diff --git a/swarms/hivemind/__init__.py b/swarms/hivemind/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/swarms/hivemind/hivemind.py b/swarms/hivemind/hivemind.py
deleted file mode 100644
index acd4d5ec..00000000
--- a/swarms/hivemind/hivemind.py
+++ /dev/null
@@ -1,82 +0,0 @@
-#  workers in unison
-# kye gomez jul 13 4:01pm, can scale up the number of swarms working on a probkem with `hivemind(swarms=4, or swarms=auto which will scale the agents depending on the complexity)`
-# this needs to change, we need to specify exactly what needs to be imported
-# add typechecking, documentation, and deeper error handling
-# TODO: MANY WORKERS
-
-import concurrent.futures
-import logging
-
-import faiss
-
-from swarms.embeddings.openai import OpenAIEmbeddings
-from swarms.swarms.swarms import HierarchicalSwarm
-from swarms.vectorstore.vectorstore import FAISS, InMemoryDocstore
-
-logging.basicConfig(
-    level=logging.DEBUG, format="%(asctime)s - %(levelname)s - %(message)s"
-)
-
-
-class HiveMind:
-    def __init__(self, openai_api_key="", num_swarms=1, max_workers=None):
-        self.openai_api_key = openai_api_key
-        self.num_swarms = num_swarms
-        self.swarms = [HierarchicalSwarm(openai_api_key) for _ in range(num_swarms)]
-        self.vectorstore = self.initialize_vectorstore()
-        self.max_workers = max_workers if max_workers else min(32, num_swarms)
-
-    def initialize_vectorstore(self):
-        try:
-            embeddings_model = OpenAIEmbeddings(openai_api_key=self.openai_api_key)
-            embedding_size = 1536
-            index = faiss.IndexFlatL2(embedding_size)
-            return FAISS(embeddings_model.embed_query, index, InMemoryDocstore({}), {})
-        except Exception as e:
-            logging.error(f"Failed to initialize vector store: {e}")
-            raise
-
-    def run_swarm(self, swarm, objective):
-        try:
-            return swarm.run(objective)
-        except Exception as e:
-            logging.error(f"An error occurred in run: {e}")
-
-    def run(self, objective, timeout=None):
-        with concurrent.futures.ThreadPoolExecutor(
-            max_workers=self.max_workers
-        ) as executor:
-            futures = {
-                executor.submit(self.run_swarm, swarm, objective)
-                for swarm in self.swarms
-            }
-            results = []
-            for future in concurrent.futures.as_completed(futures, timeout=timeout):
-                try:
-                    results.append(future.result())
-                except Exception as e:
-                    logging.error(f"An error occurred in a swarm: {e}")
-        return results
-
-    def add_swarm(self):
-        self.swarms.append(HierarchicalSwarm(self.openai_api_key))
-
-    def remove_swarm(self, index):
-        try:
-            self.swarms.pop(index)
-        except IndexError:
-            logging.error(f"No swarm found at index {index}")
-
-    def get_progress(self):
-        # this assumes that the swarms class has a get progress method
-        pass
-
-    def cancel_swarm(self, index):
-        try:
-            self.swarms[index].cancel()
-        except IndexError:
-            logging.error(f"No swarm found at index {index}")
-
-    def queue_tasks(self, tasks):
-        for task in tasks:
-            self.run(task)
diff --git a/swarmslogobanner.png b/swarmslogobanner.png
index 831820ac..f88646db 100644
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