The author also discusses the concept of Retrieval Augmented Generation (RAG) and the benefits of building your own RAG flow. They argue that having control over the text chunking, embedding models, vector database querying, and results injection into prompts can be more beneficial than relying on OpenAI's black box solutions. The author concludes by inviting readers to share their experiences with generative AI and offers their services for integrating AI into custom software systems.
Key takeaways:
- OpenAI offers several options for utilizing their LLMs, including the Chat Completion API, Assistants API, and Custom GPTs, each with their own pros and cons.
- The Assistants API is a good option for teams wanting to integrate their software with OpenAI's models but it further locks you into OpenAI and doesn't support streaming or web browsing.
- The Chat Completions API is a simpler, faster option that doesn't lock you into OpenAI but doesn't support RAG or prompt management out of the box.
- Custom GPTs are easy to set up and publish, and support web browsing and image generation, but you have little control over how it works and only people with Chat GPT Plus subscriptions can use it.