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| from agentscope.agent import AgentBase | |
| from agentscope.message import Msg | |
| class AgentGPT_Agent(AgentBase): | |
| """ | |
| AgentScope integration for the 100M parameter model. | |
| """ | |
| def __init__(self, name, model_wrapper): | |
| super().__init__() | |
| self.name = name | |
| self.model_wrapper = model_wrapper # RecursiveAgenticLoop instance | |
| async def reply(self, x: Msg = None) -> Msg: | |
| # Use the recursive reasoning loop to generate a response | |
| response_text = self.model_wrapper.generate_with_reasoning(x.content) | |
| # Format as AgentScope Message | |
| msg = Msg(self.name, content=response_text, role="assistant") | |
| return msg | |
| def setup_agentscope(model, tokenizer, workspace_path="."): | |
| from agent.recursive_reasoning import RecursiveAgenticLoop | |
| from agent.agentic_core import MCPDiscoveryProtocol | |
| discovery = MCPDiscoveryProtocol(workspace_path) | |
| model_wrapper = RecursiveAgenticLoop(model, tokenizer, discovery_protocol=discovery) | |
| # Create the agent | |
| agent = AgentGPT_Agent(name="NanoAgent", model_wrapper=model_wrapper) | |
| return agent | |