worker agent

setup.py

@@ -3,7 +3,7 @@ from setuptools import setup, find_packages
 setup(
   name = 'swarms',
   packages = find_packages(exclude=[]),
-  version = '0.1.7',
+  version = '0.1.8',
   license='MIT',
   description = 'Swarms - Pytorch',
   author = 'Kye Gomez',

swarms/agents/workers/auto_agent.py

@@ -53,43 +53,41 @@ class MultiModalVisualAgentTool(BaseTool):
 
 
 
-embeddings_model = OpenAIEmbeddings(openai_api_key="")
-embedding_size = 1536
-index = faiss.IndexFlatL2(embedding_size)
-vectorstore = FAISS(embeddings_model.embed_query, index, InMemoryDocstore({}), {})
 
+class WorkerAgent:
+    def __init__(self, objective: str, api_key: str):
+        self.objective = objective
+        self.api_key = api_key
+        self.worker = self.create_agent_worker()
 
+    def create_agent_worker(self):
+        os.environ['OPENAI_API_KEY'] = self.api_key
 
+        llm = ChatOpenAI(model_name="gpt-4", temperature=1.0)
+        embeddings_model = OpenAIEmbeddings()
+        embedding_size = 1536
+        index = faiss.IndexFlatL2(embedding_size)
+        vectorstore = FAISS(embeddings_model.embed_query, index, InMemoryDocstore({}), {})
 
         query_website_tool = WebpageQATool(qa_chain=load_qa_with_sources_chain(llm))
-
-# !pip install duckduckgo_search
         web_search = DuckDuckGoSearchRun()
 
-
-#MM CHILD AGENT
         multimodal_agent = MultiModalVisualAgent()
-
-#
-multimodal_agent_tool = MultiModalVisualAgentTool(MultiModalVisualAgent)
+        multimodal_agent_tool = MultiModalVisualAgentTool(multimodal_agent)
 
         tools = [
-    
             web_search,
             WriteFileTool(root_dir="./data"),
             ReadFileTool(root_dir="./data"),
-    process_csv,
-
-    # multimodal_agent_tool,
-
 
+            multimodal_agent_tool,
+            process_csv,
             query_website_tool,
             Terminal,
-    CodeWriter,
-    CodeEditor
 
 
-    # HumanInputRun(), # Activate if you want the permit asking for help from the human
+            CodeWriter,
+            CodeEditor
         ]
 
         agent_worker = AutoGPT.from_llm_and_tools(
@@ -98,11 +96,23 @@ agent_worker = AutoGPT.from_llm_and_tools(
             tools=tools,
             llm=llm,
             memory=vectorstore.as_retriever(search_kwargs={"k": 8}),
-    human_in_the_loop=True, # Set to True if you want to add feedback at each step.
+            human_in_the_loop=True,
         )
 
         agent_worker.chain.verbose = True
 
+        return agent_worker
+
+        # objective = "Your objective here"
+        # api_key = "Your OpenAI API key here"
+
+        # worker_agent = WorkerAgent(objective, api_key)
+
+    
+
+
+
+
 # worker_agent = agent_worker
 # tree_of_thoughts_prompt = """