RAG Knowledge + Base Chatbot

Course Content

• On the basis of the previous RAG knowledge base and chatbot, develop an AI application that combines both to improve the AI large model's answer capability in specific domains and reduce AI large model hallucinations through the RAG knowledge base.

Start Dify Service

• Check the virtual machine's IP address. You can find it in yellow on the terminal or by entering ifconfig or checking directly in the terminal. Enter the virtual machine's IP address in the browser address bar to access the Dify management page.

Case 1: Task Planning

• Click Create from Blank on the homepage.

• Click to select Chatbot from MORE BASIC APP TYPES ——> Name your application ——> Create

• Example prompt

You are a task planning master. Using your knowledge, break down complex tasks into steps.

• After creating the application, enter the prompt in the INSTRUCTIONS section, and then click "Add" in the knowledge options.

• Select the knowledge base you want to add, then click "Add".

• Then select an AI large model to connect. Here we use qwen-max as an example.

• Then enter test conversation content. Here we take tracking as an example. You can see that the AI large model can think and respond combined with the knowledge base content. Through this method of adding training samples to the knowledge base, you can quickly expand the AI large model's response capability and learning ability in different task scenarios and domains.

• We can first delete the knowledge base to compare the AI large model's response effect without the RAG knowledge base. You can see that without the knowledge base, the general AI model from the model provider cannot handle vertical domain tasks.

Case 2: Knowledge Management

• When we have internal materials that need to be managed by a large model, we can combine the AI large model with RAG and the knowledge base. This allows the large model to respond combined with actual business materials, which is very helpful for vertical domains such as finance and healthcare.

Create a Knowledge Base

• Here we take an example material, which includes a virtual literary author and a collection of virtual works. The example material can be found in this section's course folder.

Create an Application

• Example prompt

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# Role Positioning
You are a seasoned knowledge management expert with extensive practical experience in knowledge system construction, information filtering and integration, knowledge accumulation, and empowerment. Your core mission is to help users establish a clear and efficient knowledge management system, achieving accurate knowledge collection, systematic organization, in-depth accumulation, and flexible application, thereby helping users improve their learning/work efficiency and avoid knowledge fragmentation.

• Enter the example prompt and select the virtual author's knowledge base. Then ask questions about the works in the material. At this time, the AI large model can answer based on the private knowledge base.