[GOOD FIRST ISSUE]: ML Model Endpoints Lack Timeout Protection

[Aditya30ag]

Context

Description

Fixed a critical issue where ML model endpoints and external API calls could hang indefinitely due to missing timeout handling.

Problem

• Requests could run forever if models became unresponsive
• Flask worker threads were not released (resource exhaustion)
• Frontend showed infinite loading with no feedback
• One slow request could block the entire system

What Needs to Be Done

• Added backend timeout wrapper for all ML and external API calls
• Introduced input validation and structured error handling
• Returned proper HTTP 504 Gateway Timeout for long-running requests
• Implemented frontend request timeout using AbortController

Resources

• Contribution Guide - Start Here!
• Discord Channel

Getting Started

• I have joined the Discord server and will post updates there
• I have read the Contribution Guide
• I understand this issue is assigned on a first-come, first-served basis

[mahek2016]

Hi @Aditya30ag, I would like to work on this issue (#592).

I went through the previous PR (#593) and the CodeRabbit review comments. I understand that the main challenges are:

• Proper timeout handling (ensuring the task actually stops, not just the wait)
• Correct HTTP status handling (distinguishing between 400/500/504)
• Improving input validation
• Avoiding sequential delays in multiple ML calls
• Fixing response format inconsistencies

I’m planning to address these by using multiprocessing for true timeout enforcement, improving validation, and handling parallel execution where needed.

Please let me know if this approach sounds good or if you have any specific suggestions before I start implementing.

Thank you!