Building RAG With OpenAI GPT-4o(omni) Model Using Objectbox Vector Database
In this video we will be using OpenAI GPT-4o model for creating a RAG application using Object Vector Database.GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction—it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time(opens in a new window) in a conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models.
Docs: https://docs.objectbox.io/ann-vector-...
github code: https://github.com/krishnaik06/Update...
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