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Solution for RAG Lake Warehouse Intelligent Customer Service

Build a knowledge Q&A system based on Large Language Model (LLM) and Hucang technology, which can intelligently understand the questions raised by internal personnel of the enterprise and search for relevant answers from the massive professional technical documents uploaded by the enterprise. By introducing Retrieval Enhanced Generative (RAG) technology, the system can efficiently retrieve relevant information from massive documents and combine language models to generate accurate and professional answers, thereby improving the efficiency of knowledge management and problem-solving within the enterprise

RAG Intelligent Expert System

LakeSoul provides a native Python interface that integrates support for mainstream AI frameworks such as PyTorch for direct data calling, training, and inference. It can also support training of large models and RAG applications

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Case

Expert consultation scenario pain points for a certain new energy vehicle company

· Build an engineering knowledge Q&A system based on LLM and Hucang, which can intelligently understand the questions raised by engineering management personnel of various institutions in the automotive industry

· Search for relevant answers from professional engineering technical documents uploaded by engineering evaluation experts

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