
autobe
AI Vibe Coding Agent of TS backend server, enhanced by compiler skills, generating 100% working code
Stars: 592

AutoBE is an AI-powered no-code agent that builds backend applications, enhanced by compiler feedback. It automatically generates backend applications using TypeScript, NestJS, and Prisma following a waterfall development model. The generated code is validated by review agents and OpenAPI/TypeScript/Prisma compilers, ensuring 100% working code. The tool aims to enable anyone to build backend servers, AI chatbots, and frontend applications without coding knowledge by conversing with AI.
README:
flowchart
subgraph "Backend Coding Agent"
coder("Facade Controller")
end
subgraph "Functional Agents"
coder --"Requirements Analysis"--> analyze("Analyze")
coder --"ERD"--> prisma("Prisma")
coder --"API Design"--> interface("Interface")
coder --"Test Codes" --> test("Test")
coder --"Main Program" --> realize("Realize")
end
subgraph "Compiler Feedback"
prisma --"validates" --> prismaCompiler("Prisma Compiler")
interface --"validates" --> openapiValidator("OpenAPI Validator")
interface --"generates" --> tsCompiler("TypeScript Compiler")
test --"validates" --> tsCompiler("TypeScript Compiler")
realize --"validates" --> tsCompiler("TypeScript Compiler")
end
An AI-powered no-code agent that builds backend applications, enhanced by compiler feedback.
@autobe
is a no-code AI agent that analyzes user requirements and automatically generates backend applications using the stack below, following a waterfall development model. Since @autobe
-generated code is validated by review agents and OpenAPI/TypeScript/Prisma compilers, it delivers 100% working code.
- TypeScript
- NestJS
- Prisma (Postgres / SQLite)
https://github.com/user-attachments/assets/b995dd2a-23bd-43c9-96cb-96d5c805f19f
https://stackblitz.com/github/wrtnlabs/autobe-playground-stackblitz
Experience the @autobe
agent through our interactive playground above.
To see examples of backend applications generated by @autobe
, explore these interactive demos. These showcase @autobe
's ability to generate production-ready backend code with proper structure, API documentation, TypeScript interfaces, and e2e test functions.
- Discussion Board: https://github.com/wrtnlabs/autobe-example-bbs
- To Do List: https://github.com/wrtnlabs/autobe-example-todo
- Reddit Community: https://github.com/wrtnlabs/autobe-example-reddit
-
E-Commerce: https://github.com/wrtnlabs/autobe-example-shopping
- Requirements Analysis: Report
- Database Design: Entity Relationship Diagram / Prisma Schema
- API Design: API Controllers / DTO Structures
- E2E Test Functions:
test/features/api
- API Impelementations:
src/providers
- AI Review: AI_REVIEW.md
If you're unsure what to try, start with the BBS example script below.
- I want to create a political/economic discussion board. Since I'm not familiar with programming, please write a requirements analysis report as you see fit.
- Design the database schema.
- Create the API interface specification.
- Make the e2e test functions.
- Implement API functions.
By the way, when you want to run @autobe
on your local machine (for using Local LLMs or when the playground website isn't working), you can set it up with the following commands:
git clone https://github.com/wrtnlabs/autobe
cd autobe
pnpm install
pnpm run playground
Find comprehensive resources at our official website.
- ππ»ββοΈ Introduction
- π¦ Setup
- π Concepts
- π€ Agent Library
- π‘ WebSocket Protocol
- π οΈ Backend Stack
- π No-Code Ecosystem
- π Roadmap
- π§ API Documentation
A 70-year-old grandmother who grows tomatoes in the countryside created an online debate website in just 10 minutes. Despite being unfamiliar with coding or computers, she built this current affairs and economics discussion community simply by talking with Wrtn's AI. What's remarkable is that users can write posts and comments entirely through voice commands and even engage in current affairs debates with AI.
The next day, the grandmother spent another 20 minutes launching an agricultural products shopping mall. Customers can simply say "I'd like to order 2kg of tomatoes" to complete their purchase, while the grandmother manages everything from orders and shipping to inventory through simple chat conversations.
This is the vision that we, the WrtnLabs team, are pursuing. We aim to create a world where anyone can build backend servers, AI chatbots, and frontend applications without any coding knowledgeβsimply by conversing with AI.
To realize this vision, the WrtnLabs team is developing two additional projects: @agentica
and @autoview
.
-
@agentica
: Automatically creates AI chatbots when you provide aswagger.json
file -
@autoview
: Automatically generates frontend applications when you provide aswagger.json
file
You're not limited to just creating backends with @autobe
. Once you've built a no-code backend application through @autobe
, you can immediately create an AI chatbot and frontend applications alongside it.
Can you converse? Then you're a full-stack developer.
import { Agentica, assertHttpController } from "@agentica/core";
import OpenAI from "openai";
import typia from "typia";
import { MobileFileSystem } from "./services/MobileFileSystem";
const agent = new Agentica({
vendor: {
api: new OpenAI({ apiKey: "********" }),
model: "gpt-4o-mini",
},
controllers: [
// functions from TypeScript class
typia.llm.controller<MobileFileSystem, "chatgpt">(
"filesystem",
MobileFileSystem(),
),
// functions from Swagger/OpenAPI
assertHttpController({
name: "shopping",
model: "chatgpt",
document: await fetch(
"https://shopping-be.wrtn.ai/editor/swagger.json",
).then(r => r.json()),
connection: {
host: "https://shopping-be.wrtn.ai",
headers: { Authorization: "Bearer ********" },
},
}),
],
});
await agent.conversate("I wanna buy MacBook Pro");
gantt
dateFormat YYYY-MM-DD
title AutoBE Roadmap for Beta Release
section Analyze Agent
Debate Enhancement: done, 2025-06-01, 7d
Prefix Rule: done, 2025-06-12, 7d
Multimodal: done, 2025-07-02, 31d
section Prisma Agent
Compiler Development: done, 2025-06-01, 14d
Prohibition Rule: done, 2025-06-08, 7d
SQLite Support: done, 2025-06-16, 7d
Review Agent: done, 2025-08-04, 13d
section Interface Agent
Keyworded SDK: done, 2025-06-01, 10d
Authorization: done, 2025-06-19, 18d
Snapshot Logic: done, 2025-06-23, 14d
Review Agent: done, 2025-08-04, 13d
Authorization: done, 2025-08-04, 27d
section Test Agent
Scenario Agent: done, 2025-06-01, 10d
Coding Agent: done, 2025-06-12, 14d
Compiler Feedback: done, 2025-06-12, 14d
Function Calling: done, 2025-06-18, 14d
Compiler Development: done, 2025-07-02, 60d
Authorization: done, 2025-08-04, 27d
section Realize Agent
Planner Agent: done, 2025-07-02, 30d
Coding Agent: done, 2025-07-02, 30d
Compiler Feedback: done, 2025-07-17, 15d
Function Calling: done, 2025-07-17, 31d
Runtime Validation: done, 2025-08-01, 30d
section VSCode Extensions
Interlocking VSCode: done, 2025-08-01, 1d
Interlocking React for WebView: done, 2025-08-04, 2d
Connect autobe without event listener: done, 2025-08-06, 2d
File System: done, 2025-08-11, 5d
Connect personal LLM: done, 2025-08-18, 4d
Apply a lot of AutoBE events: done, 2025-08-25, 5d
section Complementation
Benchmark: done, 2025-06-12, 50d
Demonstration: done, 2025-06-16, 14d
Documentation: done, 2025-06-16, 45d
Articles: done, 2025-07-02, 61d
Review Agent: done, 2025-07-02, 45d
Maintenance: done, 2025-08-01, 30d
section Ecosystem
Agentica Prerequisite: done, 2025-06-18, 13d
WebSocket Streaming (Deprecated): crit, 2025-07-02, 14d
History Manipulation: done, 2025-07-16, 30d
AI Chatbot Development (Deprecated): crit, 2025-07-16, 30d
Data Seeder Agent (Deprecated): crit, 2025-08-01, 30d
@autobe
's comprehensive three-month beta development roadmap spans from 2025-06-01 through 2025-08-31, marking a critical phase in our journey toward production readiness.
Following the successful completion of our alpha release on 2025-05-31, we have established a robust foundation with fully developed Analysis, Prisma, and Interface Agents. These core components have successfully automated the most complex challenges in backend development: comprehensive requirements analysis, intelligent database architecture, and seamless API design. This achievement represents a significant milestone in our mission to completely automate backend application design.
The upcoming beta phase strategically focuses on delivering and refining the Test Agent and Realization Agent while ensuring system-wide stability and performance optimization across the entire @autobe
ecosystem. Our ambitious target for 2025-08-31 is to achieve a breakthrough: a 100% reliable No-Code Agent platform that can autonomously handle any backend application development challenge without human intervention.
@autobe
and all backend applications generated by @autobe
are licensed under the GNU Affero General Public License v3.0 (AGPL-3.0). Additionally, any client applications that interact with @autobe
-generated backend servers are also subject to AGPL-3.0 licensing requirements due to the copyleft nature of the license.
For those who wish to avoid open source disclosure obligations, commercial licenses are available for purchase (coming soon).
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