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https://github.com/hwchase17/langchain
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langchain[patch]: deprecate AnalyzeDocumentChain (#23769)
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@ -640,7 +640,7 @@
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"metadata": {},
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"source": [
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"## Splitting and summarizing in a single chain\n",
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"For convenience, we can wrap both the text splitting of our long document and summarizing in a single `AnalyzeDocumentsChain`."
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"For convenience, we can wrap both the text splitting of our long document and summarizing in a single [chain](/docs/how_to/sequence):"
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]
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},
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{
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@ -650,12 +650,11 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.chains import AnalyzeDocumentChain\n",
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"def split_text(text: str):\n",
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" return text_splitter.create_documents([text])\n",
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"\n",
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"summarize_document_chain = AnalyzeDocumentChain(\n",
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" combine_docs_chain=chain, text_splitter=text_splitter\n",
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")\n",
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"summarize_document_chain.invoke(docs[0].page_content)"
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"\n",
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"summarize_document_chain = split_text | chain"
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]
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},
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{
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@ -3,6 +3,7 @@
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from abc import ABC, abstractmethod
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from typing import Any, Dict, List, Optional, Tuple, Type
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from langchain_core._api import deprecated
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from langchain_core.callbacks import (
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AsyncCallbackManagerForChainRun,
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CallbackManagerForChainRun,
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@ -157,12 +158,70 @@ class BaseCombineDocumentsChain(Chain, ABC):
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return extra_return_dict
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@deprecated(
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since="0.2.7",
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alternative=(
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"example in API reference with more detail: "
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"https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.AnalyzeDocumentChain.html" # noqa: E501
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),
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removal="1.0",
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)
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class AnalyzeDocumentChain(Chain):
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"""Chain that splits documents, then analyzes it in pieces.
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This chain is parameterized by a TextSplitter and a CombineDocumentsChain.
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This chain takes a single document as input, and then splits it up into chunks
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and then passes those chucks to the CombineDocumentsChain.
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This class is deprecated. See below for alternative implementations which
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supports async and streaming modes of operation.
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If the underlying combine documents chain takes one ``input_documents`` argument
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(e.g., chains generated by ``load_summarize_chain``):
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.. code-block:: python
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split_text = lambda x: text_splitter.create_documents([x])
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summarize_document_chain = split_text | chain
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If the underlying chain takes additional arguments (e.g., ``load_qa_chain``, which
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takes an additional ``question`` argument), we can use the following:
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.. code-block:: python
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from operator import itemgetter
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from langchain_core.runnables import RunnableLambda, RunnableParallel
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split_text = RunnableLambda(
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lambda x: text_splitter.create_documents([x])
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)
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summarize_document_chain = RunnableParallel(
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question=itemgetter("question"),
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input_documents=itemgetter("input_document") | split_text,
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) | chain.pick("output_text")
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To additionally return the input parameters, as ``AnalyzeDocumentChain`` does,
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we can wrap this construction with ``RunnablePassthrough``:
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.. code-block:: python
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from operator import itemgetter
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from langchain_core.runnables import (
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RunnableLambda,
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RunnableParallel,
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RunnablePassthrough,
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)
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split_text = RunnableLambda(
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lambda x: text_splitter.create_documents([x])
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)
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summarize_document_chain = RunnablePassthrough.assign(
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output_text=RunnableParallel(
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question=itemgetter("question"),
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input_documents=itemgetter("input_document") | split_text,
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) | chain.pick("output_text")
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)
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"""
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input_key: str = "input_document" #: :meta private:
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