Create browser automation as if you were teaching a human using GPT-4 Vision.
vignshwarar/AI-Employe 排名第 16,591,有 583 个星标。
同类别比较
vignshwarar/AI-Employe 排名第 16,591,此处有 8 个同类条目;agentic-in/elephant-agent 排名第 16,595。
同类别比较| 名称 | 排名 | 指标 |
|---|
| rokpiy/auto-commenter | 16,555 | - 星标数:
- 585
- 分叉数:
- 111
- 简介:
- A Claude skill that automatically posts personalized, authentic comments in your target communities.
|
|---|
| biaogebusy/web-builder | 16,568 | - 语言:
- TypeScript
- 星标数:
- 584
- 分叉数:
- 99
- 简介:
- AI 驱动 UI 生成和发布的低代码平台,基于TailwindCss,通过拖拽可视化快速构建现代化响应式UI、动态自定义组件、多主题、多语言的网站应用。AI-powered UI generation and publishing low code platform, built on TailwindCSS, enabling rapid drag-and-drop visual creation of modern responsive UIs, dynamic customizable components, multi-theme, and multi-language web applications.
|
|---|
| brianxiadong/auto-paper-digest | 16,569 | - 语言:
- Python
- 星标数:
- 584
- 分叉数:
- 54
- 简介:
- auto-paper-digest: An automated pipeline that tracks Hugging Face weekly AI papers, downloads PDFs, imports them into NotebookLM, generates video overviews, and archives everything into a searchable weekly digest.
|
|---|
| kac89/vulnrepo | 16,575 | - 语言:
- TypeScript
- 星标数:
- 584
- 分叉数:
- 117
- 简介:
- VULNRΞPO - Free vulnerability report generator and repository, end-to-end encrypted! Templates of issues, CWE,CVE,MITRE ATT&CK,PCI DSS, import Nmap/Nessus/Burp/OpenVAS/Bugcrowd/Trivy, Jira export, TXT/JSON/MARKDOWN/HTML/DOCX, attachments, automatic changelog, stats, vulnerability management, bugbounty, local ai/llm, super fast pentest reporting!
|
|---|
| agentic-in/elephant-agent | 16,595 | - 语言:
- Python
- 星标数:
- 582
- 分叉数:
- 62
- 简介:
- Personal-Model First Self Evolving AI Agent 🐘
|
|---|
| devflowinc/uzi | 16,597 | - 语言:
- Go
- 星标数:
- 582
- 分叉数:
- 28
- 简介:
- CLI for running large numbers of coding agents in parallel with git worktrees
|
|---|
| microsoft/AI2BMD | 16,605 | - 语言:
- Python
- 星标数:
- 582
- 分叉数:
- 85
- 简介:
- AI-powered ab initio biomolecular dynamics simulation
|
|---|
| KelvinQiu802/llm-mcp-rag | 16,614 | - 语言:
- TypeScript
- 星标数:
- 581
- 分叉数:
- 97
- 简介:
- LLM + MCP + RAG = Magic
|
|---|
关键参数与规格
关键参数与规格| 参数 | 值 |
|---|
| 语言 | TypeScript |
|---|
| 类别 | Applications |
|---|
| 子类别 | Productivity |
|---|
| 关键词 | Automation, Browser |
|---|
| 星标数 | 583 |
|---|
| 分叉数 | 52 |
|---|
| 贡献者 | 1 |
|---|
| 创建日期 | 2023-12-21 |
|---|
| 更新日期 | 2026-10-13 |
|---|
| 1 天星标数 | 0 |
|---|
| 7 天星标数 | -1 |
|---|
| 排名 | 16,591 |
|---|
| 上次排名 | 16,382 |
|---|
| 排名变化 | -209 |
|---|
| 7 天星标排名 | 17,914 |
|---|
| 上次 7 天星标排名 | 17,861 |
|---|
| 7 天星标排名变化 | -53 |
|---|
| 总星标排名 | 17,174 |
|---|
| 上次总星标排名 | 17,146 |
|---|
| 总星标排名变化 | -28 |
|---|
| 国家 | France |
|---|
README 摘录
Install Try without Firebase authentication (temporary solution): Our stack consists of Next. js, Rust, Postgres, MeiliSearch, and Firebase Auth for authentication. Please sign up for a Firebase account and create a project. In Firebase, navigate to Project settings -> Service accounts, generate a private key, and save it inside if it's for development or prod. After that, make sure you install the dependencies before starting the app. env file with your credentials Run Run Run (for development) Run (for production) Run
(for production) Once you have run 'dev' or 'build', you will find the extension built inside the folder. You can then load this folder as an unpacked extension in your browser. How it Works There are several problems with current browser agents. Here, we explain the problems and how we have solved them. Problem 1: Finding the Right Element There are several techniques for this, ranging from sending a shortened form of HTML to GPT-3, creating a bounding box
with IDs and sending it to GPT-4-vision to take actions, or directly asking GPT-4-vision to obtain the X and Y coordinates of the element. However, none of these methods were reliable; they all led to hallucinations. To address this, we developed a new technique where we index the entire DOM in MeiliSearch, allowing GPT-4-vision to generate commands for which element's inner text to click, copy, or perform other actions. We then search the index
with the generated text and retrieve the element ID to send back to the browser to take action. There are a few limitations here, but we have implemented some techniques to overcome them, such as dealing with the same text in multiple elements or clicking on an icon (we are still working on this). Problem 2: GPT Derailing from Workflow To prevent GPT from derailing from tasks, we use a technique that is akin to retrieval-augmented generation, but we
kind of call it Actions Augmented Generation. Essentially, when a user creates a workflow, we don't record the screen, microphone, or camera, but we do record the DOM element changes for every action (clicking, typing, etc. We then use the workflow title, objective, and recorded actions to generate a set of tasks. Whenever we execute a task, we embed all the actions the user took on that particular domain with the prompt. This way, GPT stays on track with the
task, even if the user has not provided a very brief title and objective; their actions will guide GPT to complete the task. Roadmap [x] Workflows [x] Chat with what you see [ ] More actions support scrolling, opening links in a new tab, etc. [ ] Loop in workflows [ ] Clever Tab management [ ] Share workflows [ ] Open source models support [ ] Community shared workflows [ ] Cloud version of AI Employe [ ] Control browser by text [ ] Control browser by voice [ ] more to come.
常见问题
记录了多少星标和分叉?
vignshwarar/AI-Employe 有 583 个星标和 52 个分叉。
仓库排名是多少?
vignshwarar/AI-Employe 排名第 16,591。
记录的语言和类别是什么?
vignshwarar/AI-Employe 有 583 个星标,语言为 TypeScript,类别为 Applications。
哪个仓库排名最接近?
vignshwarar/AI-Employe 与 agentic-in/elephant-agent 比较,后者排名第 16,595,有 582 个星标。
Install
Try without Firebase authentication (temporary solution): https://github.com/vignshwarar/AI-Employe/issues/2#issuecomment-1880328518
Our stack consists of Next.js, Rust, Postgres, MeiliSearch, and Firebase Auth for authentication. Please sign up for a Firebase account and create a project.
In Firebase, navigate to Project settings -> Service accounts, generate a private key, and save it inside firebaseAdmin/cert/dev.json if it's for development or prod.json if it's for production.
After that, make sure you install the dependencies before starting the app.
- Copy the the .env.sample file to .env.production or .env.development
- Fill the .env file with your credentials
- Run
npm install
- Run
npm run db:deploy
- Run
npm run dev (for development)
- Run
npm run build (for production)
- Run
npm run start (for production)
Once you have run 'dev' or 'build', you will find the extension built inside the ./client/extension/build folder. You can then load this folder as an unpacked extension in your browser.
How it Works
There are several problems with current browser agents. Here, we explain the problems and how we have solved them.
Problem 1: Finding the Right Element
There are several techniques for this, ranging from sending a shortened form of HTML to GPT-3, creating a bounding box with IDs and sending it to GPT-4-vision to take actions, or directly asking GPT-4-vision to obtain the X and Y coordinates of the element. However, none of these methods were reliable; they all led to hallucinations.
To address this, we developed a new technique where we index the entire DOM in MeiliSearch, allowing GPT-4-vision to generate commands for which element's inner text to click, copy, or perform other actions. We then search the index with the generated text and retrieve the element ID to send back to the browser to take action. There are a few limitations here, but we have implemented some techniques to overcome them, such as dealing with the same text in multiple elements or clicking on an icon (we are still working on this).
Problem 2: GPT Derailing from Workflow
To prevent GPT from derailing from tasks, we use a technique that is akin to retrieval-augmented generation, but we kind of call it Actions Augmented Generation. Essentially, when a user creates a workflow, we don't record the screen, microphone, or camera, but we do record the DOM element changes for every action (clicking, typing, etc.) the user takes. We then use the workflow title, objective, and recorded actions to generate a set of tasks. Whenever we execute a task, we embed all the actions the user took on that particular domain with the prompt. This way, GPT stays on track with the task, even if the user has not provided a very brief title and objective; their actions will guide GPT to complete the task.
Roadmap
- [x] Workflows
- [x] Chat with what you see
- [ ] More actions support scrolling, opening links in a new tab, etc.
- [ ] Loop in workflows
- [ ] Clever Tab management
- [ ] Share workflows
- [ ] Open source models support
- [ ] Community shared workflows
- [ ] Cloud version of AI Employe
- [ ] Control browser by text
- [ ] Control browser by voice
- [ ] more to come...