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Chrome Browser Error 🐛

map-DGOtniGL.js:3852 THREE.WebGLRenderer: A WebGL context could not be created. Reason:  Could not create a WebGL context, VENDOR = 0x1b36, DEVICE = 0x0100, GL_VENDOR = Google Inc. (Mesa), GL_RENDERER = ANGLE (Mesa, llvmpipe (LLVM 19.1.1 256 bits), OpenGL ES 3.2 Mesa 24.2.8-1ubuntu1~24.04.1), GL_VERSION = 24.2.8, Sandboxed = no, Optimus = no, AMD switchable = no, Reset notification strategy = 0x8252, ErrorMessage = BindToCurrentSequence failed: .

Cause of Error

Note

This is usually because your web browser cannot load 3D graphics because it is using a slow, software-based renderer called llvmpipe instead of your actual graphics card (GPU).

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Note

This guide is to quick remove unnecessary bloatware and maximise available storage space on a Windows operating system.

Instructions 📘

1. Open up Powershell with admin privileges:

2. Run the following powershell command:

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Note

This is a guide to quickly set up a shared folder between Ubuntu Virtual Machine and Ubuntu Host Machine.

Instructions 📘

1. Set Enable shared memory to true for the instance. See screenshot below:

2. Add New Virtual Hardware. See screenshot below:

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Note

This is a quick reference guide on how to set up your Docker usage such that docker images are stored on an external drive.

Why Do This?

If, like me, you are constantly having to worry about limited disk space on your host device where you doing your development, it would likely benefit you to have the images stored separately.

Warning

This guide makes a loose assumption that your external drive will be mounted on the following:

• /home/$USER/Mounts

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Note

This guide is a copy-paste-observe list of quick instructional steps on how to set up Docker quickly without wasting any cognitive energy.

Instructions 📘

Run these commands to update your system and install prerequisite packages needed for adding Docker’s official repository and signing keys:

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Note

This guide provides a copy-paste-observe list of quick instructional steps to install Docker instantly on a RaspberryPi, assuming it has a Linux-based operating system on it.

Note

Verified on RaspberryPi 4B.

Instructions 📘

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Note

This is a quick copy-paste-observe guide for people in a hurry to quickly set up a Deep Local Research Agent where there are no reliance on proprietary web search api usage while still being useful in providing detailed reports on selected user topics.

For this guide, we will be using LearningCircuit's local_deep_research implementation with the following setup structure:

• [Web Search] - Dockerised
• [Deep Local Research] - Dockerized
• [Ollama] - Host

Instructions 📘

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Note

This is a quick copy-paste-observe guide for people in a hurry to quickly set up Open-WebUI such that one can run and access a local Large Language Model (LLM) as a web application similar to OpenAI's ChatGPT.

Tip

This setup is recommended if your GPU hardware specifications falls below what is the typical minimum 64000 token context window required for agentic coding. Eg. Nvidia Geforce RTX 3060 with 12GB VRAM.

Instructions 📘

1. Install Ollama using the command below:

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Note

This is a quick copy-paste-observe guide for people in a hurry to quickly set up a local coding agent at no additional costs using OpenCode and Ollama.

Instructions 📘

1. Install Ollama using the command below:

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Note

This is a quick copy-paste-observe guide for people in a hurry to quickly set up a local coding agent at no additional costs using OpenCode and Claude Code.

Instructions 📘

1. Install Ollama using the command below: