/research?mode=search
Every AI team has a backlog of techniques they want to try but never have time to evaluate. The pace of change means what was best practice weeks ago may already be suboptimal, but scanning arXiv, GitHub, and HuggingFace manually doesn’t scale.
Search provides semantic search across research papers, GitHub repositories, HuggingFace models, and more, matched to what your team is building. Pre-built Docker environments let you test a technique in minutes instead of spending days on dependency setup.
Search Interface
Type a natural-language query into the search bar. Remyx runs hybrid retrieval (BM25 + dense vector + re-ranking) across its resource index and returns ranked results./search/assets enforces a server-side deadline. If a query runs long, it returns a structured timeout (with a request id and the elapsed time) instead of hanging. Retry the request, and include the request id if you report a slow query.Filtering and Sorting
A toolbar appears above results after you search:
The Runnable tab filters to resources with verified Docker environments — useful when you want to test a technique immediately without environment setup.
Personalized Suggestions
Authenticated Users
When you’re logged in and haven’t searched yet, the page shows:- Suggestion cards built from your experiment tags — topics you’ve already explored, surfaced as quick-search shortcuts
- “Relevant to your work” section with resources matched to your team’s experiment history
Anonymous Users
When not logged in, the page shows:- Trending suggestion cards populated from live search queries
- Recent resources section with highlights from the index
Resource Detail Viewer
Click View on any result to open the resource detail page:- Details
- Chat
- Annotations
- Full abstract / README
- Resource links (arXiv, GitHub, HuggingFace)
- Citation count and categories
- Docker image reference (if available)
- Dockerfile contents (if available)
Briefs
When you create a repo-backed Research Interest, Remyx runs a typed, cited deep-research pass and stores a section-grained research brief for that repo: domain framing, a survey of approaches, future directions, candidate changes, and citations. The brief feeds recommendation ranking and grounds your agents’ drafting context. You can also ask questions about a brief and its runs by mentioning@remyx-ai on a pull request or issue an agent opened.
Briefs
How research briefs are built and stored, the Remyx bot, and paper enrichment
Related
Feed
Personalized daily recommendations
Agents
The agents that draw on this same index