Build ChatGPT Clone in 30 minutes
AI chat applications are everywhere now. From ChatGPT to coding assistants and support bots, conversational AI has become one of the most exciting areas for developers. But here’s the good…
AI chat applications are everywhere now. From ChatGPT to coding assistants and support bots, conversational AI has become one of the most exciting areas for developers. But here’s the good…
Artificial Intelligence is transforming the way developers write code, debug applications, and build software. In 2026, AI powered tools are no longer optional they have become an essential part of…
Llama 3, developed by Meta AI, is one of the most powerful open source large language models available today. It can generate text, assist with programming, answer questions, summarize information,…
AI is no longer limited to cloud providers. In 2026, developers are increasingly running powerful AI models locally on old laptops, unused desktops, and home servers. In this guide, you’ll…
LangChain is built around the idea of connecting different component LLMs, prompts, parsers, memory, and tools to create powerful AI workflows. Before building RAG systems, agents, or LangGraph workflows, you…
LangChain is one of the most popular frameworks for building AI apps in Python.If you want zero API cost, offline AI, and fast local inference, then using Ollama + Llama3…
Grok is a family of large language models developed by xAI.Using the xAI API gives developers programmatic access to Grok models: you can build chatbots, automation tools, AI powered apps,…
virtualenv is a Python tool that creates isolated environments. Each environment can have its own: This is extremely helpful when: Prerequisite Check Python & pip Installation Open your terminal (or…
AI development has changed dramatically since large language models (LLMs) like GPT-4, GPT-5, Claude, and Llama became mainstream.While these models are extremely powerful, building real applications on top of them…
In earlier articles, we installed Ollama and learned how to run models from the terminal. Now it’s time to take the next step using Ollama with Python. This is where…