世界数字智能体网 digitalagent.world

描述需求，我们搭一个真正属于你的智能体Describe a need, we build an agent you actually own

两条路，任选一条：① 选一个现成成品，直接交付；② 用大白话跟 AI 对话，按你的需要设计。同一套引擎，同一个账户，同一个算力钱包。Two ways in: pick a ready-made product, or describe your need in plain words and let the AI design it. One engine, one account, one compute wallet.

选现成成品Browse ready-made 跟 AI 对话定制Design it by chatting 登录 / 充值算力Log in / top up compute
20现成成品模板ready-made templates
661K+借鉴的开源底座 star 数stars of the open-source bases we borrow
10算力起（成品）compute to start (ready-made)
42算力（定制全流程）compute (full custom pipeline)

同一个账户 · 同一个算力钱包One account · one compute wallet

矩阵里每个站共用同一套引擎和同一个交付中心。你在任一站充值算力，另一站直接可用。Every site in the matrix shares one engine and one delivery centre. Compute you top up on one site works on the others.

工具网

你想要什么软件，功能按你的问题定制，排版也先问你。Tell us what software you want: features from your problem, layout asked of you first.

机器人网

说场景，我们给图纸、材料清单和 AI 大脑，硬件你自己买。Describe the scenario; we deliver drawings, a parts list and an AI brain. You buy the hardware.

数字经济教育

数字经济知识、案例与术语，免费学，不卖课。Digital-economy knowledge, cases and terms — free to learn, no courses sold.

最强开源底座（实测数据，2026-10-17 GitHub API）Strongest open-source bases (verified via GitHub API, 2026-10-17)

我们不从零造轮子：先选最强的开源代码做基础，再按你的需求改。We do not reinvent the wheel: we start from the strongest open-source code, then adapt it to your need.

langgenius/dify

158,716 stars · open (extra terms)
可视化编排 + 知识库 + 模型路由

browser-use/browser-use

118,322 stars · MIT
浏览器智能体：自动操作网页

OpenHands/OpenHands

91,128 stars · MIT
AI 软件开发 agent，Docker 沙箱执行

FoundationAgents/MetaGPT

70,896 stars · MIT
PM→架构→工程师→QA 多角色协作做软件

crewAIInc/crewAI

59,798 stars · MIT
多 agent 角色编排

langchain-ai/langgraph

43,411 stars · MIT
resilient 工作流图，可持久记忆

OpenBMB/ChatDev

34,539 stars · Apache-2.0
问答→完整小软件（多角色）

agentscope-ai/agentscope

33,423 stars · Apache-2.0
可观测、可信任的 agent 框架

huggingface/smolagents

29,896 stars · Apache-2.0
轻量、代码式 agent，易本地跑

coze-dev/coze-studio

21,721 stars · Apache-2.0
零代码智能体平台，可离线部署

模板库：先选一个做好的Template library: start from something already built

跟 AI 对话，按你的需要设计Design it by talking to the AI

用大白话说你想要什么…Describe in plain words…"> 
{
  "site": "世界数字智能体网",
  "goal": "",
  "clarify": {},
  "engine_base": [
    "langgenius/dify",
    "browser-use/browser-use",
    "OpenHands/OpenHands"
  ],
  "compute_cost": "42 算力"
}

算力与模型：你选，直接登录直接充值Compute and models: you choose, log in and top up directly

直接登录 / 注册Log in / register 直接充值算力Top up compute 我的算力余额与 API KeyMy balance and API key
模型池与主站选器一致：自动 / 本地 Qwen3.8-27B / DeepSeek V4-Flash / DeepSeek V4-Pro / 你自己的模型。The model pool matches the picker already on digitalmarket.world: auto / local Qwen3.8-27B / DeepSeek V4-Flash / DeepSeek V4-Pro / your own model.

交付中心：你拿到什么Delivery centre: what you actually get

  • Docker 镜像 + 配置文件 + 提示词库 + 知识库Docker image + config + prompt library + knowledge base
  • 一键桌面版（双击即用）One-click desktop build
  • 傻瓜版与专业版两份部署指引Beginner and pro setup guides
下载一个真实交付包示例Download a real sample package 我的产出与算力My outputs and compute
计费规则：成本 1 元 = 10 算力，定价不低于成本 2 倍；成品统一 10 算力起，定制全流程 42 算力。Muse 建议免费，执行按算力计费。不承诺收益。Billing: 1 yuan cost = 10 compute, price never below 2x cost. Ready-made starts at 10 compute, the full custom pipeline is 42. Muse advice is free, execution is billed. No income promises.

常见问题FAQ

成品和定制有什么区别？What is the difference between ready-made and custom?

成品：选模板 → 扣 10 算力 → 直接下载交付包。定制：AI 追问澄清 → 方案预览 → 执行 → 交付，全流程 42 算力。Ready-made: pick a template, spend 10 compute, download the package. Custom: the AI clarifies, previews the plan, executes and delivers — 42 compute for the full pipeline.

我能接自己的模型吗？Can I use my own model?

可以。交付包里包含统一模型适配器，本地（Ollama / llama.cpp）或任意云端 API 都能接。Yes. The package ships a model adapter: local (Ollama / llama.cpp) or any cloud API.

我的数据会被拿去训练吗？Will my data be used for training?

知识库和提示词在你自己的机器上。我们接受搜索收录，不把用户私有数据用于模型训练。Your knowledge base and prompts live on your own machine. We allow search indexing; we do not use private user data for model training.