Lynavo/rag-gpt
RAG-GPT, leveraging LLM and RAG technology, learns from user-customized knowledge bases to provide contextually relevant answers for a wide range of queries, ensuring rapid and accurate information retrieval.
RAG-GPT, leveraging LLM and RAG technology, learns from user-customized knowledge bases to provide contextually relevant answers for a wide range of queries, ensuring rapid and accurate information retrieval.
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Latest capture 2026-06-20 03:08
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RAG-GPT, leveraging LLM and RAG technology, learns from user-customized knowledge bases to provide contextually relevant answers for a wide range of queries, ensuring rapid and accurate information retrieval.
RAG Web UI is an intelligent dialogue system based on RAG (Retrieval-Augmented Generation) technology.
⚡️ Build Your Own chatgpt Bot|🧀 Discord/Slack/Kook/Telegram |⛓ ToolCall|🔖 Plugin Support | 🌻 out-of-box | gpt-4o
Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.
🥤 RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL
RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.