Flowise is a solid open-source low-code option for building AI workflows fast — production-ready, multi-model and easy to integrate. How to install it with secure Entra ID authentication for Azure OpenAI and add observability with Phoenix.
Keep reading: Building AI applications with Flowise and Phoenix →
Run an AI process that reads bingo cards and checks whether the numbers make a bingo, using local LLMs with Ollama for inference and Nginx as a security layer for SSL and authentication.
Keep reading: Local AI with Ollama and Nginx: A Guide to Automated Validation →
In this tutorial we'll walk through a simple example of how to summarise news from different sources and languages using artificial intelligence.
How to build an AI chatbot using RAG, Qdrant as the vector database and an agent to manage memory, with a graphical user interface (GUI).
Keep reading: AI Chatbot with RAG, Memory and a User Interface →
How to use the AutoGen framework to build an agent that answers questions based on documents stored in a vector database, with Azure OpenAI.
How to turn a video into a written tutorial with artificial intelligence: extract frames, convert them to base64 and use Azure OpenAI's multimodal GPT-4o model to write the tutorial from them.
How to work with ChromaDB, a database for embedding vectors: running a server with authentication in Docker, then creating collections, adding documents and querying them from Python.
How to use PowerShell with REST APIs and an Azure Service Principal to monitor the status of several Flows — especially useful for managing and automating alerts on critical flows.
Keep reading: PowerShell + REST APIs to monitor the status of MS Flows →
How to build an AI agent that answers questions using Active Directory and a knowledge base (KB), with LangChain and Azure.
How to set up an AI bot with documents and memory (RAG with chat history) using Azure OpenAI and LangChain.
