RAG-Based-LLM-Chatbot and openvino-llm-chatbot-rag
These are competitors: both are complete RAG chatbot implementations that independently combine a local LLM with retrieval and embedding components, differing primarily in their choice of inference engine (Llama 3.2 vs. OpenVINO) rather than filling complementary roles.
About RAG-Based-LLM-Chatbot
GURPREETKAURJETHRA/RAG-Based-LLM-Chatbot
RAG Based LLM Chatbot Built using Open Source Stack (Llama 3.2 Model, BGE Embeddings, and Qdrant running locally within a Docker Container)
This tool helps individuals who need to quickly extract information from their PDF documents. You upload your PDFs, and the application processes them, allowing you to ask questions and get answers directly from your document content using a conversational chatbot. It's ideal for researchers, analysts, or anyone who frequently works with large collections of PDF files and needs an easier way to find specific details.
About openvino-llm-chatbot-rag
yas-sim/openvino-llm-chatbot-rag
LLM chatbot example using OpenVINO with RAG (Retrieval Augmented Generation).
This project helps developers, particularly those working with OpenVINO, quickly find answers to their technical questions directly from OpenVINO's official documentation. You provide the official OpenVINO web documentation as input, and it creates a local, offline Q&A chatbot. This allows you to ask questions about OpenVINO and get relevant answers without an internet connection or relying on cloud services.
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