The Rerank model in RAG needs to support independent score_threshold and top_k

[hustyichi]

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1. Is this request related to a challenge you're experiencing? Tell me about your story.

Currently, the retrieval model and the re-ranking stage share the score_threshold and top_k parameters, which currently have the following problems:

1. The retrieval model and the re-ranking model have different score distributions and need to use different thresholds, which cannot be supported under the current solution;
2. In order to ensure the integrity of the information, as much text as possible is generally recalled during the retrieval stage, and compressed to a relatively small number after the re-ranking is completed to match the input context of the large model. Currently, when top_k is shared, if top_k is set too small, the retrieval stage cannot recall enough content, affecting the recall rate, or if top_k is set too large, it exceeds the context of the large model;

2. Additional context or comments

No response

3. Can you help us with this feature?

• [ ] I am interested in contributing to this feature.

[nadirvishun]

A lot of people have been giving feedback for a long time, like: #7187, and the officials are aware of it, but are slow to change it.