Kweaver

<p align="center"> <picture> <source media="(prefers-color-scheme: dark)" srcset="./assets/logo/dark.png" /> <source media="(prefers-color-scheme: light)" srcset="./assets/logo/light.png" /> <img alt="KWeaver" src="./assets/logo/light.png" width="320" /> </picture> </p>

中文 | English

The KWeaver project includes KWeaver Core and KWeaver DIP.

KWeaver Core is a harness-first foundation for enterprise decision agents. It turns fragmented data, knowledge, tools, and policies into governed context, safe execution, and verifiable feedback loops. With semantic modeling, real-time access, runtime control, and TraceAI, it helps AI systems reason, adapt, and act reliable in complex enterprises.

KWeaver DIP is an AI-native platform for developing and managing digital employees, built on business knowledge networks for understandable, executable, and governable enterprise intelligence.

📚 Quick Links

• 🌐 Live Demo - Try KWeaver online (username: kweaver, password: 111111)
• 🤝 Contributing - Guidelines for contributing to the project
• 🚢 Deployment - One-click deploy to Kubernetes
• 📘 Documentation - Product documentation and usage guides
• 📝 Blog - KWeaver technical articles and updates
• 🚀 Release Guidelines - Version management and release process
• 🏗️ Architecture - Architecture design specification
• 🧾 Changelog - All notable changes
• 📄 License - Apache License 2.0
• 🐛 Report Bug - Report a bug or issue
• 💡 Request Feature - Suggest a new feature

🎬 Demo Video

<div align="center"> <a href="https://www.bilibili.com/video/BV1nGXVBTEmo/?vd_source=4cdad687b2ac18a0b25e434f1fafe2f7" target="_blank"> <img src="./docs/demo-cover.png" alt="KWeaver Demo Video" width="75%"/> </a>

Click the image to watch the KWeaver demo on Bilibili

</div>

🚀 Quick Start

1. Source deployment: see the Deployment Guide.
2. Prerequisites: follow the prerequisites described in deploy/README.md.
3. Run installation scripts:

git clone https://github.com/kweaver-ai/kweaver.git
cd kweaver/deploy
chmod +x deploy.sh

# Full one-click deployment (recommended)
./deploy.sh kweaver-core install     # Infrastructure + KWeaver application services

./deploy.sh --help

4. Verify the deployment:

# Check cluster status
kubectl get nodes
kubectl get pods -A

# Check service status
./deploy.sh kweaver status

5. Access the system:
   • Deployment console: https://<node-ip>/deploy, account admin, initial password eisoo.com
   • KWeaver Studio: https://<node-ip>/studio

Platform Architecture

┌─────────────────────────────────────────────┐
│                 KWeaver                     │
│  ┌───────────────────────────────────────┐  │
│  │           KWeaver SDK                 │  │
│  ├───────────────────────────────────────┤  │
│  │           KWeaver DIP                 │  │
│  ├───────────────────────────────────────┤  │
│  │           KWeaver Core                │  │
│  └───────────────────────────────────────┘  │
└─────────────────────────────────────────────┘

Core Subsystems

| Sub-project | Description | Repository | | --- | --- | --- | | KWeaver SDK | CLI and SDK (TypeScript/Python) for AI agents and developers to access KWeaver knowledge networks and Decision Agents programmatically | kweaver-sdk | | KWeaver DIP | Include AI application and component marketplace, DIP Studio - Visual development and management interface | AI Store<br>DIP Studio| | KWeaver Core | AI-native platform foundation — Decision Agent, AI Data Platform (BKN Engine, VEGA Engine, Context Loader, Execution Factory), Info Security Fabric, Trace AI |ADP <br>Decision Agent <br>ISF <br>Trace AI |

KWeaver SDK

kweaver-sdk gives AI agents (Claude Code, GPT, custom agents, etc.) access to KWeaver knowledge networks and Decision Agents via the kweaver CLI. It also provides Python and TypeScript SDKs for programmatic integration.

AI Agent Skills

Install skills from kweaver-sdk with npx skills.

Install both skills at once (recommended):

npx skills add https://github.com/kweaver-ai/kweaver-sdk \
  --skill kweaver-core --skill create-bkn

• kweaver-core — full KWeaver APIs and CLI conventions so assistants can operate KWeaver on your behalf. See skills/kweaver-core/SKILL.md.
• create-bkn — guided workflow and tooling to create and manage Business Knowledge Networks (BKN) from your AI coding assistant. See skills/create-bkn/SKILL.md.

Install a single skill only (optional):

npx skills add https://github.com/kweaver-ai/kweaver-sdk --skill kweaver-core
# or
npx skills add https://github.com/kweaver-ai/kweaver-sdk --skill create-bkn

Before using any skill, authenticate with your KWeaver instance:

npm install -g @kweaver-ai/kweaver-sdk
kweaver auth login https://your-kweaver-instance.com

Self-signed certificate? If your instance uses a self-signed or untrusted TLS certificate (common for fresh deployments without a CA-issued cert), add -k to skip certificate verification:

kweaver auth login https://your-kweaver-instance.com -k

Headless login (SSH, CI, containers — no browser)

The npm kweaver CLI can complete OAuth without a local graphical browser:

1. On a machine with a browser, run kweaver auth login https://your-instance. After success, copy the one-line command from the callback page, or run kweaver auth export / kweaver auth export --json.
2. On the headless host, run that command — it uses --client-id, --client-secret, and --refresh-token to exchange tokens and save credentials under ~/.kweaver/ as usual.

You can also run kweaver auth login <url> --client-id … --client-secret … --refresh-token … directly on the headless machine if you already have those values.

Full details: kweaver-sdk — Headless / Server Authentication (TypeScript package README). The Python kweaver CLI still uses interactive browser login; reuse the same ~/.kweaver/ directory copied from a machine where the Node CLI finished login, or set KWEAVER_BASE_URL / KWEAVER_TOKEN (see kweaver-sdk Authentication).

CLI

kweaver auth login https://your-kweaver.com     # authenticate (-k for self-signed certs)
kweaver bkn list                                 # browse knowledge networks
kweaver bkn search <kn-id> "query"              # semantic search over a BKN
kweaver bkn build <kn-id> --wait                # rebuild index and wait for completion
kweaver bkn object-type list <kn-id>            # inspect object types
kweaver bkn action-type execute <kn-id> <at-id> # execute an action
kweaver agent list                               # list Decision Agents
kweaver agent chat <agent-id> -m "Hello"        # chat with an agent
kweaver ds import-csv <ds-id> --files "*.csv"   # import CSV files into a datasource
kweaver context-loader kn-search "query"        # semantic search via Context Loader
kweaver call /api/...                            # raw API call

TypeScript & Python SDK

Simple API (recommended):

import kweaver from "@kweaver-ai/kweaver-sdk/kweaver";
kweaver.configure({ config: true, bknId: "your-bkn-id", agentId: "your-agent-id" });

const results = await kweaver.search("What risks exist in the supply chain?");
const reply   = await kweaver.chat("Summarise the top 3 risks");
await kweaver.weaver({ wait: true });   // rebuild BKN index

import kweaver
kweaver.configure(config=True, bkn_id="your-bkn-id", agent_id="your-agent-id")

results = kweaver.search("What risks exist in the supply chain?")
reply   = kweaver.chat("Summarise the top 3 risks")

Full client API (advanced):

import { KWeaverClient } from "@kweaver-ai/kweaver-sdk";
const client = new KWeaverClient();   // reads ~/.kweaver/ credentials

const kns   = await client.knowledgeNetworks.list();
const reply = await client.agents.chat("agent-id", "Hello");
await client.agents.stream("agent-id", "Hello", {
  onTextDelta: (chunk) => process.stdout.write(chunk),
});

from kweaver import KWeaverClient, ConfigAuth
client = KWeaverClient(auth=ConfigAuth())
kns  = client.knowledge_networks.list()
msg  = client.conversations.send_message("", "Hello", agent_id="agent-id")

---

KWeaver Core

KWeaver Core is the AI-native platform foundation for autonomous decision-making. It sits between AI Agents (above) and AI/Da