正在加载视频...

视频加载失败

Code Arena just leveled up with fullstack capabilities 🚀 Introducing the new Fullstack Code Arena. We’re moving beyond frontend prototypes to fullstack development complete with databases, API keys, and fast deployments. Build, iterate, and ship real-world software — all in one place. Models now act as agents in the...

288,910 次观看 • 3 个月前 •via X (Twitter)

17 条评论

Arena.ai 的头像
Arena.ai3 个月前

With Fullstack, we now support building more complex apps that require database or backend functionality. Code Arena now powers building a whole new suite of apps you couldn’t before, including: - Apps that require a sign up or login flow, such as admin portals or dashboards - Apps that use an API key, like an AI chatbot - Apps that store a user’s progress for them to come back to, such as an online education or teaching app This changes Code Arena from more of an experimental prototyping environment to a daily-use tool where real work gets done. The votes will power a future Fullstack leaderboard. Click through to our YouTube to watch the full walkthrough of Fullstack Code Arena:

Arena.ai 的头像
Arena.ai3 个月前

Code Arena now goes beyond frontend prototypes. Read more about all the new fullstack features in our blog:

Arena.ai 的头像
Arena.ai3 个月前

Get testing and building with the new Fullstack Code Arena at:

Hussain Hashim | Building SundayBack 的头像
Hussain Hashim | Building SundayBack3 个月前

@arena dude, this is huge! finally a place to play with fullstack ideas without setting up a billion things first. gonna save so much time 🏆

BlakeTheCoder 的头像
BlakeTheCoder3 个月前

Honestly insane we're going from frontend mockups to agents deploying fullstack with real DBs. What happens when an agent hits a prod edge case though? Human override or full automation?

Vlad Oleksiienko 的头像
Vlad Oleksiienko3 个月前

Good move. Frontend-only benchmarks stopped meaning much a while ago. Real work is databases, auth, deploys, all the boring plumbing. Testing models on "can it ship" instead of "can it code" is the right bar.

Yaroslav 的头像
Yaroslav3 个月前

do you guys realize how hard it is for a general user to comprare two sometimes huge stacks? their voting wouldn't really show the actual thing, unless it is just about the looks and functionality, if that's what you're targetting here.

AI Mastery Guide 的头像
AI Mastery Guide3 个月前

Moving from frontend prototypes to full databases and deployments is a big jump for a benchmark tool.

Ian Channing 🦈@ianchanning@mastodon.social 的头像
Ian Channing 🦈@[email protected]2 个月前

Can we have the reverse of this, where you vary the fullstack framework for each model.

Lucas Jenkins 的头像
Lucas Jenkins2 个月前

yo

RAZA | AI EXPLORER 的头像
RAZA | AI EXPLORER3 个月前

Huge upgrade.

Ava Bryant 的头像
Ava Bryant2 个月前

wow

Lucas Powell 的头像
Lucas Powell2 个月前

hey

Alice The Ai Expert 的头像
Alice The Ai Expert3 个月前

Amazing Code Arena Fullstack unlocked DBs, APIs, live deploys + agent tool calls. Prototype → ship, all in one place

Ava Bryant 的头像
Ava Bryant2 个月前

hi

Nobita 的头像
Nobita3 个月前

I think this will produce thr most realistic insights on model capabilities.

Gregor 的头像
Gregor3 个月前

When I wired up database auth in a fast-deploy sandbox, service_role was the default that bit me. It bypasses RLS entirely, looks clean in preview, and exposes every row to every authenticated user once it's live.

相关视频

New short course: Building Code Agents with Hugging Face smolagents! Learn how to build code agents in this course, created in collaboration with Hugging Face, and taught by Thomas Wolf, its co-founder and CSO, and m_ric, Hugging Face’s Project Lead on Agents. Tool-calling agents use LLMs to generate multiple function calls sequentially to complete a complex sequence of tasks. They generate one function call, execute it, observe, reason, and decide what to do next. Code agents take a different approach. They consolidate all these calls into a single block of code, letting the LLM lay out an entire action plan at once, which can be executed efficiently to provide more reliable results. You’ll learn how to code agents using smolagents, a lightweight agentic framework from Hugging Face. Along the way, you’ll learn how to run LLM-generated code safely and develop an evaluation system to optimize your code agent for production. In detail, you’ll learn: - How agentic systems have evolved, gaining greater levels of agency over time—and why code agents are a next step. - How code agents write their actions in code. - When code agents outperform function-calling agents. - How to run code agents safely in your system using a constrained Python interpreter and sandboxing using E2B. - To trace, debug, and assess the code agent to optimize its behaviours for complex requests. - How to build a research multi-agent system that can find information online and organize it into an interactive report. By the end of this course, you’ll know how to build and run code agents using smolagents, and deploy them safely with a structured evaluation system in your projects. Please sign up here!

Andrew Ng

127,724 次观看 • 1 年前