​
Setup

  • Before using the AWS Bedrock LLM, make sure you have the appropriate model access from Bedrock Console.
  • You will also need to authenticate the boto3 client by using a method in the AWS documentation
  • You will have to export AWS_REGION, AWS_ACCESS_KEY, and AWS_SECRET_ACCESS_KEY to set environment variables.

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Usage

import os
from mem0 import Memory

os.environ["OPENAI_API_KEY"] = "your-api-key" # used for embedding model
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"})

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Config

All available parameters for the aws_bedrock config are present in Master List of All Params in Config.

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