[6.7.9]

api/main.py

@@ -2,7 +2,6 @@
 import os
 import secrets
 import signal
-import sys
 import traceback
 from concurrent.futures import ThreadPoolExecutor
 from datetime import datetime, timedelta
@@ -974,7 +973,7 @@ def run_server():
         asyncio.run(server.startup())
     except Exception as e:
         logger.error(f"Failed to start API: {str(e)}")
-        print(f"Error starting server: {str(e)}"
+        print(f"Error starting server: {str(e)}")
 
 
 if __name__ == "__main__":

group_chat_example.py

@@ -1,7 +1,7 @@
 import os
 from dotenv import load_dotenv
 from swarm_models import OpenAIChat
-from swarms import Agent, GroupChat, expertise_based
+from swarms import Agent, GroupChat
 
 
 if __name__ == "__main__":
@@ -61,7 +61,6 @@
         name="Investment Advisory",
         description="Financial, tax, and stock analysis group",
         agents=agents,
-        speaker_fn=expertise_based,
     )
 
     history = chat.run(

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "swarms"
-version = "6.7.8"
+version = "6.7.9"
 description = "Swarms - TGSC"
 license = "MIT"
 authors = ["Kye Gomez <[email protected]>"]

swarms/structs/groupchat.py

@@ -65,6 +65,40 @@ def random_selection(history: List[str], agent: Agent) -> bool:
     return random.choice([True, False])
 
 
+def custom_speaker(history: List[str], agent: Agent) -> bool:
+    """
+    Custom speaker function with complex logic.
+
+    Args:
+        history: Previous conversation messages
+        agent: Current agent being evaluated
+
+    Returns:
+        bool: Whether agent should speak
+    """
+    # No history - let everyone speak
+    if not history:
+        return True
+
+    last_message = history[-1].lower()
+
+    # Check for agent expertise keywords
+    expertise_relevant = any(
+        keyword in last_message
+        for keyword in agent.description.lower().split()
+    )
+
+    # Check for direct mentions
+    mentioned = agent.agent_name.lower() in last_message
+
+    # Check if agent hasn't spoken recently
+    not_recent_speaker = not any(
+        agent.agent_name in msg for msg in history[-3:]
+    )
+
+    return expertise_relevant or mentioned or not_recent_speaker
+
+
 def most_recent(history: List[str], agent: Agent) -> bool:
     """
     Most recent speaker function.
@@ -128,9 +162,14 @@ def _get_response_sync(
             AgentResponse: The agent's response captured in a structured format.
         """
         try:
-            context = f"""You are {agent.name} with role: {agent.system_prompt}.
-                         Other agents: {[a.name for a in self.agents if a != agent]}
-                         Previous messages: {[t.responses[-3:] for t in self.chat_history.turns[-3:]]}"""
+            # Provide the agent with information about the chat and other agents
+            chat_info = f"Chat Name: {self.name}\nChat Description: {self.description}\nAgents in Chat: {[a.agent_name for a in self.agents]}"
+            context = f"""You are {agent.agent_name} 
+                        Conversation History: 
+                        \n{chat_info}
+                        Other agents: {[a.agent_name for a in self.agents if a != agent]}
+                        Previous messages: {self.get_full_chat_history()}
+            """  # Updated line
 
             message = agent.run(context + prompt)
             return AgentResponse(
@@ -150,6 +189,21 @@ def _get_response_sync(
                 preceding_context=[],
             )
 
+    def get_full_chat_history(self) -> str:
+        """
+        Get the full chat history formatted for agent context.
+
+        Returns:
+            str: The full chat history with sender names.
+        """
+        messages = []
+        for turn in self.chat_history.turns:
+            for response in turn.responses:
+                messages.append(
+                    f"{response.agent_name}: {response.message}"
+                )
+        return "\n".join(messages)
+
     def get_recent_messages(self, n: int = 3) -> List[str]:
         """
         Get the most recent messages in the chat.

swarms/structs/swarm_builder.py

@@ -2,6 +2,7 @@
 import subprocess
 from typing import List, Optional
 
+from loguru import logger
 from pydantic import BaseModel, Field
 from pydantic.v1 import validator
 from swarm_models import OpenAIChat
@@ -13,7 +14,6 @@
 
 from swarms.structs.agent import Agent
 from swarms.structs.swarm_router import SwarmRouter, SwarmType
-from loguru import logger
 
 logger.add("swarm_builder.log", rotation="10 MB", backtrace=True)
 
@@ -507,7 +507,10 @@ def swarm_router(
     swarm_type="ConcurrentWorkflow",
 )
 
-result = swarm.run(
-    "Design a new AI accelerator chip optimized for transformer model inference..."
-)
-print(result)
+try:
+    result = swarm.run(
+        "Design a new AI accelerator chip optimized for transformer model inference..."
+    )
+    print(result)
+except Exception as e:
+    print(f"An error occurred: {e}")