MInD is a Python-based memory framework designed to augment LLM-driven AI agents with robust memory capabilities. It enables agents to capture user inputs and system events as episodic logs, condense those logs into semantic summaries, and retrieve contextually relevant memories on demand. With configurable retention policies, similarity search, and automated summarization, MInD maintains a persistent knowledge base that agents consult during inference. This ensures they recall prior interactions accurately, adapt responses based on history, and deliver personalized, coherent dialogues across multiple sessions.

OLI (OpenAI Logic Interpreter) is a client-side framework designed to simplify the creation of AI agents within web applications by leveraging the OpenAI API. Developers can define custom functions that OLI intelligently selects based on user prompts, manage conversational context to maintain coherent state across multiple interactions, and chain API calls for complex workflows such as booking appointments or generating reports. Furthermore, OLI includes utilities for parsing responses, handling errors, and integrating third-party services through webhooks or REST endpoints. Because it’s fully modular and open-source, teams can customize agent behaviors, add new capabilities, and deploy OLI agents on any web platform without backend dependencies. OLI accelerates development of conversational UIs and automations.