1st hivemind class

Former-commit-id: ae765e277eaf36f8784314ab9bf51b41df117c07

swarms/hivemind.py

@@ -1,2 +1,47 @@
 # many boss + 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)`
+#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)`
+
+import concurrent.futures
+import logging
+
+from swarms.swarms import Swarms
+from swarms.tools.agent_tools import *
+
+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 = [Swarms(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_swarms(objective)
+        except Exception as e:
+            logging.error(f"An error occurred in run_swarms: {e}")
+
+    def run_swarms(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