Generative-Ai

Introduction # Large Language Models (LLMs) have become a cornerstone of modern AI applications, from chatbots that provide customer support to content generation tools for images and videos. They power virtual assistants, automated translation systems, and personalized recommendation engines, showcasing their versatility across industries. However, running these models on a local machine has traditionally been a complex and resource-intensive task, requiring significant configuration and technical expertise. This complexity often deters beginners and even intermediate users who are eager to explore the capabilities of LLMs in a private, local environment.

TL;DR # This article demonstrates how to build a REST API that converts natural language into SQL queries using multiple LLM providers (OpenAI, Azure OpenAI, Claude, and Gemini). The system dynamically selects the appropriate AI service based on configuration, executes the generated SQL against a database, and returns structured results. It includes a complete implementation with a service factory pattern, Docker setup, and example usage.