wanwu

🚀 3 Deployment Methods: Reach Business On‑Site

After capability building, Wanwu provides 3 deployment paths to minimize FDE delivery difficulty:

📦 Method 1: Out‑of‑the‑Box Platform

Use directly via visual interface; no coding required for creating agents, workflows, and Q&A. Zero‑threshold AI productivity for rapid on‑site validation and delivery.

🔗 Method 2: API Seamless Integration

RESTful API (BaaS) for embedding into OA, CRM, ERP, etc. Fine‑grained permission control enables deep AI integration without changing user habits.

🖥️Method 3: Skill + UniClaw Dedicated Client

For high‑privilege scenarios (local PC control, DingTalk messages, etc.). FDEs develop Skills and execute via UniClaw to handle cross‑system high‑privilege on‑site operations.

UniClaw download: https://maas.ai-yuanjing.com/app/uniclaw/uniclaw-official.html

🛠️ Infrastructure & Ecosystem

• 🔥 Apache‑2.0 License: Free extension, secondary development, and commercial use.
• ✔ Model Hub: Unified access to hundreds of proprietary/open‑source models; deep OpenAI API compatibility and Yuanjing ecosystem support; multiple inference backends.
• ✔ Skill Plaza: 100+ built‑in industry Skills ready to use; no adapters needed for external capabilities.
• ✔ Web Search: Real‑time information, multi‑source integration, intelligent retrieval strategies.
• ✔ Multi‑tenant architecture: Isolated accounts for cost control, data security, and elastic scaling.
• ✔ Xinchuang compliance: Certified Xinchuang AI Software/Hardware System Inspection Certificate. Supports Kunpeng CPUs, Euler, Kylin, CULinux, TiDB, OceanBase, etc.

🚀 Quick Start

• The workflow module of the Wanwu AI Agent Platform uses the following project, you can go to its warehouse to view the details.

  • v0.1.8 and earlier: wanwu-agentscope project
  • v0.2.0 and later: wanwu-workflow project

• Recommended Configuration:

  • CPU: 8-core or 16-core; RAM: 32GB; Storage: 200GB or more; GPU: Not required.

• Model Requirements:

  • When using WanwuBot (General Agent) or creating Skills with a single command, the selected model must have a context length >= 32000 when importing.

• Security Statement:

  • All middleware components (MySQL, Redis, MinIO, Kafka, Elasticsearch, etc.) support custom passwords configured in the .env file.
  • For front-end and back-end user password transmission, RSA asymmetric encryption is used to encrypt passwords. The key pair is automatically generated on first service startup; custom key pairs can also be configured via WANWU_BFF_LOGIN_RSA_PATH in .env.
  • It is strongly recommended to change all default passwords and keep them secure before deploying in a production environment to avoid security risks associated with default credentials.

• Docker Installation (Recommended)

1. Before the first run

   1.1 Copy the environment variable file

   cp .env.example .env
   

   1.2 Modify the WANWU_ARCH and WANWU_EXTERNAL_IP variables in the .env file according to the system

   # amd64 / arm64
   WANWU_ARCH=amd64
   
   # external ip port (Note: if the browser accesses Wanwu deployed on a non-localhost server, you need to change localhost to the external IP, for example, 192.168.xx.xx)
   WANWU_EXTERNAL_IP=localhost
   

   1.3 Configure the WANWU_BFF_JWT_SIGNING_KEY variable in the .env file, a custom complex random string used for generating JWT tokens

   # bff
   WANWU_BFF_JWT_SIGNING_KEY=
   

   1.4 Copy environment variable file (Ontology Agent)

   cp .env.ontology.example .env.ontology
   

   1.5 (Optional) Generate custom RSA keys before the first run (Ontology Agent)

   Skip this step to use the default keys baked into the images. To use independent keys in production, generate them as follows.

   • 1.5.1 Generate RSA ke