clean up

swarms/swarms.py

@@ -7,61 +7,57 @@ class Swarms:
         self.openai_api_key = openai_api_key
 
     def initialize_llm(self):
+        # Initialize language model
         return ChatOpenAI(model_name="gpt-4", temperature=1.0, openai_api_key=self.openai_api_key)
 
     def initialize_tools(self, llm):
+        # Initialize tools
         web_search = DuckDuckGoSearchRun()
         tools = [
             web_search,
             WriteFileTool(root_dir=ROOT_DIR),
             ReadFileTool(root_dir=ROOT_DIR),
             process_csv,
-            
             WebpageQATool(qa_chain=load_qa_with_sources_chain(llm)),
-
-            # Tool(name='terminal', func=Terminal.execute, description='Operates a terminal'),
-            # Tool(name='code_writer', func=CodeWriter(), description='Writes code'),
-            # Tool(name='code_editor', func=CodeEditor(), description='Edits code'),#
         ]
         return tools
 
     def initialize_vectorstore(self):
+        # Initialize vector store
         embeddings_model = OpenAIEmbeddings()
         embedding_size = 1536
         index = faiss.IndexFlatL2(embedding_size)
         return FAISS(embeddings_model.embed_query, index, InMemoryDocstore({}), {})
 
     def initialize_worker_node(self, llm, tools, vectorstore):
+        # Initialize worker node
         worker_node = WorkerNode(llm=llm, tools=tools, vectorstore=vectorstore)
         worker_node.create_agent(ai_name="AI Assistant", ai_role="Assistant", human_in_the_loop=False, search_kwargs={})
         return worker_node
 
-    def initialize_boss_node(self, llm, vectorstore):
-        todo_prompt = PromptTemplate.from_template("You are a planner who is an expert at coming up with a todo list for a given objective. Come up with a todo list for this objective: {objective}""")
+    def initialize_boss_node(self, llm, vectorstore, worker_node):
+        # Initialize boss node
+        todo_prompt = PromptTemplate.from_template("You are a planner who is an expert at coming up with a todo list for a given objective. Come up with a todo list for this objective: {objective}")
         todo_chain = LLMChain(llm=OpenAI(temperature=0), prompt=todo_prompt)
-        # search = SerpAPIWrapper()
         tools = [
-            # Tool(name="Search", func=search.run, description="useful for when you need to answer questions about current events"),
             Tool(name="TODO", func=todo_chain.run, description="useful for when you need to come up with todo lists. Input: an objective to create a todo list for. Output: a todo list for that objective. Please be very clear what the objective is!"),
-            # Tool(name="AUTONOMOUS Worker AGENT", func=self.worker_node, description="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")
-            self.worker_node,
+            worker_node,
         ]
-
         suffix = """Question: {task}\n{agent_scratchpad}"""
         prefix = """You are an Boss in a swarm who performs one task based on the following objective: {objective}. Take into account these previously completed tasks: {context}.\n"""
         prompt = ZeroShotAgent.create_prompt(tools, prefix=prefix, suffix=suffix, input_variables=["objective", "task", "context", "agent_scratchpad"],)
-
         llm_chain = LLMChain(llm=OpenAI(temperature=0), prompt=prompt)
         agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=[tool.name for tool in tools])
         agent_executor = AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=True)
         return BossNode(self.openai_api_key, llm, vectorstore, agent_executor, verbose=True, max_iterations=5)
 
     def run_swarms(self, objective):
+        # Run the swarm with the given objective
         llm = self.initialize_llm()
         tools = self.initialize_tools(llm)
         vectorstore = self.initialize_vectorstore()
         worker_node = self.initialize_worker_node(llm, tools, vectorstore)
-        boss_node = self.initialize_boss_node(llm, vectorstore)
+        boss_node = self.initialize_boss_node(llm, vectorstore, worker_node)
         task = boss_node.create_task(objective)
         boss_node.execute_task(task)
         worker_node.run_agent(objective)

swarms/tools/agent_tools.py

@@ -39,7 +39,7 @@ ROOT_DIR = "./data/"
 openai_api_key = os.environ["OPENAI_API_KEY"]
 llm = ChatOpenAI(model_name="gpt-4", temperature=1.0, openai_api_key=openai_api_key)
 
-tools = [
+worker_tools = [
     DuckDuckGoSearchRun(),
     WriteFileTool(root_dir=ROOT_DIR),
     ReadFileTool(root_dir=ROOT_DIR),