eXact-RAG integrates LangChain, Ollama, FastAPI, and ChromaDB/Elasticsearch, with a user-friendly interface on Streamlit, advancing LLM capabilities.
RAG is an architectural approach enhancing Large Language Model applications by retrieving relevant data/documents for context, beneficial for chatbots and Q&A systems.
RAG involves two phases - retrieval and content generation, sourcing facts from indexed internet documents in open-domain settings or specific sources in enterprise contexts.
eXact-RAG combines RAG principles of retrieval-based conversational agents with multimodal features to process and generate responses across various modes.
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