fix: correct scoring in WeightRerankRunner for hybrid search

[myml]

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Summary

Fixes #28125

• Prevent text search scores from being mistakenly treated as vector search scores during deduplication, which caused inaccurate ranking
• Fix usage of document.vector for cosine similarity, as document does not have this field

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Before	After

Checklist

• [ ] This change requires a documentation update, included: Dify Document
• [x] I understand that this PR may be closed in case there was no previous discussion or issues. (This doesn't apply to typos!)
• [x] I've added a test for each change that was introduced, and I tried as much as possible to make a single atomic change.
• [x] I've updated the documentation accordingly.
• [x] I ran dev/reformat(backend) and cd web && npx lint-staged(frontend) to appease the lint gods

[gemini-code-assist[bot]]

Summary of Changes

Hello @myml, I'm Gemini Code Assist[^1]! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request resolves a critical issue in the hybrid search mechanism where the scoring of results was flawed due to the misinterpretation of full-text search scores as vector scores. The changes introduce a more robust reranking logic within the WeightRerankRunner, ensuring that keyword and vector search components are appropriately weighted and combined, leading to more accurate and relevant search result rankings.

Highlights

• Hybrid Search Scoring Correction: Implemented a fix to prevent full-text search scores from being incorrectly treated as vector search scores during the deduplication process in hybrid search, which previously led to inaccurate ranking.
• Reranking Logic Refinement: Refactored the WeightRerankRunner to correctly calculate and combine keyword and vector scores for documents, ensuring that the final score accurately reflects both search components.
• document.vector Usage Removal: Addressed an issue where document.vector was incorrectly accessed for cosine similarity calculation, as the document object does not possess this field. Vector scores are now expected to be pre-calculated or handled differently.

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[crazywoola]

Thanks for the PR, please resolve the lint errors :)