### What problem does this PR solve?
Fix: Create dataset performance unmatched between HTTP api and web ui
#10925
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Introduced gpu profile in .env
Added Dockerfile_tei
fix datrie
Removed LIGHTEN flag
### Type of change
- [x] Documentation Update
- [x] Refactoring
### What problem does this PR solve?
- Modify error message assertion in chunk update test to check for
document ownership
- Add GraphRAG configuration with `use_graphrag: False` in dataset
update tests
- Fix actions:
https://github.com/infiniflow/ragflow/actions/runs/16863637898/job/47767511582
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
- Update BaseModel to use model_config instead of Config class
- Replace StrEnum with Literal types for method fields
- Convert Field declarations to Annotated style
### Type of change
- [x] Refactoring
### What problem does this PR solve?
- Update `get_parser_config` to merge provided configs with defaults
- Add GraphRAG configuration defaults for all chunk methods
- Make raptor and graphrag fields non-nullable in ParserConfig schema
- Update related test cases to reflect config changes
- Ensure backward compatibility while adding new GraphRAG support
- #8396
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Updated the default `chunk_token_num` value in `api_utils.py` and
`validation_utils.py` to 512 to accommodate larger text chunks. Adjusted
corresponding test cases in HTTP and SDK API tests to reflect this
change.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Previous:
- Defaulted to hardcoded model 'BAAI/bge-large-zh-v1.5@BAAI'
- Did not respect user-configured default embedding_model
Now:
- Correctly prioritizes user-configured default embedding_model
Other:
- Make embedding_model optional in CreateDatasetReq with proper None
handling
- Add default embedding model fallback in dataset update when empty
- Enhance validation utils to handle None values and string
normalization
- Update SDK default embedding model to None to match API changes
- Adjust related test cases to reflect new validation rules
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
- Remove pagerank from CreateDatasetReq and add to UpdateDatasetReq
- Add pagerank update logic in dataset update endpoint
- Update API documentation to reflect changes
- Modify related test cases and SDK references
#8208
This change makes pagerank a mutable property that can only be set after
dataset creation, and only when using elasticsearch as the doc engine.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
