Component Bge Reranker

Rerank candidate documents by cross-encoder relevance score with a local BGE reranker model (BAAI/bge-reranker-large). Use after first-stage retrieval when semantic precision matters more than latency.

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BGE Reranker Component

Provide the reranker capability for an Agentic RAG slot.

Interface

Input RerankRequest:

  • query: original retrieval query
  • documents: JSON-compatible documents containing id and text
  • top_k: maximum returned documents
  • optional model, batch_size, max_length, device

Output RerankResult:

  • documents: documents re-ranked by normalized cross-encoder score

Execution

Run scripts/component.py:run(inputs, context). The Component lazily loads the local BGE cross-encoder and scores (query, passage) pairs with a Sigmoid-normalized relevance score. It performs reranking only; do not use it for first-stage retrieval or generation.

DocAILab/Agentic-RAG-Skill/tree/main/framework/skills/components/component-bge-reranker commit 75ecdea3de

Frequently asked questions

npx skillmds@latest add docailab/component-bge-reranker