langchain/docs/extras/expression_language/cookbook/memory.ipynb

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   "cell_type": "markdown",
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   "source": [
    "# Adding memory\n",
    "\n",
    "This shows how to add memory to an arbitrary chain. Right now, you can use the memory classes but need to hook it up manually"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7998efd8",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.chat_models import ChatOpenAI\n",
    "from langchain.memory import ConversationBufferMemory\n",
    "from langchain.schema.runnable import RunnableMap\n",
    "from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
    "\n",
    "model = ChatOpenAI()\n",
    "prompt = ChatPromptTemplate.from_messages([\n",
    "    (\"system\", \"You are a helpful chatbot\"),\n",
    "    MessagesPlaceholder(variable_name=\"history\"),\n",
    "    (\"human\", \"{input}\")\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fa0087f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "memory = ConversationBufferMemory(return_messages=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "06b531ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'history': []}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "memory.load_memory_variables({})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d9437af6",
   "metadata": {},
   "outputs": [],
   "source": [
    "chain = RunnableMap({\n",
    "    \"input\": lambda x: x[\"input\"],\n",
    "    \"memory\": memory.load_memory_variables\n",
    "}) | {\n",
    "    \"input\": lambda x: x[\"input\"],\n",
    "    \"history\": lambda x: x[\"memory\"][\"history\"]\n",
    "} | prompt | model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bed1e260",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AIMessage(content='Hello Bob! How can I assist you today?', additional_kwargs={}, example=False)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inputs = {\"input\": \"hi im bob\"}\n",
    "response = chain.invoke(inputs)\n",
    "response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "890475b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "memory.save_context(inputs, {\"output\": response.content})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e8fcb77f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'history': [HumanMessage(content='hi im bob', additional_kwargs={}, example=False),\n",
       "  AIMessage(content='Hello Bob! How can I assist you today?', additional_kwargs={}, example=False)]}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "memory.load_memory_variables({})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d837d5c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AIMessage(content='Your name is Bob.', additional_kwargs={}, example=False)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inputs = {\"input\": \"whats my name\"}\n",
    "response = chain.invoke(inputs)\n",
    "response"
   ]
  }
 ],
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