Hi,
I’m trying to build an AI chatbot for an internal use web application, something similar in functionality to Intercom’s AI Agent (Fin). At the same time, this will be a good practice for some of my skills.
I want to validate whether my approach is correct and also get the community’s feedback on parts I haven’t thought through.
Tenant (User) Creation
- User signs up
- I assign them a unique
tenant_id
Providing Knowledge to their AI Agent
- User uploads PDF or provides raw text
- If PDF, I extract the text from the PDF
- Generate embeddings using OpenAI’s Embeddings API
- Store the embeddings for each tenant in a vector DB such as Supabase Vector DB
User Interaction
- User types in their question to the chatbot from their own web app
- The widget sends the query and the tenant ID to my backend
- The backend queries the Vector DB to get the embeddings
- Then, using the embeddings as a foundation I call the actual ChatGPT API
- I forward the response to the user
I’m not looking for something overly complex, I am trying to get an MVP up and running, I just want to understand whether I’ve thought this through.