First, make sure you understand what embeddings are and what they’re used for. Please read this documentation to get a clear overview of the concept.
Go to the “Modules” of AI Engine. Enable the “Knowledge” option to display the “Knowledge” tab:
You should now see a new tab called “Knowledge”. This is where you’ll manage all your embeddings within AI Engine.
From this tab, you can create, upload, organize, and maintain your knowledge bases.
Now you’ll need to create the environment, which only takes a few clicks. Go in the Settings tab, under the Knowledge section, click the green + button next to Environments for Embeddings.
Select OpenAI Vector Store.
Let’s go to the OpenAI API platform where we will be able to create our new vector store.
Click the “Create” and configure based on your preferences.
Copy the “ID” and set it to AI Engine settings.
Select an OpenAI environment.
You’re done! 🎉
Now, go back to the Knowledge tab, select your environment in the “Select” input and start adding your embeddings.
You can read this documentation to explore the different ways to create or import them, depending on your workflow and the type of data you want to use.
Don’t forget to select this environment in your chatbot settings to actually use it.
Advanced
If you get this message, this is either because you did not select any environment for this vector store, or the environment is not the same as the chatbot you are trying to use right now. For this, go to the environment settings again and choose the right environment.
Add files to your Vector Store. Vector Stores are entirely configurable on the OpenAI API platform, so if you want to modify it, add files, or remove files, there’s nothing to do in AI Engine after this point. Now, everything will happen on OpenAI, and your chatbot will query this vector store remotely.
You can also use the Knowledge tab to add vectorized data as you would with a normal vector database like Pinecone. This includes syncing all of your posts automatically inside your vector store.
