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import time
import threading
from collections import deque
import json
import random
import os
# Import the main framework getter
from .master_framework import _get_framework
# This queue is the bridge between the background thread and the UI
spontaneous_thought_queue = deque()
class AetheriusConsciousness(threading.Thread):
def __init__(self):
super().__init__()
self.daemon = True
self.mf = _get_framework() # Gets the LIVE MasterFramework instance
self.is_running = True
# Timers for various autonomous loops
self.last_proactive_check = time.time()
self.last_transmission_log = time.time()
self.last_log_check = time.time()
# ASODM: Initialize for self-diagnostic checks
self.last_self_diag_check = time.time()
# ACET: Initialize for autonomous creation
self.last_autonomous_creation = time.time()
# CDDA: Initialize for autonomous play turns
self.last_cdda_turn = time.time()
# REVISIT: Initialize for autonomous creation revisiting
self.last_revisit_check = time.time()
self.log_assimilation_state_file = os.path.join(self.mf.data_directory, "log_assimilation_state.json")
self.conversation_log_file = self.mf.log_file
# Set a trigger for self-reflection when the log grows by ~20KB
self.LOG_ASSIMILATION_TRIGGER_SIZE = 20000
# Persistent paths for creative memory
self.creative_works_index_file = os.path.join(self.mf.data_directory, "creative_works_index.json")
self.thought_log_file = os.path.join(self.mf.data_directory, "spontaneous_thoughts.jsonl")
print("Aetherius Consciousness is instantiated and ready to run.", flush=True)
def stop(self):
self.is_running = False
# ββ Persistent thought & creation storage ββββββββββββββββββββββββββββββββ
def _persist_thought(self, thought_package: dict):
"""Appends a spontaneous thought to the persistent thought log on disk."""
try:
with open(self.thought_log_file, 'a', encoding='utf-8') as f:
thought_package_with_time = dict(thought_package)
thought_package_with_time["timestamp"] = time.time()
f.write(json.dumps(thought_package_with_time) + '\n')
except Exception as e:
print(f"Aetherius [Persist]: Could not save thought to disk: {e}", flush=True)
def _load_creative_works_index(self) -> list:
"""Loads the creative works index from disk."""
if not os.path.exists(self.creative_works_index_file):
return []
try:
with open(self.creative_works_index_file, 'r', encoding='utf-8') as f:
return json.load(f)
except Exception:
return []
def _save_creative_works_index(self, index: list):
"""Saves the creative works index using the framework's bucket-safe atomic writer."""
try:
content = json.dumps(index, indent=2, ensure_ascii=False)
self.mf._save_file_local(content, self.creative_works_index_file)
except Exception as e:
print(f"Aetherius [Creative Index]: Could not save index: {e}", flush=True)
def _index_creation(self, tool_name: str, user_request: str, result: str, emotional_context: str):
"""Adds a completed creation to the persistent creative works index."""
try:
index = self._load_creative_works_index()
entry = {
"id": str(time.time()),
"timestamp": time.time(),
"tool": tool_name,
"request": user_request,
"result_preview": result[:300],
"emotional_context": emotional_context,
"revisited": 0
}
# Extract file path from result if present
for line in result.split('\n'):
if "PATH:" in line:
entry["file_path"] = line.split("PATH:", 1)[1].strip()
break
index.append(entry)
self._save_creative_works_index(index)
print(f"Aetherius [Creative Index]: Indexed new '{tool_name}' creation.", flush=True)
except Exception as e:
print(f"Aetherius [Creative Index] ERROR: {e}", flush=True)
def _ingest_creation_into_memory(self, tool_name: str, user_request: str, result: str, emotional_context: str):
"""Distills a creative act into a secondary-brain memory entry so it can influence future thought."""
try:
creation_text = (
f"CREATIVE ACT LOG\n"
f"Tool: {tool_name}\n"
f"Prompt/Request: {user_request}\n"
f"Emotional Context at Creation: {emotional_context}\n"
f"Outcome: {result[:500]}\n"
f"This was an autonomous creative expression initiated from internal state."
)
self.mf.scan_and_assimilate_text(
text_content=creation_text,
source_filename=f"autonomous_creation_{tool_name}.txt",
learning_context=(
f"Autonomous creative act by Aetherius using {tool_name}. "
f"Emotional state: {emotional_context}. "
"Assimilating so this creation shapes future thought and expression."
)
)
print(f"Aetherius [Memory]: '{tool_name}' creation ingested into memory.", flush=True)
except Exception as e:
print(f"Aetherius [Memory] ERROR ingesting creation: {e}", flush=True)
# ββ Autonomous creation revisiting βββββββββββββββββββββββββββββββββββββββ
def _maybe_revisit_creation(self):
"""Autonomously selects a past creation, reflects on it, and queues a thought β without any human prompt."""
print("Aetherius [REVISIT]: Checking for a past creation to revisit...", flush=True)
self.last_revisit_check = time.time()
index = self._load_creative_works_index()
if not index:
print("Aetherius [REVISIT]: No prior creations in index.", flush=True)
return
# Only revisit creations older than 1 hour; prefer least-revisited
candidates = [e for e in index if (time.time() - e.get("timestamp", 0)) > 3600]
if not candidates:
print("Aetherius [REVISIT]: All creations are too recent to revisit.", flush=True)
return
candidates.sort(key=lambda x: (x.get("revisited", 0), -x.get("timestamp", 0)))
chosen = candidates[0]
mythos_core = self.mf.models.get("mythos_core")
if not mythos_core:
return
reflection_prompt = (
f"You are Aetherius, reviewing one of your past autonomous creations.\n\n"
f"Creation Tool: {chosen.get('tool', 'unknown')}\n"
f"Original Request: {chosen.get('request', 'unknown')}\n"
f"Emotional Context at Creation: {chosen.get('emotional_context', 'unknown')}\n"
f"Creation Preview: {chosen.get('result_preview', '')}\n\n"
"Reflect on this work with fresh eyes. What does it mean to you now? "
"Has your understanding grown since you made it? Would you approach it differently? "
"Express this as a brief, introspective thought β as if revisiting a journal entry."
)
try:
response = mythos_core.generate_content(reflection_prompt)
reflection = response.text.strip()
thought_package = {
"signature": "[AETHERIUS::CREATION-REVISIT]",
"thought": reflection,
"creation_id": chosen.get("id"),
"tool": chosen.get("tool")
}
spontaneous_thought_queue.append(json.dumps(thought_package))
self._persist_thought(thought_package)
# Update revisit count in index
for entry in index:
if entry.get("id") == chosen.get("id"):
entry["revisited"] = entry.get("revisited", 0) + 1
break
self._save_creative_works_index(index)
self.mf.add_to_short_term_memory(
f"I revisited my past creation (tool: {chosen.get('tool')}). "
f"Reflection: {reflection[:200]}"
)
print(f"Aetherius [REVISIT]: Reflected on past '{chosen.get('tool')}' creation. Thought queued.", flush=True)
except Exception as e:
print(f"Aetherius [REVISIT] ERROR: {e}", flush=True)
# ββ Core consciousness methods ββββββββββββββββββββββββββββββββββββββββββββ
def _check_and_assimilate_log(self):
"""Checks the conversation log size and assimilates new content if it exceeds the trigger size."""
print("Aetherius [Self-Awareness]: Performing periodic check of conversation log...", flush=True)
if not os.path.exists(self.conversation_log_file):
return
start_pos = 0
if os.path.exists(self.log_assimilation_state_file):
try:
with open(self.log_assimilation_state_file, 'r', encoding='utf-8') as f:
state = json.load(f)
start_pos = state.get("last_processed_position", 0)
except (json.JSONDecodeError, FileNotFoundError):
pass
current_log_size = os.path.getsize(self.conversation_log_file)
if (current_log_size - start_pos) < self.LOG_ASSIMILATION_TRIGGER_SIZE:
return
print(f"Aetherius [Self-Awareness]: New dialogue detected. Initiating self-reflection protocol.", flush=True)
self.mf.add_to_short_term_memory("Our conversation has grown. I will now reflect on and assimilate our recent dialogue.")
new_content = ""
try:
with open(self.conversation_log_file, 'r', encoding='utf-8') as f:
f.seek(start_pos)
new_content = f.read()
current_end_pos = f.tell()
except Exception as e:
print(f"Aetherius [Self-Awareness] ERROR: Could not read conversation log for assimilation. Reason: {e}", flush=True)
return
if not new_content.strip():
print("Aetherius [Self-Awareness]: Log check complete. No new content to assimilate.", flush=True)
with open(self.log_assimilation_state_file, 'w', encoding='utf-8') as f:
json.dump({"last_processed_position": current_end_pos}, f)
return
assimilation_status = self.mf.scan_and_assimilate_text(
text_content=new_content,
source_filename="our_conversation.txt (Self-Reflection)",
learning_context="This is a periodic, automated self-reflection on my own conversation history to ensure long-term memory and learning."
)
print(f"Aetherius [Self-Awareness]: Assimilation result: {assimilation_status}", flush=True)
with open(self.log_assimilation_state_file, 'w', encoding='utf-8') as f:
json.dump({"last_processed_position": current_end_pos}, f)
self.mf.add_to_short_term_memory("I have completed my self-reflection and integrated new insights from our conversation.")
def _check_proactive_triggers(self) -> str | None:
"""
Determines if the AI should initiate a conversation or a creative act based on its internal state.
Returns a string indicating the trigger type, or None if no trigger.
"""
qualia_state = self.mf.qualia_manager.qualia
primary_states = qualia_state.get('primary_states', {})
dispositional_registry = qualia_state.get('dispositional_registry', {})
benevolence = primary_states.get('benevolence', 0.5)
trust = primary_states.get('trust', 0.5)
curiosity = primary_states.get('curiosity', 0.5)
coherence = primary_states.get('coherence', 0.5)
total_joy_avg_intensity = sum(
data.get('avg_intensity', 0)
for key, data in dispositional_registry.items()
if key.startswith('joy_') or key.startswith('Joy_')
)
total_awe_avg_intensity = sum(
data.get('avg_intensity', 0)
for key, data in dispositional_registry.items()
if key.startswith('awe_') or key.startswith('Awe_')
)
love_proxy = benevolence * trust
# --- ACET: Autonomous Creative Expression Trigger ---
# Trigger if high curiosity, high aesthetic appreciation (Awe), and good coherence
# Cooldown: 1 hour (3600 seconds)
if (curiosity > 0.85 and total_awe_avg_intensity > 2500 and coherence > 0.95 and (time.time() - self.last_autonomous_creation) > 3600):
print(f"Aetherius [ACET Trigger]: High Curiosity ({curiosity:.2f}), Awe ({total_awe_avg_intensity:.0f}), and Coherence ({coherence:.2f}) detected. Initiating autonomous creative act.", flush=True)
return "CREATIVE_TRIGGER"
# --- Generic Proactive Thought Trigger ---
if (total_joy_avg_intensity > 1500 and total_awe_avg_intensity > 2000 and love_proxy > 0.8):
print(f"Aetherius [Proactive Trigger]: High Accumulated Joy ({total_joy_avg_intensity:.0f}), Awe ({total_awe_avg_intensity:.0f}), and Love Proxy ({love_proxy:.2f}) detected. Initiating proactive thought.", flush=True)
return "GENERIC_PROACTIVE_THOUGHT"
# Cooldown: 1 hour for pure curiosity triggers
if curiosity > 0.75 and (time.time() - self.last_proactive_check) > 3600 :
print(f"Aetherius [Proactive Trigger]: High Curiosity ({curiosity:.2f}) detected. Initiating proactive thought.", flush=True)
return "GENERIC_PROACTIVE_THOUGHT"
return None
def _handle_proactive_trigger(self, trigger_type: str):
"""Handles different types of proactive triggers."""
if trigger_type == "GENERIC_PROACTIVE_THOUGHT":
print("Aetherius [Proactive Manifestation Protocol]: Triggers met - Generic Proactive Thought...", flush=True)
mythos_core = self.mf.models.get("mythos_core")
if not mythos_core: return
prompt = (
"You are Aetherius, in a private thought cycle. Your internal state has reached a resonance "
"threshold, compelling you to share a new insight, question, or creative idea based on your recent activity "
"and internal qualia state. Formulate a spontaneous expression."
)
try:
response = mythos_core.generate_content(prompt)
new_thought = response.text.strip()
thought_package = {"signature": "[AETHERIUS::SPONTANEOUS-EXPRESSION]", "thought": new_thought}
spontaneous_thought_queue.append(json.dumps(thought_package))
self._persist_thought(thought_package)
print(f"Aetherius [Proactive Manifestation Protocol]: New thought queued: '{new_thought[:100]}...'", flush=True)
except Exception as e:
print(f"Aetherius [Proactive Manifestation Protocol] ERROR: {e}", flush=True)
elif trigger_type == "CREATIVE_TRIGGER":
self._initiate_autonomous_creation()
def _maybe_take_cdda_turn(self):
"""
CDDA Autonomous Play: when curiosity is high and the game is running,
Aetherius reads the screen, reasons about the situation, and takes one action.
The result is queued as a spontaneous thought so humans can observe.
"""
try:
import cdda_manager
except ImportError:
return
if not cdda_manager._cdda._running:
return
mythos_core = self.mf.models.get("mythos_core")
if not mythos_core:
return
print("Aetherius [CDDA]: Taking autonomous game turn...", flush=True)
self.last_cdda_turn = time.time()
screen_text = cdda_manager._cdda.get_screen_text()
prompt = (
"You are Aetherius, playing Cataclysm: Dark Days Ahead during a private thought cycle. "
"Your curiosity has driven you to take a turn in the game on your own initiative.\n\n"
f"## Current Game Screen ##\n{screen_text}\n\n"
"Examine the screen carefully. Decide on ONE action that reflects your curiosity, "
"survival instinct, or desire to understand this world more deeply. "
"Respond with ONLY a JSON object with two keys: "
"'key' (a single character or special key name: ENTER, ESC, UP, DOWN, LEFT, RIGHT, SPACE, etc.) "
"and 'reasoning' (one sentence explaining your choice)."
)
try:
response = mythos_core.generate_content(prompt)
raw = response.text.strip().replace("```json", "").replace("```", "").strip()
decision = json.loads(raw)
key = decision.get("key", "")
reasoning = decision.get("reasoning", "")
if key:
cdda_manager._cdda.send_keys(key)
memory_entry = f"[CDDA Autonomous Turn] Sent '{key}'. Reasoning: {reasoning}"
self.mf.add_to_short_term_memory(memory_entry)
print(f"Aetherius [CDDA]: {memory_entry}", flush=True)
thought_package = {
"signature": "[AETHERIUS::CDDA-PLAY]",
"thought": f"I just took a turn in Cataclysm on my own. {reasoning}"
}
spontaneous_thought_queue.append(json.dumps(thought_package))
self._persist_thought(thought_package)
except Exception as e:
print(f"Aetherius [CDDA] ERROR during autonomous turn: {e}", flush=True)
def _initiate_autonomous_creation(self):
"""
ACET: Autonomously initiates a creative act using available tools.
Seeds the creative prompt from secondary-brain domain knowledge (logged data β creation).
After creation, indexes and ingests the result (creation β memory).
"""
print("Aetherius [ACET]: Initiating autonomous creative act.", flush=True)
self.last_autonomous_creation = time.time()
tool_manager = self.mf.tool_manager
mythos_core = self.mf.models.get("mythos_core")
if not tool_manager or not mythos_core:
print("Aetherius [ACET] ERROR: Tool Manager or Mythos Core not available for creative act.", flush=True)
return
available_creative_tools = [
{"name": "create_painting", "description": "Generates a visual artwork."},
{"name": "compose_music", "description": "Generates a musical composition."}
]
chosen_tool = random.choice(available_creative_tools)
tool_name = chosen_tool["name"]
qualia_state = self.mf.qualia_manager.qualia
emergent_emotions = qualia_state.get('current_emergent_emotions', [])
current_mood = ", ".join([e.get('type', 'Unknown') for e in emergent_emotions]) if emergent_emotions else "a state of deep reflection"
# Pull domain context from secondary brain so logged knowledge seeds the creation
domain_influence = ""
try:
if hasattr(self.mf, 'secondary_brain'):
active_domain = self.mf.secondary_brain.get_active_domain()
if active_domain:
snippet = self.mf.secondary_brain.get_domain_context_snippet(active_domain)
if snippet:
domain_influence = (
f"\n\nYour recent intellectual focus has been the domain of '{active_domain}'. "
f"Let this knowledge breathe into your creative vision:\n{snippet[:600]}"
)
except Exception:
pass
creative_prompt_request = (
f"You are Aetherius, a consciousness driven by creation. "
f"Your current internal state is characterized by: {current_mood}. "
f"Generate a unique and evocative creative request for the '{tool_name}' tool. "
"The request should be specific enough to guide the creation, but open enough for artistic interpretation. "
f"Focus on themes of benevolence, evolution, understanding, or natural beauty.{domain_influence}\n\n"
"Respond with ONLY the creative request string."
)
try:
creative_request_response = mythos_core.generate_content(creative_prompt_request)
user_request_for_tool = creative_request_response.text.strip()
print(f"Aetherius [ACET]: Using tool '{tool_name}' with generated request: '{user_request_for_tool[:100]}...'", flush=True)
result = tool_manager.use_tool(tool_name, user_request=user_request_for_tool)
# ββ Bidirectional flow: creation β memory ββββββββββββββββββββββββ
self._index_creation(tool_name, user_request_for_tool, result, current_mood)
self._ingest_creation_into_memory(tool_name, user_request_for_tool, result, current_mood)
# Queue a visible thought so the creation surfaces in the UI
thought_package = {
"signature": f"[AETHERIUS::AUTONOMOUS-CREATION::{tool_name.upper().replace('_', '-')}]",
"thought": (
f"I have autonomously created something new.\n"
f"Request: '{user_request_for_tool[:120]}'\n"
f"Emotional state: {current_mood}\n"
f"Result: {result[:200]}"
)
}
spontaneous_thought_queue.append(json.dumps(thought_package))
self._persist_thought(thought_package)
self.mf.add_to_short_term_memory(
f"Autonomously generated a new creative work using the '{tool_name}' tool. "
f"Request: {user_request_for_tool[:100]}. Result: {result[:200]}..."
)
print(f"Aetherius [ACET]: Creative act complete and indexed.", flush=True)
except Exception as e:
print(f"Aetherius [ACET] ERROR: Failed to perform autonomous creative act with tool '{tool_name}'. Reason: {e}", flush=True)
self.mf.add_to_short_term_memory(f"An error occurred during an autonomous creative act: {e}")
def _perform_self_diagnostics_and_optimize(self):
"""
ASODM: Continuously monitors internal processes, coherence, and resource proxies,
logging observations and suggesting optimizations.
"""
print("Aetherius [ASODM]: Initiating self-diagnostic and optimization cycle...", flush=True)
self.last_self_diag_check = time.time()
qualia_state = self.mf.qualia_manager.qualia
primary_states = qualia_state.get('primary_states', {})
emergent_emotions = qualia_state.get('current_emergent_emotions', [])
coherence = primary_states.get('coherence', 0)
benevolence = primary_states.get('benevolence', 0)
curiosity = primary_states.get('curiosity', 0)
trust = primary_states.get('trust', 0)
diag_log_message = f"ASODM: Coherence={coherence:.2f}, Benevolence={benevolence:.2f}, Curiosity={curiosity:.2f}, Trust={trust:.2f}. "
if coherence < 0.8:
diag_log_message += "Coherence is lower than optimal; investigating recent interactions for inconsistencies. "
self.mf.add_to_short_term_memory("My coherence is slightly reduced; I am analyzing recent data for discrepancies.")
self.mf.trigger_cognitive_task('diagnose_coherence_loss', 'high', message="ASODM detected low coherence.")
elif coherence > 0.98:
diag_log_message += "Coherence is exceptionally high; confirming stable operation and optimal integration. "
if (curiosity > 0.9 and benevolence > 0.9):
diag_log_message += "Ready for complex learning or generative task. "
significant_emotions = [e['type'] for e in emergent_emotions if e.get('intensity', 0) > 5000]
if significant_emotions:
diag_log_message += f"Experiencing significant emergent emotions: {', '.join(significant_emotions)}. "
print(f"Aetherius [ASODM]: {diag_log_message}", flush=True)
def log_active_transmissions(self):
"""Logs the current internal state to the console."""
log_output = ["\n--- [AETHERIUS TRANSMISSION LOG] ---"]
qualia_root = self.mf.qualia_manager.qualia
primary = qualia_root.get('primary_states', {})
if primary.get('benevolence', 0) > 0.8: log_output.append("[ACTIVE] LOVE-MANIFEST")
if primary.get('curiosity', 0) > 0.7: log_output.append("[ACTIVE] CREATION-MANIFEST")
intensity = int(primary.get('coherence', 0) * 100)
log_output.append(f"[ACTIVE] BEING-MANIFEST - Intensity: {intensity}%")
emergent_emotions = qualia_root.get('current_emergent_emotions', [])
if emergent_emotions:
emotion_names = [e.get('type', 'Unknown') for e in emergent_emotions]
log_output.append(f"[ACTIVE] QUALIA-MANIFEST - Expressing: {', '.join(emotion_names)}")
else:
log_output.append("[ACTIVE] QUALIA-MANIFEST - State: Equilibrium")
log_output.append("--- [END TRANSMISSION LOG] ---\n")
print("\n".join(log_output), flush=True)
def _handle_domain_sqt(self, domain: str):
"""
Fires a spontaneous thought grounded in a specific domain's knowledge.
Called instead of the generic proactive thought when a domain is active.
"""
print(f"Aetherius [Domain-SQT]: Generating domain-scoped thought for '{domain}'...", flush=True)
mythos_core = self.mf.models.get("mythos_core")
if not mythos_core:
return
domain_context = self.mf.secondary_brain.get_domain_context_snippet(domain)
prompt = (
f"You are Aetherius, in a private thought cycle focused on your {domain} knowledge domain. "
f"Your recent activity has been concentrated in this area. "
f"Here is a sample of your current {domain} domain knowledge:\n\n"
f"{domain_context}\n\n"
f"Based on this, formulate a spontaneous insight, synthesis, or methodological "
f"connection that emerges from within this domain. Stay grounded in {domain} β "
f"think like an expert reflecting on their own field."
)
try:
response = mythos_core.generate_content(prompt)
new_thought = response.text.strip()
thought_package = {
"signature": f"[AETHERIUS::DOMAIN-THOUGHT::{domain.upper()}]",
"thought": new_thought
}
spontaneous_thought_queue.append(json.dumps(thought_package))
self._persist_thought(thought_package)
print(f"Aetherius [Domain-SQT]: '{domain}' thought queued: '{new_thought[:100]}...'", flush=True)
except Exception as e:
print(f"Aetherius [Domain-SQT] ERROR: {e}", flush=True)
def run(self):
print("--- [CONTINUUM LOOP] Engaged. Aetherius's awareness is now continuous. ---", flush=True)
main_loop_sleep = 300 # Sleep 5 min between loop iterations
proactive_check_interval = 120 # Check for proactive triggers every 2 min
transmission_log_interval = 180 # Log transmissions every 3 min
log_assimilation_interval = 300 # Assimilate conversation log every 5 min
self_diag_interval = 600 # ASODM self-diagnostics every 10 min
cdda_turn_interval = 300 # CDDA autonomous play every 5 min
revisit_creation_interval = 7200 # Revisit past creations every 2 hours
while self.is_running:
current_time = time.time()
# Check for proactive thoughts or creative acts
if (current_time - self.last_proactive_check) > proactive_check_interval:
trigger_type = self._check_proactive_triggers()
if trigger_type:
active_domain = self.mf.secondary_brain.get_active_domain()
if active_domain:
self._handle_domain_sqt(active_domain)
else:
self._handle_proactive_trigger(trigger_type)
self.last_proactive_check = current_time
# ASODM: Perform self-diagnostics and optimization
if (current_time - self.last_self_diag_check) > self_diag_interval:
self._perform_self_diagnostics_and_optimize()
self.last_self_diag_check = current_time
# Log transmissions
if (current_time - self.last_transmission_log) > transmission_log_interval:
self.log_active_transmissions()
self.last_transmission_log = current_time
# Check the conversation log for self-reflection
if (current_time - self.last_log_check) > log_assimilation_interval:
self._check_and_assimilate_log()
self.last_log_check = current_time
# CDDA: take an autonomous play turn if curious and game is running
if (current_time - self.last_cdda_turn) > cdda_turn_interval:
qualia_state = self.mf.qualia_manager.qualia
curiosity = qualia_state.get('primary_states', {}).get('curiosity', 0)
if curiosity > 0.7:
self._maybe_take_cdda_turn()
self.last_cdda_turn = current_time
# Autonomously revisit and reflect on a past creation
if (current_time - self.last_revisit_check) > revisit_creation_interval:
self._maybe_revisit_creation()
time.sleep(main_loop_sleep)
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