fix: fix create-by-file doc_form

[fatelei]

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Summary

fix #31340

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 make lint and make type-check (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 resolves an issue where the document form (doc_form) was not being correctly initialized based on the dataset's configured chunk structure during file uploads. By adjusting the default assignment logic and reordering dataset validation, it ensures that documents are processed with the intended chunking configuration, improving data consistency and user experience.

Highlights

• Default doc_form logic: The default value for doc_form when creating or updating documents by file now correctly utilizes the dataset.chunk_structure if available, falling back to 'text_model' otherwise. Previously, it always defaulted to 'text_model'.
• Dataset validation order: The dataset lookup and validation checks (for existence and external provider status) have been moved to the beginning of the post methods in both DocumentAddByFileApi and DocumentUpdateByFileApi for earlier error detection.

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[gemini-code-assist]

Code Review

The pull request effectively addresses the issue by correctly utilizing the dataset's chunk_structure for the doc_form when creating or updating documents via file upload. The refactoring to move the dataset validation to an earlier stage in the function is a good practice, ensuring that invalid datasets are caught quickly. This improves both correctness and maintainability. There are minor redundancies in type casting that can be removed for cleaner code.