RequestHunt is a community-driven platform that collects and curates feature requests from X (Twitter), Reddit, and GitHub. We help product teams discover what features real users are asking for, making it easier to validate product ideas and prioritize feature development based on actual user demand.

How does RequestHunt collect feature requests?

RequestHunt uses AI-powered extraction to automatically collect feature requests from social media platforms including X, Reddit, and GitHub. The platform monitors discussions, issues, and posts to identify genuine user feature requests, extracting key information like the requested feature, product mentioned, and user sentiment.

Who uses RequestHunt?

RequestHunt is used by product managers, founders, developers, and product teams who want to discover what features real users are requesting. It's particularly valuable for startups looking to validate ideas, established companies prioritizing their roadmap, and developers building products that solve real user problems.

Is RequestHunt free to use?

Yes, browsing and searching feature requests on RequestHunt is completely free. We also offer API access for developers who want to integrate feature request data into their own applications. Check our pricing page for API plan details.

How often is RequestHunt data updated?

RequestHunt continuously collects feature requests from Reddit, X (Twitter), and GitHub. You can also trigger on-demand scraping via the API or web interface to get the freshest data for any topic.

[verl] LoRA support for Async VLLM

The user requests LoRA support for the Async VLLM worker in verl.

Original Source

@@aakashks | 8 pts | 6/16/2025

currently, LoRA seems to be supported only for the vLLMRollout (sync. one) https://github.com/volcengine/verl/blob/7737bf06e5c598a8ff4c05d07b713450d4cf308d/verl/workers/sharding_manager/fsdp_vllm.py#L266 inference_engine for the async worker doesn't have the attribute llm_engine, and thus an error is raised. is anyone working on this issue? if not, I'd love to contribute!

Discussion

Loading comments...