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📢 Announcing our research paper: Zentry achieves 26% higher accuracy than OpenAI Memory, 91% lower latency, and 90% token savings! Read the paper to learn how we're revolutionizing AI agent memory.
Graph Memory is a powerful feature that allows users to create and utilize complex relationships between pieces of information.

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Graph Memory supports the following features:

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Using Custom Prompts

Users can specify a custom prompt that will be used to extract specific entities from the given input text. This allows for more targeted and relevant information extraction based on the user’s needs. Here’s an example of how to specify a custom prompt: 
from zentry import Memory

config = {
    "graph_store": {
        "provider": "neo4j",
        "config": {
            "url": "neo4j+s://xxx",
            "username": "neo4j",
            "password": "xxx"
        },
        "custom_prompt": "Please only extract entities containing sports related relationships and nothing else.",
    }
}

m = Memory.from_config(config_dict=config)
If you want to use a managed version of Zentry, please check out Zentry. If you have any questions, please feel free to reach out to us using one of the following methods:

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