šŸ“¢ 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.
To use OpenAI LLM models, you have to set the OPENAI_API_KEY environment variable. You can obtain the OpenAI API key from the OpenAI Platform.

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Usage

import os
from Zentry import Memory

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

config = {
    "llm": {
        "provider": "openai",
        "config": {
            "model": "gpt-4o",
            "temperature": 0.2,
            "max_tokens": 2000,
        }
    }
}

# Use Openrouter by passing it's api key
# os.environ["OPENROUTER_API_KEY"] = "your-api-key"
# config = {
#    "llm": {
#        "provider": "openai",
#        "config": {
#            "model": "meta-llama/llama-3.1-70b-instruct",
#        }
#    }
# }

m = Memory.from_config(config)
messages = [
    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
    {"role": "assistant", "content": "How about a thriller movies? They can be quite engaging."},
    {"role": "user", "content": "Iā€™m not a big fan of thriller movies but I love sci-fi movies."},
    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
]
m.add(messages, user_id="alice", metadata={"category": "movies"})
We also support the new OpenAI structured-outputs model. 
import os
from Zentry import Memory

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

config = {
    "llm": {
        "provider": "openai_structured",
        "config": {
            "model": "gpt-4o-2024-08-06",
            "temperature": 0.0,
        }
    }
}

m = Memory.from_config(config)

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Config

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