Run AI CoWork Locally with OpenClaw & Ollama (Complete Setup)

Open Claw & Olama Integration: A Beginner’s Guide

Key Concepts:

• Open Claw (formerly Clawbot/Moltbot): An AI assistant capable of managing inbox, emails, calendar, flights, and controlling a computer via chat applications (WhatsApp, Telegram, Slack).
• Olama: A framework for running large language models (LLMs) locally.
• LLMs (Large Language Models): AI models like GPT OSS 20B, designed to understand and generate human-like text.
• Tokens: Units of text used by LLMs; context length refers to the maximum number of tokens the model can process at once.
• Socket Mode: A method for Slack apps to receive events in real-time without requiring a public URL.
• Context Length: The amount of text an LLM can consider when generating a response. A larger context length allows for more complex interactions.

1. Introduction & Open Claw Overview

The video details a step-by-step guide to integrating Open Claw, a versatile AI assistant, with Olama, a local LLM framework. This setup allows users to run AI models privately on their computers and control them through chat applications like Slack, Telegram, or WhatsApp. Open Claw, previously known as Clawbot and Moltbot, offers functionalities such as inbox management, email handling, calendar scheduling, and flight checks, all accessible via simple chat commands. The presenter demonstrates controlling a computer directly from Slack using Open Claw. A key benefit highlighted is data privacy, as all processing occurs locally.

2. Installation: Open Claw & Olama

The process begins with installing Open Claw via the Node Package Manager (npm). The command npm install -g openclaw@latest is used to install the package globally. Next, Olama is downloaded from olama.com. The presenter emphasizes the availability of official documentation for both tools (linked in the video description).

3. Model Selection & Download with Olama

Olama provides a selection of LLMs, including recommended models like Quen 3, Coder, GLM 4.7, GPT OSS 20B, and GPT OSS 120B. The presenter chooses GPT OSS 20B for local execution. Two methods for downloading the model are presented:

• Olama Chat Interface: Downloading directly through the Olama application’s chat interface.
• Terminal Command: Using the command olama pull GPT OSS 20B in the terminal.

The presenter successfully downloads the model by simply typing "hi" into the Olama chat interface, triggering the download and a confirmation message ("Hello, how can I assist you today?").

4. Olama Configuration: Context Length

Optimizing performance requires configuring the context length. The presenter sets this to 64,000 tokens within the Olama settings. This allows the model to process larger amounts of text, enabling more complex interactions. The configuration is automatically saved within the Olama settings.

5. Launching Open Claw with Olama

Open Claw is launched using the command lama launch openclaw (or lama launch clawbot for compatibility with older Olama versions). This initiates the process of running Open Claw with the selected LLM (GPT OSS 20B in this case). The first launch automatically prompts the user to choose a model if one hasn't been pre-selected. The presenter notes that the "Oama gateway is already running" in the background.

6. Open Claw Web UI & Testing

Open Claw provides a web UI for testing. The command open claw configure section web is used to enable the web interface. The presenter confirms running it locally and enabling web fetching. Accessing the provided link reveals the web UI, where a simple "hi" command confirms the system is functioning correctly.

7. Slack Integration & Computer Control

The presenter references a previous video (link in description) detailing Slack integration. This involves creating a Slack app, configuring OAuth permissions, enabling socket mode, subscribing to events, and enabling the messages tab. Using a Slack bot named "Praise AI," the presenter demonstrates controlling the computer directly from Slack. Commands are executed by tagging the bot (e.g., "@Praise AI list files in my folder"). The bot successfully lists files from the presenter’s computer, showcasing remote control capabilities. The presenter highlights the ability to read calendars and emails as well.

8. Capabilities & Data Privacy

The video emphasizes the broad range of tasks Open Claw can perform, including file management, calendar access, and email handling, all controllable from various messaging apps (Slack, WhatsApp, Telegram). Crucially, the presenter reiterates that the entire setup runs locally, ensuring 100% data privacy.

9. Conclusion & Call to Action

The presenter encourages viewers to experiment with Open Claw and share their experiences in the comments. They also recommend watching the accompanying video on Slack integration for a complete setup guide. The key takeaway is the ability to create a powerful, private AI assistant capable of controlling a computer through simple chat commands.

Notable Quote:

“All the models all the data remains private.” – The presenter, emphasizing the data privacy benefits of the local setup.

Data/Statistics:

• Context Length: Configured to 64,000 tokens.
• LLM Options: Quen 3, Coder, GLM 4.7, GPT OSS 20B, and GPT OSS 120B are listed as available models.

This summary provides a detailed, step-by-step account of the video’s content, preserving the technical language and specific instructions provided by the presenter. It aims to be a comprehensive guide for anyone looking to replicate the Open Claw and Olama integration.