Скачать или смотреть Building a Professional Chat User Interface for your Agents | First Steps

Build a real, usable frontend UI for your AI agents using Google AI Studio’s Build feature and Gemini models — without writing everything from scratch.

In this video, we take the first practical step toward turning AI agents from backend code into interactive applications that users can actually use.

We start with Google AI Studio, describe an idea in plain English, and watch as Gemini generates a complete web application — including:
• A streaming chat interface
• Model selection via dropdown
• Chat history stored in local storage
• Renameable conversations
• Image generation UI
• Light / dark theme support

This is not a toy demo.
This is a serious starting point for anyone building:
• AI agents
• Agent-based apps
• LLM chat interfaces
• Image generation tools
• Internal AI tools
• Developer-facing AI products

You’ll also learn how to think architecturally about extending this UI into a production-grade application later — even though we intentionally keep this video focused on Gemini’s standard APIs only.

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🎯 What This Video Covers

✔️ Using Google AI Studio Build to generate a full web UI
✔️ Creating a chat UI for AI agents
✔️ Streaming responses from Gemini models
✔️ Viewing and expanding model “thinking” / reasoning
✔️ Selecting different Gemini models dynamically
✔️ Storing chat history in frontend local storage
✔️ Adding chat management features (new chat, rename chat, clear chat)
✔️ Adding an image generation interface
✔️ Understanding the generated TypeScript / React architecture
✔️ Learning how the service layer connects UI → Gemini APIs

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🚫 What This Video Does NOT Cover (Intentionally)

To keep this tutorial focused and approachable, we do not implement:

❌ User authentication (Google Sign-In, etc.)
❌ Backend databases (Firestore, SQL, etc.)
❌ Custom agent frameworks (ADK, MCP, A2A, etc.)
❌ Deployment & infrastructure (Cloud Run, hosting, domains)

However, we do explain:
• How this UI is architected
• Where Gemini integration lives
• How you would replace Gemini APIs with your own agent URL
• What you need to add later for a production app

This makes the video ideal as a foundation tutorial before moving into more advanced backend and agent integration topics.

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🧠 Who This Video Is For
• Developers building AI agents
• Engineers working with Gemini, MCP, ADK, or agent frameworks
• Anyone struggling to build a UI for their AI tools
• Frontend developers entering AI app development
• Backend engineers who want a usable frontend fast
• Students and indie builders exploring AI products

If you already have agents running locally or on a server and are asking:

“How do I turn this into an actual app?”

This video is for you.

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🛠️ Tools & Technologies Used
• Google AI Studio (Build feature)
• Gemini chat models
• Gemini image generation models
• TypeScript + React (generated)
• Browser local storage
• Streaming AI responses

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🧩 Chapters

00:00 Intro and Quick Preview of What We’ll Build
01:25 Aspects beyond UI for Production Apps
02:46 Feature 1 - Make Base App
06:54 Feature 2 - Add Model Selector
07:52 Feature 3 - Add Chat History
09:37 Feature 4 - Chat Rename
10:16 Feature 5 - Image Generation
12:29 Understanding the Gemini & Custom Model Integration
16:48 Understanding User Authentication, Database, Deployment
18:41 Outro

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📂 Source Code

👉 https://theailanguage.com/onlySubscri...

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🚀 Why This Matters

AI agents are powerful — but without a UI, they remain invisible.

This video shows you how to:
• Go from idea → working UI
• Iterate rapidly using AI itself
• Understand the architecture instead of blindly copying code
• Build something you can actually show users

This is how modern AI apps are built.

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If you found this helpful, consider liking, subscribing, and checking out the rest of the channel where we dive deeper into:
• Agent architectures
• MCP & A2A
• Gemini advanced usage
• Production-ready AI systems

Thanks for watching — see you in the next video.

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