Spring AI - Bring your own data by Stuffing the Prompt

In this tutorial we will take a look at a technique known as stuffing the prompt. This will allow us to add some context to our prompts when sending a request to the LLM. In this example we use Open AI's GPT-4 Model but this technique will work with all of the supported LLMs.
🔗Resources & Links mentioned in this video:
Spring AI Introduction: • Spring AI Introduction...
GitHub Repository: github.com/danvega/spring-int...
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[@jodye6279]

As a junior developer your explanations are sooooo good! Thanks again for the awesome content

[@hfk0123]

Dan! You're the man! These Spring AI OpenAI videos have been tremendously helpful in building out my own Spring Boot chatbot that uses the OpenAI Assistants API to get real-time data with an external function call. A video dealing with using Assistants to trigger external API calls would be great!

[@sohamsarkar174]

Thank you dan for back to back video

[@LordLamers]

Thanks. And the next video extend this example and use a vector "database".

[@DanVega]

Those are my next 2 videos 🤩

[@satyaprakashnayak1363]

Hi Dan, this is a nicely explained video on AI using Spring. Trust me no one really talks about it. However, I have just one concern, as far as I know these "context" value has restricted token length. Because of that we need to learn RAG architecture. In short resolving problem with this approach is not feasible in real world.

[@tomaszw6449]

👍👍👍