Worker autonomous agent example

Former-commit-id: 23ee3bb77d

example.py

@@ -67,14 +67,14 @@
 
 
 ##########
-from swarms import AutoBot
+from swarms import Worker
 
 
-worker = AutoBot(
+node = Worker(
     openai_api_key="",
     ai_name="Optimus Prime",
 )
 
 task = "What were the winning boston marathon times for the past 5 years (ending in 2022)? Generate a table of the year, name, country of origin, and times."
-response = worker.run(task)
+response = node.run(task)
 print(response)

swarms/__init__.py

@@ -2,7 +2,8 @@
 from swarms.orchestrator.autoscaler import AutoScaler
 
 # worker
-from swarms.workers.worker_node import WorkerNode
+# from swarms.workers.worker_node import WorkerNode
+from swarms.workers.workers import Workers
 from swarms.workers.autobot import AutoBot
 
 #boss

swarms/workers/workers.py

@@ -0,0 +1,104 @@
+import faiss
+from langchain.chat_models import ChatOpenAI
+from langchain.docstore import InMemoryDocstore
+from langchain.embeddings import OpenAIEmbeddings
+from langchain.vectorstores import FAISS
+from langchain_experimental.autonomous_agents import AutoGPT
+
+from swarms.agents.tools.autogpt import (
+    ReadFileTool,
+    WriteFileTool,
+    process_csv,
+    # web_search,
+    query_website_tool,
+)
+from swarms.utils.decorators import error_decorator, log_decorator, timing_decorator
+
+ROOT_DIR = "./data/"
+
+
+class Workers:
+    @log_decorator
+    @error_decorator
+    @timing_decorator
+    def __init__(self, 
+                 model_name="gpt-4", 
+                 openai_api_key=None,
+                 ai_name="Autobot Swarm Worker",
+                 ai_role="Worker in a swarm",
+                #  embedding_size=None,
+                #  k=None,
+                 temperature=0.5):
+        self.openai_api_key = openai_api_key
+        self.temperature = temperature
+        
+        try:
+            self.llm = ChatOpenAI(model_name=model_name, 
+                                openai_api_key=self.openai_api_key, 
+                                temperature=self.temperature)
+        except Exception as error:
+            raise RuntimeError(f"Error Initializing ChatOpenAI: {error}")    
+        
+        self.ai_name = ai_name
+        self.ai_role = ai_role
+
+        # self.embedding_size = embedding_size
+        # # self.k = k
+
+        self.setup_tools()
+        self.setup_memory()
+        self.setup_agent()
+    
+    @log_decorator
+    @error_decorator
+    @timing_decorator
+    def setup_tools(self):
+        self.tools = [
+            WriteFileTool(root_dir=ROOT_DIR),
+            ReadFileTool(root_dir=ROOT_DIR),
+            process_csv,
+            query_website_tool,
+        ]
+
+    def setup_memory(self):
+        try:
+            embeddings_model = OpenAIEmbeddings(openai_api_key=self.openai_api_key)
+            embedding_size = 1536
+            index = faiss.IndexFlatL2(embedding_size)
+            self.vectorstore = FAISS(embeddings_model.embed_query, index, InMemoryDocstore({}), {})
+        except Exception as error:
+            raise RuntimeError(f"Error setting up memory perhaps try try tuning the embedding size: {error}")
+        
+    
+    def setup_agent(self):
+        try: 
+            self.agent = AutoGPT.from_llm_and_tools(
+                ai_name=self.ai_name,
+                ai_role=self.ai_role,
+                tools=self.tools,
+                llm=self.llm,
+                memory=self.vectorstore.as_retriever(search_kwargs={"k": 8}),
+            )
+        
+        except Exception as error:
+            raise RuntimeError(f"Error setting up agent: {error}")
+    
+    @log_decorator
+    @error_decorator
+    @timing_decorator
+    def run(self, task):
+        try:
+            result = self.agent.run([task])
+            return result
+        except Exception as error:
+            raise RuntimeError(f"Error while running agent: {error}")
+    
+    @log_decorator
+    @error_decorator
+    @timing_decorator
+    def __call__(self, task):
+        try:
+            results = self.agent.run([task])
+            return results
+        except Exception as error:
+            raise RuntimeError(f"Error while running agent: {error}")