feat: support jina rerank for text & image#62
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Signed-off-by: Keming <kemingyang@tensorchord.ai>
Signed-off-by: Keming <kemingyang@tensorchord.ai>
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Pull Request Overview
This PR adds support for Jina rerank functionality for both text and image documents. It introduces a new JinaReranker class that can handle multimodal reranking and extends the existing rerank infrastructure to support both text-only and multimodal reranking scenarios.
- Added Jina rerank provider with support for text and image document types
- Extended the base reranker interface to include multimodal reranking capabilities
- Updated pipeline to handle multimodal reranking when multimodal embeddings are configured
Reviewed Changes
Copilot reviewed 6 out of 6 changed files in this pull request and generated 3 comments.
Show a summary per file
| File | Description |
|---|---|
| vechord/utils.py | Added rate limit constant for Jina rerank API |
| vechord/rerank.py | Added abstract multimodal rerank method and JinaReranker implementation |
| vechord/provider.py | Added JinaRerankProvider class and removed docstring comments |
| vechord/pipeline.py | Updated pipeline to support multimodal reranking and removed some validation |
| vechord/model/jina.py | Added Jina rerank request/response models with multimodal support |
| vechord/model/init.py | Exported new Jina rerank model classes |
Comments suppressed due to low confidence (1)
vechord/rerank.py:102
- The
modelparameter is required infrom_query_docsbut has a default value in the JinaReranker constructor. This could cause confusion as the method signature doesn't match the expected usage pattern.
def fuse(self, retrieved_chunks: list[list[T]]) -> list[T]:
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