- Fix import order in packages/leann-backend-hnsw/leann_backend_hnsw/hnsw_backend.py (Ruff I001)
- Update benchmarks/run_evaluation.py
- Update apps/base_rag_example.py and leann-core API usage
- Add benchmarks/data/README.md
- Update uv.lock
- Misc cleanup
- Note: added paru-bin as an embedded git repo; consider making it a submodule (git rm --cached paru-bin) if unintended
* docs: config guidance
* feat: add comprehensive configuration guide and update README
- Create docs/configuration-guide.md with detailed guidance on:
- Embedding model selection (small/medium/large)
- Index selection (HNSW vs DiskANN)
- LLM engine and model comparison
- Parameter tuning (build/search complexity, top-k)
- Performance optimization tips
- Deep dive into LEANN's recomputation feature
- Update README.md to link to the configuration guide
- Include latest 2025 model recommendations (Qwen3, DeepSeek-R1, O3-mini)
* chore: move evaluation data .gitattributes to correct location
* docs: Weaken DiskANN emphasis in README
- Change backend description to emphasize HNSW as default
- DiskANN positioned as optional for billion-scale datasets
- Simplify evaluation commands to be more generic
* docs: Adjust DiskANN positioning in features and roadmap
- features.md: Put HNSW/FAISS first as default, DiskANN as optional
- roadmap.md: Reorder to show HNSW integration before DiskANN
- Consistent with positioning DiskANN as advanced option for large-scale use
* docs: Improve configuration guide based on feedback
- List specific files in default data/ directory (2 AI papers, literature, tech report)
- Update examples to use English and better RAG-suitable queries
- Change full dataset reference to use --max-items -1
- Adjust small model guidance about upgrading to larger models when time allows
- Update top-k defaults to reflect actual default of 20
- Ensure consistent use of full model name Qwen/Qwen3-Embedding-0.6B
- Reorder optimization steps, move MLX to third position
- Remove incorrect chunk size tuning guidance
- Change README from 'Having trouble' to 'Need best practices'
* docs: Address all configuration guide feedback
- Fix grammar: 'If time is not a constraint' instead of 'time expense is not large'
- Highlight Qwen3-Embedding-0.6B performance (nearly OpenAI API level)
- Add OpenAI quick start section with configuration example
- Fold Cloud vs Local trade-offs into collapsible section
- Update HNSW as 'default and recommended for extreme low storage'
- Add DiskANN beta warning and explain PQ+rerank architecture
- Expand Ollama models: add qwen3:0.6b, 4b, 7b variants
- Note OpenAI as current default but recommend Ollama switch
- Add 'need to install extra software' warning for Ollama
- Remove incorrect latency numbers from search-complexity recommendations
* docs: add a link
