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Learn how to build a powerful, AI-powered chat feature for your iOS app! In this video, from the Firebase team shows you how to use Firebase AI Logic to create a conversational interface from scratch.
We'll start by tackling the biggest challenge in AI chat: the "stateless" nature of LLMs. You'll learn why models have no "memory" and how Firebase AI Logic's Chat API (sendMessage) automatically manages conversation history for you, making complex, multi-turn conversations possible.
Using a "Friendly Meals" sample app built with Swift and SwiftUI, you will learn how to:
Set up the Gemini 2.5 Flash model with Firebase.
Use System Instructions to give your AI a unique personality.
Enable multimodal chat (sending images like PNGs and JPEGs).
Implement real-time streaming responses (sendMessageStream) to create a smooth, modern UX and avoid lag.
Chapters:
00:04 - Introduction
01:58 - LLMs can't actually keep conversation history 🤯
03:02 - The secret to conversation: managing context
05:19 - Preparing for chat
05:55 - System instructions
06:28 - Starting a chat
06:52 - Sending messages
08:41 - Multimodal chat
10:03 - Streaming chat for improved UX
12:22 - Demo
12:39 - Conclusion
Resources:
Friendly Meals Sample App (GitHub) →
Video: Getting started with Firebase AI Logic on iOS →
Video: Gemini Developer API vs. Vertex AI API (What is Firebase AI Logic?) →
Firebase AI Logic Documentation →
Watch more Firebase Fundamentals →
Subscribe to Firebase →
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2025/11/06
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