TEN Framework
Overview
An open-source framework for building autonomous AI agents that interact with the real world through tools and memory.
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TEN Framework is an open-source modular system for building autonomous AI agents capable of reasoning, memory management, and tool usage. Designed to reflect real-world constraints, it incorporates a Thought-Emission-Norm (TEN) architecture, encouraging agents to think before acting. The framework supports open-ended planning, persistent memory storage, and tool augmentation. Developers can use TEN to experiment with agent autonomy and deploy agents that simulate complex decision-making workflows.
Autonomy level
88%
Reasoning: The TEN Framework enables high autonomy through its real-time multimodal processing and dynamic state management. Its modular extension architecture allows agents to independently handle tasks like speech processing, translation, and decision-making without constant human intervention. The edge-cloud integration further supports autonomous operatio...
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Some of the use cases of TEN Framework:
- Creating autonomous agents that use memory and tools to solve tasks.
- Building experimental AI agents with a focus on decision-making and planning.
- Deploying agents that emulate human-like reasoning processes.
- Extending or researching agent autonomy with modular plug-ins.
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Popularity level: 71%
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