run swarms

swarms/agents/workers/worker_agent.py

@@ -8,14 +8,12 @@ from langchain.callbacks.manager import (
 
 class WorkerNode(BaseTool):
     """Useful for when you need to spawn an autonomous agent instance as a worker to accomplish complex tasks, it can search the internet or spawn child multi-modality models to process and generate images and text or audio and so on """
-    name = "WorkerNode"
-    description = "A worker node that can perform complex tasks"
-    llm: Any = Field(description="Language model")
-    tools: List[Tool] = Field(description="List of tools")
-    vectorstore: VectorStore = Field(description="Vector store")
 
-    def __init__(self, **data):
-        super().__init__(**data)
+    def __init__(self, llm, tools, vectorstore):
+        super().__init__()
+        self.llm = llm
+        self.tools = tools
+        self.vectorstore = vectorstore
 
     def create_agent(self, ai_name, ai_role, human_in_the_loop, search_kwargs):
         self.agent = AutoGPT.from_llm_and_tools(

swarms/swarms.py

@@ -65,10 +65,13 @@ class Swarms:
         llm = self.initialize_llm()
         tools = self.initialize_tools(llm)
         vectorstore = self.initialize_vectorstore()
-        worker_node = self.initialize_worker_node(llm, tools, vectorstore)  # Corrected here
+        worker_node = self.initialize_worker_node(llm, tools, vectorstore)
         boss_node = self.initialize_boss_node(llm, vectorstore)
         task = boss_node.create_task(objective)
         boss_node.execute_task(task)
+        worker_node.run_agent(objective)
+
+
 # class Swarms:
 #     def __init__(self, num_nodes: int, llm: BaseLLM, self_scaling: bool): 
 #         self.nodes = [WorkerNode(llm) for _ in range(num_nodes)]