RAG-system and WikiRag
These are competitors—both implement RAG pipelines for Wikipedia-based question answering, differing only in implementation details and maturity (WikiRag has slightly more stars), so users would select one based on preference rather than using them together.
About RAG-system
xumozhu/RAG-system
Retrieval-Augmented Generation system: ask a question, retrieve relevant documents, and generate precise answers. RAG demo: document retrieval + LLM answering
About WikiRag
MauroAndretta/WikiRag
WikiRag is a Retrieval-Augmented Generation (RAG) system designed for question answering, it reduces hallucination thanks to the RAG architecture. It leverages Wikipedia content as a knowledge base.
Implements a vectorization pipeline that embeds Wikipedia articles into Qdrant vector database using HuggingFace embeddings, then chains retrieval with local Ollama LLM inference. Optional DuckDuckGo web search expands context when Wikipedia knowledge proves insufficient, with evaluation metrics (semantic similarity, factual correctness) provided via Ragas library. Includes a Streamlit UI for interactive querying.
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