入口:https://developer.amd.com/ai-developer-program/,在 Join the AMD AI Developer Program 区域:
- 没有 AMD ADP 账户:点击 Create Account,填写个人信息创建账户;
- 已有账户:点击 Log In,按页面提示登录。
第二步:在 Member Perks 申请 Cloud Credits
注册并登录后:
- 点击顶部导航栏中的 Member Perks;
- 找到 Cloud Credit Options;
- 点击底部的 Request Cloud Credits。
第三步:填写申请表
进入申请表后填写个人信息:
- Product Needed 处选择 Fireworks AI;
- Profile 处提供至少一个公开资料用于账户验证:LinkedIn、GitHub、Portfolio、公司 / 学校主页、WeChat、WeCom 等均可。
填完页面中其他带 * 的必填项,检查邮箱、身份、产品选项与公开资料链接无误后提交。
第四步:等待审核
AMD 会验证账户与申请资料,通常需要 2–3 个工作日;实际时间可能因申请量、资料完整度或节假日而变化。
第五步:收到兑换码并兑换
审核通过后,AMD 会向申请邮箱发送包含唯一 Coupon Code 的邮件,可兑换 $50 Fireworks AI Credits。请妥善保存,不要公开、转发或提交到代码仓库。
兑换与创建 API key:
- 打开 https://fireworks.ai/ 并登录;
- 点击 Redeem Promo,输入邮件中的 Coupon Code,兑换 $50 Credits;
- 点击 Create API Key,生成 Fireworks API key。
在 PenguinHarness 中用起来
拿到 API key 后,三步接入:
1. 安装并启动
curl -fsSL https://penguin.ooo/install.sh | sh
penguin web # 打开 http://127.0.0.1:7364(首次登录:admin / penguin-2026)
2. 配置 Fireworks 模型
进入「模型仓库」页,找到 Fireworks AI 分组,点击「统一配置 key」粘贴刚创建的 API key。分组预置了五个模型——GLM 5.2、Kimi K2.7 Code、DeepSeek V4 Pro、MiniMax M3、DeepSeek V4 Flash——base URL 与价格已填好,任选一个设为默认即可;也可以点组头的「测速」,实测各模型的 TTFT 与 TPS 再决定。
3. 开始使用
回到对话页,把第一个任务交给 Agent——例如「分析 data.csv,输出各季度销售额汇总」。
参考链接
- AMD AI Developer Program
- AMD 官方 Cloud Credits 申请视频演示
- 申请步骤与截图整理自 WhatGhost 的申请指南(中文 / English),感谢原作者
- PenguinHarness 模型配置文档