[AI Mem0] Large Language Models: One-stop Integration of Multiple Top AI Models to Boost Efficiency

Overview

Mem0 comes with built-in support for various popular large language models. It can leverage the large language models provided by the user, ensuring efficient use for specific needs.

OpenAI
Groq
Together
AWS Bedrock
Litellm
Google AI
Anthropic
Mistral AI
OpenAI Azure

OpenAI

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import os
from mem0 import Memory

os.environ["OPENAI_API_KEY"] = "your-api-key"

config = {
    "llm": {
        "provider": "openai",
        "config": {
            "model": "gpt-4o",
            "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"})

Groq

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import os
from mem0 import Memory

os.environ["GROQ_API_KEY"] = "your-api-key"

config = {
    "llm": {
        "provider": "groq",
        "config": {
            "model": "mixtral-8x7b-32768",
            "temperature": 0.1,
            "max_tokens": 1000,
        }
    }
}

m = Memory.from_config(config)
m.add("Likes to play cricket on weekends", user_id="alice", metadata={"category": "hobbies"})

Together

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import os
from mem0 import Memory

os.environ["TOGETHER_API_KEY"] = "your-api-key"

config = {
    "llm": {
        "provider": "togetherai",
        "config": {
            "model": "mistralai/Mixtral-8x7B-Instruct-v0.1",
            "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"})

AWS Bedrock

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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"})

Litellm

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import os
from mem0 import Memory

os.environ["OPENAI_API_KEY"] = "your-api-key"

config = {
    "llm": {
        "provider": "litellm",
        "config": {
            "model": "gpt-3.5-turbo",
            "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"})

Google AI

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import os
from mem0 import Memory

os.environ["GEMINI_API_KEY"] = "your-api-key"

config = {
    "llm": {
        "provider": "litellm",
        "config": {
            "model": "gemini/gemini-pro",
            "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"})

Anthropic

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import os
from mem0 import Memory

os.environ["ANTHROPIC_API_KEY"] = "your-api-key"

config = {
    "llm": {
        "provider": "litellm",
        "config": {
            "model": "claude-3-opus-20240229",
            "temperature": 0.1,
            "max_tokens": 2000,
        }
    }
}

m = Memory.from_config(config)
m.add("Likes to play cricket on weekends", user_id="alice", metadata={"category": "hobbies"})

Mistral AI

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import os
from mem0 import Memory

os.environ["MISTRAL_API_KEY"] = "your-api-key"

config = {
    "llm": {
        "provider": "litellm",
        "config": {
            "model": "open-mixtral-8x7b",
            "temperature": 0.1,
            "max_tokens": 2000,
        }
    }
}

m = Memory.from_config(config)
m.add("Likes to play cricket on weekends", user_id="alice", metadata={"category": "hobbies"})

OpenAI Azure

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import os
from mem0 import Memory

os.environ["AZURE_API_KEY"] = "your-api-key"

# Needed to use custom models
os.environ["AZURE_API_BASE"] = "your-api-base-url"
os.environ["AZURE_API_VERSION"] = "version-to-use"

config = {
    "llm": {
        "provider": "litellm",
        "config": {
            "model": "azure_ai/command-r-plus",
            "temperature": 0.1,
            "max_tokens": 2000,
        }
    }
}

m = Memory.from_config(config)
m.add("Likes to play cricket on weekends", user_id="alice", metadata={"category": "hobbies"})