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* 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
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📈 Roadmap
🎯 Q2 2025
- HNSW backend integration
- DiskANN backend with MIPS/L2/Cosine support
- Real-time embedding pipeline
- Memory-efficient graph pruning
🚀 Q3 2025
- Advanced caching strategies
- Add contextual-retrieval https://www.anthropic.com/news/contextual-retrieval
- Add sleep-time-compute and summarize agent! to summarilze the file on computer!
- Add OpenAI recompute API
🌟 Q4 2025
- Integration with LangChain/LlamaIndex
- Visual similarity search
- Query rewrtiting, rerank and expansion