Build fast, private AI agents that run fully on your machine. No cloud, no API keys. In this post, I'll show how to set up a local agent that scrapes news headlines and summarizes them using open-source tools like LangChain and Ollama.

A Comprehensive Overview of Prompt Engineering

It's possible to run an LLM like Gemma3 4b using Ollama in a basic CircleCI pipeline, which allows you to integrate lightweight AI capabilities, such as semantic unittests or simple agents, into your CI/CD workflows.

Traditional unit tests struggle with AI-generated text that varies slightly each time. Semantic unit testing solves this by comparing meaning rather than exact wording, making it ideal for validating AI outputs like classification, summarization, and text moderation.

AI Language Model Breakthrough: New Method Enables Self-Correcting Text Generation

Just something I wanted to share: Me: when working with Copilot, many things get easier, but the core problems remain the same and fixing hairy problems such as concurrency issues and the like, or test edge cases etc are still manual work. It helps mainly with boilerplate code, which aren't difficult to write anyway, but it saves time ChatGPT said:

site-packages/urllib3/__init__.py:34: NotOpenSSLWarning: urllib3 v2 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with 'LibreSSL 2.8.3'. See: Turns out that urllib3 version 2 wants OpenSSL to work properly. The earlier versions of urllib3 version 2 even stopped entirely, the later ones throw this warning. But my current ssl module appears to be LibreSSL. The idea is to install an…

I want to read the config for my backend from a yaml file and when installing the yaml package I am getting the following error: pip install yaml Looking in indexes: ERROR: Could not find a version that satisfies the requirement yaml (from versions: none) ERROR: No matching distribution found for yaml Quick Answer pip install pyyaml More Details…

CodeGen is an AI (LLM) from Salesforce that can generate source code, as well as describe what a piece of code does. It comes under the Apache license and has a good performance while being lightweight enough to run on a laptop for both inference and fine tuning. Here is how to set it up and how to use it. …

A dataset of 22,600 verified Python code examples. Tested for functionality and sourced from top projects, it’s perfect for training AI models on reliable, clean code.