too much

living_agents/roleplay_system.py

@@ -0,0 +1,91 @@
+from typing import List, Dict, Literal
+from living_agents import LLMAgent, Character, CharacterAgent, Memory
+import logging
+from datetime import datetime, timedelta
+
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.DEBUG)
+
+
+class RoleplaySystem:
+    agents: Dict[Character, CharacterAgent]
+    global_time: datetime
+    scene_state: Dict
+
+    def __init__(self):
+        self.agents = {}
+        self.global_time = datetime.now()
+        self.scene_state = {
+            "location": "cozy coffee shop",
+            "time": "afternoon",
+            "atmosphere": "quiet and peaceful",
+            "active_conversations": [],
+            "events": []
+        }
+
+    async def setup_characters(self, characters: List[Character]):
+        logger.info('Setting up Characters.')
+
+        for character in characters:
+            self.agents[character] = CharacterAgent(character, LLMAgent(temperature=0.9))
+            await self.agents[character].initialize_memories()
+
+    async def get_character_response(self, character: Character, user_input: str) -> str:
+
+        print(f"🧠 {character} accessing memories...")
+
+        # Agent perceives user interaction
+        await self.agents[character].perceive(f"Someone asked me: '{user_input}'")
+
+        # Generate response
+        response = await self.agents[character].react_to_situation(user_input)
+        return response
+
+    async def character_chat(self, character_1: Character, character_2: Character, context: str) -> str:
+        """Make two characters interact with each other"""
+        interaction = await self.character_interaction(character_1, character_2, context)
+
+        result = f"\n💬 **{character_1}**: {interaction[character_1]}\n💬 **{character_2}**: {interaction[character_2]}\n"
+        return result
+
+    async def advance_time(self, hours: int = 1):
+        """Advance scene time and trigger agent planning"""
+        self.global_time += timedelta(hours=hours)
+        self.scene_state["time"] = self.global_time.strftime("%I:%M %p")
+
+        # Each agent plans their next actions
+        for character, agent in self.agents.items():
+            await agent.perceive(f"Time is now {self.scene_state['time']}")
+
+    def get_character_memories(self, character: Character, memory_type: Literal['all', 'observation', 'reflection', 'plan'] = "all") -> List[Memory]:
+        return self.agents[character].memory_stream.memories
+
+    async def get_character_summary(self, character: Character) -> str:
+        """Get AI-generated summary of character based on their memories"""
+
+        summary = await self.agents[character].get_summary()
+
+        return f"\n📝 Current summary of {character}:\n{summary}\n"
+
+    async def character_interaction(self, character_1: Character, character_2: Character, context: str) -> Dict[Character, str]:
+        """Handle interaction between two characters"""
+
+        char1_agent = self.agents[character_1]
+        char2_agent = self.agents[character_2]
+
+        # Both characters observe the interaction context
+        await char1_agent.perceive(f"Interacting with {character_2}: {context}")
+        await char2_agent.perceive(f"Interacting with {character_1}: {context}")
+
+        # Generate responses
+        char1_response = await char1_agent.react_to_situation(f"You are talking with {character_2}. Context: {context}")
+        char2_response = await char2_agent.react_to_situation(f"{character_1} said: '{char1_response}'")
+
+        # Both remember the conversation
+        await char1_agent.perceive(f"Conversation with {character_2}: I said '{char1_response}', they replied '{char2_response}'")
+        await char2_agent.perceive(f"Conversation with {character_1}: They said '{char1_response}', I replied '{char2_response}'")
+
+        return {
+            character_1: char1_response,
+            character_2: char2_response
+        }