Tutorials: Chat

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

Have you ever wanted to chat with the characters in your favorite book? Talk to Heathcliff about his origins, Harry Potter about his first impressions of Hogwarts, Jane Eyre about Lowood, or Lizzie Bennet about Mr. Darcy's proposal. Or, maybe, like us, you can’t wait to interrogate WebRTC For The Curious to learn more about

Earlier this year, payment service Klarna launched an AI customer service assistant. Within the first month, this AI had 2.3 million conversations, the equivalent of 700 agents, and led to a 25% drop in repeated inquiries. Klarna estimated it would “drive $40 million USD in profit improvement” in 2024. Customer success is an ideal opportunity

In this post, we will see how we can build a NodeJS server that will allow frontend chat SDKs to start and stop an assistant for a given 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

Large Language Models (LLMs) are becoming increasingly prevalent, and many developers are integrating various LLM providers, such as OpenAI, Anthropic, Gemini, and others into their Stream Chat applications across multiple SDKs. To help developers get started and accelerate their development with Stream Chat and AI, we've created a platform-specific, step-by-step guide. To follow along, we

This tutorial will demonstrate how easy it is to build an AI assistant with Stream React Native Chat SDK. While this tutorial features Anthropic and OpenAI APIs as the LLM provider, you can integrate any LLM service with Stream and still benefit from the same features, such as generation indicators, markdown support, tables, etc. No

In this tutorial, we will demonstrate how easy it is to build an AI assistant for iOS using the Stream Flutter Chat SDK on both the client and server sides. For this example, we will use the Anthropic and OpenAI APIs as the LLM service, but you can use any LLM service with Stream Chat.

In this tutorial, we will demonstrate how easy it is to create an AI assistant for iOS using Stream Chat. In this example, we will use the Anthropic and OpenAI APIs as our example LLM; however, developers are free to use whichever LLM provider they like and still benefit from Stream’s rich UI support for