Added autogen agentics from gaiagraph

app.py

@@ -42,12 +42,53 @@ team = [
 
 
 # Prompt and data flow refinement
-combined_data = f"{user_prompt}\n{generate_synthetic_data(f'Simulate scenarios for {user_prompt}')}"
-
-#  [TONIC PLEASE HELP LOL]
-for agent in team:
-    combined_data = agent.process(combined_data)
-
+message = f"{user_prompt}\n{generate_synthetic_data(f'Simulate scenarios for {user_prompt}')}"
+
+# Agents Group Chat Finite State Machine
+class GroupChatFSM:
+    def __init__(self, teams_config):
+        """
+        Initialize with configurations for teams.
+        """
+        self.teams = {team_name: self.Team(team_agents) for team_name, team_agents in teams_config.items()}
+        self.states = ["waiting", "interacting", "finalizing"]
+        self.current_state = "waiting"
+
+    def transition(self, to_state):
+        """
+        Transition the state of the group chat based on FSM rules.
+        """
+        if to_state in self.states:
+            self.current_state = to_state
+        else:
+            raise ValueError("Invalid state transition attempted.")
+
+    def broadcast(self, message):
+        """
+        Broadcast a message to all teams based on the current FSM state.
+        """
+        if self.current_state == "interacting":
+            responses = {team_name: team.broadcast(message) for team_name, team in self.teams.items()}
+            return responses
+        else:
+            return "The group chat is not in an interacting state."
+
+    class Team:
+        def __init__(self, agents_config):
+            self.agents = [self.Agent(agent_config) for agent_config in agents_config]
+
+        def broadcast(self, message):
+            responses = [agent.respond(message) for agent in self.agents]
+            return responses
+
+        class Agent:
+            def __init__(self, config):
+                self.agent_name = config['agent_name']
+                self.api_key = config['api_key']
+                self.model = config['model']
+
+            def respond(self, message):
+                return f"{self.agent_name} responding with {self.model}"
 
 # Multimedia output production (using Langchain's Text-Davinci-003 as default) because I don't know how to implement DSPy properly yet  [TONIC PLEASE HELP LOL]
 def produce_outputs(processed_data):