AI UI Designer for APIs

[ashitaprasad]

Tell us about the task you want to perform and are unable to do so because the feature is not available

Develop an AI Agent which transforms API responses into dynamic, user-friendly UI components, enabling developers to visualize and interact with data effortlessly. By analyzing API response structures—such as JSON or XML—the agent automatically generates UI elements like tables, charts, forms, and cards, eliminating the need for manual UI development. One can connect an API endpoint, receive real-time responses, and instantly generate UI components that adapt to the data format. It must also support customization options, allowing developers to configure layouts, styles, and interactive elements such as filters, pagination, and sorting. Finally, users must be able to easily export the generated UI and integrate it in their Flutter or Web apps.

[synapsecode]

Hi, I am interested in taking on this task for GSoC'25. Should this feature be implemented as a button in the application that triggers the AI agent, providing users with a selection of different UI options?
The user would then be able to choose one, modify certain aspects of it and receive the corresponding frontend code. This is how i envision this feature.

Please let me know if this aligns with your vision for the product. If so, I can start working on a rough implementation.

additionally, is there any restriction on the agent types or is it left to us to decide?

Thanks!

[Thanshir]

Hi Developers,

I'm very interested in contributing to the AI UI Designer for APIs project for GSoC'25. My approach involves developing a Python-based AI engine that:

1. Fetches API responses (JSON/XML) dynamically and analyzes the structure.
2. Uses AI-driven parsing to determine the best UI components (tables, charts, forms, cards, etc.).
3. Provides an interactive customization layer, allowing users to modify layouts, styles, and interactions.
4. Generates ready-to-use frontend code in Flutter (Dart), React (JavaScript), or HTML/CSS.

For the AI engine, I’m considering a Python-based implementation using:
-> FastAPI for API handling.
-> Pydantic for JSON schema validation.
-> AI/ML models (optional) for smart UI recommendations.

Would this align with your vision for the project? If so, I’d love to start working on an initial prototype to validate the approach.

Also, is there any restriction on the AI agent type, or do we have full flexibility in choosing the best approach (rule-based, ML, LLM-powered, etc.)?

Looking forward to your thoughts!

Thanks!
Thanshir Mohammed

[devojyotimisra]

@ashitaprasad Hi, I read the idea and got fascinated by it, i would love to be a part of this and start contributing, i brainstroned and got these ideas.

• AI-Powered Contextual UI Suggestions
• Real-Time Data Simulation
• Collaborative UI Design
• Adaptive UI for End-User Personalization
• Cross-Platform UI Consistency Checker
• API-to-UI Storytelling Mode
• Self-Optimizing UI Components
• One-Click Theme Generator
• API Response Prediction

Thanks!!!

[ashitaprasad]

Hi, I am interested in taking on this task for GSoC'25. Should this feature be implemented as a button in the application that triggers the AI agent, providing users with a selection of different UI options? The user would then be able to choose one, modify certain aspects of it and receive the corresponding frontend code. This is how i envision this feature.

Please let me know if this aligns with your vision for the product. If so, I can start working on a rough implementation.

additionally, is there any restriction on the agent types or is it left to us to decide?

Thanks!

Nice @synapsecode. You can through the updated application guide here to learn how you can share an idea doc to get feedback post which you can send a draft PR with your rough implementation.

[ashitaprasad]

Hi Developers,

I'm very interested in contributing to the AI UI Designer for APIs project for GSoC'25. My approach involves developing a Python-based AI engine that:

1. Fetches API responses (JSON/XML) dynamically and analyzes the structure.
2. Uses AI-driven parsing to determine the best UI components (tables, charts, forms, cards, etc.).
3. Provides an interactive customization layer, allowing users to modify layouts, styles, and interactions.
4. Generates ready-to-use frontend code in Flutter (Dart), React (JavaScript), or HTML/CSS.

For the AI engine, I’m considering a Python-based implementation using: -> FastAPI for API handling. -> Pydantic for JSON schema validation. -> AI/ML models (optional) for smart UI recommendations.

Would this align with your vision for the project? If so, I’d love to start working on an initial prototype to validate the approach.

Also, is there any restriction on the AI agent type, or do we have full flexibility in choosing the best approach (rule-based, ML, LLM-powered, etc.)?

Looking forward to your thoughts!

Thanks! Thanshir Mohammed

@Thanshir As API Dash is a privacy first API client. No data has to be sent to server.
The feature should be integrated in API Dash. So initially you can experiment in Python, but the final agent has to be written in Dart not Python. It can use Ollama as LLM backend (default) or can call ChatGPT, Anthropic APIs (in case the user chooses to use them as a backend)

You can through the updated application guide here to learn how you can share your ideas and get feedback and then work on a draft PR.

[ashitaprasad]

@ashitaprasad Hi, I read the idea and got fascinated by it, i would love to be a part of this and start contributing, i brainstroned and got these ideas.

• AI-Powered Contextual UI Suggestions
• Real-Time Data Simulation
• Collaborative UI Design
• Adaptive UI for End-User Personalization
• Cross-Platform UI Consistency Checker
• API-to-UI Storytelling Mode
• Self-Optimizing UI Components
• One-Click Theme Generator
• API Response Prediction

Thanks!!!

@devojyotimisra You can through the updated application guide #564 to learn how you can share more details on your ideas, get feedback and then work on a draft PR implementation.

[Dishika18]

Hi @ashitaprasad, I’d love to work on this task for GSoC’25!
I’m thinking of implementing this as a drag-and-drop interface where users can visually arrange UI components based on API data. The AI Agent will analyze the response and suggest an initial layout, which users can refine by dragging in elements like tables, charts, or forms. They’ll also be able to customize styles, interactions, and layout options before exporting the final code. This way, the process stays flexible and user-friendly.

Does this approach align with your vision for the project?
Additionally, are there any specific technologies or constraints I should consider while implementing it?

Thanks!

[ashitaprasad]

Hi @ashitaprasad, I’d love to work on this task for GSoC’25! I’m thinking of implementing this as a drag-and-drop interface where users can visually arrange UI components based on API data. The AI Agent will analyze the response and suggest an initial layout, which users can refine by dragging in elements like tables, charts, or forms. They’ll also be able to customize styles, interactions, and layout options before exporting the final code. This way, the process stays flexible and user-friendly.

Does this approach align with your vision for the project? Additionally, are there any specific technologies or constraints I should consider while implementing it?

Thanks!

@Dishika18 Then I think a good start will be this issue #120

[SyedAbdullah58-dev]

Hi @ashitaprasad
I reviewed the task and wanted to share my understanding before moving forward. The goal is to develop an AI Agent that can dynamically transform API responses (JSON/XML) into interactive UI components like tables, charts, forms, and cards. This would allow developers to visualize and interact with API data effortlessly, without manually designing UIs.

Key features would include:
1.Automated UI generation based on API response structure
2.Support for customization (layouts, themes, filters, sorting, pagination)
3.Real-time updates as data changes
4.Export functionality for seamless integration into Flutter or Web apps

I’m interested in contributing to this and would love to discuss how I can help. Let me know if there’s a specific area you’d like me to focus on first!

Looking forward to your thoughts.

[ashitaprasad]

Hi @ashitaprasad I reviewed the task and wanted to share my understanding before moving forward. The goal is to develop an AI Agent that can dynamically transform API responses (JSON/XML) into interactive UI components like tables, charts, forms, and cards. This would allow developers to visualize and interact with API data effortlessly, without manually designing UIs.

Key features would include: 1.Automated UI generation based on API response structure 2.Support for customization (layouts, themes, filters, sorting, pagination) 3.Real-time updates as data changes 4.Export functionality for seamless integration into Flutter or Web apps

I’m interested in contributing to this and would love to discuss how I can help. Let me know if there’s a specific area you’d like me to focus on first!

Looking forward to your thoughts.

@SyedAbdullah58-dev you can go through the application guide #564 to learn how you can share more details on your ideas, get feedback and then work on a draft PR implementation.

[vedantpatel07756]

Hello @ashitaprasad,

I'm interested in contributing to this issue as part of my GSOC 2025 participation. With my expertise in Flutter and AI integration using Gemini, I’d like to help build the AI-driven UI generator for API responses.

My Approach:
Analyze API Responses – Develop a mechanism to parse JSON/XML structures and categorize data fields.
Generate Dynamic UI Components – Use Flutter to automatically create UI elements like tables, forms, and cards based on API response formats.
Implement Customization Options – Add filters, sorting, and pagination controls to enhance UI usability.
AI Integration – Leverage Gemini AI to suggest optimized UI layouts and improve user experience.
Export & Integration – Allow users to export the generated UI and integrate it seamlessly into their projects.
I'd love to discuss this further and align my implementation with the project's vision. Please let me know how I can proceed!

Looking forward to your feedback.

Best regards,
Vedant Patel

[ashitaprasad]

Hello @ashitaprasad,

I'm interested in contributing to this issue as part of my GSOC 2025 participation. With my expertise in Flutter and AI integration using Gemini, I’d like to help build the AI-driven UI generator for API responses.

My Approach: Analyze API Responses – Develop a mechanism to parse JSON/XML structures and categorize data fields. Generate Dynamic UI Components – Use Flutter to automatically create UI elements like tables, forms, and cards based on API response formats. Implement Customization Options – Add filters, sorting, and pagination controls to enhance UI usability. AI Integration – Leverage Gemini AI to suggest optimized UI layouts and improve user experience. Export & Integration – Allow users to export the generated UI and integrate it seamlessly into their projects. I'd love to discuss this further and align my implementation with the project's vision. Please let me know how I can proceed!

Looking forward to your feedback.

Best regards, Vedant Patel

@vedantpatel07756 you can go through the application guide #564 to learn how you can share more details on your ideas, get feedback and then work on a draft PR implementation.

[adityakumar-dev]

@ashitaprasad
Hi everyone,

I am eager to contribute to this project for GSoC 2025 and excited about the potential of leveraging AI-driven automation to enhance API response visualization. The concept of an AI Agent that intelligently transforms structured data (JSON/XML) into dynamic UI components aligns well with modern development trends, accelerating rapid prototyping and improving developer efficiency.

With my experience in Flutter, React, and Next.js, along with a strong background in API integrations and UI/UX development, I see this as an opportunity to bring cutting-edge AI-driven UI generation to developers. To ensure alignment with the project’s vision, I have a few key questions:

Should the AI agent generate multiple UI component options, allowing users to select and refine them, or should it focus on an optimized, context-aware generation?
What level of customization and adaptability is expected? Should users have granular control over layouts, styles, and interactive elements like sorting, pagination, and filtering?
Are there any preferred AI/ML models or existing frameworks that would best fit this implementation?
I am particularly interested in applying AI-powered automation for streamlining frontend development and would love to collaborate on defining an architecture that ensures scalability, maintainability, and real-time adaptability. Looking forward to feedback from the mentors and the community!

Best regards,
Aditya Kumar

[ashitaprasad]

@ashitaprasad Hi everyone,

I am eager to contribute to this project for GSoC 2025 and excited about the potential of leveraging AI-driven automation to enhance API response visualization. The concept of an AI Agent that intelligently transforms structured data (JSON/XML) into dynamic UI components aligns well with modern development trends, accelerating rapid prototyping and improving developer efficiency.

With my experience in Flutter, React, and Next.js, along with a strong background in API integrations and UI/UX development, I see this as an opportunity to bring cutting-edge AI-driven UI generation to developers. To ensure alignment with the project’s vision, I have a few key questions:

Should the AI agent generate multiple UI component options, allowing users to select and refine them, or should it focus on an optimized, context-aware generation? What level of customization and adaptability is expected? Should users have granular control over layouts, styles, and interactive elements like sorting, pagination, and filtering? Are there any preferred AI/ML models or existing frameworks that would best fit this implementation? I am particularly interested in applying AI-powered automation for streamlining frontend development and would love to collaborate on defining an architecture that ensures scalability, maintainability, and real-time adaptability. Looking forward to feedback from the mentors and the community!

Best regards, Aditya Kumar

@adityakumar-dev Do some research and submit an idea doc as mentioned in our application guide #564

[AllenWn]

Hi mentors,
My name is Ning, a second-year undergraduate student majoring in Computer Engineering at the University of Illinois at Urbana-Champaign. I have experience in Python, Dart, Flutter, and React, and I’ve built full-stack projects and AI-powered tools that involve API integration, UI generation, and model-based automation.
In my past internships, I’ve worked on multimodal AI models and backend system design, and I’ve developed an AI-assisted email management app using Flutter and Go, which deepened my understanding of both frontend design and API-driven interfaces. I'm particularly excited about combining AI and UI automation, and I’m eager to contribute to tools that help developers work faster and smarter.

I’m particularly interested in contributing to the “AI UI Designer for APIs” idea.
This project aligns closely with both my technical background and my interests — I enjoy working at the intersection of APIs, frontend automation, and developer tooling. I’ve previously built apps that automatically generate UI from structured inputs, and I find the idea of using AI to simplify repetitive UI development both exciting and impactful.
I’m drawn to this idea because it turns raw data into something instantly useful — and I love building tools that reduce friction for developer

From what I understand, the goal of this project is to build an AI agent that can take an API response (like JSON or XML) and automatically turn it into dynamic UI components — such as tables, forms, or charts — that developers can customize and export. This would allow users to quickly visualize API data and generate usable frontend code, without manually designing the UI from scratch. The final agent should be fully integrated into the API Dash app, written in Dart/Flutter, and support interactive customization of layouts, styles, and functionality.

And then is my approach to achieve this.
STEP1:
The first step is to take in raw API responses — usually in JSON or XML — and understand their structure. This includes detecting: The type of data (string, number, object, array, etc.), The nesting level, Any special patterns (like timestamp, currency, list of items, etc.)
I'll build a parser that can walk through the response and output a clean structure or schema. This will be the input to the UI generator. For now, I’ll focus on JSON first and add XML support later. Tools: Dart JSON parser / simple recursive parser.
STEP2:
And then the second step is to Design the AI Agent Logic. This part decides what kind of UI to generate based on the data. I'll start with a rule-based approach, for example: If it's a list of objects → generate a table, If it's a number over time → suggest a line chart, If it's a simple key-value object → make a card or form.
Then, I plan to optionally plug in an LLM-based backend like Ollama or GPT to get more context-aware suggestions, such as naming fields or reordering layout. The user will be able to trigger the AI agent manually and choose from suggestions.
STEP3:
Step 3 is to Build the UI Component Generator (Flutter)
Once we know the structure and the layout plan, I’ll dynamically generate Flutter widgets like: DataTable for tabular data, Card or Container for object views, TextField, Dropdown for interactive elements, (Optional) Chart widgets like fl_chart for visualizations
I’ll also build a way for users to: Rearrange layouts (maybe drag-and-drop or form-based), Customize styles, labels, visibility, Preview the generated UI
All of this will happen inside the API Dash interface, so the experience is smooth and consistent.
STEP4:
Step 4 is to Export and Reuse the Generated Code
After the user finalizes their design, they should be able to export the UI as actual Flutter code (or optionally JSON if we go for config-based rendering).
This step will include: Formatting and organizing the generated Dart code, Optional download or copy-to-clipboard feature, (Optional) Export as a standalone component or snippet
This makes it easy to plug the generated UI directly into real projects.
STEP5:
The Last Step is to Integrate It All into API Dash
Finally, I’ll integrate everything into the API Dash app: Add a button like “AI UI Designer” next to API response, Open a UI editor view that shows suggestions, Make sure everything runs locally (privacy-friendly), then Write proper tests, docs, and cleanup UI polish
I’ll follow API Dash’s current architecture and contribute in line with their best practices (I’ve already started exploring the repo and Dev Guide).

I’ve already started exploring the API Dash repository and developer documentation to better understand the architecture and how new features are integrated. I'm also experimenting with parsing sample API responses and thinking through how to structure the UI generation logic.
I’d love to hear your feedback on this plan — does this direction align with what you envision for the project? If it looks good, I’d like to start drafting my proposal based on this approach.
Also, in case this idea already has a contributor assigned, I’m completely open to switching to another project within API Dash. If there are other ideas that you think would be a good fit for my background and skills, I’d really appreciate your suggestions!
Thanks again for your time and guidance — I’m excited to keep learning and contributing!

[ashitaprasad]

Hi @AllenWn You can take a look at the application guide here and learn how to share your idea details with architecture and implementation plan and get feedback.

[rkmaurya93049]

Hi @ashitaprasad ,

I am thrilled to express my interest in contributing to this fascinating project for GSoC 2025. The concept of developing an AI Agent that intelligently transforms structured API responses (JSON/XML) into dynamic, customizable UI components resonates strongly with my passion for leveraging automation to enhance developer workflows and efficiency.

With my hands-on experience in Flutter, React, and Next.js, alongside a solid background in API integrations and UI/UX design, I believe I can make meaningful contributions to this project. This opportunity excites me as it aligns perfectly with my expertise and interest in modern, AI-driven development approaches.
To ensure my understanding aligns with the project’s vision, I would like to clarify the following aspects:

I am keen on contributing to an architecture that ensures scalability, maintainability, and real-time adaptability, bringing cutting-edge innovations to the developer community. I look forward to collaborating with the mentors and the community on this exciting venture.

Best regards,
Raushan Kumar

[soh-123]

Hi @ashitaprasad

I'm excited about the opportunity to contribute to this project for GSoC 2025! The idea of building an AI agent that intelligently translates structured API responses (JSON/XML) into dynamic, customizable UI components perfectly aligns with my passion for automation and improving developer workflows.

With hands-on experience in Flutter, React, and Next.js, as well as a solid background in API integrations and UI/UX design, I’m confident that I can bring valuable contributions to the project. This challenge excites me because it combines modern AI-driven approaches with practical solutions for developers.

To ensure my approach aligns with the project’s vision, I’d love to clarify a few key aspects. I’m particularly interested in designing an architecture that prioritizes scalability, maintainability, and real-time adaptability, making the solution both efficient and future-proof. Looking forward to collaborating with mentors and the community on this exciting journey!

Best
Sohier Lotfy

[animator]

@soh-123 You have to send across a draft PR implementing some part of your proposal.