Amazon AWS DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability.
This notebook goes over how to use DynamoDB to store chat message history with DynamoDBChatMessageHistory class.

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Setup

First make sure you have correctly configured the AWS CLI. Then make sure you have installed the langchain-community package, so we need to install that. We also need to install the boto3 package. 
pip install -U langchain-community boto3
It’s also helpful (but not needed) to set up LangSmith for best-in-class observability 
# os.environ["LANGSMITH_TRACING"] = "true"
# os.environ["LANGSMITH_API_KEY"] = getpass.getpass()

from langchain_community.chat_message_histories import (
    DynamoDBChatMessageHistory,
)

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Create Table

Now, create the DynamoDB Table where we will be storing messages: 
import boto3

# Get the service resource.
dynamodb = boto3.resource("dynamodb")

# Create the DynamoDB table.
table = dynamodb.create_table(
    TableName="SessionTable",
    KeySchema=[{"AttributeName": "SessionId", "KeyType": "HASH"}],
    AttributeDefinitions=[{"AttributeName": "SessionId", "AttributeType": "S"}],
    BillingMode="PAY_PER_REQUEST",
)

# Wait until the table exists.
table.meta.client.get_waiter("table_exists").wait(TableName="SessionTable")

# Print out some data about the table.
print(table.item_count)

0

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DynamoDBChatMessageHistory

history = DynamoDBChatMessageHistory(table_name="SessionTable", session_id="0")

history.add_user_message("hi!")

history.add_ai_message("whats up?")

history.messages

[HumanMessage(content='hi!'), AIMessage(content='whats up?')]

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DynamoDBChatMessageHistory with Custom Endpoint URL

Sometimes it is useful to specify the URL to the AWS endpoint to connect to. For instance, when you are running locally against Localstack. For those cases you can specify the URL via the endpoint_url parameter in the constructor. 
history = DynamoDBChatMessageHistory(
    table_name="SessionTable",
    session_id="0",
    endpoint_url="http://localhost.localstack.cloud:4566",
)

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DynamoDBChatMessageHistory With Composite Keys

The default key for DynamoDBChatMessageHistory is {"SessionId": self.session_id}, but you can modify this to match your table design.

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Primary Key Name

You may modify the primary key by passing in a primary_key_name value in the constructor, resulting in the following: {self.primary_key_name: self.session_id}

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Composite Keys

When using an existing DynamoDB table, you may need to modify the key structure from the default of to something including a Sort Key. To do this you may use the key parameter. Passing a value for key will override the primary_key parameter, and the resulting key structure will be the passed value. 
composite_table = dynamodb.create_table(
    TableName="CompositeTable",
    KeySchema=[
        {"AttributeName": "PK", "KeyType": "HASH"},
        {"AttributeName": "SK", "KeyType": "RANGE"},
    ],
    AttributeDefinitions=[
        {"AttributeName": "PK", "AttributeType": "S"},
        {"AttributeName": "SK", "AttributeType": "S"},
    ],
    BillingMode="PAY_PER_REQUEST",
)

# Wait until the table exists.
composite_table.meta.client.get_waiter("table_exists").wait(TableName="CompositeTable")

# Print out some data about the table.
print(composite_table.item_count)

0

my_key = {
    "PK": "session_id::0",
    "SK": "langchain_history",
}

composite_key_history = DynamoDBChatMessageHistory(
    table_name="CompositeTable",
    session_id="0",
    endpoint_url="http://localhost.localstack.cloud:4566",
    key=my_key,
)

composite_key_history.add_user_message("hello, composite dynamodb table!")

composite_key_history.messages

[HumanMessage(content='hello, composite dynamodb table!')]

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Chaining

We can easily combine this message history class with LCEL Runnables To do this we will want to use OpenAI, so we need to install that 
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain_core.runnables.history import RunnableWithMessageHistory
from langchain_openai import ChatOpenAI

prompt = ChatPromptTemplate.from_messages(
    [
        ("system", "You are a helpful assistant."),
        MessagesPlaceholder(variable_name="history"),
        ("human", "{question}"),
    ]
)

chain = prompt | ChatOpenAI()

chain_with_history = RunnableWithMessageHistory(
    chain,
    lambda session_id: DynamoDBChatMessageHistory(
        table_name="SessionTable", session_id=session_id
    ),
    input_messages_key="question",
    history_messages_key="history",
)

# This is where we configure the session id
config = {"configurable": {"session_id": "<SESSION_ID>"}}

chain_with_history.invoke({"question": "Hi! I'm bob"}, config=config)

AIMessage(content='Hello Bob! How can I assist you today?')

chain_with_history.invoke({"question": "Whats my name"}, config=config)

AIMessage(content='Your name is Bob! Is there anything specific you would like assistance with, Bob?')