clean up

Former-commit-id: c41e5edd5a3919381e84e15bdc6d21077682954e

swarms/agents/utils/AgentBuilder.py

@@ -15,7 +15,8 @@ from langchain.chat_models import ChatOpenAI
 from .EvalOutputParser import EvalOutputParser
 
 
-class AgentBuilder:
+
+class AgentSetup:
     def __init__(self, toolsets: list[BaseToolSet] = [], openai_api_key: str = None, serpapi_api_key: str = None, bing_search_url: str = None, bing_subscription_key: str = None):
         self.llm: BaseChatModel = None
         self.parser: BaseOutputParser = None
@@ -28,7 +29,7 @@ class AgentBuilder:
         if not self.openai_api_key:
             raise ValueError("OpenAI key is missing, it should either be set as an environment variable or passed as a parameter")
 
-    def build_llm(self, callback_manager: BaseCallbackManager = None, openai_api_key: str = None):
+    def setup_llm(self, callback_manager: BaseCallbackManager = None, openai_api_key: str = None):
         if openai_api_key is None:
             openai_api_key = os.getenv('OPENAI_API_KEY')
             if openai_api_key is None:
@@ -36,16 +37,15 @@ class AgentBuilder:
         
         self.llm = ChatOpenAI(openai_api_key=openai_api_key, temperature=0.5, callback_manager=callback_manager, verbose=True)
 
-    def build_parser(self):
+    def setup_parser(self):
         self.parser = EvalOutputParser()
 
-    def build_global_tools(self):
+    def setup_global_tools(self):
         if self.llm is None:
             raise ValueError("LLM must be initialized before tools")
 
         toolnames = ["wikipedia"]
 
-
         if self.serpapi_api_key:
             toolnames.append("serpapi")
         

swarms/agents/utils/AgentManager.py

@@ -1,22 +1,20 @@
-from typing import Dict, Optional
+import os
 import logging
-
+from typing import Dict, Optional
 from celery import Task
-
 from langchain.agents.agent import AgentExecutor
 from langchain.callbacks.manager import CallbackManager
 from langchain.chains.conversation.memory import ConversationBufferMemory
 from langchain.memory.chat_memory import BaseChatMemory
-
 from swarms.tools.main import BaseToolSet, ToolsFactory
-from .AgentBuilder import AgentBuilder
+from swarms.prompts.prompts import EVAL_PREFIX, EVAL_SUFFIX
-from .Calback import EVALCallbackHandler, ExecutionTracingCallbackHandler
 
+from swarms.agents.utils.AgentBuilder import AgentSetup
+from swarms.agents.utils.EvalOutputParser import EVALCallbackHandler, ExecutionTracingCallbackHandler
 
 callback_manager_instance = CallbackManager(EVALCallbackHandler())
 
-
+class AgentCreator:
-class AgentManager:
     def __init__(self, toolsets: list[BaseToolSet] = []):
         if not isinstance(toolsets, list):
             raise TypeError("Toolsets must be a list")
@@ -38,9 +36,8 @@ class AgentManager:
 
     def create_executor(self, session: str, execution: Optional[Task] = None, openai_api_key: str = None) -> AgentExecutor:
         try:
-            builder = AgentBuilder(self.toolsets)
+            builder = AgentSetup(self.toolsets)
-            builder.build_parser()
+            builder.setup_parser()
-
 
             callbacks = []
             eval_callback = EVALCallbackHandler()
@@ -52,15 +49,13 @@ class AgentManager:
                 execution_callback.set_parser(builder.get_parser())
                 callbacks.append(execution_callback)
 
-            #llm init
             callback_manager = CallbackManager(callbacks)
-            builder.build_llm(callback_manager, openai_api_key)
+            builder.setup_llm(callback_manager, openai_api_key)
             if builder.llm is None:
                 raise ValueError('LLM not created')
 
-            builder.build_global_tools()
+            builder.setup_global_tools()
 
-            #agent init
             agent = builder.get_agent()
             if not agent:
                 raise ValueError("Agent not created")
@@ -77,9 +72,6 @@ class AgentManager:
             for tool in tools:
                 tool.callback_manager = callback_manager
 
-            # Ensure the 'agent' key is present in the values dictionary
-            # values = {'agent': agent, 'tools': tools}
-
             executor = AgentExecutor.from_agent_and_tools(
                 agent=agent,
                 tools=tools,
@@ -98,7 +90,7 @@ class AgentManager:
             raise e
 
     @staticmethod
-    def create(toolsets: list[BaseToolSet]) -> "AgentManager":
+    def create(toolsets: list[BaseToolSet]) -> "AgentCreator":
         if not isinstance(toolsets, list):
             raise TypeError("Toolsets must be a list")
-        return AgentManager(toolsets=toolsets)
+        return AgentCreator(toolsets=toolsets)