Category: ML-AI
Streamlining LLM Integration with LiteLLM
In the rapidly evolving landscape of Large Language Model (LLM) applications, developers often face significant challenges when integrating multiple LLM providers. Each provider—whether OpenAI, Anthropic, Cohere, or others—comes with its own API structure, authentication methods, and response formats, creating a complex integration landscape. What is LiteLLM? LiteLLM is an open-source library that provides a unified…
Building a MCP Server So LLMs Can Count Letters
Large Language Models (LLMs) sometimes struggle with simple counting tasks like determining the number of ‘r’s in words like “strawberry” or “raspberry”. While this is often used as a gotcha test for LLMs, there’s a practical solution – creating a Model Context Protocol (MCP) server to handle these counting tasks reliably. MCP is an innovative…
LangGraph Basics: Building Advanced AI Agents with Graph Architecture
Why LangGraph? Before diving into installation, let’s understand why LangGraph is a powerful tool for building AI agents: Installation and Setup with uv Please see our uv tutorial for instructions on installing and setting up uv. These commands will work with pip and a standard virtual environment as well. Installation Steps Here’s how to set up your…
Using TensorFlow.js ML Models for Pose Detection in the Browser
Machine learning has traditionally required specialized knowledge and powerful servers, but TensorFlow.js now brings these capabilities directly to web browsers. By leveraging TensorFlow.js pretrained models we can quickly perform a variety of machine learning tasks. Browser-based machine learning offers several compelling advantages: In this tutorial, we’ll build a real-time gesture control application that uses your…
Classifying Technical Documentation with TensorFlow: Building a GitHub README Classifier
In this tutorial, I’ll walk you through how to build a machine learning system that automatically classifies GitHub README files by programming language. This practical application of natural language processing demonstrates how to use TensorFlow to analyze and categorize technical documentation. To provide a simple development environment we’re going to use a Jupyter Notebook. Each…