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cool beans
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‎citations.txt

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@@ -238,3 +238,4 @@ https://jetsonhacks.com/2023/05/30/jetson-orin-nano-tutorial-ssd-install-boot-an
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https://web.archive.org/web/20191125073329/http://alexsharry.com/ - {reflect.app}
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https://edu.irobot.com/what-we-offer/create3
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https://blog.gregbrockman.com/

‎web-ui/docs/10-environmental-challenges-and-solutions-for-sensor-deployment.md

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# 10-environmental-challenges-and-solutions-for-sensor-deployment
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Content for 10-environmental-challenges-and-solutions-for-sensor-deployment

‎web-ui/docs/8-integrating-sensors-with-machine-learning-on-edge-devices.md

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# 8-integrating-sensors-with-machine-learning-on-edge-devices
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Content for 8-integrating-sensors-with-machine-learning-on-edge-devices

‎web-ui/docs/blag/iindex.html

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‎web-ui/docs/blag/index.md

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# Best Of
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1. Making RObotics odyssey: robot to feed cats
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2. Making Llama-tools
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3. Functional reactive infrastructure
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# Introduction to Sensors
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1. What are Sensors and Their Applications in Robotics
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2. Types of Sensors Used in Robotics: From Proximity to LIDAR
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3. How to Interface Sensors with Jetson Modules
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4. Choosing the Right Sensors for Your Robotics Project
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5. Top 10 Affordable Sensors for Hobbyists
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6. Sensor Fusion Techniques for Reliable Robotics Applications
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7. Using Zig to Manage Sensor Data in Real-Time Systems
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8. Integrating Sensors with Machine Learning on Edge Devices
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9. Best Practices for Calibration and Maintenance of Sensors
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10. Environmental Challenges and Solutions for Sensor Deployment
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# NVIDIA Jetson Series
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1. Getting Started with NVIDIA Jetson Nano for Robotics
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2. Differences Between Jetson Nano, Xavier, and Orin Explained
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3. Setting Up a Robotics Development Environment on Jetson
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4. Running AI Models on Jetson Devices with PyTorch
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5. Jetson as an Edge Device for Distributed Computing in Swarms
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6. Using Zig for Efficient Device Control on Jetson Boards
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7. Comparing Jetson Xavier NX with Raspberry Pi for Vision Tasks
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8. Deep Learning with Jetson: A Practical Guide
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9. Building ROS-Based Robots with Jetson Orin
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10. Jetson as a Brain for Autonomous Mobile Robots
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# Robotic Arms
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1. Building a Low-Cost Robotic Arm with Dynamixel Servos
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2. Robotic Arm Kinematics Explained: From Math to Implementation
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3. 3D Printed Robotic Arms: Design and Limitations
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4. Programming Robotic Arm Movements with ROS
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5. Integrating Robotic Arms with Jetson for Machine Learning Applications
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6. Using Zig to Optimize Robotic Arm Control Loops
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7. Selecting Servo Motors for Your Robotic Arm Project
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8. Collaborative Robots: Designing a User-Friendly Arm
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9. Precision Control for Robotic Arms in Manufacturing
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10. DIY Projects: Assembling a Robotic Arm Under $500
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Locomotion and Mobility Systems
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1. An Overview of Locomotion Types: Wheels, Legs, and Tracks
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2. Creating a Bipedal Robot: Challenges and Solutions
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3. Balancing Algorithms for Two-Wheeled Robots
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4. Mobile Robotics with Jetson: Mapping and Navigation
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5. Integration of Sensor Data for Autonomous Locomotion
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6. Zig for Writing Efficient Motion Control Programs
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7. Choosing the Right Wheels and Motors for Your Robot
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8. Designing a Modular Locomotion System for Versatility
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9. Swarm Robotics and Locomotion Synchronization Techniques
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10. Robotics Locomotion in Rough Terrain: Challenges and Strategies
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3D Printing for Robotics
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1. Designing 3D-Printed Parts for Robotics Projects
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2. Best 3D Printers for Robotic Prototyping
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3. Materials for 3D Printing Robotic Components: PLA vs. ABS
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4. Printing Jigs and Fixtures for Assembling Robots
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5. Integrating 3D-Printed Parts with Off-the-Shelf Electronics
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6. Customizing Robotic Arm Components Using 3D Printing
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7. Common Issues with 3D Printed Parts and How to Fix Them
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8. Combining 3D Printing with CNC Machining for Precision
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9. 3D Printing Gears for Robotic Applications: Tips and Tricks
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10. Designing Lightweight Yet Strong Robotic Components
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Zig for Systems Engineering
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1. Why Use Zig for Systems-Level Robotics Programming?
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2. Getting Started with Zig for Hardware Control
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3. Comparing Zig to C/C++ for Robotics Projects
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4. Writing Low-Latency Sensor Drivers in Zig
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5. Memory Safety in Zig: Advantages for Robotics Systems
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6. Using Zig to Interface with Real-Time Operating Systems
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7. Building Modular Robotics Software Architectures in Zig
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8. Code Examples: Interfacing Motors with Zig
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9. Best Practices for Zig in Embedded Systems
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10. Debugging Robotics Applications Written in Zig
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Introduction to LlamaOps
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1. What is LlamaOps and How Does It Work?
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2. Llama Models Explained: From GPT to Llama 3
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3. Deploying Llama Models on Local Servers vs. Cloud
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4. Training Llama Models for Robotics Applications
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5. Optimizing Llama Inference for Real-Time Systems
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6. Using LlamaOps for Conversational AI in Robotics
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7. Comparing Llama with GPT-4 for Technical Applications
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8. Hosting Llama Models with Docker and Kubernetes
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9. Privacy Concerns in Using Llama for On-Device AI
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10. Fine-Tuning Llama Models for Niche Applications
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Llama Model Training and Deployment
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1. How to Train Llama Models with Custom Datasets
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2. Understanding the Compute Requirements for Llama Training
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3. Using Jetson Devices to Run Llama Inference Efficiently
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4. Quantization Techniques to Optimize Llama Models
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5. Comparing Llama and BERT for Domain-Specific Tasks
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6. Hosting a Llama API for Your Robotics Project
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7. Using Zig with LlamaOps for Low-Level Optimizations
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8. Combining Llama Models with OpenCV for Object Detection
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9. Model Evaluation Metrics for Llama in Robotics Contexts
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10. Deploying Llama on Edge Devices for Offline Use
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Llama for Robotics
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1. Voice-Controlled Robotics Using Llama-Based NLP
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2. LlamaOps in Human-Robot Interaction Scenarios
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3. Integrating LlamaOps with ROS for Seamless Operation
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4. Creating an AI Chatbot for Your Robot with LlamaOps
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5. Using Llama for Fault Diagnosis in Autonomous Systems
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6. Exploring Multi-Agent Communication with LlamaOps
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7. Generating Movement Commands with Llama Language Models
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8. LlamaOps for Knowledge Sharing Among Robot Swarms
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9. Comparing Llama with Traditional ML for Command Execution
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10. Using Reinforcement Learning with Llama Models in Robotics
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Introduction to Computer Vision
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1. Basics of Computer Vision for Robotics Beginners
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2. Setting Up OpenCV on Jetson Devices
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3. How Computer Vision Powers Robotics Today
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4. Key Algorithms in Computer Vision: A Beginner’s Guide
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5. Using YOLO for Object Detection in Robotics
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6. Deep Learning Models for Computer Vision Tasks
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7. Camera Calibration for Accurate Computer Vision
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8. Combining Computer Vision with Llama for Perception
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9. Evaluating Object Recognition Models for Robotics
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10. Edge vs. Cloud: Where to Deploy Computer Vision Models
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Advanced Computer Vision Techniques
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1. Training Your Own Computer Vision Model with PyTorch
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2. Using GANs for Image Synthesis in Robotics Applications
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3. Segmentation Techniques in Robotics Using SAM
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4. Real-Time Image Processing for Mobile Robots
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5. Depth Estimation for 3D Perception in Robots
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6. Using Zig for Optimizing Vision Algorithms on Edge Devices
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7. Combining Lidar and Camera Data for Better Vision
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8. Object Tracking Techniques for Robotic Applications
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9. Using CUDA to Speed Up Vision Processing
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10. Evaluating SLAM Algorithms for Visual Localization
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Advanced Computer Graphics Techniques
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1. NERF
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2. Gaussian Splatting
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3. Point Cloud Rendering
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4. Voxels and Stixels
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5. Server Side WebGPU Streaming
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6. Ray Tracing (2D and 3D) - Visibility

‎web-ui/docs/making-llama-tools.md

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# making-llama-tools
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Content for making-llama-tools

‎web-ui/docs/making-robotics-odyssey-robot-to-feed-cats.md

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# making-robotics-odyssey-robot-to-feed-cats
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Content for making-robotics-odyssey-robot-to-feed-cats

‎web-ui/docs/nvidia-jetson-series.md

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# nvidia-jetson-series
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Content for nvidia-jetson-series

‎web-ui/js/bun-helper-server.tsx

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const ollama = require('ollama');
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import {$} from 'bun'
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import { renderToString } from "react-dom/server";
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import React, { Suspense, lazy } from 'react';
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import Bun from 'bun'
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import llamaRoutes from './bun_handlers/llama-backend.js'
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import CgiRoutes from './bun_handlers/cgi-backend.js'
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import { renderToReadableStream } from 'react-dom/server';
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import TurndownService from 'turndown';
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const port = 8080;
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console.log(`Server running at http://localhost:${port}`);
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});
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}
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function on_save_blag(req: Request) {
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ollama.generate({
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model: "llama3.2",
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prompt: "predict if there are errors before running thiss"
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})
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//run thing
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ollama.generate({
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//model: "llama3.2",
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model: "llama3.2",
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prompt: "if errors - suggest fixes"
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})
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}
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async function serveBlagArchive(req: Request) {
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const url = `https://reflect.site/g/awahab/500-blog-posts---prolific---show-steps---12yr-exec--phd-x-7-in-2-yrs/d1ea069679c64f649827dd990648b17c`
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const response = await fetch(url);
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const htmlContent = await response.text();
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try {
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const filePath = path.join(process.cwd(), "docs/blag/index.md");
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// console.log('filePath', filePath);
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// const htmlContent = fs.readFileSync(filePath, "utf-8");
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const turndownService = new TurndownService();
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const markdownContent = turndownService.turndown(htmlContent);
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const lines = markdownContent.split('\n');
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// async function convertHtmlToMarkdown(htmlContent) {
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// const ask_ollama = async (prompt) => {
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// const proc = Bun.spawn(["ollama", "run", "llama3.2", "prompt", prompt]);
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// const output = await new Response(proc.stdout).text();
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// return output;
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// };
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// const prompt = "Convert the following HTML content to Markdown:\n\n" + htmlContent;
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const docsPath = path.join(process.cwd(), 'docs');
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if (!fs.existsSync(docsPath)) {
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fs.mkdirSync(docsPath, { recursive: true });
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}
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// const markdownContent = await ask_ollama(prompt);
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// return markdownContent;
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// }
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lines.forEach(line => {
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if (line.startsWith('#')) {
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const header = line.replace(/#/g, '').trim();
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const folderName = header.replace(/\s+/g, '-');
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const folderPath = path.join(docsPath, folderName);
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if (!fs.existsSync(folderPath)) {
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fs.mkdirSync(folderPath, { recursive: true });
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}
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const markdownContent = fs.readFileSync(filePath, "utf-8");
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//console.log('markdownContent', markdownContent);
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//const lines = markdownContent.split('\n');
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// Create an HTML file in the folder with the title
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const htmlContent = `<html><head><title>${header}</title></head><body><h1>${header}</h1></body></html>`;
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const filePath = path.join(folderPath, `${folderName}.html`);
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fs.writeFileSync(filePath, htmlContent, 'utf-8');
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//console.log('lines', lines);;
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//immutable functional reactive infra -> on save -> refresh + replit but faster - tailwind 4 robots
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const lines = markdownContent.split('\n')
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const docsPath = path.join(process.cwd(), 'docs');
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if (!fs.existsSync(docsPath)) {
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fs.mkdirSync(docsPath, { recursive: true });
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}
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});
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const content = `${lines.map((line, i) => {
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let content = '<ul>';
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for (let i = 0; i < 500; i++) {
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const randomLink = `https://example.com/${Math.random()}`;
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content += `<li><a href="${randomLink}">Link ${i + 1}</a></li>`;
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}
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content += '</ul>';
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if (line.startsWith('#')) {
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return `<h1>${line.slice(2)}</h1>`;
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}
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return new Response(content, {
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headers: {
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"Content-Type": "text/html",
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},
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});
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const cleanedLine = line.slice(3).replace(/[^a-zA-Z0-9\s-]/g, '').trim();
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if (cleanedLine === ' ') {
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return '';
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}
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return new Response('blag archive')
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const simplifiedLink = cleanedLine.replace(/\s+/g, '-').toLowerCase();
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return `<div><a href="blag/${simplifiedLink}">${cleanedLine}</a></div>`;
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}).join('<br/>')}`;
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return new Response(content, {
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headers: {
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"Content-Type": "text/html",
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},
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});
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} catch (error) {
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console.error('Error in serveBlagArchive:', error);
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return new Response('An error occurred while processing your request', { status: 500 });
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}
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}
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const CgiRoutesHandlers = Object.fromEntries(
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"/blag": (req: Request) => serveBlag(req),
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"/llama-tools": (req: Request) => serveLlamaTools(req),
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"/cgi-tools": (req: Request) => serveCgiTools(req),
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"/blag-archive": (req: Request) => serveBlagArchive(req),
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...CgiRoutesHandlers,
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async function fetch(req: Request) {
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const url = new URL(req.url);
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if (!req.url) {
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console.error('Request URL is undefined');
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return new Response('Invalid request', { status: 400 });
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}
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if (url.pathname.startsWith("/blag/")) {
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const route = url.pathname.replace("/blag/", "");
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const filePath = `./docs/${route}.md`;
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try {
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await Bun.write(filePath, `# ${route}\n\nContent for ${route}`);
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const fileExists = await Bun.file(filePath).exists();
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if (fileExists) {
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return new Response(await Bun.file(filePath).text(), { status: 200 });
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} else {
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const prompt = `Generate a paragraph of PhD level content and 10 citations related to the topic described in the file: ${filePath}`;
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const response = await ollama.chat({
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model: 'llama3.1',
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messages: [{ role: 'user', content: prompt }],
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})
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const generatedContent = await response.message.content;
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const content = generatedContent.text;
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await Bun.write(filePath, content);
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return new Response(content, { status: 200 });
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}
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//return new Response(`File created at ${filePath}`, { status: 201 });
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} catch (error) {
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console.error('Error creating file:', error);
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return new Response('An error occurred while creating the file', { status: 500 });
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}
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}
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console.log('url', url.pathname)
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if (url.pathname.startsWith("/assets")) return Bun.file('/Users/shelbernstein/homelab_status_page/web-ui/assets/output.css')
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// }
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//import RoboticsOdyssey from "views/odyssey/robotics-odyssey.tsx";
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