Human-in-loop implementations are becoming critical as situations arise where evaluations and corrections are necessary based on the response generated. These act as breakpoints in the graph where it pauses waits for the input and continues based on the input.
View my previous posts for more context! An introduction to langchain
Github link: https://github.com/sushmasush/langGraph/blob/main/humanInLoopLangGraphSummarizer.ipynb
Table of Contents
Use case: Get the summary of the paper along with the top 5 web results (if the user needs them)
View my notebook that contains details of each step
Conclusion
Using the human-in-loop method one can create breakpoints at certain points in the flow, edit the contents, verify the responses, or provide feedback about the quality of answers. This can be enhanced as per the requirements.
🗝My portfolio: https://wp.me/PccXal-wv
🤝 Connect for a 1:1 https://lnkd.in/g6FDTxcM
References
https://langchain-ai.github.io/langgraph/concepts/human_in_the_loop
