workernode re-creation

swarms/agents/workers/worker_agent.py

@@ -1,15 +1,17 @@
-from swarms.tools.agent_tools import *
+from tools.agent_tools import *
+from langchain.tools import BaseTool
+from typing import Optional, Type
+from langchain.callbacks.manager import (
+    AsyncCallbackManagerForToolRun,
+    CallbackManagerForToolRun,
+)
 
 # ---------- Worker Node ----------
-# Define the input schema for the WorkerNode
-class WorkerNodeInput(BaseModel):
-    llm: Any = Field(description="Language model")
-    tools: List[Tool] = Field(description="List of tools")
-    vectorstore: VectorStore = Field(description="Vector store")
-
-@tool("WorkerNode", args_schema=WorkerNodeInput)
-class WorkerNode:
+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"
+
     def __init__(self, llm, tools, vectorstore):
         self.llm = llm
         self.tools = tools
@@ -19,15 +21,25 @@ class WorkerNode:
         self.agent = AutoGPT.from_llm_and_tools(
             ai_name=ai_name,
             ai_role=ai_role,
-            tools=tools,
+            tools=self.tools,
             llm=self.llm,
             memory=self.vectorstore.as_retriever(search_kwargs=search_kwargs),
             human_in_the_loop=human_in_the_loop,
         )
         self.agent.chain.verbose = True
 
-    def run_agent(self, prompt):
+    def _run(
+        self, prompt: str, run_manager: Optional[CallbackManagerForToolRun] = None
+    ) -> str:
+        """Use the tool."""
         tree_of_thoughts_prompt = """
         Imagine three different experts are answering this question. All experts will write down each chain of thought of each step of their thinking, then share it with the group. Then all experts will go on to the next step, etc. If any expert realises they're wrong at any point then they leave. The question is...
         """
-        self.agent.run([f"{tree_of_thoughts_prompt} {prompt}"])
+        self.agent.run([f"{tree_of_thoughts_prompt}{prompt}"])
+        return "Task completed by WorkerNode"
+
+    async def _arun(
+        self, prompt: str, run_manager: Optional[AsyncCallbackManagerForToolRun] = None
+    ) -> str:
+        """Use the tool asynchronously."""
+        raise NotImplementedError("WorkerNode does not support async")