Adding RAG Capabilities to Our Chatbot with LlamaIndex

Create a new interface to add RAG functionality to the chatbot with the power of LlamaIndex.

RAG can be helpful when we want the model to quickly adapt to new information. For example, this information can be in research papers on the latest generative AI developments. Since this information is readily changing, it would be better to have a process such as RAG that can easily ingest new information.

We already tested this in the previous lesson. Let’s now focus on building this functionality into the Gradio chatbot. Since this functionality is slightly different from our multimodal chatbot, we will also separate it by creating an interface with tabs.

Uploading the PDF

Gradio provides a simple way to upload files with the File component. This will create a widget that opens a modal window, allowing the user to choose a file to upload. We will also create a tabbed interface using the Tab component.

To keep the purpose of our chatbot application clear, we will name the tabs as follows:

  • Multimodal chatbot: “Learning Assistant,” since this will be used for general learning.

  • RAG chatbot: “Document Expert,” since this would be used for interacting with specific documents and asking questions about their content.

For the sake of brevity, we have not included the multimodal chatbot code under its respective tab.

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