OpenAI Assistants API: Walk-through and Coding a Research Assistant

I want to show you something exciting today — building OpenAI Assistant for academic research!

We can all foresee that Assistants will be deeply integrated into our personal and professional lives very soon. They will never sleep, eat, or take a break from helping you to progress in your life in myriad of ways.

This is really big news because researchers and practitioners have long dreamed of employing multiple agents for solving complex problems, and with the recent advancements in closed and open source LLMs, developers have already been trying to build custom experiences around LLMs. So what was the challenge?

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In practice, developing and serving custom LLMs require a tremendous amount of work around managing infrastructure, data, models, pipelines, prompts, context windows, application states, observability, embeddings, storage mechanisms, caching and augmented generation, you name it!

This means a lot of time stitching tech together just to make it work and very little time to solve customer problems.

Assistants API is designed to do this heavy-lifting for us by initially providing,

• Persistent threading for ongoing conversations
• Retrieval mechanisms for digging through data
• Code interpretation for those tricky programming…