Latest
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Deploying MCP Servers with Azure Container Apps
In this article, we explore how to deploy and run multiple Model Context Protocol (MCP) servers using Azure Container Apps. We’ll demonstrate how to enable AI agents to dynamically interact with tools like weather data, energy services, and hybrid document search, using LangGraph and Semantic Kernel for seamless integration. Read more
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The Perfect AI Team: Azure Cosmos DB and Azure App Service
AI advancements are impressive, and their true impact emerges when seamlessly integrated into business processes. Azure Cosmos DB and Azure App Service create the perfect… Read more
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Chat History with Azure Cosmos DB and Semantic Kernel
In conversational AI, maintaining chat history across sessions and devices is key to delivering seamless user experiences. This article explores how Azure Cosmos DB, in… Read more
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Enhance Customer Support with Semantic Kernel and Azure OpenAI
This article explores an Azure OpenAI RAG Customer Support Solution built with .NET, Semantic Kernel, Azure AI Search, Cosmos DB, and Bicep for simplified resource… Read more
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Creating Intelligent Systems for Jira with Azure OpenAI and AI Search
This article explores an advanced LLM application that leverages Azure AI Search and Azure OpenAI Service for efficient Jira issue management. It covers prerequisites, objectives,… Read more
Curated Materials
Issue 1 – June 2024
This guide provides essential tips and best practices for managing and optimizing partitioning in Azure Cosmos DB.
Guided Journey – July 2024
Azure Machine Learning
This guide provides a comprehensive walkthrough for using Azure Machine
Learning to build a classification model based on risk data pulled from Azure.
Archives
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Effortlessly Vectorize Your Data with Azure AI Search: Step-by-Step Tutorial
This article explains how to utilize Azure AI Search and the data vectorization wizard to create vector embeddings easily. These embeddings optimize content retrieval by indexing it, leading to improved search performance. Azure AI Search offers advanced search capabilities and seamless integration with Azure services for developers. Read more
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Deploy Azure Machine Learning Models for Real-Time Predictions
This article is a comprehensive guide on utilizing Azure Machine Learning. It covers data preprocessing, model training, and model registration within Azure Machine Learning. The guide also addresses the deployment of the trained model as an online endpoint for real-time inferencing, along with its integration into web applications for seamless user interactions. Read more
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Deploying AI Agent LLM Web Application on Azure App Service
This article demonstrates deploying an AI Travel Agent on Azure using Azure App Service, GitHub Actions, and Azure Cosmos DB for MongoDB. It includes steps for environment setup, deploying Python FastAPI and ReactJS, and integrating with OpenAI API, highlighting Azure App Service’s capabilities for hosting AI applications. Read more
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Cross-Region Replication with Azure Cosmos DB for MongoDB vCore
Explore the benefits of cross-region replication with Azure Cosmos DB for MongoDB vCore. Learn how to enhance data availability, scale read operations globally, and simplify disaster recovery. This post provides a detailed guide on setting up cross-region replication to ensure robust data management in a distributed environment. Read more
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Effortlessly Add Traces to Your LangChain Agent with LangSmith
After developing your LangChain Agent or LLM application, ensuring its ongoing performance is crucial. LangSmith provides seamless trace capabilities, bridging the gap between prototypes and production-grade applications. This article demonstrates how to implement LangSmith tracing to monitor and optimize your agent’s behavior effectively. Read more
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Semantic Kernel Python Vector Search with Cosmos DB for MongoDB
This article serves as a fundamental guide for utilizing Semantic Kernel and Python with Azure Cosmos DB for MongoDB. It covers setting up Python, and loading data into Azure Cosmos DB. The process facilitates seamless Semantic Kernel integration and offers powerful language capabilities for developers. Read more
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Empower your AI Agent with Azure Cosmos DB
This article explores the implementation of a LangChain Agent using Azure Cosmos DB for MongoDB vCore to handle traveler inquiries and bookings. The project provides detailed instructions for setting up the environment and loading travel data, aiming to empower developers to integrate similar agents into their solutions. Read more
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Improve LLM Performance Using Semantic Cache with Cosmos DB
Explore the advantages of leveraging Azure Cosmos DB Semantic Cache to boost LLM retrieval performance with OpenAI, resulting in cost savings and enhanced response times. This article offers a detailed walkthrough for seamlessly integrating the semantic cache into your current web application, showcasing its effects on LLM retrieval time, API expenses, and scalability. Read more
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Azure Cosmos DB for MongoDB HNSW Vector Search
This article discusses leveraging the new HNSW Vector Index feature in Azure Cosmos DB for MongoDB vCore using Python and LangChain. It covers enabling the HNSW index, setting up Python, loading data, and conducting a vector search. Read more
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LangChain RAG with React, FastAPI, Cosmos DB Vectors: Part 3
In Part 3, we focus on crafting a dynamic React web interface, the final step in our series. This installment marks the conclusion of our three-part journey, where we’ve achieved significant milestones, from loading vectors into Azure Cosmos DB for MongoDB vCore to developing our React UI. Read more
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