Building a Summarization System with LangChain and GPT-3 - Part 2

In this video, you will learn how to use the LangChain Summarization Checker to help reduce hallucination in the summarized output. This is a useful technique for improving your understanding of how prompting LLMs is so important.

My Links:

Github:

#LangChain #BuildingAppswithLLMs

[venkatesanr]

Thanks for your videos/inputs & precious inputs for my queries....

[faisalsultan]

Thanks, really informative video! You mentioned combining with a knowledge graph, would love to see how you do this 🙂

[MadsVoigtHingelberg]

Thank you for a very informative video.
You use articles. How would you approach a minutes of meetin summary, where participants may have discussion. The assumption is that the individual participants are not separated by name.

[mayanklohani]

How does it verify the facts?
from google or the text itself?

[mkim]

How to summarize a long document?. I got an error "This model's maximum context length is 4097 tokens, however you requested 11958 tokens (11702 in your prompt; 256 for the completion). Please reduce your prompt; or completion length"

[venkatesanr]

How to do semantic search over text inside images ( text extracted easyocr)/any blip2 or clip. Can you give inputs on multimodal hybrid