Intelligent Industrial AI agent with Retrieval-Augmented Generation (RAG) capabilityThe Industrial Agent can make production decisions using real-time OPCUA data, maintenance documents, and semantic search. In this solution using Python and LangChain the Industrial AI Agent has Agentic RAG capabilities which allows the system to reason over structured data (Real-time OPC UA and data from Postgres databases) as well as unstructured documents (maintenance schedules, calibration certificates, equipment reports). The RAG Pipeline uses an embedding model (mxbai-embed-large) running locally on Ollama along with Mistral LLM running locally on Ollama and ChromaDB Vector Database is used for persistent storage. NOTE: The below demo video is hosted on YouTube and incase you are unable to view this demo video then access has to be specifically provided.
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