Initial commit

.gitignore

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+**/build
+**/.venv
+**/dist
+**/langgraph_checkpoint_dynamodb.egg-info
+**/.idea

LICENSE

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+MIT License
+
+Copyright (c) 2024 researchwiseai
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+# langgraph-checkpoint-dynamodb
+
+Implementation of a LangGraph CheckpointSaver that uses a AWS's DynamoDB
+
+## Inspiration
+
+Based on: https://github.com/researchwiseai/langgraphjs-checkpoint-dynamodb
+
+## Required DynamoDB Tables
+
+To be able to use this checkpointer, two DynamoDB table's are needed, one to store
+checkpoints and the other to store writes. Below are some examples of how you
+can create the required tables.
+
+### Terraform
+
+```hcl
+# Variables for table names
+variable "checkpoints_table_name" {
+  type = string
+}
+
+variable "writes_table_name" {
+  type = string
+}
+
+# Checkpoints Table
+resource "aws_dynamodb_table" "checkpoints_table" {
+  name         = var.checkpoints_table_name
+  billing_mode = "PAY_PER_REQUEST"
+
+  hash_key  = "thread_id"
+  range_key = "checkpoint_id"
+
+  attribute {
+    name = "thread_id"
+    type = "S"
+  }
+
+  attribute {
+    name = "checkpoint_id"
+    type = "S"
+  }
+}
+
+# Writes Table
+resource "aws_dynamodb_table" "writes_table" {
+  name         = var.writes_table_name
+  billing_mode = "PAY_PER_REQUEST"
+
+  hash_key  = "thread_id_checkpoint_id_checkpoint_ns"
+  range_key = "task_id_idx"
+
+  attribute {
+    name = "thread_id_checkpoint_id_checkpoint_ns"
+    type = "S"
+  }
+
+  attribute {
+    name = "task_id_idx"
+    type = "S"
+  }
+}
+```
+
+### AWS CDK
+
+```python
+from aws_cdk import (
+    Stack,
+    aws_dynamodb as dynamodb,
+)
+from constructs import Construct
+
+class DynamoDbStack(Stack):
+    def __init__(self, scope: Construct, id: str, **kwargs):
+        super().__init__(scope, id, **kwargs)
+
+        checkpoints_table_name = 'YourCheckpointsTableName'
+        writes_table_name = 'YourWritesTableName'
+
+        # Checkpoints Table
+        dynamodb.Table(
+            self,
+            'CheckpointsTable',
+            table_name=checkpoints_table_name,
+            billing_mode=dynamodb.BillingMode.PAY_PER_REQUEST,
+            partition_key=dynamodb.Attribute(
+                name='thread_id',
+                type=dynamodb.AttributeType.STRING,
+            ),
+            sort_key=dynamodb.Attribute(
+                name='checkpoint_id',
+                type=dynamodb.AttributeType.STRING,
+            ),
+        )
+
+        # Writes Table
+        dynamodb.Table(
+            self,
+            'WritesTable',
+            table_name=writes_table_name,
+            billing_mode=dynamodb.BillingMode.PAY_PER_REQUEST,
+            partition_key=dynamodb.Attribute(
+                name='thread_id_checkpoint_id_checkpoint_ns',
+                type=dynamodb.AttributeType.STRING,
+            ),
+            sort_key=dynamodb.Attribute(
+                name='task_id_idx',
+                type=dynamodb.AttributeType.STRING,
+            ),
+        )
+```
+
+## Using the Checkpoint Saver
+
+### Default
+
+To use the DynamoDB checkpoint saver, you only need to specify the names of
+the checkpoints and writes tables. In this scenario the DynamoDB client will
+be instantiated with the default configuration, great for running on AWS Lambda.
+
+```python
+from langgraph_checkpoint_dynamodb import DynamoDBSaver
+...
+checkpoints_table_name = 'YourCheckpointsTableName'
+writes_table_name = 'YourWritesTableName'
+
+memory = DynamoDBSaver(
+    checkpoints_table_name=checkpoints_table_name,
+    writes_table_name=writes_table_name,
+)
+
+graph = workflow.compile(checkpointer=memory)
+```
+
+### Providing Client Configuration
+
+If you need to provide custom configuration to the DynamoDB client, you can
+pass in an object with the configuration options. Below is an example of how
+you can provide custom configuration.
+
+```python
+memory = DynamoDBSaver(
+    checkpoints_table_name=checkpoints_table_name,
+    writes_table_name=writes_table_name,
+    client_config={
+        'region': 'us-west-2',
+        'accessKeyId': 'your-access-key-id',
+        'secretAccessKey': 'your-secret-access-key',
+    }
+)
+```