Building and Monetizing ChatGPT Plugins With Spring AI and PostgreSQL pgvector

In this hands-on session, you will learn how to create custom ChatGPT plugins using Spring AI with PostgreSQL pgvector and launch the plugins on the OpenAI marketplace.

We'll start with the basics, developing a RAG-based gen AI application that uses an LLM, PostgreSQL pgvector, and Spring AI to search for information requested by users. Then, we'll introduce capabilities that will let the AI perform actions following user prompts. Finally, we'll turn the application into a plugin and launch it on the OpenAI marketplace.

0:00 OpenAI marketplace and plugin overview
6:30 Backend implementation with ChatClient
16:04 Backend implementation with EmbeddingClient
27:00 Starting the plugin configuration
35:45 Configuring REST APIs for the plugin
41:04 Finalizing the plugin configuration
44:09 Launching and testing the plugin

GitHub repo:

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[efficiencygeek]

Thanks Denis for putting this great tutorial together. One of the best topics I encountered in PGDay Chicago 2024. It was a pleasure being a cohost during your session.

[ifeolu]

Hi Denis, is there a way we could use PostgresML to specify it text if addressing certain topic, we could go to another table. This way we enhance the power of PostgresML and Spring AI