Awesome presentation. Clear, well-structured, and easy-to-follow. Love the term "Dynamic QA System" rather than bucketing all internal knowledge query use-cases into RAG. Adding agents at different locations of a vanilla RAG workflow seems to be a powerful system architecture for solving a large set of QA use cases. Lots of food for thought!
good presentation, my issue is using langchain/llama in production, they just add another unnecessary and buggy layer, maybe things will change moving forward, also adding layers of agents can ramp up costs quite significantly, which is where need for good open source llms comes in.
Awesome presentation. Clear, well-structured, and easy-to-follow. Love the term "Dynamic QA System" rather than bucketing all internal knowledge query use-cases into RAG. Adding agents at different locations of a vanilla RAG workflow seems to be a powerful system architecture for solving a large set of QA use cases. Lots of food for thought!
The best presentation about simple for loop.
good presentation, my issue is using langchain/llama in production, they just add another unnecessary and buggy layer, maybe things will change moving forward, also adding layers of agents can ramp up costs quite significantly, which is where need for good open source llms comes in.
Nice presentation. Just didn’t see enough from llama index… but very well spoken and interesting.
15:39 what is ReAct’s performance like when it loops many times? I assume it can be costly and slow if it loops 10+ times.
It is but the output is much more clarified that what you would have in one loop