pengjunjie/ragflow
1
0
Fork 1
mirror of https://github.com/infiniflow/ragflow.git synced 2025-12-08 20:42:30 +08:00
Code Issues Packages Projects Releases Wiki Activity

Docs: Knowledge base renamed to dataset. (#10269)

Browse Source 
### What problem does this PR solve?

### Type of change

- [x] Documentation Update
This commit is contained in:
writinwaters
2025-09-25 09:45:27 +08:00
committed by GitHub
parent 3f595029d7
commit 4058715df7
30 changed files with 152 additions and 152 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
docs/guides/dataset/best_practices/_category_.json
View File

@ -3,6 +3,6 @@
"position": 11,
"link": {
"type": "generated-index",
"description": "Best practices on configuring a knowledge base."
"description": "Best practices on configuring a dataset."
}
}

6
docs/guides/dataset/best_practices/accelerate_doc_indexing.mdx
View File

@ -13,7 +13,7 @@ A checklist to speed up document parsing and indexing.
Please note that some of your settings may consume a significant amount of time. If you often find that document parsing is time-consuming, here is a checklist to consider:
- Use GPU to reduce embedding time.
- On the configuration page of your knowledge base, switch off **Use RAPTOR to enhance retrieval**.
- On the configuration page of your dataset, switch off **Use RAPTOR to enhance retrieval**.
- Extracting knowledge graph (GraphRAG) is time-consuming.
- Disable **Auto-keyword** and **Auto-question** on the configuration page of your knowledge base, as both depend on the LLM.
- **v0.17.0+:** If all PDFs in your knowledge base are plain text and do not require GPU-intensive processes like OCR (Optical Character Recognition), TSR (Table Structure Recognition), or DLA (Document Layout Analysis), you can choose **Naive** over **DeepDoc** or other time-consuming large model options in the **Document parser** dropdown. This will substantially reduce document parsing time.
- Disable **Auto-keyword** and **Auto-question** on the configuration page of your dataset, as both depend on the LLM.
- **v0.17.0+:** If all PDFs in your dataset are plain text and do not require GPU-intensive processes like OCR (Optical Character Recognition), TSR (Table Structure Recognition), or DLA (Document Layout Analysis), you can choose **Naive** over **DeepDoc** or other time-consuming large model options in the **Document parser** dropdown. This will substantially reduce document parsing time.