[BUGF][Agent]

playground/structs/agent_rearrange.py

@@ -0,0 +1,73 @@
+from swarms import Agent, AgentRearrange, rearrange, Anthropic
+
+
+
+# Initialize the director agent
+
+director = Agent(
+    agent_name="Director",
+    system_prompt="Directs the tasks for the workers",
+    llm=Anthropic(),
+    max_loops=1,
+    dashboard=False,
+    streaming_on=True,
+    verbose=True,
+    stopping_token="<DONE>",
+    state_save_file_type="json",
+    saved_state_path="director.json",
+)
+
+
+# Initialize worker 1
+
+worker1 = Agent(
+    agent_name="Worker1",
+    system_prompt="Generates a transcript for a youtube video on what swarms are",
+    llm=Anthropic(),
+    max_loops=1,
+    dashboard=False,
+    streaming_on=True,
+    verbose=True,
+    stopping_token="<DONE>",
+    state_save_file_type="json",
+    saved_state_path="worker1.json",
+)
+
+
+# Initialize worker 2
+worker2 = Agent(
+    agent_name="Worker2",
+    system_prompt="Summarizes the transcript generated by Worker1",
+    llm=Anthropic(),
+    max_loops=1,
+    dashboard=False,
+    streaming_on=True,
+    verbose=True,
+    stopping_token="<DONE>",
+    state_save_file_type="json",
+    saved_state_path="worker2.json",
+)
+
+
+# Create a list of agents
+agents = [director, worker1, worker2]
+
+# Define the flow pattern
+flow = "Director -> Worker1 -> Worker2"
+
+# Using AgentRearrange class
+agent_system = AgentRearrange(agents=agents, flow=flow)
+output = agent_system.run(
+    "Create a format to express and communicate swarms of llms in a structured manner for youtube"
+)
+print(output)
+
+
+# Using rearrange function
+output = rearrange(
+    agents,
+    flow,
+    "Create a format to express and communicate swarms of llms in a structured manner for youtube",
+)
+
+print(output)

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "swarms"
-version = "4.9.8"
+version = "5.0.0"
 description = "Swarms - Pytorch"
 license = "MIT"
 authors = ["Kye Gomez <kye@apac.ai>"]

swarms/__init__.py

@@ -13,4 +13,4 @@ from swarms.prompts import *  # noqa: E402, F403
 from swarms.structs import *  # noqa: E402, F403
 from swarms.telemetry import *  # noqa: E402, F403
 from swarms.tools import *  # noqa: E402, F403
-from swarms.utils import *  # noqa: E402, F403
+from swarms.utils import *  # noqa: E402, F403

swarms/structs/__init__.py

@@ -155,5 +155,5 @@ __all__ = [
     "pydantic_type_to_yaml_schema",
     "YamlModel",
     "MessagePool",
-    "rearrange"
+    "rearrange",
 ]

swarms/structs/agent.py

@@ -314,11 +314,10 @@ class Agent:
         self.execute_tool = execute_tool
         self.planning = planning
         self.planning_prompt = planning_prompt
-
+        
+        
         # Name
         self.name = agent_name
-
-        # Description
         self.description = agent_description
         # Agentic stuff
         self.reply = ""
@@ -334,14 +333,6 @@ class Agent:
         if self.multi_modal:
             self.sop = MULTI_MODAL_AUTO_AGENT_SYSTEM_PROMPT_1
 
-        # If the user inputs a list of strings for the sop then join them and set the sop
-        if self.sop_list:
-            self.sop = "\n".join(self.sop_list)
-            self.short_memory.add(role=self.user_name, content=self.sop)
-
-        if self.sop is not None:
-            self.short_memory.add(role=self.user_name, content=self.sop)
-
         # Memory
         self.feedback = []
 
@@ -451,7 +442,7 @@ class Agent:
             # Add the tool schema to the short memory
             logger.info("Adding tool schema to short memory")
             self.short_memory.add(
-                role=self.user_name, content=tool_schema_str
+                role=self.user_name, content=tool_schemas
             )
 
         # If the algorithm of thoughts is enabled then set the sop to the algorithm of thoughts
@@ -466,6 +457,15 @@ class Agent:
             logger.info(f"Beginning of Agent {self.agent_name} History")
             logger.info(self.short_memory.return_history_as_string())
             logger.info(f"End of Agent {self.agent_name} History")
+            
+        # If the user inputs a list of strings for the sop then join them and set the sop
+        if self.sop_list:
+            self.sop = "\n".join(self.sop_list)
+            self.short_memory.add(role=self.user_name, content=self.sop)
+
+        if self.sop is not None:
+            self.short_memory.add(role=self.user_name, content=self.sop)
+
 
     def set_system_prompt(self, system_prompt: str):
         """Set the system prompt"""