reca11-memory 0.1.1

Memory layer and SDK for LLMs

Reca11 — Memory Layer for LLMs

Reca11 is a plug-and-play memory architecture designed to add persistent context to your LLM applications. It intelligently tracks and stores three core components of every conversation:

• Recent chat history
• Core user facts
• Evolving thematic summaries

This enables better recall, continuity, and personalization in any app powered by large language models.

Link to research article: COMING SOON!

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Installation

Install the SDK via pip:

pip install reca11-memory

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Generate an API Key

To use the memory service, you’ll need an API key.

Visit: https://reca11-memory-1.onrender.com
Click the "Generate API Key" button to instantly receive a unique key.

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Quickstart

Here’s how to get up and running in just a few lines:

from reca11 import Reca11

rc = Reca11(
    api_key="your-api-key",
    openai_key="your-openai-key",
    project_name="my-project"
)

chat_pair = {
    "assistant": "Hi! What did you do today?",
    "user": "I tried pineapple on pizza. Safe to say I'm not a fan!"
}

memory = rc.recall(chat_pair)

print(memory)

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Health Check

To verify the backend is online:

GET https://reca11-memory.onrender.com/health

Expected response:

{ "status": "ok" }

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License

This project is open-sourced under the terms of the MIT License.