Install OpenLM AI module management on Windows

1️⃣ Install Python

  • OpenLM is Python-based. Make sure you have Python 3.9+ installed.

  • Check installation:

    python --version
    pip --version

  • If missing, install from python.org.

  • Optional: Add Python to PATH during installation.


2️⃣ Install OpenLM Module Manager

Open a Windows Command Prompt or PowerShell:

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pip install openlm

This installs the CLI and API server tools.


3️⃣ Initialize OpenLM Repository

Create the module storage folder:

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openlm init
  • This will create folders like:

    C:\Users<User>.openlm
    modules
    configs
    logs\

  • All AI modules you register will be stored here.


4️⃣ Register / Add AI Modules

Suppose you have an AI module or script (e.g., weather-agent):

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openlm add-module --name weather-agent --type agent --path "D:\project\weather-agent" --gpu 0
  • --name → module ID

  • --type → agent / model / tool

  • --path → folder with code or checkpoint

  • --gpu → GPU index if available

You can repeat this for all your AI modules.


5️⃣ List Registered Modules

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openlm list

Example output:

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ID      Name            Type       Status
1       weather-agent   agent      ready
2       code-reviewer   model      ready

6️⃣ Start the Module Server

Open a terminal in Windows 11:

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openlm serve
  • Starts a local REST API server , typically at http://localhost:8000.

  • Each module is exposed via endpoints like /run?module=weather-agent.


7️⃣ Use a Module via Python

Example: call a module to check last 7 days' weather:

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import requests

resp = requests.post("http://localhost:8000/run", json={
    "module": "weather-agent",
    "input": "Check last 7 days rain in New York"
})

print(resp.json())
  • Works for agents, models, and tools

  • Responses are JSON objects with module output.


8️⃣ Update or Remove Modules

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openlm update-module --name weather-agent --path "D:\project\weather-agent-new"
openlm remove-module --name old-module
  • Keeps your modules versioned and organized.

9️⃣ Notes for Windows Users

  • GPU usage: Make sure CUDA drivers are installed and PyTorch detects the GPU.

  • Firewall: Allow Python/Server through firewall if you want remote access.

  • Paths : Use double quotes "D:\folder\path" in CMD / PowerShell.

  • PowerShell vs CMD: Both work; PowerShell allows better scripting.


If you want, I can also make a diagram showing OpenLM on Windows + OpenClaw + GPU + modules, so you can see visually how everything interacts.

Do you want me to do that?

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