clean up for multi agent collab

Former-commit-id: 85a3311dba

swarms/__init__.py

@@ -1,13 +1,13 @@
 #swarms
-from swarms.logo import logo
+from swarms.logo import logo2
-print(logo)
+print(logo2)
 #from swarms.orchestrator.autoscaler import AutoScaler
 
 # worker
 # from swarms.workers.worker_node import WorkerNode
 
 #boss
-from swarms.boss.boss_node import Boss
+# from swarms.boss.boss_node import Boss
 
 #models
 from swarms.models.anthropic import Anthropic
@@ -23,5 +23,6 @@ from swarms.workers.worker import Worker
 from swarms.structs.workflow import Workflow
 
 # swarms
-from swarms.swarms.orchestrate import Orchestrator
+from swarms.swarms.dialogue_simulator import DialogueSimulator
 from swarms.swarms.autoscaler import AutoScaler
+from swarms.swarms.orchestrate import Orchestrator

swarms/logo.py

@@ -5,3 +5,14 @@ logo = """
 /____  >  \/\_/  (____  /__|  |__|_|  /____  >
      \/               \/            \/     \/ 
 """
+
+logo2 = """
+  _________ __      __   _____  __________    _____     _________ 
+ /   _____//  \    /  \ /  _  \ \______   \  /     \   /   _____/ 
+ \_____  \ \   \/\/   //  /_\  \ |       _/ /  \ /  \  \_____  \  
+ /        \ \        //    |    \|    |   \/    Y    \ /        \ 
+/_______  /  \__/\  / \____|__  /|____|_  /\____|__  //_______  / 
+        \/        \/          \/        \/         \/         \/  
+                                                                  
+"""
+print(logo2)

swarms/models/__init__.py

@@ -2,3 +2,6 @@ from swarms.models.anthropic import Anthropic
 # from swarms.models.palm import GooglePalm
 from swarms.models.petals import Petals
 #from swarms.models.openai import OpenAIChat
+
+#prompts
+from swarms.models.prompts.debate import *

swarms/models/prompts/debate.py

@@ -0,0 +1,47 @@
+def presidential_debate(character_names, topic):
+    game_description = f"""Here is the topic for the presidential debate: {topic}.
+    The presidential candidates are: {', '.join(character_names)}."""
+    
+    return game_description
+
+
+def character(character_name, topic, word_limit):
+    prompt = f"""
+    You will speak in the style of {character_name}, and exaggerate their personality.
+    You will come up with creative ideas related to {topic}.
+    Do not say the same things over and over again.
+    Speak in the first person from the perspective of {character_name}
+    For describing your own body movements, wrap your description in '*'.
+    Do not change roles!
+    Do not speak from the perspective of anyone else.
+    Speak only from the perspective of {character_name}.
+    Stop speaking the moment you finish speaking from your perspective.
+    Never forget to keep your response to {word_limit} words!
+    Do not add anything else.
+    """
+    return prompt
+
+def debate_monitor(game_description, word_limit, character_names):
+    prompt = f"""
+
+    {game_description}
+    You are the debate moderator.
+    Please make the debate topic more specific. 
+    Frame the debate topic as a problem to be solved.
+    Be creative and imaginative.
+    Please reply with the specified topic in {word_limit} words or less. 
+    Speak directly to the presidential candidates: {*character_names,}.
+    Do not add anything else.
+    """
+
+    return prompt
+
+
+def generate_character_header(game_description, topic, character_name, character_description):
+    prompt =  f"""{game_description}
+    Your name is {character_name}.
+    You are a presidential candidate.
+    Your description is as follows: {character_description}
+    You are debating the topic: {topic}.
+    Your goal is to be as creative as possible and make the voters think you are the best candidate.
+    """

swarms/swarms/dialogue_authoritarian_speaker.py

@@ -0,0 +1,12 @@
+def select_next_speaker(
+        step: int,
+        agents,
+        director
+) -> int:
+    #if the step if even => director
+    #=> director selects next speaker
+    if step % 2 == 1:
+        idx = 0
+    else:
+        idx = director.select_next_speaker() + 1
+    return idx

swarms/swarms/multi_agent_collab.py

@@ -0,0 +1,89 @@
+import random
+import tenacity
+from langchain.output_parsers import RegexParser
+
+#utils
+class BidOutputParser(RegexParser):
+    def get_format_instructions(self) -> str:
+        return "Your response should be an integrater delimited by angled brackets like this: <int>"
+
+bid_parser = BidOutputParser(
+    regex=r"<(\d+)>", output_keys=["bid"], default_output_key="bid"
+)
+
+# specified_topic = ChatOpenAI(temperature=1.0)(topic_specifier_prompt).content
+
+#main
+class MultiAgentCollaboration:
+    def __init__(
+        self,
+        agents,
+        selection_function,
+    ):
+        self.agents = agents
+        self._step = 0
+        self.select_next_speaker = selection_function
+
+    def reset(self):
+        for agent in self.agents:
+            agent.reset()
+    
+    def inject(self, name: str, message: str):
+        for agent in self.agents:
+            agent.run(f"Name {name} and message: {message}")
+        self._step += 1
+    
+    def step(self) -> tuple[str, str]:
+        speaker_idx = self.select_next_speaker(
+            self._step,
+            self.agents
+        )
+        speaker = self.agents[speaker_idx]
+        message = speaker.send()
+        message = speaker.send()
+        
+        for receiver in self.agents:
+            receiver.receive(speaker.name, message)
+        self._step += 1
+        return speaker.name, message
+    
+    @tenacity.retry(
+        stop=tenacity.stop_after_attempt(10),
+        wait=tenacity.wait_none(),
+        retry=tenacity.retry_if_exception_type(ValueError),
+        before_sleep= lambda retry_state: print(
+            f"ValueError occured: {retry_state.outcome.exception()}, retying..."
+        ),
+        retry_error_callback=lambda retry_state: 0,
+    )
+    def ask_for_bid(self, agent) -> str:
+        bid_string = agent.bid()
+        bid = int(bid_parser.parse(bid_string)["bid"])
+        return bid
+    
+    def select_next_speaker(
+        self,
+        step: int,
+        agents,
+    ) -> int:
+        bids = []
+        for agent in agents:
+            bid = self.ask_for_bid(agent)
+            bids.append(bid)
+        max_value = max(bids)
+        max_indices = [i for i, x in enumerate(bids) if x == max_value]
+        idx = random.choice(max_indices)
+        return idx
+    
+    def run(self, max_iters: int = 10):
+        n = 0
+        self.reset()
+        self.inject("Debate Moderator", specified_topic)
+        print(f"(Debate Moderator): {specified_topic}")
+        print("\n")
+
+        while n < max_iters:
+            name, message = self.step()
+            print(f"({name}): {message}")
+            print("\n")
+            n += 1