From 25de47878bd48606a755a98b22caad3d34cfc2eb Mon Sep 17 00:00:00 2001
From: ccurme <chester.curme@gmail.com>
Date: Fri, 5 Jul 2024 14:00:23 -0400
Subject: [PATCH] langchain[patch]: deprecate AnalyzeDocumentChain (#23769)

---
 docs/docs/tutorials/summarization.ipynb       | 11 ++--
 .../chains/combine_documents/base.py          | 59 +++++++++++++++++++
 2 files changed, 64 insertions(+), 6 deletions(-)

diff --git a/docs/docs/tutorials/summarization.ipynb b/docs/docs/tutorials/summarization.ipynb
index 20f4087ddb..410bd17f5a 100644
--- a/docs/docs/tutorials/summarization.ipynb
+++ b/docs/docs/tutorials/summarization.ipynb
@@ -640,7 +640,7 @@
    "metadata": {},
    "source": [
     "## Splitting and summarizing in a single chain\n",
-    "For convenience, we can wrap both the text splitting of our long document and summarizing in a single `AnalyzeDocumentsChain`."
+    "For convenience, we can wrap both the text splitting of our long document and summarizing in a single [chain](/docs/how_to/sequence):"
    ]
   },
   {
@@ -650,12 +650,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.chains import AnalyzeDocumentChain\n",
+    "def split_text(text: str):\n",
+    "    return text_splitter.create_documents([text])\n",
     "\n",
-    "summarize_document_chain = AnalyzeDocumentChain(\n",
-    "    combine_docs_chain=chain, text_splitter=text_splitter\n",
-    ")\n",
-    "summarize_document_chain.invoke(docs[0].page_content)"
+    "\n",
+    "summarize_document_chain = split_text | chain"
    ]
   },
   {
diff --git a/libs/langchain/langchain/chains/combine_documents/base.py b/libs/langchain/langchain/chains/combine_documents/base.py
index 6746c9df8f..90e965996d 100644
--- a/libs/langchain/langchain/chains/combine_documents/base.py
+++ b/libs/langchain/langchain/chains/combine_documents/base.py
@@ -3,6 +3,7 @@
 from abc import ABC, abstractmethod
 from typing import Any, Dict, List, Optional, Tuple, Type
 
+from langchain_core._api import deprecated
 from langchain_core.callbacks import (
     AsyncCallbackManagerForChainRun,
     CallbackManagerForChainRun,
@@ -157,12 +158,70 @@ class BaseCombineDocumentsChain(Chain, ABC):
         return extra_return_dict
 
 
+@deprecated(
+    since="0.2.7",
+    alternative=(
+        "example in API reference with more detail: "
+        "https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.AnalyzeDocumentChain.html"  # noqa: E501
+    ),
+    removal="1.0",
+)
 class AnalyzeDocumentChain(Chain):
     """Chain that splits documents, then analyzes it in pieces.
 
     This chain is parameterized by a TextSplitter and a CombineDocumentsChain.
     This chain takes a single document as input, and then splits it up into chunks
     and then passes those chucks to the CombineDocumentsChain.
+
+    This class is deprecated. See below for alternative implementations which
+    supports async and streaming modes of operation.
+
+    If the underlying combine documents chain takes one ``input_documents`` argument
+    (e.g., chains generated by ``load_summarize_chain``):
+
+        .. code-block:: python
+
+            split_text = lambda x: text_splitter.create_documents([x])
+
+            summarize_document_chain = split_text | chain
+
+    If the underlying chain takes additional arguments (e.g., ``load_qa_chain``, which
+    takes an additional ``question`` argument), we can use the following:
+
+        .. code-block:: python
+
+            from operator import itemgetter
+            from langchain_core.runnables import RunnableLambda, RunnableParallel
+
+            split_text = RunnableLambda(
+                lambda x: text_splitter.create_documents([x])
+            )
+            summarize_document_chain = RunnableParallel(
+                question=itemgetter("question"),
+                input_documents=itemgetter("input_document") | split_text,
+            ) | chain.pick("output_text")
+
+    To additionally return the input parameters, as ``AnalyzeDocumentChain`` does,
+    we can wrap this construction with ``RunnablePassthrough``:
+
+        .. code-block:: python
+
+            from operator import itemgetter
+            from langchain_core.runnables import (
+                RunnableLambda,
+                RunnableParallel,
+                RunnablePassthrough,
+            )
+
+            split_text = RunnableLambda(
+                lambda x: text_splitter.create_documents([x])
+            )
+            summarize_document_chain = RunnablePassthrough.assign(
+                output_text=RunnableParallel(
+                    question=itemgetter("question"),
+                    input_documents=itemgetter("input_document") | split_text,
+                ) | chain.pick("output_text")
+            )
     """
 
     input_key: str = "input_document"  #: :meta private: