[AI Mem0] 大语言模型：一站式集成多种顶级AI模型，提升工作效率

概览

Mem0 内置了对多种流行的大型语言模型的支持。它可以利用用户提供的大型语言模型，确保针对特定需求的高效使用。

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"})