Building a Production-Ready AI Image Generator with Nano Banana and No-Code

The true value of powerful generative models like Google's Gemini 2.5 Flash Image (internally known as Nano Banana) lies in their deployment within robust, full-stack applications. Moving beyond a simple API playground requires integrating critical features like user authentication, payment processing, and complex business logic.

This tutorial outlines the steps to build and monetize a specialized AI image generation application using a no-code development platform, following the architecture demonstrated on Momen.

Step 1: Understanding the AI Core (Nano Banana)

Before building, understand the specific advantages of the model you're using. Nano Banana excels at:

• Photorealism and Accuracy: Generating high-fidelity images with high positional accuracy.

• Inpainting/Editing: Precisely adding or modifying elements within an existing image based on a natural language prompt.

• Multi-Modal Input: Accepting prompts that include text, a starting image, or both, making it ideal for editing and creative composition.

Step 2: Set Up the Application Structure

A monetizable application needs three core pages and a backend environment.

1. Generate Page: The primary user interface where users upload an image and input their desired prompt (the core generator).

2. User Center/Library: A personalized area where users can view and access the images they have generated previously. This requires connecting to the application's database.

3. Registration/Login Page: Standard authentication for managing user accounts and payment history.

4. Backend Workflows: Set up server-side flows for secure actions, such as creating payment orders and updating user permissions.

Step 3: Configure the Prompt Optimizer AI Agent

AI configuration in Momen

A critical feature for a polished application is prompt enhancement. This requires an intermediate AI agent to refine the user's input before it reaches the image model. Here we use Momen to build it.

1. Create an AI Agent: Within Momen's AI Agent Builder, create a new agent named "Prompt Optimizer."

2. Define the Goal: Set the agent's instructions (its System Prompt) to be an expert image prompt writer, tasked with transforming the user's input into a highly detailed, descriptive prompt suitable for Gemini 2.5 Flash.

3. Provide a Playbook: Feed the agent a list of successful prompting rules (a "Playbook")—these are examples of effective structure, technical terms (e.g., lighting, lens type), and style requirements. This data trains the agent to consistently output high-quality, professional prompts.

4. Bind Input: Ensure the agent receives both the user's text prompt and the uploaded image so it can create a context-aware refined prompt.

Step 4: Implement the Secure Monetization Workflow 💰

The core business logic resides in the backend workflow triggered when a user attempts to generate an image. This example uses a paywall that checks if the user has paid.

1. Trigger the Workflow: On the Generate Page, connect the main action button ("Enhance with AI") to a new workflow.

2. Check Payment Status: The first step is a conditional check: IF Logged-in User has_paid is FALSE.

   • If FALSE (Not Paid):

     • Create Order (Backend): Use a server-side Action Flow to securely calculate the price and create a new order record in the database. Crucially, the user cannot control this price.

     • Initiate Stripe Payment: Use the order ID and amount to call the integrated Stripe service.

     • Update Status: Upon successful payment, an asynchronous webhook from Stripe calls back to the application to update the user's has_paid status to TRUE.

   • If TRUE (Paid):

     • Bypass Payment: Skip the payment block.

3. Start Generation: Following the payment check/success block, initiate a conversation with the Prompt Optimizer AI Agent (from Step 3).

4. Final Generation: Take the refined output from the Prompt Optimizer and use it as the prompt input for the Nano Banana Image Generation API call.

5. Save Result: Write the final generated image to the user's personal database library (User Center).

Step 5: Enforce Backend Permissions

To ensure that unpaid users cannot simply find the AI agent endpoint, you must enforce permissions directly on the service.

1. AI Agent Permission: In the platform's configuration settings for the Prompt Optimizer agent, set a hard rule: Only allow use IF logged_in_user.has_paid is TRUE.

2. Credit-Based Scaling (Advanced): For a more scalable model, replace the boolean has_paid field with an integer field called credits. In the backend Action Flow, instead of simply updating to TRUE after payment, increment the credits field. The AI permission check then becomes: Only allow use IF logged_in_user.credits is GREATER THAN 0.

By following these structured steps, you leverage a no-code platform's architecture to build a highly functional, secure, and revenue-generating application powered by the sophisticated image generation capabilities of Nano Banana.