map_reduce

Combine documents by recursively reducing them.

This involves

• combine_documents_chain
• collapse_documents_chain

combine_documents_chain is ALWAYS provided. This is final chain that is called.

We pass all previous results to this chain, and the output of this chain is returned as a final result.

collapse_documents_chain is used if the documents passed in are too many to all be passed to combine_documents_chain in one go. In this case, collapse_documents_chain is called recursively on as big of groups of documents as are allowed.

Chain to run queries against LLMs.

This class is deprecated. See below for an example implementation using LangChain runnables:

from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import PromptTemplate
from langchain_openai import OpenAI

prompt_template = "Tell me a {adjective} joke"
prompt = PromptTemplate(input_variables=["adjective"], template=prompt_template)
model = OpenAI()
chain = prompt | model | StrOutputParser()

chain.invoke("your adjective here")

Combining documents by mapping a chain over them, then combining results.

We first call llm_chain on each document individually, passing in the page_content and any other kwargs. This is the map step.

We then process the results of that map step in a reduce step. This should likely be a ReduceDocumentsChain.