MemoryConfig¶

Configuration class for GraphMem.

Constructor¶

from graphmem import MemoryConfig

config = MemoryConfig(
    # LLM Configuration
    llm_provider: str,
    llm_api_key: str,
    llm_model: str,
    llm_api_base: str = None,

    # Embedding Configuration
    embedding_provider: str,
    embedding_api_key: str,
    embedding_model: str,
    embedding_api_base: str = None,

    # Azure Configuration
    azure_endpoint: str = None,
    azure_deployment: str = None,
    azure_embedding_deployment: str = None,
    azure_api_version: str = "2024-02-15-preview",

    # Storage Configuration
    turso_db_path: str = None,
    turso_url: str = None,
    turso_auth_token: str = None,
    neo4j_uri: str = None,
    neo4j_username: str = "neo4j",
    neo4j_password: str = None,
    redis_url: str = None,

    # Evolution Configuration
    evolution_enabled: bool = True,
    auto_evolve: bool = False,
    decay_enabled: bool = True,
    decay_half_life_days: int = 30,
    consolidation_threshold: float = 0.85,
)

Parameters¶

LLM Configuration¶

Parameter	Type	Required	Description
`llm_provider`	str	Yes	Provider: "openai", "azure_openai", "anthropic", "openai_compatible", "ollama"
`llm_api_key`	str	Yes	API key for the provider
`llm_model`	str	Yes	Model name (e.g., "gpt-4o-mini")
`llm_api_base`	str	No	Custom API base URL (for OpenRouter, Azure, local models)

Embedding Configuration¶

Parameter	Type	Required	Description
`embedding_provider`	str	Yes	Provider for embeddings
`embedding_api_key`	str	Yes	API key for embeddings
`embedding_model`	str	Yes	Model (e.g., "text-embedding-3-small")
`embedding_api_base`	str	No	Custom API base URL (for OpenRouter, Azure, local models)

Azure Configuration¶

Parameter	Type	Required	Description
`azure_deployment`	str	For Azure	LLM deployment name
`azure_embedding_deployment`	str	For Azure	Embedding deployment name
`azure_api_version`	str	No	API version (default: "2024-02-15-preview")

Azure Base URL

For Azure OpenAI, use llm_api_base and embedding_api_base to specify your Azure endpoint (e.g., https://your-resource.openai.azure.com/).

Storage Configuration¶

Parameter	Type	Required	Description
`turso_db_path`	str	No	Local SQLite file path
`turso_url`	str	No	Turso cloud URL
`turso_auth_token`	str	No	Turso auth token
`neo4j_uri`	str	No	Neo4j connection URI
`neo4j_username`	str	No	Neo4j username
`neo4j_password`	str	No	Neo4j password
`redis_url`	str	No	Redis connection URL

Evolution Configuration¶

Parameter	Type	Default	Description
`evolution_enabled`	bool	True	Enable evolution
`auto_evolve`	bool	False	Auto-evolve on ingest
`decay_enabled`	bool	True	Enable memory decay
`decay_half_life_days`	int	30	Decay half-life
`consolidation_threshold`	float	0.85	Merge threshold (0-1)

Examples¶

OpenAI¶

config = MemoryConfig(
    llm_provider="openai",
    llm_api_key="sk-...",
    llm_model="gpt-4o-mini",
    embedding_provider="openai",
    embedding_api_key="sk-...",
    embedding_model="text-embedding-3-small",
)

Azure OpenAI¶

config = MemoryConfig(
    llm_provider="azure_openai",
    llm_api_key="your-azure-key",
    llm_api_base="https://your-resource.openai.azure.com/",  # Azure endpoint
    azure_deployment="gpt-4",
    llm_model="gpt-4",
    azure_api_version="2024-02-15-preview",

    embedding_provider="azure_openai",
    embedding_api_key="your-azure-key",
    embedding_api_base="https://your-resource.openai.azure.com/",  # Azure endpoint
    azure_embedding_deployment="text-embedding-ada-002",
    embedding_model="text-embedding-ada-002",
)

OpenRouter¶

config = MemoryConfig(
    llm_provider="openai_compatible",
    llm_api_key="sk-or-v1-...",
    llm_api_base="https://openrouter.ai/api/v1",  # Custom base URL
    llm_model="google/gemini-2.0-flash-001",
    embedding_provider="openai_compatible",
    embedding_api_key="sk-or-v1-...",
    embedding_api_base="https://openrouter.ai/api/v1",  # Custom base URL
    embedding_model="openai/text-embedding-3-small",
)

Local Models (Ollama)¶

config = MemoryConfig(
    llm_provider="openai_compatible",
    llm_api_key="not-needed",
    llm_api_base="http://localhost:11434/v1",  # Ollama base URL
    llm_model="llama3.2",
    embedding_provider="openai_compatible",
    embedding_api_key="not-needed",
    embedding_api_base="http://localhost:11434/v1",  # Ollama base URL
    embedding_model="nomic-embed-text",
)

With Turso¶

config = MemoryConfig(
    # LLM config...
    turso_db_path="my_memory.db",
)

With Neo4j + Redis¶

config = MemoryConfig(
    # LLM config...
    neo4j_uri="neo4j+s://xxx.databases.neo4j.io",
    neo4j_password="your-password",
    redis_url="redis://default:password@host:port",
)

Full Production¶

import os

config = MemoryConfig(
    # LLM
    llm_provider="azure_openai",
    llm_api_key=os.getenv("AZURE_OPENAI_KEY"),
    llm_api_base=os.getenv("AZURE_ENDPOINT"),  # e.g., "https://your-resource.openai.azure.com/"
    azure_deployment="gpt-4",
    llm_model="gpt-4",
    azure_api_version="2024-02-15-preview",

    # Embeddings
    embedding_provider="azure_openai",
    embedding_api_key=os.getenv("AZURE_OPENAI_KEY"),
    embedding_api_base=os.getenv("AZURE_ENDPOINT"),  # Same endpoint for embeddings
    azure_embedding_deployment="text-embedding-ada-002",
    embedding_model="text-embedding-ada-002",

    # Storage
    neo4j_uri=os.getenv("NEO4J_URI"),
    neo4j_password=os.getenv("NEO4J_PASSWORD"),
    redis_url=os.getenv("REDIS_URL"),

    # Evolution
    evolution_enabled=True,
    auto_evolve=False,
    decay_half_life_days=30,
)