Tutorials: Chat

Deepseek is the latest LLM to hit the digital shelves. It boasts high-quality reasoning at a fraction of the cost of current state-of-the-art models, OpenAI o1 and o3-mini, and Gemini 2.0 Flash Thinking. DeepSeek R1 is open-source, which means two things. First, developers can examine the model's architecture, training process, and weights directly, enabling a

Chat has become a necessary feature in most products. Businesses want to integrate quick, real-time communication to connect with their users. It can be for HR team management, hiring, onboarding, or within existing teams – but chat is almost everywhere. If you are a developer or product manager looking to integrate a chat API into

JavaScript is the foundation of the modern web. Without it, you don’t have the rich interaction you expect from websites, like real-time updates, video, or chat. But JS brings a problem: bloat. Modern web apps often ship megabytes of JavaScript to the browser. This slows initial page load and hurts performance, especially for mobile devices.

AI agent chats are mostly a 1:1 experience. But that misses a clear opportunity--having an AI member of your team. If every team member was participating in a chat with AI, you could collaborate as a group, create shared knowledge bases, or solve problems together more efficiently. So, let's build that. We're going to extend

Integrating AI into enterprise applications often challenges getting accurate and efficient results from LLMs. The main reason is that LLMs are trained on large datasets rather than specifically on your enterprise's data. These challenges may usually include hallucinations, outdated information presentation, and more. This article explores the integration of AI agents, or, Agentic Retrieval Augmented

In the previous article, we extended our API with endpoints to create and retrieve notes and integrated the new endpoints into the application. In this article, we will extend our application with full-stack functionality for editing and deleting notes. Editing Notes Adding the API Request Before creating the API, let's set up a dependency to

In the previous article, we extended our application with authentication and integrated it with the API. Now, will start building a note-taking application. We will focus on adding full-stack functionality for creating and viewing notes. Adding Dependencies Before building, let's add a few dependencies on the client side. Run the following command in a terminal

In this post, we will see how to build a Python server allowing frontend chat SDKs to start and stop an AI agent for a channel in Stream Chat. Building polished AI assistants can be challenging. Features like streaming responses, table components, and code generation require complex implementation across SDKs and the backend. To ease