AI agents & chatbot
In the previous lesson you added Storage in DYPAI in a simple way. This video is about building an AI agent for your app.
Credentials and Gemini
You will use the Gemini API. As in the first tutorials, API credentials must live under Credentials in your project—Add new if you do not have them yet. Once Gemini is saved, your agent can use it when you choose which model it should run.
Dybot and the assistant endpoint
Open a new conversation and ask the AI to implement an AI assistant for your site (a chat you can talk to). The agent will look up the credentials you added, scan nodes and documentation, and start generating the right endpoint for the assistant.
First tests
When the run finishes, try a simple prompt—for example “hello” or “how do I create a task?” You should get an answer because the stack is already wired to DYPAI Web. By default the assistant may pick a baseline model; you can change it.
Changing the model
In the UI (for example the Dybot / agent area), pick the agent you created. You can switch from Gemini 2 Flash to a newer profile such as Gemini 3 Flash, hit Save, and the agent on the web updates automatically—no extra deploy step for that choice.
Endpoints as tools
One of the features that stands out in DYPAI: your own endpoints can become tools for the agent. Endpoints you already use from the UI—for create task, list tasks, and so on—can be turned into tools and assigned to the agent.
You can do that manually (for example turn create task into a tool and see it under Tools in the assistant), or you can ask your AI to wire create, search, group, and delete tasks so everything is connected. Send the prompt and wait until implementation finishes.
Verify in DYPAI Web
Refresh DYPAI Web: you should see those endpoints enabled as tools for the agent—so you can inspect what the AI configured.
End-to-end test
Back in the chat, ask the assistant to create a task in a test group. It should run the tools it has; you should see a success message. Refresh the app, open the test group, and confirm the task the agent created. In the dashboard, the same flows appear as tools tied to your agent.
Why this scales
As you grow your backend, agents inside DYPAI can keep using the same tools you built for users. That opens the door beyond a single visual app: other products and AI systems can connect to DYPAI and run those tools too.
What you'll learn
- Creating Gemini credentials in Credentials
- Implementing a Dybot / assistant chat and choosing the model
- Turning endpoints into tools and assigning them to the agent
- Testing task creation and confirming tools in DYPAI Web
Next
Continue with Payments. More features coming in future videos.