Add AWS Bedrock support (#1482)

docs/llms.mdx

@@ -10,6 +10,7 @@ Mem0 includes built-in support for various popular large language models. Memory
   <Card title="OpenAI" href="#openai"></Card>
   <Card title="Groq" href="#groq"></Card>
   <Card title="Together" href="#together"></Card>
+  <Card title="AWS Bedrock" href="#aws_bedrock"></Card>
 </CardGroup>
 
 ## OpenAI
@@ -92,3 +93,33 @@ config = {
 m = Memory.from_config(config)
 m.add("Likes to play cricket on weekends", user_id="alice", metadata={"category": "hobbies"})
 ```
+
+## AWS Bedrock
+
+### Setup
+- Before using the AWS Bedrock LLM, make sure you have the appropriate model access from [Bedrock Console](https://us-east-1.console.aws.amazon.com/bedrock/home?region=us-east-1#/modelaccess).
+- You will also need to authenticate the `boto3` client by using a method in the [AWS documentation](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html#configuring-credentials)
+- You will have to export `AWS_REGION`, `AWS_ACCESS_KEY`, and `AWS_SECRET_ACCESS_KEY` to set environment variables.
+
+```python
+import os
+from mem0 import Memory
+
+os.environ['AWS_REGION'] = 'us-east-1'
+os.environ["AWS_ACCESS_KEY"] = "xx"
+os.environ["AWS_SECRET_ACCESS_KEY"] = "xx"
+
+config = {
+    "llm": {
+        "provider": "aws_bedrock",
+        "config": {
+            "model": "arn:aws:bedrock:us-east-1:123456789012:model/your-model-name",
+            "temperature": 0.2,
+            "max_tokens": 1500,
+        }
+    }
+}
+
+m = Memory.from_config(config)
+m.add("Likes to play cricket on weekends", user_id="alice", metadata={"category": "hobbies"})
+```