DeepSieve is an open source Retrieval Augmented Generation (RAG) framework with key features including:
- Query decomposition: Split a complex query into multiple simple sub-problems to facilitate precise processing.
- Sub-issue routing: Intelligent assignment of sub-questions to appropriate tools or data sources (e.g., local databases or global knowledge bases).
- Reflection mechanisms: Automatically detects failed searches and retries them, supporting up to two reflections.
- Convergence of answers: Integrate sub-question answers to generate the final complete response.
- Supports multiple data sources: Handles heterogeneous data such as SQL tables, JSON logs, Wikipedia, etc.
- Two RAG modes: Provides two search modes, Naive and Graph, to suit different needs.
- Detailed logging: Save intermediate results, fusion hints and performance metrics for each query for debugging and optimization.
- modular design: Users can enable or disable function modules with command line switches for flexibility.
This answer comes from the articleDeepSieve: a RAG Intelligent Information Screening Tool for Processing Complex Query SourcesThe
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