DEDUPED Hot AI repos, turned into use cases Get 5 a day

How to rerank retrieved documents with Jev Noul scores with Awesome Jev

Send candidate documents as Noul questions in one request and sort by the returned scores.

Who it is forA developer building retrieval search who wants a reranker for candidate documents from a vector store.

The problemThe first retrieval pass returns plausible but loosely ordered documents, and the best match is often lower in the list.

The outcomeCandidates sorted by Jev relevance scores, with each document still tied to its original index.

What you need first

  • Access to Jev through the TypeSafe early-access entry point at typesafe.ai
  • A small labeled sample of your own data to check Jev answers before relying on them

Steps

  1. Open the milvus-model repository at github.com/milvus-io/milvus-model and install its Python reranker adapter as its README describes.
  2. Pass your query and the candidate documents to the Jev reranker adapter in one request.
  3. Check that the returned scores are sorted and that original document indices are preserved.
  4. Compare the new order with your current reranker on a set of known queries.

Prompt for your agent

Using the Jev reranker adapter in the milvus-model repository at github.com/milvus-io/milvus-model, rerank the candidate documents for <query> from <candidate set>. Output the sorted documents with original indices and scores. Verify that the top result matches a hand-judged best match for three queries.

Caveat. The hosted Jev model accepts text only, so only text documents can be reranked this way.

Share: X LinkedIn Hacker News Email Copy link

Disclaimer

Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked "Seen in the wild", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email [email protected] and we will look at it promptly. Full disclaimer page