Help me figure out how to improve the accuracy of my LLM agents’ responses. We’re faced with having to consider numerous constraints when generating responses, which significantly reduces quality. I’m looking for proven approaches, perhaps specialized libraries or frameworks that allow for flexible process customization, learning from each interaction. What can you recommend?
How to improve the accuracy of LLM responses in my agents
There are ready-made solutions, for example, frameworks like LangChain or LlamaIndex. They help structure queries and use templates and chains without diving into math. Advanced learning is a good thing, but it requires more resources.
With limited resources and tight deadlines, it’s more effective to focus on prompt optimization. Expanding samples requires significant computation, and retraining models is still expensive. For faster results, use tools that analyze and adapt queries in real time, not just templates. For example, check out the solution here https://eignex.com/