Harrison/summary memory history (#4649)

Co-authored-by: engkheng <60956360+outday29@users.noreply.github.com>

docs/modules/memory/types/summary.ipynb

@@ -18,7 +18,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.memory import ConversationSummaryMemory\n",
+    "from langchain.memory import ConversationSummaryMemory, ChatMessageHistory\n",
     "from langchain.llms import OpenAI"
    ]
   },
@@ -125,6 +125,59 @@
     "memory.predict_new_summary(messages, previous_summary)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "fa3ad83f",
+   "metadata": {},
+   "source": [
+    "## Initializing with messages\n",
+    "\n",
+    "If you have messages outside this class, you can easily initialize the class with ChatMessageHistory. During loading, a summary will be calculated."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "80fd072b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "history = ChatMessageHistory()\n",
+    "history.add_user_message(\"hi\")\n",
+    "history.add_ai_message(\"hi there!\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "ee9c74ad",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "memory = ConversationSummaryMemory.from_messages(llm=OpenAI(temperature=0), chat_memory=history, return_messages=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "0ce6924d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\\nThe human greets the AI, to which the AI responds with a friendly greeting.'"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "memory.buffer"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "4fad9448",

langchain/memory/summary.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from typing import Any, Dict, List, Type
 
 from pydantic import BaseModel, root_validator
@@ -8,6 +10,7 @@ from langchain.memory.chat_memory import BaseChatMemory
 from langchain.memory.prompt import SUMMARY_PROMPT
 from langchain.prompts.base import BasePromptTemplate
 from langchain.schema import (
+    BaseChatMessageHistory,
     BaseMessage,
     SystemMessage,
     get_buffer_string,
@@ -40,6 +43,22 @@ class ConversationSummaryMemory(BaseChatMemory, SummarizerMixin):
     buffer: str = ""
     memory_key: str = "history"  #: :meta private:
 
+    @classmethod
+    def from_messages(
+        cls,
+        llm: BaseLanguageModel,
+        chat_memory: BaseChatMessageHistory,
+        *,
+        summarize_step: int = 2,
+        **kwargs: Any,
+    ) -> ConversationSummaryMemory:
+        obj = cls(llm=llm, chat_memory=chat_memory, **kwargs)
+        for i in range(0, len(obj.chat_memory.messages), summarize_step):
+            obj.buffer = obj.predict_new_summary(
+                obj.chat_memory.messages[i : i + summarize_step], obj.buffer
+            )
+        return obj
+
     @property
     def memory_variables(self) -> List[str]:
         """Will always return list of memory variables.