docs/tutorials/extraction/

[giscus[bot]]

docs/tutorials/extraction/

This guide assumes familiarity with the following concepts:

https://python.langchain.com/docs/tutorials/extraction/

[sanjeed5]

This was helpful! Good tutorial!

[OkYongChoi]

Gracias! Super useful!!

[dawngo]

This tutorial is very, very good！

[hakim89]

Any chance this tutorial can be ran using Ollama running mistal locally?
if I do

from langchain_ollama import OllamaLLM
llm = OllamaLLM(model="mistral")
structured_llm = llm.with_structured_output(schema=Person)

I get an error: NotImplementedError

appreciate any advice.

[efriis]

Hey there! You'll have to use ChatOllama instead of OllamaLLM to use structured output

[lcombita09]

how does one can combine this with a retriever, to perform data extraction for large documents? It is possible to pass to the retriever also the schema in order to extract the relevant documents?

[efriis]

Not sure exactly what you mean so making some assumptions, but it sounds like you want to do some kind of map-reduce on the retrieved documents, where you're determining if each document is relevant using an llm. would recommend using langgraph map reduce branches for this if that's the case! https://langchain-ai.github.io/langgraph/how-tos/map-reduce/

[lcombita09]

hey! thanks for the response. What I mean, is that here on the examples the extraction is done from a text, but what if I want to do it on a 100 pages pdf, there must be a way to pass to the llm just the relevant chunks to extract the information needed, that is what I meant