too much

character_explorer.py

@@ -1,6 +1,9 @@
 import asyncio
 import os
+import pickle
 from pprint import pprint
+from datetime import datetime
+from typing import Optional, List
 
 import yaml
 from pathlib import Path
@@ -8,14 +11,102 @@ from dotenv import load_dotenv
 from living_agents import CharacterAgent, PromptManager
 import logging
 
+from llm_connector import LLMMessage
+
 logger = logging.getLogger(__name__)
 
 
+def save_character_to_cache(agent: CharacterAgent, template_path: Path):
+    """Save a character agent to cache"""
+    cache_path = Path('.cache') / f"{template_path.stem}.pkl"
+
+    try:
+        # Create cache data with metadata
+        cache_data = {
+            'character': agent.character,
+            'memories': agent.memory_stream.memories,
+            'template_path': template_path,
+            'cached_at': datetime.now(),
+            'cache_version': '1.0'
+        }
+
+        with open(cache_path, 'wb') as f:
+            pickle.dump(cache_data, f)
+
+        print(f"💾 Character saved to cache: {cache_path.name}")
+
+    except Exception as e:
+        print(f"⚠️ Warning: Could not save character to cache: {e}")
+
+
+def load_character_from_cache(template_path: Path) -> Optional[CharacterAgent]:
+    """Load a character agent from cache, return None if not found or invalid"""
+    cache_path = Path('.cache') / f"{template_path.stem}.pkl"
+
+    if not cache_path.exists():
+        return None
+
+    try:
+        with open(cache_path, 'rb') as f:
+            cache_data = pickle.load(f)
+
+        # Verify cache data structure
+        required_keys = ['character', 'memories', 'template_path', 'cached_at']
+        if not all(key in cache_data for key in required_keys):
+            print(f"⚠️ Invalid cache file format: {cache_path.name}")
+            return None
+
+        # Check if template file is newer than cache
+        template_mtime = Path(template_path).stat().st_mtime
+        cache_time = cache_data['cached_at'].timestamp()
+
+        if template_mtime > cache_time:
+            print(f"📝 Template file is newer than cache, will recreate character")
+            return None
+
+        # Reconstruct CharacterAgent
+        from living_agents import LLMAgent
+        agent = CharacterAgent(cache_data['character'], LLMAgent())
+        agent.memory_stream.memories = cache_data['memories']
+
+        cached_date = cache_data['cached_at'].strftime('%Y-%m-%d %H:%M:%S')
+        print(f"💾 Loaded character from cache (created: {cached_date})")
+
+        return agent
+
+    except Exception as e:
+        print(f"⚠️ Could not load character from cache: {e}")
+        return None
+
+
+def get_cache_info(template_path: Path) -> Optional[dict]:
+    """Get information about cached character"""
+    cache_path = Path('.cache') / f"{template_path.stem}.pkl"
+
+    if not cache_path.exists():
+        return None
+
+    try:
+        with open(cache_path, 'rb') as f:
+            cache_data = pickle.load(f)
+
+        return {
+            'cache_file': cache_path.name,
+            'cached_at': cache_data['cached_at'],
+            'character_name': cache_data['character'].name,
+            'memory_count': len(cache_data['memories'])
+        }
+    except:
+        return None
+
+
 class CharacterExplorer:
     """Interactive explorer for testing CharacterAgent functionality"""
+    chat_history: List[LLMMessage]
 
     def __init__(self, character_agent: CharacterAgent):
         self.agent = character_agent
+        self.chat_history = []
 
     async def start_interactive_session(self):
         """Start the interactive exploration menu"""
@@ -27,23 +118,29 @@ class CharacterExplorer:
             self._show_menu()
 
             try:
-                choice = input("\nChoose option (1-6): ").strip()
+                choice = input("\nChoose option (1-8): ").strip()
 
                 if choice == "1":
                     await self._handle_ask_question()
-                elif choice == "2":
-                    await self._handle_list_memories()
+                if choice == "2":
+                    await self._handle_chat()
                 elif choice == "3":
-                    await self._handle_view_memory()
+                    await self._handle_list_memories()
                 elif choice == "4":
-                    await self._handle_memory_stats()
+                    await self._handle_view_memory()
                 elif choice == "5":
-                    await self._handle_character_summary()
+                    await self._handle_memory_stats()
                 elif choice == "6":
+                    await self._handle_character_summary()
+                elif choice == "7":
+                    # Regenerate character
+                    if await self._handle_regenerate_character():
+                        break  # Exit to main menu after regeneration
+                elif choice == "8":
                     print("👋 Goodbye!")
                     break
                 else:
-                    print("❌ Invalid choice. Please enter 1-6.")
+                    print("❌ Invalid choice. Please enter 1-8.")
 
             except KeyboardInterrupt:
                 print("\n👋 Goodbye!")
@@ -51,16 +148,31 @@ class CharacterExplorer:
             except Exception as e:
                 print(f"❌ Error: {e}")
 
+    def clear_character_cache(self) -> bool:
+        """Clear cached character for a template"""
+        cache_file = Path('.cache') / f"{self.agent.character.template_file.stem}.pkl"
+
+        if cache_file.exists():
+            try:
+                cache_file.unlink()
+                return True
+            except Exception as e:
+                print(f"❌ Could not clear cache: {e}")
+                return False
+        return False
+
     def _show_menu(self):
         """Display the interactive menu options"""
         print(f"\n🎭 Character Explorer Menu")
         print("=" * 30)
-        print("1. 💬 Ask a question")
-        print("2. 📚 List all memories")
-        print("3. 🔍 View specific memory (with related)")
-        print("4. 📊 Memory statistics")
-        print("5. 👤 Character summary")
-        print("6. 🚪 Exit")
+        print(f"1. 💬 Ask {self.agent.character.name} a question")
+        print(f"2. 💬 Chat with {self.agent.character.name}")
+        print("3. 📚 List all memories")
+        print("4. 🔍 View specific memory (with related)")
+        print("5. 📊 Memory statistics")
+        print("6. 👤 Character summary")
+        print("7. 🔄 Regenerate character")
+        print("8. 🚪 Exit")
 
     async def _handle_ask_question(self):
         """Handle asking questions to the character"""
@@ -82,6 +194,33 @@ class CharacterExplorer:
         except Exception as e:
             print(f"❌ Error getting response: {e}")
 
+    async def _handle_chat(self):
+        """Handle chat with a  character"""
+        if not self.chat_history:
+            scenario_content = input(f"\n💬 Set a scenario for a new chat with {self.agent.character.name}: ").strip()
+            if not scenario_content:
+                return
+
+            self.chat_history.append({'role': 'system', 'content': scenario_content})
+
+        scenario_content = input(f"\n💬 Ask {self.agent.character.name}: ").strip()
+        if not scenario_content:
+            return
+
+        print(f"\n🤔 {self.agent.character.name} is thinking...")
+        try:
+            response = await self.agent.react_to_situation(scenario_content)
+            print(f"💬 {self.agent.character.name}: {response}")
+
+            # Show which memories were retrieved for this response
+            relevant_memories = await self.agent.memory_stream.retrieve_related_memories(scenario_content, k=5)
+            print(f"\n🧠 Memories used for this response:")
+            for i, mem in enumerate(relevant_memories, 1):
+                print(f"   {i}. [{mem.memory_type}] {mem.description[:80]}{'...' if len(mem.description) > 80 else ''}")
+
+        except Exception as e:
+            print(f"❌ Error getting response: {e}")
+
     async def _handle_list_memories(self):
         """List all memories with filtering options"""
         print("\n📚 Memory Filter Options:")
@@ -204,6 +343,7 @@ class CharacterExplorer:
             print(f"   Occupation: {self.agent.character.occupation}")
             print(f"   Location: {self.agent.character.location}")
             print("")
+            print(f"      - File: {self.agent.character.template_file}")
             print(f"   Traits")
             traits_summary = "\n".join([f"   - {trait.strength}/10 {trait.name} ({trait.description})" for trait in self.agent.character.traits]) if self.agent.character.traits else "No traits yet."
             print(traits_summary)
@@ -220,47 +360,150 @@ class CharacterExplorer:
         except Exception as e:
             print(f"❌ Error generating summary: {e}")
 
+    async def _handle_regenerate_character(self) -> bool:
+        """Handle regenerating the current character"""
+        character_name = self.agent.character.name
 
-async def load_and_explore_character(template_path: str):
+        print(f"\n🔄 Regenerate {character_name}")
+        print("This will clear the cache and recreate the character from scratch.")
+        print("All current memories and traits will be lost!")
+
+        # Confirm regeneration
+        confirm = input(f"Regenerate {character_name}? (y/N): ").strip().lower()
+        if confirm not in ['y', 'yes']:
+            print("❌ Regeneration cancelled")
+            return False
+
+        template_file = self.agent.character.template_file
+        if self.agent.character.template_file is None:
+            print(f"❌ Could not find template file for {character_name}")
+            return False
+
+        # Clear the cache
+        if self.clear_character_cache():
+            print(f"🗑️  Cleared cache for {character_name}")
+        else:
+            print("❌ Failed to clear cache")
+            return False
+
+        await load_and_explore_character(template_file)
+        return True
+
+
+def select_character_template(show_cache_info: bool = True) -> Path:
+    """Show character template selection menu and return chosen template path"""
+
+    templates_dir = Path(__file__).parent / 'character_templates'
+
+    # Find all .yml files in the character_templates directory
+    template_files = list(templates_dir.glob('*.yml'))
+
+    if not template_files:
+        print("❌ No character templates found in character_templates/")
+        return None
+
+    print("\n🎭 Available Character Templates:")
+    print("=" * 60)
+
+    # Display template options with cache info
+    for i, template_file in enumerate(template_files, 1):
+        # Try to load the template to get the name
+        try:
+            with open(template_file, 'r', encoding='utf-8') as f:
+                template_data = yaml.safe_load(f)
+                character_name = template_data.get('name', template_file.stem)
+        except:
+            character_name = template_file.stem
+
+        # Check for cached version if requested
+        if show_cache_info:
+            cache_info = get_cache_info(template_file)
+            if cache_info:
+                cache_status = f"💾 (cached {cache_info['cached_at'].strftime('%m/%d %H:%M')})"
+            else:
+                cache_status = "🔄 (will create new)"
+            print(f"{i}. {character_name} ({template_file.name}) {cache_status}")
+        else:
+            print(f"{i}. {character_name} ({template_file.name})")
+
+    print(f"{len(template_files) + 1}. 🚪 Exit")
+
+    # Get user choice
+    while True:
+        try:
+            choice = input(f"\nChoose a character template (1-{len(template_files) + 1}): ").strip()
+            choice_num = int(choice)
+
+            if choice_num == len(template_files) + 1:
+                return None  # Exit choice
+            elif 1 <= choice_num <= len(template_files):
+                return template_files[choice_num - 1]
+            else:
+                print(f"❌ Invalid choice. Please enter 1-{len(template_files) + 1}.")
+        except ValueError:
+            print(f"❌ Please enter a valid number (1-{len(template_files) + 1}).")
+        except KeyboardInterrupt:
+            return None
+
+
+async def load_and_explore_character(template_path: Path):
     """Load a character template and start exploration"""
 
     # Load environment
-    # env_path = Path(__file__).parent.parent / '.env'
     load_dotenv()
 
-    # Load template
-    if not Path(template_path).exists():
-        print(f"❌ Template file not found: {template_path}")
-        return None
+    # Try to load from cache first
+    print(f"📁 Loading character from {template_path.name}...")
+    agent = load_character_from_cache(template_path)
 
-    try:
-        with open(template_path, 'r', encoding='utf-8') as f:
-            template = yaml.safe_load(f)
-    except Exception as e:
-        print(f"❌ Error loading template: {e}")
-        return None
+    if agent is None:
+        # No cache or cache invalid, create from template
+        try:
+            with open(template_path, 'r', encoding='utf-8') as f:
+                template = yaml.safe_load(f)
+                template['yaml_file'] = template_path
+        except Exception as e:
+            print(f"❌ Error loading template: {e}")
+            return None
 
-    print(f"📁 Loading character from {template_path}...")
-    print(f"🤖 Creating memories and scoring importance...")
+        print(f"🤖 Creating memories and scoring importance...")
 
-    try:
-        # Create character agent
-        agent = await CharacterAgent.create_from_template(template)
+        try:
+            # Create character agent from template
+            agent = await CharacterAgent.create_from_template(template)
+            print(f"✅ {agent.character.name} created successfully!")
+
+            # Save to cache for next time
+            save_character_to_cache(agent, template_path)
+
+        except Exception as e:
+            print(f"❌ Error creating character: {e}")
+            import traceback
+            traceback.print_exc()
+            return None
+    else:
         print(f"✅ {agent.character.name} loaded successfully!")
 
-        # Start explorer
-        explorer = CharacterExplorer(agent)
-        await explorer.start_interactive_session()
+    # Start explorer
+    explorer = CharacterExplorer(agent)
+    await explorer.start_interactive_session()
 
-        return agent
+    return agent
 
-    except Exception as e:
-        print(f"❌ Error creating character: {e}")
-        import traceback
-        traceback.print_exc()
-        return None
+
+async def main():
+    """Main function with character selection"""
+    print("🎭 Welcome to the Living Agents Character Explorer!")
+
+    selected_template = select_character_template(show_cache_info=True)
+
+    if selected_template is None:
+        print("👋 Goodbye!")
+        return
+
+    # Load and explore the selected character
+    await load_and_explore_character(selected_template)
 
 
 if __name__ == '__main__':
-    template = Path(__file__).parent / 'character_templates' / 'Alice.yml'
-    asyncio.run(load_and_explore_character(str(template)))
+    asyncio.run(main())

living_agents/character_agent.py

@@ -71,6 +71,33 @@ class CharacterAgent:
 
         return response
 
+    async def chat_with(self, messages: List[LLMMessage]) -> LLMMessage:
+        """Generate reaction based on memory and character"""
+        # Retrieve relevant memories
+        relevant_memories = await self.memory_stream.retrieve_related_memories(situation, k=8)
+        memory_context = "\n".join([f"- {m.description}" for m in relevant_memories])
+
+        context = {
+            'character': self._get_character_prompt(),
+            'character_name': self.character.name,
+            'memory_context': memory_context,
+            'situation': situation}
+        prompt = PromptManager.get_prompt('react_to_situation', context)
+
+        response = await self.llm.chat([{"role": "user", "content": prompt}])
+
+        # create new memories from interaction
+        interaction_context = {
+            'situation': f'I reacted to: \n{situation}',
+            'response': f'My response was: \n{response}',
+        }
+        prompt, schema = PromptManager.get_prompt_with_schema('extract_interaction_memories', interaction_context)
+        memories_response = await self.llm.client.get_structured_response([{"role": "user", "content": prompt}], schema)
+        for new_memory in memories_response['memories']:
+            await self.perceive(new_memory)
+
+        return response
+
     async def plan_day(self) -> List[str]:
         """Generate high-level daily plan"""
         # Retrieve relevant memories about goals, habits, schedule
@@ -255,5 +282,7 @@ Summary:"""
             memory.importance_score = await instance._score_memory_importance(memory)
             await instance._analyze_trait_impact(memory)
 
+        instance.character.template_file = template['yaml_file']
+
         logger.info(f"Character {instance.character.name} created successfully")
         return instance

living_agents/datatypes.py

@@ -2,7 +2,7 @@ from dataclasses import dataclass, field
 from typing import Dict, List, Optional, Literal, TypedDict
 from datetime import datetime
 from uuid import uuid4
-import random
+from pathlib import Path
 
 
 class CharacterTemplate(TypedDict):
@@ -10,7 +10,7 @@ class CharacterTemplate(TypedDict):
     observations: List[str]
     reflections: List[str]
     plans: List[str]
-    yaml_file: str
+    yaml_file: Path
 
 
 @dataclass
@@ -72,6 +72,7 @@ class Character:
     traits: List[CharacterTrait] = field(default_factory=list)
     relationships: Dict[str, str] = field(default_factory=dict)
     goals: List[str] = field(default_factory=list)
+    template_file: Optional[Path] = None
     _id: str = field(default_factory=lambda: str(uuid4())[:8])
 
     def get_trait(self, trait_name, trait_description) -> CharacterTrait:

living_agents/memory_stream.py

@@ -41,7 +41,6 @@ class MemoryStream:
 
         # Track for reflection trigger
         self.recent_importance_sum += memory.importance_score
-        print(f"Recent Importance Sum: {self.recent_importance_sum}")
 
         # Trigger reflection if threshold exceeded
         if self.recent_importance_sum >= self.importance_threshold:

living_agents/prompts/chat_with_agent.md

@@ -0,0 +1,15 @@
+{{character}}
+
+Relevant memories from your past:
+{{memory_context}}
+
+Respond as {{character_name}} describing what you did and how you reacted. Write in first person past tense as if this
+just happened to you.
+
+Examples of the response style:
+
+- "I looked up from my book and smiled nervously..."
+- "I felt my heart race and took a deep breath before I said..."
+- "I hesitated for a moment, then decided to..."
+
+Stay completely in character and be specific about your actions, thoughts, and words.