redcache-ai

A dynamic memory framework that supports large language models and agents.

CommonProductProgrammingmemory frameworklanguage models

RedCache-AI is a dynamic memory framework designed for large language models and agents, allowing developers to build a wide range of applications, from AI-driven dating apps to medical diagnosis platforms. It addresses issues with existing solutions being expensive, closed-source, or lacking extensive support for external dependencies.

Initialize storage on disk or an SQLite database for memories.
Store text as memories and attach metadata to each memory entry.
Retrieve all memories for a specified user.
Search memories and return relevant entries based on keywords and user ID.
Update memories by modifying the text content of existing entries.
Delete memories by ID or remove all memories associated with a user.
Integrate large language models (currently supports OpenAI) to enhance memory content.
Generate memory summaries to provide concise overviews of users' memories.

The target audience includes developers and data scientists who need to build or enhance applications based on language models. RedCache-AI offers a flexible and scalable memory storage solution
enabling developers to quickly implement memory management and enhancement features.

Build an AI chatbot that uses RedCache-AI to store and manage conversation history.
Develop a medical consultation platform utilizing RedCache-AI to store patient information and historical consultation records.
Create a personalized recommendation system that uses RedCache-AI to remember user preferences and provide customized suggestions.

Install redcache-ai as a Python package.
Import required dependencies and initialize RedCache-AI
selecting either disk or SQLite as the storage option.
Use the add method to store text memories
attaching user IDs and metadata.

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