Search Results for "composition"

HyperFrames is a framework developed by HeyGen that focuses on generating and managing structured, dynamic content experiences powered by AI. It introduces the concept of “frames,” which represent modular units of content that can be dynamically composed and rendered based on context or user interaction. The system is designed to enable highly interactive and personalized experiences, particularly in applications such as video generation, storytelling, and user interfaces. It supports...

Agency Agents is a framework focused on orchestrating multiple AI agents that collaborate to complete complex tasks through structured coordination. It is designed around the idea of “agency,” where each agent has a defined role, responsibility, and interaction pattern within a larger system. The framework enables developers to define workflows where agents communicate, delegate tasks, and share context, creating a distributed problem-solving environment. It supports modular design, allowing...

AgentScope is a production-ready agent framework designed to help developers build, deploy, and scale intelligent agentic applications. It provides essential abstractions that evolve with advancing LLM capabilities, emphasizing reasoning, tool use, and flexible orchestration rather than rigid prompt constraints. With built-in support for ReAct agents, memory, planning, human-in-the-loop control, and real-time voice interaction, developers can create powerful agents in minutes. AgentScope...

TEN (Transformative Extensions Network) is an open source framework designed to empower developers to build real-time multimodal AI agents capable of voice, video, text, image, and data-stream interaction with ultra-low latency. It includes a full ecosystem, TEN Turn Detection, TEN Agent, and TMAN Designer, allowing developers to rapidly assemble human-like, responsive agents that can see, speak, hear, and interact. With support for languages like Python, C++, and Go, it offers flexible...

infiAgent is an open-source AI agent framework for building powerful, long-running autonomous agents capable of tackling complex tasks without collapsing under growing context or tool invocation histories. Designed as a “Multi-Level Agent” (MLA) system, it externalizes persistent state to the file system so that agents can operate over unlimited runtime without the need for token-intensive context compression, enabling workflows such as research paper drafting, experiments, coding, and...

EU-funded R&D project that aims to develop and validate a platform for composition of government services into complex process definitions (covering life events/business episodes) enabling semantic interoperability of particular e-Government services.