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Closes: #12889 ### What problem does this PR solve? When syncing external data sources (e.g., Jira, Confluence, Google Drive), updated documents were not being re-chunked. The raw content was correctly updated in blob storage, but the vector database retained stale chunks, causing search results to return outdated information. **Root cause:** The task digest used for chunk reuse optimization was calculated only from parser configuration fields (`parser_id`, `parser_config`, `kb_id`, etc.), without any content-dependent fields. When a document's content changed but the parser configuration remained the same, the system incorrectly reused old chunks instead of regenerating new ones. **Example scenario:** 1. User syncs a Jira issue: "Meeting scheduled for Monday" 2. User updates the Jira issue to: "Meeting rescheduled to Friday" 3. User triggers sync again 4. Raw content panel shows updated text ✓ 5. Chunk panel still shows old text "Monday" ✗ **Solution:** 1. Include `update_time` and `size` in the chunking config, so the task digest changes when document content is updated 2. Track updated documents separately in `upload_document()` and return them for processing 3. Process updated documents through the re-parsing pipeline to regenerate chunks [1.webm](https://github.com/user-attachments/assets/d21d4dcd-e189-4d39-8700-053bae0ca5a0) ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue)