Getting Started with OpenAI Embeddings Search & SingleStoreDB

In this article, we explored how to use SingleStoreDB to store and query the OpenAI Wikipedia vector database dataset. We created a new Singlestore Helios account, imported the notebook file from GitHub, and set up the environment with necessary libraries and imports. We then populated our database table by loading the Wikipedia dataset into a Pandas Dataframe and executing SQL statements to create and populate the table. Next, we defined a Python function that allows us to search for specific queries using either of two vector columns in the database. Finally, we tested SingleStoreDB using the OpenAI notebook examples, searching for modern art in Europe and famous battles in Scottish history, and formatting the results into tables using the `tabulate` library. Overall, this article demonstrated how SingleStoreDB can be used to store and query vectors with ease, providing a one-stop solution for modern applications that bring both technical and business benefits through a single product.

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