wiki-rag and WikiRag
These are competitors offering similar RAG pipelines over Wikipedia content, with the key technical difference being that moodlehq/wiki-rag targets arbitrary MediaWiki instances via API while MauroAndretta/WikiRag is specifically optimized for Wikipedia's knowledge base.
About wiki-rag
moodlehq/wiki-rag
An experimental Retrieval-Augmented Generation (RAG) system specialised in ingesting MediaWiki sites via their API and providing an OpenAI API interface to interact with them.
Implements a modular pipeline with separate executables for loading MediaWiki content via API, indexing embeddings into Milvus vector database, and serving queries through an OpenAI-compatible REST API with bearer token authentication and streaming support. Also provides an MCP server integration and supports incremental updates to avoid reprocessing unchanged pages.
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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