Building a Foundational RAG-Based Document QA System: Architecture and Lessons Learned

1. 1Design a RAG-based architecture for document QA using retrieval and generation components
2. 2Implement a retrieval module to fetch relevant documents based on user queries
3. 3Develop a generation module to produce answers based on the retrieved documents
4. 4Train and fine-tune the model using a large dataset of documents and user queries
5. 5Evaluate the performance of the RAG-based system using metrics such as accuracy and F1-score

NLP engineers and researchers can benefit from this article to improve their document understanding systems, while product managers can use this knowledge to inform their product development strategies

💡 RAG-based systems can effectively retrieve and generate answers to user queries by combining retrieval and generation components

📄 Build a RAG-based document QA system for enterprise document understanding! 💡