### What problem does this PR solve?
Fix several text issues.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
Manage message and use in agent.
Issue #4213
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Supports filter documents by empty metadata
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Deduplicate metadata lists during updates.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Document list and filter supports metadata filtering.
**OR within the same field, AND across different fields**
Example 1 (multi-field AND):
```markdown
Doc1 metadata: { "a": "b", "as": ["a", "b", "c"] }
Doc2 metadata: { "a": "x", "as": ["d"] }
Query:
metadata = {
"a": ["b"],
"as": ["d"]
}
Result:
Doc1 matches a=b but not as=d → excluded
Doc2 matches as=d but not a=b → excluded
Final result: empty
```
Example 2 (same field OR):
```markdown
Doc1 metadata: { "as": ["a", "b", "c"] }
Doc2 metadata: { "as": ["d"] }
Query:
metadata = {
"as": ["a", "d"]
}
Result:
Doc1 matches as=a → included
Doc2 matches as=d → included
Final result: Doc1 + Doc2
```
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
After a file in the file list is associated with a knowledge base, the
knowledge base document ID is returned
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
我已在下面的评论中用中文重复说明。
### What problem does this PR solve?
## Summary
This PR enhances the MinerU document parser with additional
configuration options, giving users more control over PDF parsing
behavior and improving support for multilingual documents.
## Changes
### Backend (`deepdoc/parser/mineru_parser.py`)
- Added configurable parsing options:
- **Parse Method**: `auto`, `txt`, or `ocr` — allows users to choose the
extraction strategy
- **Formula Recognition**: Toggle for enabling/disabling formula
extraction (useful to disable for Cyrillic documents where it may cause
issues)
- **Table Recognition**: Toggle for enabling/disabling table extraction
- Added language code mapping (`LANGUAGE_TO_MINERU_MAP`) to translate
RAGFlow language settings to MinerU-compatible language codes for better
OCR accuracy
- Improved parser configuration handling to pass these options through
the processing pipeline
### Frontend (`web/`)
- Created new `MinerUOptionsFormField` component that conditionally
renders when MinerU is selected as the layout recognition engine
- Added UI controls for:
- Parse method selection (dropdown)
- Formula recognition toggle (switch)
- Table recognition toggle (switch)
- Added i18n translations for English and Chinese
- Integrated the options into both the dataset creation dialog and
dataset settings page
### Integration
- Updated `rag/app/naive.py` to forward MinerU options to the parser
- Updated task service to handle the new configuration parameters
## Why
MinerU is a powerful document parser, but the default settings don't
work well for all document types. This PR allows users to:
1. Choose the best parsing method for their documents
2. Disable formula recognition for Cyrillic/non-Latin scripts where it
causes issues
3. Control table extraction based on document needs
4. Benefit from automatic language detection for better OCR results
## Testing
- [x] Tested MinerU parsing with different parse methods
- [x] Verified UI renders correctly when MinerU is selected/deselected
- [x] Confirmed settings persist correctly in dataset configuration
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
- [ ] Documentation Update
- [x] Refactoring
- [ ] Performance Improvement
- [ ] Other (please describe):
---------
Co-authored-by: user210 <user210@rt>
Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
### What problem does this PR solve?
Refactor metadata filter.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Refactoring
---------
Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
### What problem does this PR solve?
Correct metadata update behavior. #11912
When update `value` is omitted, the corresponding keys are updated to
`"value"` regardless of their current values.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Retrieval metadata filtering adds semi-automatic mode, and users can
manually check the metadata key that participates in LLM to generate
filter conditions.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Add metadata condition in document list.
Add metadata bulk update.
Add metadata summary.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Documentation Update
### What problem does this PR solve?
Fix RuntimeError when calling mindmap endpoint by converting
`gen_mindmap()` to async function and using `await` instead of
`asyncio.run()`.
### Type of change
- [ ] Bug Fix (non-breaking change which fixes an issue)
---------
Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
### What problem does this PR solve?
Manage and display memory datasets.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Treat MinerU as an OCR model.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
### What problem does this PR solve?
Cleanup synchronous functions in chat_model and implement
synchronization for conversation and dialog chats.
### Type of change
- [x] Refactoring
- [x] Performance Improvement
### What problem does this PR solve?
Feature: This PR implements a comprehensive RAG evaluation framework to
address issue #11656.
**Problem**: Developers using RAGFlow lack systematic ways to measure
RAG accuracy and quality. They cannot objectively answer:
1. Are RAG results truly accurate?
2. How should configurations be adjusted to improve quality?
3. How to maintain and improve RAG performance over time?
**Solution**: This PR adds a complete evaluation system with:
- **Dataset & test case management** - Create ground truth datasets with
questions and expected answers
- **Automated evaluation** - Run RAG pipeline on test cases and compute
metrics
- **Comprehensive metrics** - Precision, recall, F1 score, MRR, hit rate
for retrieval quality
- **Smart recommendations** - Analyze results and suggest specific
configuration improvements (e.g., "increase top_k", "enable reranking")
- **20+ REST API endpoints** - Full CRUD operations for datasets, test
cases, and evaluation runs
**Impact**: Enables developers to objectively measure RAG quality,
identify issues, and systematically improve their RAG systems through
data-driven configuration tuning.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Make RAGFlow more asynchronous 2. #11551, #11579, #11619.
### Type of change
- [x] Refactoring
- [x] Performance Improvement
### What problem does this PR solve?
Incorrect async chat streamly output. #11677.
Disable beartype for #11666.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Make RAGFlow more asynchronous 2. #11551, #11579, #11619.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
- [x] Performance Improvement
### What problem does this PR solve?
change:
new api /sequence2txt,
update QWenSeq2txt and ZhipuSeq2txt
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Try to make this more asynchronous. Verified in chat and agent
scenarios, reducing blocking behavior. #11551, #11579.
However, the impact of these changes still requires further
investigation to ensure everything works as expected.
### Type of change
- [x] Refactoring
### What problem does this PR solve?
- Update sync data source to handle metadata properly
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
### What problem does this PR solve?
New options for rag server scripts to create the super admin user when
start server.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: Zhichang Yu <yuzhichang@gmail.com>
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
issue:
#11293
change:
RagFlow not starting with Postgres DB
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Resolve the issue of missing thinking labels when viewing pre-existing
conversations
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
