Data Science Basics ：How To USE New OpenAI Embeddings Model with LlamaIndex 🦙

OpenAI introduces new Embeddings model. They are releasing new models, reducing prices for GPT-3.5 Turbo, and introducing new ways for developers to manage API keys and understand API usage. The new models include:
– Two new embedding models
– An updated GPT-4 Turbo preview model
– An updated GPT-3.5 Turbo model
– An updated text moderation model
Blog post link: https://openai.com/blog/new-embedding-models-and-api-updates

Embeddings are the secret sauce behind retrieval-augmented generation: they encode text by its meaning, allowing us to retrieve by meaning instead of keyword. The more accurate your embeddings, the better your app and these are a LOT better!

`text-embedding-3-small` should be your new go-to over its predecessor `text-embedding-ada-002`: it’s not only more accurate, it’s also 5x cheaper! And `text-embedding-3-large` squeezes even more performance out of embeddings at a higher cost.

Both embeddings support a novel “dimensions” parameter that lets you shorten the embeddings to trade accuracy for smaller vector sizes.

In this video, I will show you how to get started with the new OpenAI embeddings model with LlamaIndex.

Github link: https://github.com/sudarshan-koirala/youtube-stuffs/blob/main/llamaindex/OpenAI_new_embeddings.ipynb

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🔗 🎥 Other videos you might find helpful:

🔥 Databricks playlist: https://youtube.com/playlist?list=PLz-qytj7eIWXTqncmCCSOw-GcBu2c4K0j&si=E3Yup56kmYWM_jb6

⛓️ Langflow: https://youtu.be/18b7u_e5tnM
⛓️ Flowise: https://youtu.be/LNF2DbmADus

🔥Chainlit playlist: https://youtube.com/playlist?list=PLz-qytj7eIWWNnbCRxflmRbYI02jZeG0k

🦜️🔗 LangChain playlist: https://www.youtube.com/playlist?list=PLz-qytj7eIWVd1a5SsQ1dzOjVDHdgC1Ck

🦙 LlamaIndex Playlist: https://youtube.com/playlist?list=PLz-qytj7eIWWqLRAJh-Q_fuvs0qH739zz&si=HdV9GkOQZOMRUNpW

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#llamaindex #openai #embeddingsmodel #llm #chatgpt #ai #datasciencebasics