Hey there, Eden here and I hope you enjoyed the project so far.
And in this video we want to be adding end to end self rack and self rack is derived from the self rack
paper and is basically meaning that we are going to reflect on the answer that the model generated.
So we are going to take the generation and we're going to compare it with the documents, and we're
going to see whether the model hallucinated or not.
So we need to check whether the answer is actually grounded in the documents.
Now, if it's grounded, then that's cool.
And we're ready to the second step.
And the second step is to reflect on the answer.
However, now we want to reflect whether the answer answers the question that the user originally asked.
And if the answer is yes for that, then this means we can return the answer to the user, and if the
answer does not answer the question, then this probably means that we need to make a web search, because
we're not going to find any additional information in the vector store.
And if we hallucinated the answer so it's not grounded in the documents, then we want to regenerate
it again and to ground in the documents.
The answer.
So that's what we're going to do in this video.
We're going to implement it end to end.
We're going to write the chains.
We're going to write the tests.
We're going to add the nodes.
And we're going to add, of course, all of those conditional branches and see you in the code.