Tools: Advanced Local Ai: Building Digital Employees With Ollama + Openclaw

Chatting is not enough. Learn how to combine Ollama's powerful reasoning capabilities with OpenClaw's......

2025 was called the "Year of Local Large Models," and we've gotten used to running Llama 3 or DeepSeek with Ollama to chat and ask about code. But by 2026, simple"conversation" no longer satisfies the appetites of tech enthusiasts.

We want Agents—not just capable of speaking, but truly able to work for us.

Today let's talk about the most hardcore combination in the local AI space right now: Ollama (reasoning engine) + OpenClaw (autonomous execution framework). Under this architecture, AI is no longer just a text generator in a chat box, but a "digital employee" that can operate browsers, read and write files, and run code.

Any Agent needs a smart "brain," and in a local environment, Ollama remains the most robust choice.

If you haven't installed it yet, just go to ollama.ai to download the appropriate version. Once installed, we typically open a terminal and enter commands to download models.

For Agent applications, choose models that support Tool Calling:

But this actually brings a small annoyance: terminal downloading is a "black box."

When you want to try different models (like comparing Qwen 2.5 and Llama 3 effects), or when model files are very large (tens of GB), looking at the monotonous progress bar in the terminal makes it difficult to intuitively manage these behemoths. Moreover, once you have many models installed, deciding which to delete and how much video memory each occupies becomes a headache.

To solve this problem and also make subsequent model scheduling more relaxed, I recommend using it in conjunction with OllaMan for this step.

Source: Dev.to