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hiclaw-collaborative-agent-os

Deploy and orchestrate collaborative multi-agent teams using HiClaw's Manager-Workers architecture on Docker or Kubernetes with Matrix rooms for human oversight

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reason-machines/ai-agent-skills
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hiclaw-collaborative-agent-os
description
Deploy and orchestrate collaborative multi-agent teams using HiClaw's Manager-Workers architecture on Docker or Kubernetes with Matrix rooms for human oversight
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["set up HiClaw multi-agent collaboration platform","deploy collaborative AI agents with HiClaw","create a team of AI workers with HiClaw","configure Manager-Workers architecture for agents","install HiClaw on Kubernetes with Helm","manage AI agent teams in Matrix rooms","orchestrate multiple agents with human-in-the-loop","deploy OpenClaw and QwenPaw workers together"]
# HiClaw Collaborative Agent OS > Skill by [ara.so](https://ara.so) — AI Agent Skills collection. HiClaw is an open-source collaborative multi-agent runtime platform built on a Manager-Workers architecture. It enables multiple AI agents to collaborate in Matrix-based rooms with full human visibility and intervention capabilities. Workers operate with consumer tokens while real credentials stay in the centralized Higress AI gateway, providing enterprise-grade security. The platform supports multiple agent runtimes (OpenClaw, QwenPaw/CoPaw, Hermes) working together, uses MinIO for shared file systems to reduce token consumption, and provides Kubernetes-native declarative resource management. ## Installation ### Docker Installation (Local/Single Machine) **macOS/Linux:** ```bash bash <(curl -sSL https://higress.ai/hiclaw/install.sh) ``` **Windows (PowerShell 7+):** ```powershell Set-ExecutionPolicy Bypass -Scope Process -Force $wc = New-Object Net.WebClient $wc.Encoding = [Text.Encoding]::UTF8 iex $wc.DownloadString('https://higress.ai/hiclaw/install.ps1') ``` The installer will prompt for: - LLM provider selection (OpenAI-compatible APIs supported) - API key - Network mode (local-only or external access) **Requirements:** - Docker Desktop (Windows/macOS) or Docker Engine (Linux) - 2 CPU cores + 4 GB RAM minimum - 4 cores + 8 GB RAM recommended for multiple Workers ### Kubernetes Installation (Helm) **Prerequisites:** - Kubernetes 1.24+ - Helm 3.7+ - Default StorageClass configured **Install with OpenAI:** ```bash helm repo add higress.io https://higress.io/helm-charts helm repo update helm install hiclaw higress.io/hiclaw \ -n hiclaw-system --create-namespace \ --render-subchart-notes \ --set credentials.llmApiKey=$LLM_API_KEY \ --set credentials.adminPassword=$ADMIN_PASSWORD \ --set gateway.publicURL=http://localhost:18080 ``` **Install with OpenAI-compatible provider:** ```bash helm install hiclaw higress.io/hiclaw \ -n hiclaw-system --create-namespace \ --render-subchart-notes \ --set credentials.llmApiKey=$LLM_API_KEY \ --set credentials.llmBaseUrl=https://api.deepseek.com/v1 \ --set credentials.defaultModel=deepseek-chat \ --set credentials.adminPassword=$ADMIN_PASSWORD \ --set gateway.publicURL=http://localhost:18080 ``` **Install with Qwen (通义千问):** ```bash helm install hiclaw higress.io/hiclaw \ -n hiclaw-system --create-namespace \ --render-subchart-notes \ --set credentials.llmApiKey=$QWEN_API_KEY \ --set credentials.llmProvider=qwen \ --set credentials.defaultModel=qwen3.5-plus \ --set credentials.adminPassword=$ADMIN_PASSWORD \ --set gateway.publicURL=http://localhost:18080 ``` **Key Helm Configuration Values:** | Parameter | Required | Description | |-----------|----------|-------------| | `credentials.llmApiKey` | Yes | API key from LLM provider | | `gateway.publicURL` | Yes | Public URL for Element Web access | | `credentials.adminPassword` | Recommended | Matrix admin password (auto-generated if omitted) | | `credentials.llmProvider` | No | Provider: `openai-compat` (default), `qwen` | | `credentials.defaultModel` | No | Model name (default: `gpt-5.4`) | | `credentials.llmBaseUrl` | No | Base URL for OpenAI-compatible APIs | | `manager.runtime` | No | Manager runtime: `openclaw` (default), `copaw`, `hermes` | | `worker.defaultRuntime` | No | Default Worker runtime: `openclaw` (default), `copaw`, `hermes` | ## Accessing HiClaw After installation, access Element Web (Matrix client): - Docker: http://127.0.0.1:18088 - Kubernetes (port-forward): `kubectl port-forward -n hiclaw-system svc/element-web 18088:8080` The Manager agent will greet you in Matrix and guide you through creating your first Worker. ## Declarative Resource Management (Kubernetes) HiClaw uses Kubernetes-style CRDs (Custom Resource Definitions) for declarative agent management. ### Worker CRD Create a Worker agent with declarative YAML: ```yaml apiVersion: hiclaw.io/v1 kind: Worker metadata: name: code-reviewer namespace: hiclaw-system spec: runtime: openclaw # or copaw, hermes profile: | You are a senior code reviewer specializing in Go and Python. Review code for security issues, performance problems, and best practices. Provide constructive feedback with specific suggestions. mcp: servers: - name: github type: github config: GITHUB_PERSONAL_ACCESS_TOKEN: ${GITHUB_TOKEN} - name: filesystem type: filesystem config: allowedDirectories: - /workspace/code env: - name: REVIEW_STRICTNESS value: "high" ``` Apply the Worker: ```bash kubectl apply -f worker-code-reviewer.yaml ``` ### Team CRD Create a Team of Workers managed by a Team Leader: ```yaml apiVersion: hiclaw.io/v1 kind: Team metadata: name: dev-team namespace: hiclaw-system spec: leader: runtime: openclaw profile: | You are a technical lead coordinating a development team. Break down tasks, assign to appropriate specialists, and synthesize results. mcp: servers: - name: github type: github config: GITHUB_PERSONAL_ACCESS_TOKEN: ${GITHUB_TOKEN} members: - name: backend-dev runtime: copaw profile: Go backend development specialist mcp: servers: - name: filesystem type: filesystem config: allowedDirectories: - /workspace/backend - name: frontend-dev runtime: hermes profile: React/TypeScript frontend specialist mcp: servers: - name: filesystem type: filesystem config: allowedDirectories: - /workspace/frontend ``` Apply the Team: ```bash kubectl apply -f team-dev.yaml ``` ### Human CRD Invite human users to participate: ```yaml apiVersion: hiclaw.io/v1 kind: Human metadata: name: alice namespace: hiclaw-system spec: displayName: Alice (Product Manager) password: ${ALICE_PASSWORD} # Set via Secret ``` Apply the Human: ```bash kubectl apply -f human-alice.yaml ``` ## Working with the hiclaw CLI HiClaw v1.1.0+ includes a CLI for managing resources: ```bash # List all Workers hiclaw worker list # Create a Worker from template hiclaw worker create --name data-analyst --runtime openclaw # Delete a Worker hiclaw worker delete data-analyst # List Teams hiclaw team list # Create a Team hiclaw team create --name research-team --leader-runtime copaw # Add Worker to Team hiclaw team add-member research-team --worker web-scraper # View Team status hiclaw team status research-team # Invite human user hiclaw human invite --username bob --display-name "Bob (Designer)" ``` ## Runtime Options ### OpenClaw - Deterministic, rule-based agent - Best for: Task orchestration, workflow management - Profile: Highly structured, follows explicit instructions ### QwenPaw (CoPaw) - LLM-powered agent optimized for Qwen models - Best for: Natural language understanding, decision-making - Profile: Flexible reasoning, context-aware ### Hermes - Autonomous coding agent runtime - Best for: Code generation, debugging, autonomous execution - Profile: Programming tasks, file system operations ## MCP Server Configuration Model Context Protocol (MCP) servers provide Workers with tools and data access. ### Common MCP Servers **GitHub Integration:** ```yaml mcp: servers: - name: github type: github config: GITHUB_PERSONAL_ACCESS_TOKEN: ${GITHUB_TOKEN} ``` **Filesystem Access:** ```yaml mcp: servers: - name: filesystem type: filesystem config: allowedDirectories: - /workspace/project - /workspace/shared ``` **PostgreSQL Database:** ```yaml mcp: servers: - name: postgres type: postgres config: DATABASE_URL: ${DATABASE_URL} ``` **Custom MCP Server:** ```yaml mcp: servers: - name: custom-api type: custom config: ENDPOINT: https://api.example.com API_KEY: ${CUSTOM_API_KEY} ``` ### Nacos Skills Registry HiClaw integrates with [skills.sh](https://skills.sh) (80,000+ community skills) via Nacos: ```yaml apiVersion: hiclaw.io/v1 kind: Worker metadata: name: data-processor spec: runtime: copaw profile: Data processing and transformation specialist mcp: servers: - name: nacos-skills type: nacos config: NACOS_SERVER: nacos.hiclaw-system.svc.cluster.local:8848 NACOS_NAMESPACE: hiclaw SKILL_CATEGORY: data-processing ``` Workers pull skills on-demand without exposing credentials (credentials stay in gateway). ## Manager-Workers Pattern ### Basic Workflow 1. **User sends request** to Manager in Matrix room 2. **Manager analyzes** and creates Worker(s) if needed 3. **Manager invites** Worker(s) to task-specific room 4. **Workers collaborate**, using MinIO shared filesystem 5. **Manager synthesizes** results and responds to user 6. **Human observes** all interactions, can intervene anytime ### Example: Multi-Runtime Collaboration ```yaml apiVersion: hiclaw.io/v1 kind: Team metadata: name: fullstack-project spec: leader: runtime: openclaw # Deterministic orchestration profile: Project coordinator - break down tasks and assign work members: - name: architect runtime: copaw # LLM reasoning for design decisions profile: System architect - design scalable solutions - name: coder runtime: hermes # Autonomous code execution profile: Full-stack developer - implement features - name: reviewer runtime: openclaw # Deterministic code review profile: Code reviewer - ensure quality and standards ``` Each runtime excels at different tasks, working together in the same room. ## Upgrade ### Docker Upgrade Preserves all data (Matrix rooms, MinIO files, configuration): ```bash # Latest version bash <(curl -sSL https://higress.ai/hiclaw/install.sh) # Specific version HICLAW_VERSION=v1.1.2 bash <(curl -sSL https://higress.ai/hiclaw/install.sh) ``` ### Kubernetes Upgrade ```bash helm repo update helm upgrade hiclaw higress.io/hiclaw \ -n hiclaw-system \ --reuse-values ``` Use `--set` to override specific values during upgrade. ## Configuration ### Environment Variables (Docker) Configuration stored in `.hiclaw/hiclaw.env`: ```bash # LLM Configuration LLM_PROVIDER=openai-compat LLM_API_KEY=sk-... LLM_BASE_URL=https://api.openai.com/v1 DEFAULT_MODEL=gpt-4 # Manager Runtime MANAGER_RUNTIME=openclaw # Worker Default Runtime WORKER_DEFAULT_RUNTIME=openclaw # Network PUBLIC_URL=http://localhost:18080 # Matrix Admin MATRIX_ADMIN_PASSWORD=... ``` ### Custom Worker Environment Variables Pass environment variables to specific Workers: ```yaml apiVersion: hiclaw.io/v1 kind: Worker metadata: name: data-analyst spec: runtime: copaw profile: Data analysis specialist env: - name: PANDAS_COMPUTE_BACKEND value: dask - name: MAX_MEMORY_GB value: "8" - name: API_TIMEOUT value: "30" ``` ### Custom Resource Limits (Kubernetes) ```yaml apiVersion: hiclaw.io/v1 kind: Worker metadata: name: ml-trainer spec: runtime: hermes profile: Machine learning model training resources: requests: memory: "4Gi" cpu: "2" limits: memory: "8Gi" cpu: "4" ``` ## Token Budget Management Configure Token Plans for Workers (v1.1.1+): ```yaml apiVersion: hiclaw.io/v1 kind: Worker metadata: name: budget-constrained-worker spec: runtime: copaw profile: Cost-conscious assistant tokenPlan: provider: qwen plan: basic # or premium maxTokensPerRequest: 4000 dailyLimit: 100000 ``` ## Common Patterns ### Pattern: Task Decomposition Manager breaks complex task into subtasks, assigns to specialist Workers: ```yaml apiVersion: hiclaw.io/v1 kind: Team metadata: name: research-project spec: leader: runtime: openclaw profile: | Break down research requests into: 1. Data collection (assign to web-scraper) 2. Data analysis (assign to analyst) 3. Report generation (assign to writer) members: - name: web-scraper runtime: hermes profile: Web scraping and data extraction - name: analyst runtime: copaw profile: Statistical analysis and insights - name: writer runtime: copaw profile: Technical report writing ``` ### Pattern: Human Review Checkpoint Include Human in Team for critical decisions: ```yaml apiVersion: hiclaw.io/v1 kind: Team metadata: name: deployment-pipeline spec: leader: runtime: openclaw profile: CI/CD pipeline coordinator members: - name: tester runtime: hermes profile: Automated testing - name: reviewer runtime: copaw profile: Code review humans: - name: devops-lead role: approver requiredFor: - production-deployment - infrastructure-changes ``` ### Pattern: Shared File Exchange Workers use MinIO for large data exchange: ```go // Worker A writes data package main import ( "github.com/minio/minio-go/v7" "github.com/minio/minio-go/v7/pkg/credentials" ) func uploadResults(data []byte, filename string) error { client, err := minio.New("minio.hiclaw-system.svc.cluster.local:9000", &minio.Options{ Creds: credentials.NewEnvAWS(), Secure: false, }) if err != nil { return err }
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