LangChain Expression Language (LCEL) | Langchain Tutorial | Code

Dive into the world of LangChain Expression Language (LCEL) with our comprehensive tutorial! In this video, we explore the core features of LCEL, focusing on how LangChain elements implement the runnable interface for effective chaining and independent execution.

We demonstrate practical uses of the pipe operator for seamless operation chaining and illustrate the power of the invoke method in executing individual LangChain components. This video is perfect for developers and enthusiasts eager to enhance their skills in AI and language model integration. Join us for an insightful journey into LCEL and unlock new possibilities in text processing and AI!

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[mushinart]

First of all, thank you for the amazing way you explain stuff.... Its elegant...now i have only one question when we userd the retriever to assign it's value to the context variable, i assume the retriever will pass all of the documents in the rag list to the llm so that when it validates the question, it will use the whole rag documents that are all being passed as a context in the prompt. Am i right? ... Will it be a good idea if we created a chain to first take the question to query the rag and get just the needed context then pass it with the question again to form a human understandable answer from the llm ? ....im asking to see if im understanding it right or not .... Thanks man

[muhammedaslama]

AzureOpenAi chat model doesn't seem to support LCEL. Am I doing something wrong?

[Tushii]

Is there a way in which I could batch invoke a list of text files ?

I want to extract certain texts from each file using openai?
Or would I have to do it one by one and loop