Agent Workflow Memory is a Python library designed to augment AI agents with persistent memory across complex workflows. It leverages vector stores to encode and retrieve relevant context, enabling agents to recall past interactions, maintain state, and make informed decisions. The library integrates seamlessly with frameworks like LangChain’s WorkflowAgent, providing customizable memory callbacks, data eviction policies, and support for various storage backends. By housing conversation histories and task metadata in vector databases, it allows semantic similarity searches to surface the most relevant memories. Developers can fine-tune retrieval scopes, compress historical data, and implement custom persistence strategies. Ideal for long-running sessions, multi-agent coordination, and context-rich dialogues, Agent Workflow Memory ensures AI agents operate with continuity, enabling more natural, context-aware interactions while reducing redundancy and improving efficiency.

Airtop is an advanced web automation platform utilizing AI-powered cloud browsers. It enables users to automate web tasks such as scraping and controlling websites using natural language commands. The platform supports long-running sessions, human intervention via Live View, and interactions with sites requiring logins and captchas. With airtop, you can manage cloud browser infrastructure efficiently and scale seamlessly, freeing your team to focus on core business objectives.