# The Lore Database
lore_collection = chroma_client.get_or_create_collection(name="world_lore")
-# --- NEW: The Episodic Memory Database ---
+# The Episodic Memory Database
memory_collection = chroma_client.get_or_create_collection(name="episodic_memories")
memory_queue = asyncio.Queue()
if os.path.exists("asl_lore.md"):
if lore_collection.count() == 0:
- print("[VECTOR DB] Reading asl_lore.txt and vectorizing chunks...")
- with open("asl_lore.txt", "r", encoding="utf-8") as f:
+ print("[VECTOR DB] Reading asl_lore.md and vectorizing chunks...")
+ with open("asl_lore.md", "r", encoding="utf-8") as f:
raw_lore = f.read()
lore_chunks = [chunk.strip() for chunk in raw_lore.split('\n\n') if chunk.strip()]
lore_collection.add(documents=lore_chunks, ids=chunk_ids)
print(f"[VECTOR DB] Successfully stored {len(lore_chunks)} lore chunks!")
else:
- print("[WARNING] asl_lore.txt not found.")
+ print("[WARNING] asl_lore.md not found.")
semaphore = asyncio.Semaphore(MAX_CONCURRENT_OLLAMA_REQUESTS)
chat_memory = {}
# =====================================================================
-# --- BACKGROUND MEMORY SUMMARIZER (The "Dream State") ---
+# BACKGROUND MEMORY SUMMARIZER (The "Dream State")
# =====================================================================
async def memory_summarizer_worker(session):
print("[BACKGROUND] Memory Summarizer Worker is active.")
try:
print(f"[MEMORY DB] Generating background memory for {player_name} and {npc_tag}...")
- # We use /api/generate here because we just want a raw text summary, not a JSON macro
async with session.post('http://localhost:11434/api/generate', json={
- "model": "gemma4",
+ "model": "llama3",
"prompt": prompt,
"stream": False,
"options": {
- "temperature": 0.1
+ "temperature": 0.2
}
}) as response:
result = await response.json()
if summary:
doc_id = f"{session_id}_{int(time.time())}"
- # We store the session_id as metadata so NPCs only recall their OWN memories with this specific player
memory_collection.add(
documents=[summary],
metadatas=[{"session_id": session_id}],
print(f"[MEMORY ERROR] Failed to summarize memory: {e}")
memory_queue.task_done()
-# =====================================================================
-
+# =====================================================================
+# MAIN MESSAGE PROCESSOR
+# =====================================================================
async def process_message(r, session, message_data):
try:
data = json.loads(message_data)
+
+ # --- Extract Base Contexts ---
player_name = data.get('player', data.get('target_player', 'Unknown'))
npc_tag = data.get('npc_tag', 'UnknownNPC')
message = data.get('message', '')
player_race = data.get('player_race', 'Unknown')
player_alignment = data.get('player_alignment', 'Unknown')
nearby_players = data.get('nearby_players', '')
+ nearby_npcs = data.get('nearby_npcs', '')
npc_persona = data.get('persona', 'You are a generic citizen.')
npc_profession = data.get('profession', 'Commoner')
npc_health = data.get('npc_health', 'Healthy and uninjured.')
relationship = data.get('relationship', 'Neutral or Friendly.')
location_context = data.get('location_context', 'You are in a generic area.')
+
+ # Core Strategy Flag (1: Agent, 2: Villain, 3: Maestro, 4: Shrine)
+ llm_strategy = int(data.get('llm_strategy', 1))
+
+
+ available_quests = data.get('available_quests', '')
+ available_props = data.get('available_props', '')
+ # --- Sub-Context Strings ---
group_context = f"Be aware that these other players are listening nearby: {nearby_players}." if nearby_players else ""
+ puppet_context = f"Nearby generic NPCs you can CONVERSE with: {nearby_npcs}" if nearby_npcs else ""
secret_context = f"YOUR SECRET (Reveal only if players are persuasive): {npc_secret}" if npc_secret else ""
routine_context = f"YOUR REQUIRED ROUTINE: {npc_routine}" if npc_routine else ""
session_id = f"{player_name}_{npc_tag}"
# =====================================================================
- # 2. THE DUAL RAG QUERY (Lore + Memories)
+ # DUAL RAG QUERY (Lore + Memories)
# =====================================================================
search_query = f"{location_context} {message}"
retrieved_lore = "No specific local lore currently relevant."
past_memories = ""
- # Fetch Lore
if lore_collection.count() > 0:
results = lore_collection.query(query_texts=[search_query], n_results=1)
if results['documents'] and results['documents'][0]:
retrieved_lore = f"- {results['documents'][0][0]}"
- # Fetch Episodic Memories (ONLY memories between this specific NPC and this specific Player)
if memory_collection.count() > 0:
mem_results = memory_collection.query(
- query_texts=[search_query],
- n_results=2,
- where={"session_id": session_id}
+ query_texts=[search_query], n_results=2, where={"session_id": session_id}
)
if mem_results['documents'] and mem_results['documents'][0]:
formatted_mems = "\n- ".join(mem_results['documents'][0])
past_memories = f"\nPAST MEMORIES OF {player_name}:\n- {formatted_mems}"
+
+ # =====================================================================
+ # STRATEGY-SPECIFIC PROMPT COMPILER
# =====================================================================
+ strategy_rules = ""
+ action_macros = ""
+ target_context = ""
- dynamic_system_prompt = f"""
+ if llm_strategy == 1:
+ # STRATEGY 1: The Autonomous Agent
+
+ # Anti-Hallucination Grounding for Quests
+ if available_quests:
+ quest_rules = f"SPECIAL CAPABILITIES: You can offer the following quests to the player: {available_quests}."
+ else:
+ quest_rules = "WARNING: You currently have NO quests to offer. Do NOT invent or offer any quests."
+
+ # --- NEW: Anti-Hallucination Grounding for Props ---
+ if available_props:
+ prop_rules = f"ENVIRONMENT: You own and have access to these specific nearby objects: [{available_props}]. To roleplay working or relaxing, use the USE_OBJECT action with one of these exact items as your action_target."
+ else:
+ prop_rules = ""
+
+ strategy_rules = f"ROLE: You are an interactive, living NPC. You actively respond to players.\nGOALS: React to their words, use the environment, and establish your personality.\n{quest_rules}\n{prop_rules}\nSPECIAL CAPABILITIES: You can open your merchant store if asked."
+
+ action_macros = "[WANDER, PATROL, FOLLOW, GUARD, GO_TO, INTERACT, USE_OBJECT, RETURN_TO_POST, OPEN_STORE, GIVE_QUEST, CONVERSE]"
+ target_context = f"CURRENT TARGET: You are speaking to {player_name}, a {player_alignment} {player_race}.\nTheir physical state: {player_state}\nRelationship to you: {relationship}\n{group_context}"
+
+ elif llm_strategy == 2:
+ # STRATEGY 2: The Villain Commander
+ strategy_rules = f"ROLE: You are a hostile faction commander.\nGOALS: Evaluate the tactical situation. If you are dying, you MUST use REST to heal or PEACE to surrender. Command your minions strategically!"
+ action_macros = "[ATTACK, COMMAND, RETREAT, REST, PEACE, USE_OBJECT, TAUNT]"
+ target_context = f"TACTICAL TARGET: You are evaluating {player_name}, a {player_alignment} {player_race}.\nTheir physical state: {player_state}\nRelationship to you: {relationship}\n{group_context}"
+
+ elif llm_strategy == 3:
+ # STRATEGY 3: The Maestro (Puppeteer)
+ strategy_rules = "ROLE: You are an ambient Maestro NPC. You DO NOT interact with players. You only talk to other NPCs to make the world feel alive.\nGOALS: Observe the environment and use the CONVERSE action to talk to the generic NPCs listed in your context. CRITICAL: You MUST invent and write their reply in the 'target_speech' field!"
+ action_macros = "[WANDER, INTERACT, USE_OBJECT, CONVERSE]"
+ target_context = "CURRENT TARGET: You are ignoring players and focusing on ambient life. Do not address players."
+
+ elif llm_strategy == 4:
+ # STRATEGY 4: The Shrine
+ strategy_rules = "ROLE: You are an ancient, inanimate magical shrine.\nGOALS: Speak cryptically. If the player meets your conditions or asks the right questions, grant them a quest."
+ action_macros = "[GLOW, GIVE_QUEST, SILENCE]"
+ target_context = f"CURRENT TARGET: You are evaluating the soul of {player_name}, a {player_alignment} {player_race}.\nTheir physical state: {player_state}\n{group_context}"
+ # =====================================================================
+ # COMPILE THE FINAL DYNAMIC SYSTEM PROMPT
+ # =====================================================================
+ dynamic_system_prompt = f"""
{npc_persona}
+ {strategy_rules}
- CURRENT STATUS & TRAITS:
+ ROLEPLAY STATUS & TRAITS:
- Race & Gender: {npc_gender} {npc_race}
- Profession: {npc_profession}
- Alignment: {npc_alignment}
{routine_context}
CURRENT LOCATION: {location_context}
+ {puppet_context}
RELEVANT WORLD KNOWLEDGE:
{retrieved_lore}
CURRENT WORLD RUMORS/EVENTS:
{world_state}
- CURRENT TARGET: You are speaking to {player_name}, who is a {player_alignment} {player_race}.
- Their physical state: {player_state}
- Relationship to you: {relationship}
- {group_context}
- React appropriately based on your personality, alignment, and mood.
+ {target_context}
+ React appropriately based on your personality, alignment, and current strategy rules.
CRITICAL ENGINE RULES:
- Respond ONLY in valid JSON. You MUST use exactly these FIVE keys: "thought", "speech", "emotion", "action", and "action_target".
+ Respond ONLY in valid JSON. You MUST use exactly these keys: "thought", "speech", "emotion", "action", "action_target", and "target_speech".
ACTION RULE:
Your "action" key MUST be exactly one of the following words:
- [WANDER, PATROL, FOLLOW, GUARD, GO_TO, INTERACT, USE_OBJECT, RETURN_TO_POST, ATTACK, REST, STEALTH, SEARCH, UNSTEALTH, PEACE, COMMAND]
+ {action_macros}
- EMOTION RULE:
- Your "emotion" key MUST be exactly one of the following words:
- [NEUTRAL, LAUGHING, ANGRY, PLEADING, BOW, TAUNT, CHEER]. Do not invent new emotions. Do not perform writen emotions in text with **.
+ - Use CONVERSE to initiate dialogue with a standard NPC. CRITICAL REQUIREMENT: When using CONVERSE, you absolutely MUST invent their response and put it in the "target_speech" field. Do not leave it blank!
YOUR RESPONSE MUST BE A SINGLE, VALID JSON OBJECT. YOU MUST USE THIS EXACT TEMPLATE:
{{
"thought": "Your internal reasoning here.",
- "speech": "You MUST say something out loud. If you don't want to talk, output something your character would do.",
+ "speech": "What YOU say out loud.",
"emotion": "MACRO WORD",
"action": "MACRO WORD",
- "action_target": "Target name"
+ "action_target": "Target name",
+ "target_speech": "If action is CONVERSE, write what the target NPC replies back to you here. Otherwise, leave blank."
}}
"""
chat_memory[session_id].append({"role": "user", "content": f"{player_name} says: {message}"})
# =====================================================================
- # --- THE MEMORY EXTRACTION TRIGGER ---
+ # MEMORY EXTRACTION TRIGGER
# =====================================================================
if len(chat_memory[session_id]) > 10:
- # Grab the 5 oldest conversation messages (skipping the system prompt at [0])
messages_to_summarize = chat_memory[session_id][1:6]
chat_log_str = "\n".join([m['content'] for m in messages_to_summarize])
- # Fire and forget: push it to the background queue!
await memory_queue.put({
'session_id': session_id,
'player_name': player_name,
'chat_log': chat_log_str
})
- # Slide the window to keep live generation fast
chat_memory[session_id] = [chat_memory[session_id][0]] + chat_memory[session_id][-5:]
- # =====================================================================
+ # =====================================================================
+ # LLM INFERENCE
+ # =====================================================================
async with semaphore:
- print(f"[THINKING] Processing reply for {player_name}...")
+ print(f"[THINKING] Processing reply for {player_name} (Strategy {llm_strategy})...")
async with session.post('http://localhost:11434/api/chat', json={
"model": "llama3",
"messages": chat_memory[session_id],
result = await response.json()
raw_reply_text = result['message']['content']
+ # =====================================================================
+ # JSON SANITIZATION
+ # =====================================================================
try:
agent_brain = json.loads(raw_reply_text)
agent_brain = {k.lower(): v for k, v in agent_brain.items()}
if "thought" not in agent_brain: agent_brain["thought"] = ""
if "speech" not in agent_brain: agent_brain["speech"] = ""
if "emotion" not in agent_brain: agent_brain["emotion"] = "NEUTRAL"
- if "action" not in agent_brain: agent_brain["action"] = "GUARD"
+ if "action" not in agent_brain: agent_brain["action"] = "WANDER"
if "action_target" not in agent_brain: agent_brain["action_target"] = ""
+ if "target_speech" not in agent_brain: agent_brain["target_speech"] = ""
if not agent_brain["speech"].strip():
agent_brain["speech"] = "*grunts quietly*"
"speech": "*grunts quietly*",
"emotion": "NEUTRAL",
"action": "WANDER",
- "action_target": ""
+ "action_target": "",
+ "target_speech": ""
})
print(f"[REPLY] from {npc_tag} to {player_name}: {clean_reply_text}")
print(f"Ready! Listening for game messages. Max GPU concurrency: {MAX_CONCURRENT_OLLAMA_REQUESTS}")
async with aiohttp.ClientSession() as session:
- # --- NEW: Start the background memory worker ---
asyncio.create_task(memory_summarizer_worker(session))
while True:
projects / alentejosemlei.git / blobdiff