Sample Notebook for DynamoDB Chat Message History (#5351)

# Sample Notebook for DynamoDB Chat Message History

@dev2049

Adding a sample notebook for the DynamoDB Chat Message History class.

<!-- For a quicker response, figure out the right person to tag with @

  @hwchase17 - project lead

  Tracing / Callbacks
  - @agola11

  Async
  - @agola11

  DataLoaders
  - @eyurtsev

  Models
  - @hwchase17
  - @agola11

  Agents / Tools / Toolkits
  - @vowelparrot

  VectorStores / Retrievers / Memory
  - @dev2049
        
 -->

docs/modules/memory/examples/dynamodb_chat_message_history.ipynb

@@ -0,0 +1,347 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "91c6a7ef",
+   "metadata": {},
+   "source": [
+    "# Dynamodb Chat Message History\n",
+    "\n",
+    "This notebook goes over how to use Dynamodb to store chat message history."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3f608be0",
+   "metadata": {},
+   "source": [
+    "First make sure you have correctly configured the [AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-configure.html). Then make sure you have installed boto3."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "030d784f",
+   "metadata": {},
+   "source": [
+    "Next, create the DynamoDB Table where we will be storing messages:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "93ce1811",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0\n"
+     ]
+    }
+   ],
+   "source": [
+    "import boto3\n",
+    "\n",
+    "# Get the service resource.\n",
+    "dynamodb = boto3.resource('dynamodb')\n",
+    "\n",
+    "# Create the DynamoDB table.\n",
+    "table = dynamodb.create_table(\n",
+    "    TableName='SessionTable',\n",
+    "    KeySchema=[\n",
+    "        {\n",
+    "            'AttributeName': 'SessionId',\n",
+    "            'KeyType': 'HASH'\n",
+    "        }\n",
+    "    ],\n",
+    "    AttributeDefinitions=[\n",
+    "        {\n",
+    "            'AttributeName': 'SessionId',\n",
+    "            'AttributeType': 'S'\n",
+    "        }\n",
+    "    ],\n",
+    "    BillingMode='PAY_PER_REQUEST',\n",
+    ")\n",
+    "\n",
+    "# Wait until the table exists.\n",
+    "table.meta.client.get_waiter('table_exists').wait(TableName='SessionTable')\n",
+    "\n",
+    "# Print out some data about the table.\n",
+    "print(table.item_count)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1a9b310b",
+   "metadata": {},
+   "source": [
+    "## DynamoDBChatMessageHistory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "d15e3302",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.memory.chat_message_histories import DynamoDBChatMessageHistory\n",
+    "\n",
+    "history = DynamoDBChatMessageHistory(table_name=\"SessionTable\", session_id=\"0\")\n",
+    "\n",
+    "history.add_user_message(\"hi!\")\n",
+    "\n",
+    "history.add_ai_message(\"whats up?\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "64fc465e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[HumanMessage(content='hi!', additional_kwargs={}, example=False),\n",
+       " AIMessage(content='whats up?', additional_kwargs={}, example=False)]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "history.messages"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3b33c988",
+   "metadata": {},
+   "source": [
+    "## Agent with DynamoDB Memory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f92d9499",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.agents import Tool\n",
+    "from langchain.memory import ConversationBufferMemory\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.agents import initialize_agent\n",
+    "from langchain.agents import AgentType\n",
+    "from langchain.utilities import PythonREPL\n",
+    "from getpass import getpass\n",
+    "\n",
+    "message_history = DynamoDBChatMessageHistory(table_name=\"SessionTable\", session_id=\"1\")\n",
+    "memory = ConversationBufferMemory(memory_key=\"chat_history\", chat_memory=message_history, return_messages=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "1167eeba",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "python_repl = PythonREPL()\n",
+    "\n",
+    "# You can create the tool to pass to an agent\n",
+    "tools = [Tool(\n",
+    "    name=\"python_repl\",\n",
+    "    description=\"A Python shell. Use this to execute python commands. Input should be a valid python command. If you want to see the output of a value, you should print it out with `print(...)`.\",\n",
+    "    func=python_repl.run\n",
+    ")]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "fce085c5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "llm=ChatOpenAI(temperature=0)\n",
+    "agent_chain = initialize_agent(tools, llm, agent=AgentType.CHAT_CONVERSATIONAL_REACT_DESCRIPTION, verbose=True, memory=memory)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "952a3103",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "\n",
+      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
+      "\u001b[32;1m\u001b[1;3m{\n",
+      "    \"action\": \"Final Answer\",\n",
+      "    \"action_input\": \"Hello! How can I assist you today?\"\n",
+      "}\u001b[0m\n",
+      "\n",
+      "\u001b[1m> Finished chain.\u001b[0m\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "'Hello! How can I assist you today?'"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "agent_chain.run(input=\"Hello!\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "54c4aaf4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "\n",
+      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
+      "\u001b[32;1m\u001b[1;3m{\n",
+      "    \"action\": \"python_repl\",\n",
+      "    \"action_input\": \"import requests\\nfrom bs4 import BeautifulSoup\\n\\nurl = 'https://en.wikipedia.org/wiki/Twitter'\\nresponse = requests.get(url)\\nsoup = BeautifulSoup(response.content, 'html.parser')\\nowner = soup.find('th', text='Owner').find_next_sibling('td').text.strip()\\nprint(owner)\"\n",
+      "}\u001b[0m\n",
+      "Observation: \u001b[36;1m\u001b[1;3mX Corp. (2023–present)Twitter, Inc. (2006–2023)\n",
+      "\u001b[0m\n",
+      "Thought:\u001b[32;1m\u001b[1;3m{\n",
+      "    \"action\": \"Final Answer\",\n",
+      "    \"action_input\": \"X Corp. (2023–present)Twitter, Inc. (2006–2023)\"\n",
+      "}\u001b[0m\n",
+      "\n",
+      "\u001b[1m> Finished chain.\u001b[0m\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "'X Corp. (2023–present)Twitter, Inc. (2006–2023)'"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "agent_chain.run(input=\"Who owns Twitter?\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "f9013118",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "\n",
+      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
+      "\u001b[32;1m\u001b[1;3m{\n",
+      "    \"action\": \"Final Answer\",\n",
+      "    \"action_input\": \"Hello Bob! How can I assist you today?\"\n",
+      "}\u001b[0m\n",
+      "\n",
+      "\u001b[1m> Finished chain.\u001b[0m\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "'Hello Bob! How can I assist you today?'"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "agent_chain.run(input=\"My name is Bob.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "405e5315",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "\n",
+      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
+      "\u001b[32;1m\u001b[1;3m{\n",
+      "    \"action\": \"Final Answer\",\n",
+      "    \"action_input\": \"Your name is Bob.\"\n",
+      "}\u001b[0m\n",
+      "\n",
+      "\u001b[1m> Finished chain.\u001b[0m\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "'Your name is Bob.'"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "agent_chain.run(input=\"Who am I?\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}