Calculating the embeddings with OpenAI API
This notebook presents an end-to-end process of:

Calculating the embeddings with OpenAI API.
Storing the embeddings in a Tair instance to build a knowledge base.
Converting raw text query to an embedding with OpenAI API.
Using Tair to perform the nearest neighbour search in the created collection to find some context.
Asking LLM to find the answer in a given context.
All the steps will be simplified to calling some corresponding Langchain methods.