AI-Based Web App for File Transformations
Budget: $250 – $750 USD
Project Title
Prototype Web App: File Upload → AI Processing → Updated File Preview & Download
Project Description
I need a small, functional prototype web application to demonstrate a proof of concept.
The workflow will be:
Upload a specific type of file (XML format).
Allow the user to choose a few processing options via checkboxes or dropdowns.
Send the file along with the chosen options to an AI API (such as OpenAI) for transformation based on the selected options.
Receive an updated version of the file from the API.
Preview the updated file in the browser using a suitable rendering library.
Allow the user to download the updated file and/or print it.
Key points:
No need for user accounts or permanent storage in this prototype.
Must include basic error handling if the API returns invalid output.
The focus is on demonstrating the flow end-to-end, not on final visual design.
All third-party libraries used must be open source or have licenses compatible with commercial use.
I will provide example XML files and sample transformation instructions for testing.
Deliverables:
Web application hosted on a free-tier service (e.g., Vercel, Netlify, or similar).
Source code and documentation so it can be run locally.
Short README on how to change the AI prompts and add more processing options.
Required Skills
Frontend development: React (preferably Next.js), TypeScript or JavaScript, Tailwind CSS (or similar).
API integration: REST/JSON, OpenAI API (or similar LLM API experience).
File handling in browser: Upload/download, XML parsing/manipulation.
Rendering: Experience with displaying structured XML data visually in the browser (e.g., SVG/Canvas-based renderers).
Basic backend/serverless experience: Creating API routes in Next.js or equivalent to handle file→AI→file roundtrip.
Version control: Git.
Nice-to-Have Skills
Experience with music notation or structured document rendering (MusicXML, SVG graphics).
Experience validating and cleaning XML data before rendering.
Familiarity with serverless deployment (Vercel, Netlify Functions, or AWS Lambda).
Prototype Web App: File Upload → AI Processing → Updated File Preview & Download
Project Description
I need a small, functional prototype web application to demonstrate a proof of concept.
The workflow will be:
Upload a specific type of file (XML format).
Allow the user to choose a few processing options via checkboxes or dropdowns.
Send the file along with the chosen options to an AI API (such as OpenAI) for transformation based on the selected options.
Receive an updated version of the file from the API.
Preview the updated file in the browser using a suitable rendering library.
Allow the user to download the updated file and/or print it.
Key points:
No need for user accounts or permanent storage in this prototype.
Must include basic error handling if the API returns invalid output.
The focus is on demonstrating the flow end-to-end, not on final visual design.
All third-party libraries used must be open source or have licenses compatible with commercial use.
I will provide example XML files and sample transformation instructions for testing.
Deliverables:
Web application hosted on a free-tier service (e.g., Vercel, Netlify, or similar).
Source code and documentation so it can be run locally.
Short README on how to change the AI prompts and add more processing options.
Required Skills
Frontend development: React (preferably Next.js), TypeScript or JavaScript, Tailwind CSS (or similar).
API integration: REST/JSON, OpenAI API (or similar LLM API experience).
File handling in browser: Upload/download, XML parsing/manipulation.
Rendering: Experience with displaying structured XML data visually in the browser (e.g., SVG/Canvas-based renderers).
Basic backend/serverless experience: Creating API routes in Next.js or equivalent to handle file→AI→file roundtrip.
Version control: Git.
Nice-to-Have Skills
Experience with music notation or structured document rendering (MusicXML, SVG graphics).
Experience validating and cleaning XML data before rendering.
Familiarity with serverless deployment (Vercel, Netlify Functions, or AWS Lambda).