Entry-Level AI Integration want first year and second year student of Computer Engineering or AI/ML

I’m planning a small-scale project that connects a large-language-model back end to a simple web interface so it can take user-supplied text and return a concise, well-structured summary.

Core scope
• Integrate an LLM (OpenAI, Hugging Face, or any comparable model you’re comfortable with) into a lightweight API layer.
• Deploy that service on a mainstream cloud platform—AWS, Google Cloud, or Azure all work—using best practices for security keys and cost control.
• Provide a minimal front-end or Postman collection that shows the summarization endpoint in action.

Ideal profile
I’d like to collaborate with students in their 1st or 2nd year of Computer Engineering or AI/ML who want real-world exposure to cloud pipelines and prompt engineering. A solid grasp of Python or Node.js, Git, and basic REST principles is enough; I’ll supply the repository skeleton and access tokens where needed.

Deliverables
1. Clean, commented source code in a Git repo.
2. Deployment scripts or Terraform files that spin up the service end-to-end.
3. README with setup steps, model choice rationale, and a short report (≈500 words) benchmarking summary quality on at least three sample texts.