Imagine having a smart system that can answer any question a student might ask, using a vast library of books and subject PDFs as its knowledge base. This is exactly what I’m trying to achieve in my current project, and I’d love to share my vision with you.
The goal is to design an advanced RAG (Retrieve, Generate, and Critique) system that can retrieve relevant information from a multi-book library, generate an answer to a user’s question, and then critique that answer for correctness before presenting it to the user.
Here’s how I envision the system working:
* A user asks a question.
* The system looks into the vector embeddings of the books in the library to retrieve relevant content.
* It generates an answer based on that content.
* The answer is then critiqued for correctness before being shown to the user.
This sounds like a complex task, and it is. That’s why I’m reaching out to the community for help. If you’ve worked on a similar project or have ideas on the right architecture and tools to use, I’d love to hear from you.
## Key Components of the RAG System
* **Vector embeddings**: We’ll need a way to convert the text in the books into numerical representations that can be easily compared and analyzed.
* **Relevant content retrieval**: The system should be able to identify the most relevant content in the library that answers the user’s question.
* **Answer generation**: We’ll need a module that can take the retrieved content and generate a coherent and accurate answer.
* **Critique module**: This is where the system checks the generated answer for correctness and relevance.
## Potential Tools and Technologies
* Natural Language Processing (NLP) libraries like spaCy or Stanford CoreNLP for text analysis and vector embeddings.
* Machine learning algorithms like supervised learning or reinforcement learning for answer generation and critique.
* Knowledge graph-based approaches for representing the relationships between different concepts in the library.
If you have any experience with building similar systems or have suggestions on how to approach this project, please share your thoughts. I’m excited to learn from the community and build a robust RAG system that can help students learn more effectively.
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*Further reading: [What is a RAG System?](https://www.researchgate.net/publication/329541911_Retrieve_Generate_and_Critique_RAG_Framework_for_Question_Answering)*