example2

example2.py

@@ -0,0 +1,34 @@
+from typing import List
+from swarms import Worker
+
+class MultiAgentDebate:
+    def __init__(self, agents: List[Worker]):
+        self.agents = agents
+
+    def run(self, task: str):
+        results = []
+        for agent in self.agents:
+            response = agent.run(task)
+            results.append({
+                'agent': agent.ai_name,
+                'response': response
+            })
+        return results
+
+# Initialize agents
+agents = [
+    Worker(openai_api_key="", ai_name="Optimus Prime"),
+    Worker(openai_api_key="", ai_name="Bumblebee"),
+    Worker(openai_api_key="", ai_name="Megatron")
+]
+
+# Initialize multi-agent debate
+debate = MultiAgentDebate(agents)
+
+# Run task
+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."
+results = debate.run(task)
+
+# Print results
+for result in results:
+    print(f"Agent {result['agent']} responded: {result['response']}")

swarms/swarms/dialogue_simulator.py

@@ -21,9 +21,12 @@ class DialogueSimulator:
         while step < max_iters:
             speaker_idx = step % len(self.agents)
             speaker = self.agents[speaker_idx]
-            speaker_message = speaker.run()
+            speaker_message = speaker.run(prompt)
+
             for receiver in self.agents:
-                receiver.receive(speaker.name, speaker_message)
+                message_history = f"Speaker Name: {speaker.name} and message: {speake_message}"
+                receiver.run(message_history)
+
             print(f"({speaker.name}): {speaker_message}")
             print("\n")
             step += 1

swarms/swarms/multi_agent_debate.py

@@ -0,0 +1,34 @@
+from typing import List
+from swarms import Worker
+
+class MultiAgentDebate:
+    def __init__(self, agents: List[Worker]):
+        self.agents = agents
+
+    def run(self, task: str):
+        results = []
+        for agent in self.agents:
+            response = agent.run(task)
+            results.append({
+                'agent': agent.ai_name,
+                'response': response
+            })
+        return results
+
+# Initialize agents
+agents = [
+    Worker(openai_api_key="", ai_name="Optimus Prime"),
+    Worker(openai_api_key="", ai_name="Bumblebee"),
+    Worker(openai_api_key="", ai_name="Megatron")
+]
+
+# Initialize multi-agent debate
+debate = MultiAgentDebate(agents)
+
+# Run task
+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."
+results = debate.run(task)
+
+# Print results
+for result in results:
+    print(f"Agent {result['agent']} responded: {result['response']}")