AWS DynamoDB
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.
Setupβ
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
Itβs also helpful (but not needed) to set up LangSmith for best-in-class observability
# os.environ["LANGCHAIN_TRACING_V2"] = "true"
# os.environ["LANGCHAIN_API_KEY"] = getpass.getpass()
from langchain_community.chat_message_histories import (
DynamoDBChatMessageHistory,
)
API Reference:
Create Tableβ
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
DynamoDBChatMessageHistoryβ
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?')]
DynamoDBChatMessageHistory with Custom Endpoint URLβ
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",
)
DynamoDBChatMessageHistory With Composite Keysβ
The default key for DynamoDBChatMessageHistory is
{"SessionId": self.session_id}
, but you can modify this to match your
table design.
Primary Key Nameβ
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}
Composite Keysβ
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!')]
Chainingβ
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?')