FlexRAG and TrustRAG
FlexRAG provides a modular RAG framework optimized for retrieval and generation tasks, while TrustRAG adds a trust and reliability layer on top of RAG pipelines, making them **complements** that could be used together to build trustworthy information retrieval systems.
About FlexRAG
ictnlp/FlexRAG
FlexRAG: A RAG Framework for Information Retrieval and Generation.
Supports text, multimodal, and web-accessible RAG scenarios through a modular pipeline architecture with integrated retrieval metrics and reranking components. Built on vectorized indexing (Faiss, LanceDB) with pre-trained retrievers available on HuggingFace Hub, enabling end-to-end workflows from corpus preparation through system evaluation and benchmarking.
About TrustRAG
gomate-community/TrustRAG
TrustRAG：The RAG Framework within Reliable input,Trusted output
Implements a modular RAG pipeline with configurable components for document parsing, retrieval, reranking, and generation, supporting hybrid retrieval combining BM25 and dense embeddings. Features DeepSearch—a recursive query decomposition framework with token budgeting and action-based reasoning (search, reflect, answer, read, coding)—alongside multimodal QA, vector database integration (Milvus, Qdrant), and web search capabilities. Targets Python 3.10+ and integrates with LLMs like GLM-4 and OpenAI via configurable APIs.
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