Raspberrypi

Welcome to Day 7 of our OpenClaw series! Today we’re turning our AI assistant into an office automation powerhouse. By the end of this tutorial, your Raspberry Pi will be generating professional PowerPoint presentations and PDF documents on demand. Why Document Automation? Imagine telling your AI: “Create a presentation about Q4 sales results” or “Generate a PDF report from this data” — and having it just… happen. That’s what we’re building today. ...

On Day 3 of our journey building the ultimate AI Lab on a Raspberry Pi, we’re giving our OpenClaw agent a serious upgrade: Deep Search capabilities. While standard LLMs are great at reasoning, they often hallucinate facts or rely on outdated training data. To build a true “Researcher” agent, we need real-time, cited, and accurate information from the web. Enter Perplexity AI. Why Perplexity? Perplexity isn’t just a search wrapper; it’s an answer engine. Unlike a standard Google Search API which returns a list of links, Perplexity’s API (specifically the sonar models) returns synthesized answers with citations. This is perfect for an autonomous agent because it reduces the cognitive load of parsing raw HTML and synthesizing multiple sources—the API does the heavy lifting. ...

Yesterday, we installed OpenClaw on the Raspberry Pi. It was alive, but silent. Today, we give it a voice—and a brain. A true agent isn’t just a script; it needs a Large Language Model (LLM) to reason, understand intent, and generate human-like responses. OpenClaw makes this incredibly easy by supporting multiple providers right out of the box. In this guide, we’ll connect Google Gemini (for speed and reasoning) and OpenAI (as a backup or for specific tasks). ...