feat: skip rerank if only one dataset is retrieved

[fatelei]

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Summary

fix #29575

only one dataset skip rerank

Screenshots

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Checklist

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

[gemini-code-assist]

Summary of Changes

Hello @fatelei, I'm Gemini Code Assist¹! 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 introduces an optimization to the retrieval process by preventing unnecessary reranking. Specifically, if the system is only working with a single dataset, the second reranking step is now bypassed. This change streamlines the workflow, enhances performance by avoiding redundant processing, and addresses a specific issue related to efficiency in single-dataset scenarios.

Highlights

• Reranking Optimization: Implemented a condition to skip the reranking process when only a single dataset is being used, improving efficiency and reducing redundant computations.
• Dataset Count Tracking: Introduced a mechanism to count the number of available datasets, which is then passed to the retrieval thread to inform the reranking decision.
• Function Signature Update: The _multiple_retrieve_thread function signature was updated to accept the new dataset_count parameter, enabling conditional reranking logic within the thread.

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[gemini-code-assist]

Code Review

This pull request introduces a performance optimization by skipping the global reranking process when only a single dataset is used for retrieval. The logic is sound and correctly implemented by checking the number of datasets before initiating reranking. My primary feedback is the absence of unit tests for this new conditional logic. While the contribution checklist indicates tests were added, they are not present in the changes. Adding tests is crucial for verifying the behavior and preventing future regressions. I have added a specific comment regarding this.