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Work with OpenClaw 🦞

What is OpenClaw 🦞?

OpenClaw is an open-source personal AI assistant that runs on your own machine. Unlike cloud-based AI services, OpenClaw gives you full control over your data and infrastructure.

Key features include:

  • Multi-platform chat integration: Interact via WhatsApp, Telegram, Discord, Slack, Signal, or iMessage
  • Persistent memory: Remembers your preferences and context across sessions
  • Full system access: Read/write files, run shell commands, and control your browser
  • Extensible skills: Use community-built skills or create your own
  • Model flexibility: Works with Anthropic, OpenAI, or local models

Github repo of OpenClaw: https://github.com/openclaw/openclaw

Prerequisites

To integrate Parallax with OpenClaw, you need to meet the prerequisites for both projects:

  • Node.js: >= 22 (required by OpenClaw)
  • Python: >=3.11 (required by Parallax)

Before proceeding, we assume you have already deployed Parallax on your AI cluster. For deployment instructions, please refer to:

Start your Parallax Service

Step 1: Start the Scheduler

On your scheduler machine, run:

parallax run --host 0.0.0.0

Step 2: Select Model

Open your browser and navigate to localhost:3001 on the scheduler machine. Select your model and click Continue.

Step 3: Start Edge Nodes

On your edge nodes, run:

parallax join --max-sequence-length 65536 --max-num-tokens-per-batch 65536 --enable-prefix-cache

Step 4: Test the Model

On the scheduler machine, open your browser and navigate to localhost:3001. Use the chat interface to test if the model is working properly.

Onboard OpenClaw

Step 1: Install OpenClaw

Use the official install script to install OpenClaw, skipping the onboard wizard:

curl -fsSL https://openclaw.ai/install.sh | bash -s -- --no-onboard

Step 2: Create Configuration File

Create the configuration file at ~/.openclaw/openclaw.json with the following content:

{
  "agents": {
    "defaults": {
      "model": {
        "primary": "parallax/your-model-name"
      }
    }
  },
  "models": {
    "providers": {
      "parallax": {
        "baseUrl": "http://localhost:3001/v1",
        "apiKey": "placeholder",
        "api": "openai-completions",
        "models": [
          {
            "id": "your-model-name",
            "name": "Parallax Model"
          }
        ]
      }
    }
  }
}

Step 3: Run Onboard

openclaw onboard --install-daemon

During the onboard process:

  1. Read and accept the OpenClaw risk disclaimer
  2. When prompted for onboarding mode, select Quick Start
  3. When prompted for config handling, select Use existing values
  4. When prompted for Model/auth provider, select Skip for now
  5. When prompted for Filter models by provider, select All providers
  6. When prompted for Default model, select Keep current (parallax/your-model-name)
  7. When prompted for Select channel, configure the channel based on your needs, or select Skip for now
  8. When prompted for Select skills, configure the skills based on your needs, or select Skip for now
  9. When prompted for Enable hooks, configure the hooks based on your needs, or select Skip for now
  10. Wait a moment for Gateway services being installed.
  11. When prompted for How do you want to hatch your bot, configure the way you hatch your bot based on your needs.

Try on Browser

Open your browser and navigate to http://127.0.0.1:18789/. Start sending messages to OpenClaw and enjoy!

Q&A

Q: OOM Error

libc++abi: terminating due to uncaught exception of type std::runtime_error: [METAL] Command buffer execution failed: Insufficient Memory (00000008:kIOGPUCommandBufferCallbackErrorOutOfMemory)

A: Add the --kv-cache-memory-fraction parameter when starting Parallax on edge nodes:

parallax join --max-sequence-length 65536 --max-num-tokens-per-batch 65536 --enable-prefix-cache --kv-cache-memory-fraction 0.5

If OOM errors persist, try using a smaller value for --kv-cache-memory-fraction.