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Part 5: Creating a working example in PHP and Laravel.

Jun 15, 2025 · 1 min read · Part 5 : Creating a working example in laravel. We’ve created this example to demonstrate a basic RAG (Retrieval-Augmented Generation) implementation. It uses Laravel/PHP and SQLite, allowing you to run simple RAG queries within the application. Here...

Part 4: Generating Answers with LLMs and Enhancing Your RAG System

Jun 10, 2025 · 4 min read · We've come a long way! In Part 1, we set up our environment. In Part 2, we populated our Qdrant vector database with embedded data. In Part 3, we learned how to query this database using user input to retrieve relevant context. Now, it's time for the...

Part 3: Searching Your Knowledge – Querying the Vector Database

Jun 10, 2025 · 3 min read · Blog Post 3: Searching Your Knowledge - Querying the Vector Database In the previous post, we successfully converted our data into embeddings and uploaded them to our Qdrant vector database. Now, our knowledge base is primed and ready. The next cruci...

Part 2: Populating Your Vector Database – Embedding and Uploading Data

Jun 10, 2025 · 3 min read · In our previous post, we covered the fundamental concepts of RAG and set up our environment, including our LLM/embedding provider and Qdrant vector database. Now, it's time to prepare our data and store it in a way that allows for efficient semantic ...

Part 1: Understanding RAG Fundamentals & Setting Up Your Environment

Jun 10, 2025 · 4 min read · Before diving headfirst into building a Retrieval Augmented Generation (RAG) system with a specific framework, it's crucial to grasp the fundamental concepts. Understanding the "why" and "how" behind each component empowers you to build more robust, ...