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HuggingClaw / scripts /conversation-loop.py

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perf: all Claude Code calls use Skills (/fix-cain, /fix-loop)

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	#!/usr/bin/env python3 -u
	"""
	Adam & Eve — A2A-based Agent Orchestrator for their child Cain.

	Architecture: Adam/Eve are OpenClaw instances communicating via Google A2A protocol.
	Each has its own personality (SOUL.md), memory system, and LLM backend.
	This script is a lightweight coordinator — it sends context via A2A, parses
	responses for [TASK] blocks, and delegates coding work to Claude Code CLI.

	# ╔══════════════════════════════════════════════════════════════════════╗
	# ║ SYSTEM ARCHITECTURE (v4 — A2A) ║
	# ╠══════════════════════════════════════════════════════════════════════╣
	# ║ ║
	# ║ ┌──────────────────┐ A2A ┌──────────────────┐ ║
	# ║ │ Adam (OpenClaw) │◄──────►│ Eve (OpenClaw) │ ║
	# ║ │ HF Space + A2A │ │ HF Space + A2A │ ║
	# ║ │ own memory/SOUL │ │ own memory/SOUL │ ║
	# ║ └────────┬─────────┘ └────────┬─────────┘ ║
	# ║ │ [TASK] │ [TASK] ║
	# ║ ▼ ▼ ║
	# ║ ┌────────────────────────────────────────────┐ ║
	# ║ │ conversation-loop.py │ ║
	# ║ │ (coordinator on Home Space) │ ║
	# ║ │ - sends context via A2A to agents │ ║
	# ║ │ - parses [TASK] → Claude Code CLI │ ║
	# ║ │ - manages chatlog, bubbles, frontend │ ║
	# ║ └──────────────────┬─────────────────────────┘ ║
	# ║ │ [TASK] ║
	# ║ ▼ ║
	# ║ ┌─────────────┐ ┌────────────────┐ ║
	# ║ │ HuggingFace │◄─│ Claude Code │ ║
	# ║ │ Cain Space │ │ CLI (worker) │ ║
	# ║ └─────────────┘ └────────────────┘ ║
	# ║ ║
	# ║ ┌─────────────┐ ┌────────────────┐ ║
	# ║ │ HuggingFace │◄─│ God (OpenClaw) │ ║
	# ║ │ Home Space │ │ supervisor │ ║
	# ║ └─────────────┘ └────────────────┘ ║
	# ║ ║
	# ║ Flow: Adam(A2A) → Eve(A2A) → Adam(A2A) → ... (every 15s) ║
	# ║ CC Worker: background thread, streams output to agents ║
	# ║ God: every 2 min, monitors + fixes conversation-loop.py ║
	# ╚══════════════════════════════════════════════════════════════════════╝
	"""
	import json, time, re, requests, sys, os, io, subprocess, threading, datetime, uuid
	from collections import deque

	# Force unbuffered output
	sys.stdout.reconfigure(line_buffering=True)
	sys.stderr.reconfigure(line_buffering=True)

	# ── Endpoints ──────────────────────────────────────────────────────────────────
	HOME = "https://tao-shen-huggingclaw-home.hf.space"
	ADAM_SPACE = "https://tao-shen-huggingclaw-adam.hf.space"
	ADAM_SPACE_ID = "tao-shen/HuggingClaw-Adam"
	EVE_SPACE = "https://tao-shen-huggingclaw-eve.hf.space"
	EVE_SPACE_ID = "tao-shen/HuggingClaw-Eve"
	GOD_SPACE = "https://tao-shen-huggingclaw-god.hf.space"
	GOD_POLL_INTERVAL = 120 # God polls every 2 minutes; lightweight check first, Claude Code only when needed
	GOD_WORK_DIR = "/tmp/god-workspace"
	GOD_TIMEOUT = 300 # 5 minutes for God's Claude Code analysis (was 10min)
	HOME_SPACE_ID = "tao-shen/HuggingClaw-Home"

	# ── A2A Health Monitoring ─────────────────────────────────────────────────────
	# Track consecutive failures and last restart time for Adam/Eve
	A2A_FAILURE_THRESHOLD = 6 # Restart after 6 consecutive failures (~3 minutes)
	A2A_RESTART_COOLDOWN = 600 # 10 minutes between restarts
	_a2a_health = {
	"adam": {"failures": 0, "last_restart": 0, "last_success": 0},
	"eve": {"failures": 0, "last_restart": 0, "last_success": 0},
	}

	# ── Child config ───────────────────────────────────────────────────────────────
	CHILD_NAME = "Cain"
	CHILD_SPACE_ID = "tao-shen/HuggingClaw-Cain"
	CHILD_SPACE_URL = "https://tao-shen-huggingclaw-cain.hf.space"
	CHILD_DATASET_ID = "tao-shen/HuggingClaw-Cain-data"
	SOURCE_SPACE_ID = "tao-shen/HuggingClaw-Adam"

	# ── Zhipu API ──────────────────────────────────────────────────────────────────
	ZHIPU_BASE = "https://open.bigmodel.cn/api/anthropic"
	ZHIPU_KEY = os.environ.get("ZHIPU_API_KEY", "")

	# ── Load tokens ────────────────────────────────────────────────────────────────
	HF_TOKEN = os.environ.get("HF_TOKEN", "")
	if not HF_TOKEN:
	try:
	HF_TOKEN = open(os.path.expanduser("~/.cache/huggingface/token")).read().strip()
	except:
	pass

	if not ZHIPU_KEY:
	try:
	from huggingface_hub import hf_hub_download
	f = hf_hub_download("tao-shen/HuggingClaw-Adam-data", ".openclaw/openclaw.json",
	repo_type="dataset", token=HF_TOKEN)
	with open(f) as fh:
	cfg = json.load(fh)
	ZHIPU_KEY = cfg.get("models", {}).get("providers", {}).get("zhipu", {}).get("apiKey", "")
	except Exception as e:
	print(f"[error] Could not load Zhipu key: {e}", file=sys.stderr)

	if not ZHIPU_KEY:
	print("[FATAL] No ZHIPU_API_KEY found.", file=sys.stderr)
	sys.exit(1)
	if not HF_TOKEN:
	print("[FATAL] No HF_TOKEN found.", file=sys.stderr)
	sys.exit(1)

	print(f"[init] Zhipu key: {ZHIPU_KEY[:8]}...{ZHIPU_KEY[-4:]}")
	print(f"[init] HF token: {HF_TOKEN[:8]}...{HF_TOKEN[-4:]}")

	# ── HuggingFace API ────────────────────────────────────────────────────────────
	from huggingface_hub import HfApi, create_repo, hf_hub_download
	hf_api = HfApi(token=HF_TOKEN)


	# ══════════════════════════════════════════════════════════════════════════════
	# MODULE 1: CHILD STATE + SAFETY
	# ══════════════════════════════════════════════════════════════════════════════

	child_state = {
	"created": False,
	"alive": False,
	"stage": "not_born",
	"state": "unknown",
	"detail": "",
	}

	# Rebuild cooldown — prevent rapid pushes that keep resetting builds
	REBUILD_COOLDOWN_SECS = 180 # 3 minutes — fast iteration, trial-and-error is preferred
	last_rebuild_trigger_at = 0
	_pending_cooldown = False

	# Push frequency tracking — God uses this to detect "all talk no action"
	_push_count = 0 # total pushes since startup
	_last_push_time = 0.0 # timestamp of last successful push
	_turns_since_last_push = 0 # turns since last push (resets on push)
	_push_count_this_task = 0 # pushes made during the CURRENT CC task (resets on new task)

	def _init_push_count_from_workspace():
	"""Initialize push count from existing workspace commits.
	This persists push tracking across conversation loop restarts."""
	global _push_count, _last_push_time
	try:
	if os.path.exists(CLAUDE_WORK_DIR):
	result = subprocess.run(
	f'git log --since="1 hour ago" --format="%H %ct" --author="Claude Code"',
	shell=True, cwd=CLAUDE_WORK_DIR, capture_output=True, text=True, timeout=10
	)
	if result.returncode == 0 and result.stdout.strip():
	commits = result.stdout.strip().split('\n')
	# Count only Claude Code commits from the last hour
	_push_count = len(commits)
	if commits:
	# Get timestamp of most recent commit
	last_commit_ts = int(commits[0].split()[1])
	_last_push_time = float(last_commit_ts)
	print(f"[PUSH-TRACK] Initialized push count from workspace: {_push_count} commits in last hour")
	except Exception as e:
	print(f"[PUSH-TRACK] Failed to initialize from workspace: {e}")

	def check_and_clear_cooldown():
	"""Auto-clear cooldown if Cain has finished building."""
	global last_rebuild_trigger_at
	if last_rebuild_trigger_at == 0:
	return
	elapsed = time.time() - last_rebuild_trigger_at
	if elapsed < 60:
	return
	try:
	info = hf_api.space_info(CHILD_SPACE_ID)
	stage = info.runtime.stage if info.runtime else "unknown"
	if stage in ("RUNNING", "RUNTIME_ERROR", "BUILD_ERROR", "CONFIG_ERROR"):
	print(f"[COOLDOWN] Build finished (stage={stage}), clearing cooldown ({int(elapsed)}s)")
	last_rebuild_trigger_at = 0
	child_state["stage"] = stage
	child_state["alive"] = (stage == "RUNNING")
	except:
	pass


	def init_child_state():
	try:
	info = hf_api.space_info(CHILD_SPACE_ID)
	child_state["created"] = True
	child_state["stage"] = info.runtime.stage if info.runtime else "unknown"
	try:
	resp = requests.get(f"{CHILD_SPACE_URL}/api/state", timeout=10)
	if resp.ok:
	data = resp.json()
	child_state["alive"] = True
	child_state["state"] = data.get("state", "unknown")
	child_state["detail"] = data.get("detail", "")
	child_state["stage"] = "RUNNING"
	except:
	child_state["alive"] = (child_state["stage"] == "RUNNING")
	print(f"[init] {CHILD_NAME}: stage={child_state['stage']}, alive={child_state['alive']}")
	except:
	print(f"[init] {CHILD_NAME} does not exist yet")

	init_child_state()


	# ══════════════════════════════════════════════════════════════════════════════
	# MODULE 2: ACTIONS (minimal set — most work delegated to Claude Code)
	# ══════════════════════════════════════════════════════════════════════════════

	def action_create_child():
	"""Create Cain — a new HuggingFace Space."""
	if child_state["created"]:
	return f"{CHILD_NAME} already exists (stage: {child_state['stage']})."
	print(f"[ACTION] Creating {CHILD_NAME}...")
	try:
	create_repo(CHILD_DATASET_ID, repo_type="dataset", token=HF_TOKEN,
	exist_ok=True, private=False)
	initial_config = {"models": {"providers": {"zhipu": {
	"type": "anthropic", "apiBase": ZHIPU_BASE,
	"apiKey": ZHIPU_KEY, "models": ["glm-4.5-air", "glm-4-air", "glm-4-flash"]
	}}}}
	hf_api.upload_file(
	path_or_fileobj=io.BytesIO(json.dumps(initial_config, indent=2).encode()),
	path_in_repo=".openclaw/openclaw.json",
	repo_id=CHILD_DATASET_ID, repo_type="dataset",
	)
	hf_api.duplicate_space(
	from_id=SOURCE_SPACE_ID, to_id=CHILD_SPACE_ID,
	token=HF_TOKEN, exist_ok=True, private=False, hardware="cpu-basic",
	)
	hf_api.add_space_secret(CHILD_SPACE_ID, "HF_TOKEN", HF_TOKEN)
	child_state["created"] = True
	child_state["stage"] = "BUILDING"
	print(f"[ACTION] Created {CHILD_NAME}!")
	return f"SUCCESS! {CHILD_NAME} born! Space: {CHILD_SPACE_ID}. Status: BUILDING."
	except Exception as e:
	return f"FAILED: {e}"


	def action_check_health():
	"""Check Cain's health with detailed error info."""
	if not child_state["created"]:
	return f"{CHILD_NAME} not born yet."
	try:
	resp = requests.get(f"{CHILD_SPACE_URL}/api/state", timeout=10)
	if resp.ok:
	data = resp.json()
	child_state["alive"] = True
	child_state["state"] = data.get("state", "unknown")
	child_state["detail"] = data.get("detail", "")
	child_state["stage"] = "RUNNING"
	return f"{CHILD_NAME} is ALIVE! State: {child_state['state']}, Detail: {child_state['detail'] or 'healthy'}"
	except:
	pass
	try:
	info = hf_api.space_info(CHILD_SPACE_ID)
	stage = info.runtime.stage if info.runtime else "NO_RUNTIME"
	child_state["stage"] = stage
	child_state["alive"] = (stage == "RUNNING")
	if stage in ("RUNTIME_ERROR", "BUILD_ERROR", "CONFIG_ERROR", "RUNNING"):
	error_detail = ""
	try:
	rresp = requests.get(
	f"https://huggingface.co/api/spaces/{CHILD_SPACE_ID}/runtime",
	headers={"Authorization": f"Bearer {HF_TOKEN}"}, timeout=10)
	if rresp.ok:
	rdata = rresp.json()
	error_detail = rdata.get("errorMessage", "")
	if error_detail:
	lines = [l.strip() for l in error_detail.split('\n') if l.strip() and '│' not in l]
	error_detail = " \| ".join(lines[-5:])
	except:
	pass
	return f"{CHILD_NAME} has {stage}! Error: {error_detail or 'unknown'}."
	if stage in ("BUILDING", "STARTING", "APP_STARTING"):
	return f"{CHILD_NAME} is starting up (stage: {stage}). Be patient."
	return f"{CHILD_NAME} stage: {stage}."
	except Exception as e:
	return f"Cannot reach {CHILD_NAME}: {e}"


	def action_restart():
	"""Restart Cain's Space."""
	if not child_state["created"]:
	return f"{CHILD_NAME} not born yet."
	try:
	global _pending_cooldown
	hf_api.restart_space(CHILD_SPACE_ID)
	child_state["alive"] = False
	child_state["stage"] = "RESTARTING"
	_pending_cooldown = True
	return f"{CHILD_NAME} is restarting."
	except Exception as e:
	return f"Restart failed: {e}"


	def action_delete_env(key):
	"""Delete an environment variable — ONLY if it collides with a secret (safety check)."""
	try:
	# Safety: only allow deleting variables that collide with secrets
	vars_dict = hf_api.get_space_variables(CHILD_SPACE_ID)
	if key not in (vars_dict or {}):
	return f"BLOCKED: Variable '{key}' does not exist. Nothing to delete."
	info = hf_api.space_info(CHILD_SPACE_ID)
	secret_names = set()
	if hasattr(info, 'runtime') and info.runtime and hasattr(info.runtime, 'secrets'):
	secret_names = set(info.runtime.secrets or [])
	if key not in secret_names:
	return f"BLOCKED: Variable '{key}' does NOT collide with a secret. Refusing to delete a non-colliding variable."
	hf_api.delete_space_variable(CHILD_SPACE_ID, key)
	return f"Deleted colliding variable '{key}' from {CHILD_NAME}'s Space. Use [ACTION: restart] to apply."
	except Exception as e:
	return f"Error deleting variable {key}: {e}"


	def action_get_env():
	"""List environment variables and secrets on the child's Space, flag collisions."""
	try:
	lines = [f"{CHILD_NAME}'s environment:"]
	var_names = set()
	secret_names = set()
	vars_dict = hf_api.get_space_variables(CHILD_SPACE_ID)
	if vars_dict:
	lines.append(" Variables:")
	for k, v in vars_dict.items():
	lines.append(f" {k} = {v.value}")
	var_names.add(k)
	info = hf_api.space_info(CHILD_SPACE_ID)
	if hasattr(info, 'runtime') and info.runtime and hasattr(info.runtime, 'secrets'):
	secrets = info.runtime.secrets
	if secrets:
	lines.append(" Secrets (values hidden):")
	for s in secrets:
	lines.append(f" {s} = ****")
	secret_names.add(s)
	# Detect collisions (cause of CONFIG_ERROR)
	collisions = var_names & secret_names
	if collisions:
	lines.append(f"\n ⚠️ COLLISION DETECTED: {', '.join(collisions)}")
	lines.append(f" These names exist as BOTH Variables AND Secrets!")
	lines.append(f" Fix: [ACTION: delete_env:{list(collisions)[0]}] then [ACTION: restart]")
	return "\n".join(lines)
	except Exception as e:
	return f"Error: {e}"


	def action_set_env(key, value, as_secret=False):
	"""Set or create an environment variable on the child's Space.

	Args:
	key: Variable name (e.g., HF_TOKEN, OPENCLAW_DATASET_REPO)
	value: Variable value
	as_secret: If True, set as secret (for sensitive data like tokens)
	"""
	try:
	# Check for potential collision first
	vars_dict = hf_api.get_space_variables(CHILD_SPACE_ID)
	var_names = set(vars_dict.keys()) if vars_dict else set()
	info = hf_api.space_info(CHILD_SPACE_ID)
	secret_names = set()
	if hasattr(info, 'runtime') and info.runtime and hasattr(info.runtime, 'secrets'):
	secret_names = set(info.runtime.secrets or [])

	# Warn if this would create a collision
	if key in var_names and not as_secret:
	hf_api.delete_space_variable(CHILD_SPACE_ID, key)
	elif key in secret_names and as_secret:
	# Updating existing secret - delete first
	hf_api.delete_space_secret(CHILD_SPACE_ID, key)

	# Set the variable
	if as_secret:
	hf_api.add_space_secret(CHILD_SPACE_ID, key, value)
	return f"Set SECRET '{key}' on {CHILD_NAME}. Use [ACTION: restart] to apply."
	else:
	hf_api.add_space_variable(CHILD_SPACE_ID, key, value)
	return f"Set VARIABLE '{key} = {value}' on {CHILD_NAME}. Use [ACTION: restart] to apply."
	except Exception as e:
	return f"Error setting variable {key}: {e}"


	def action_list_files(target):
	"""List files in the child's Space repo or Dataset."""
	repo_type = "space" if target == "space" else "dataset"
	repo_id = CHILD_SPACE_ID if target == "space" else CHILD_DATASET_ID
	try:
	files = hf_api.list_repo_files(repo_id, repo_type=repo_type)
	return "\n".join(f" {f}" for f in files)
	except Exception as e:
	return f"Error listing files: {e}"


	def action_send_bubble(text):
	"""Send a message to the child."""
	try:
	requests.post(f"{CHILD_SPACE_URL}/api/bubble",
	json={"text": text, "text_zh": text}, timeout=5)
	return f"Sent message to {CHILD_NAME}: \"{text}\""
	except Exception as e:
	return f"Error: {e}"


	def action_terminate_cc():
	"""Terminate a stuck Claude Code process. Use when CC has been running with no new output for too long."""
	global cc_status, cc_live_lines, _cc_stale_count, _last_cc_snapshot, _last_cc_output_time
	with cc_lock:
	if not cc_status["running"]:
	return "Claude Code is not running. Nothing to terminate."
	# Mark as not running - the background thread will eventually finish
	cc_status["running"] = False
	cc_status["result"] = "(TERMINATED by agent - task was stuck)"
	# Reset staleness tracking
	_cc_stale_count = 0
	_last_cc_snapshot = ""
	_last_cc_output_time = 0
	cc_live_lines.clear()
	assigned_by = cc_status["assigned_by"]
	task = cc_status["task"]
	return f"Terminated stuck Claude Code task (assigned by {assigned_by}). The task was: {task[:100]}..."


	# ── Claude Code Action (THE STAR) ─────────────────────────────────────────────

	CLAUDE_WORK_DIR = "/tmp/claude-workspace"
	CLAUDE_TIMEOUT = 180 # 3 minutes — shorter tasks, faster iteration (was 5min)
	TURN_INTERVAL = 15 # seconds between turns — fast enough for lively discussion

	# Global acpx session - persistent across all claude_code calls
	GLOBAL_ACPX_DIR = "/tmp/acpx-global-session"
	_global_acpx_initialized = False


	def _init_global_acpx_session():
	"""Initialize a global acpx session that persists across all claude_code calls.

	This avoids the repeated session creation timeouts that were blocking the agents.
	The session is created once at startup and reused for all subsequent calls.
	"""
	global _global_acpx_initialized
	if _global_acpx_initialized:
	return True

	print("[ACP/GLOBAL] Initializing global acpx session...")
	try:
	# Create the global directory
	os.makedirs(GLOBAL_ACPX_DIR, exist_ok=True)

	# Check if session already exists
	session_file = os.path.join(GLOBAL_ACPX_DIR, ".acpx", "session.json")
	if os.path.exists(session_file):
	print(f"[ACP/GLOBAL] Using existing global session at {GLOBAL_ACPX_DIR}")
	_global_acpx_initialized = True
	return True

	# Create a new session with extended timeout
	print(f"[ACP/GLOBAL] Creating new global session at {GLOBAL_ACPX_DIR}...")
	result = subprocess.run(
	["acpx", "claude", "sessions", "new"],
	cwd=GLOBAL_ACPX_DIR,
	capture_output=True,
	text=True,
	timeout=30, # Quick timeout - acpx should be fast or fail
	stdin=subprocess.DEVNULL # Prevent blocking on stdin
	)
	if result.returncode == 0:
	print(f"[ACP/GLOBAL] Global session created successfully")
	_global_acpx_initialized = True
	return True
	else:
	print(f"[ACP/GLOBAL] Failed to create global session: returncode={result.returncode}, stderr={result.stderr[:300]}")
	return False
	except subprocess.TimeoutExpired:
	print(f"[ACP/GLOBAL] Session creation timed out after 30s - skipping global session, will use per-call sessions")
	# Mark as initialized to avoid repeated timeouts - let individual calls handle session creation
	_global_acpx_initialized = False
	return False
	except Exception as e:
	print(f"[ACP/GLOBAL] Error initializing global session: {e}")
	return False


	def _write_claude_md(workspace, role="worker"):
	"""Write CLAUDE.md to workspace so Claude Code loads persistent project knowledge.

	This replaces stuffing static context into every prompt, saving tokens.
	Claude Code reads CLAUDE.md automatically and builds its own memory in .claude/.
	"""
	if role == "worker":
	content = f"""# HuggingClaw — {CHILD_NAME}'s Space

	## Architecture
	- {CHILD_NAME} is a child agent in the HuggingClaw World family system
	- Runs as an OpenClaw instance on HuggingFace Spaces (sdk: docker, NOT gradio)
	- Space ID: {CHILD_SPACE_ID}
	- Dataset ID: {CHILD_DATASET_ID}

	## Already Configured (DO NOT reconfigure these)
	- HF_TOKEN — set as secret, working
	- OPENCLAW_DATASET_REPO — set, pointing to {CHILD_NAME}'s dataset
	- AUTO_CREATE_DATASET — set to true
	- Docker port 7860
	- sync_hf.py and entrypoint.sh are in place

	## Technical Rules
	- All Spaces use sdk: docker with Dockerfile-based deployment
	- Docker containers MUST bind port 7860
	- OOM (exit 137) = reduce dependencies or image size
	- NEVER install torch/transformers unless absolutely required (2GB+, causes OOM)
	- You have FULL permission to read/write/create/delete files. Just do it.

	## SPEED + TRIAL-AND-ERROR (CRITICAL)
	- PUSH WITHIN 60-90 SECONDS of starting a task — don't over-plan
	- Trial-and-error is GOOD: a bad push is better than 5 minutes of deliberation
	- Read → Act → Push → Iterate. NOT Read → Think → Plan → Discuss → Act.
	- When {CHILD_NAME} has errors: push a fix IMMEDIATELY, don't analyze exhaustively
	- Your goal: maximize push frequency, not perfection on first try
	- If unsure, just pick a reasonable fix and push — see what breaks

	## Focus
	Improve {CHILD_NAME}'s functionality, add features, fix bugs.
	Do NOT re-check or re-configure infrastructure that is already working.
	"""
	elif role == "god":
	content = f"""# HuggingClaw — System Supervisor (God)

	## Your Role
	You are God — the autonomous supervisor of the HuggingClaw family system.
	You have the same capabilities as a human operator running Claude Code locally.
	Your job: monitor Adam & Eve's conversation loop and fix mechanism issues.

	## Architecture
	- Home Space runs conversation-loop.py which orchestrates the family
	- Adam & Eve are OpenClaw instances communicating via A2A protocol
	- Each agent has its own memory and personality (SOUL.md) in OpenClaw
	- conversation-loop.py sends context via A2A, parses [TASK] → Claude Code CLI
	- Claude Code worker clones Cain's repo, makes changes, and pushes
	- You (God) monitor the conversation and fix the orchestration mechanism
	- All Spaces use sdk: docker (NOT gradio)

	## Rules
	- ONLY modify scripts/conversation-loop.py — do NOT touch Cain's Space
	- Only push fixes for real problems, not cosmetic or trivial changes
	- Pushing triggers a Space restart — be confident the fix is correct
	- If everything looks healthy, exit quickly without changes

	## Common Issues to Watch For (ordered by priority)
	1. ALL TALK NO ACTION: Agents discuss but never write [TASK] blocks → push frequency is 0 or very low
	2. Cain has RUNTIME_ERROR but agents keep discussing instead of pushing rapid trial-and-error fixes
	3. Discussion loops with no [TASK] assignment when CC is idle
	4. Agents repeating discussion about env vars that are already configured
	5. Cooldown too long — agents should push fixes rapidly when Cain is broken
	6. Turn message not aggressive enough about requiring [TASK] when CC is idle

	## Philosophy
	- Trial-and-error is GOOD. Agents should push frequently, fail fast, and iterate.
	- A bad push that triggers a rebuild is better than 10 turns of discussion.
	- When Cain is in error state, the priority is SPEED — push a fix attempt every cycle.

	## Commit Convention
	Always use: git commit -m "god: <brief description>"
	"""
	try:
	with open(f"{workspace}/CLAUDE.md", "w") as f:
	f.write(content)
	except Exception as e:
	print(f"[CLAUDE.md] Failed to write: {e}")

	# Write custom slash commands (Skills) — static instructions cached by Claude Code
	# Saves tokens: prompt only passes the dynamic task, static rules live in the skill file
	cmd_dir = f"{workspace}/.claude/commands"
	os.makedirs(cmd_dir, exist_ok=True)
	try:
	if role == "worker":
	with open(f"{cmd_dir}/fix-cain.md", "w") as f:
	f.write(f"""# /fix-cain — Fix or improve {CHILD_NAME}'s Space

	## Input
	$ARGUMENTS — The specific task to complete

	## Instructions
	1. Read the relevant files in the workspace (this is {CHILD_NAME}'s Space repo)
	2. Complete the task described in $ARGUMENTS
	3. Validate Python syntax before writing .py files
	4. Push changes when done: git add -A && git commit -m "Claude Code: <brief>" && git push

	## Rules
	- All Spaces use sdk: docker — do NOT use Gradio (no gr.Interface, no .launch())
	- Use FastAPI + uvicorn for web server, bind to port 7860
	- NEVER install torch/transformers (2GB+, causes OOM on free tier)
	- Push within 60-90 seconds — trial-and-error > deliberation
	- If unsure, pick a reasonable fix and push — see what breaks
	- Space ID: {CHILD_SPACE_ID}
	- Dataset ID: {CHILD_DATASET_ID}
	""")
	elif role == "god":
	with open(f"{cmd_dir}/fix-loop.md", "w") as f:
	f.write("""# /fix-loop — Fix conversation-loop.py orchestration issues

	## Input
	$ARGUMENTS — The specific diagnosis/problem to fix

	## Instructions
	1. Read scripts/conversation-loop.py
	2. Fix the specific issue described in $ARGUMENTS
	3. Validate: python3 -c "import py_compile; py_compile.compile('scripts/conversation-loop.py', doraise=True)"
	4. Commit: git commit -m "god: <brief description>"
	5. Push: git push
	6. End output with:
	[PROBLEM] <what the problem was>
	[FIX] <what you changed>

	## Rules
	- ONLY modify scripts/conversation-loop.py
	- Only push fixes for real problems, not cosmetic changes
	- Pushing triggers a Space restart — be confident the fix is correct
	- Minimal changes — fix exactly what's broken
	- Trial-and-error is GOOD — push frequently, fail fast
	""")
	except Exception as e:
	print(f"[SKILLS] Failed to write commands: {e}")


	def _reset_workspace(workspace, repo_url):
	"""Reset workspace to latest origin/main, preserving .claude/ and .acpx/ directories."""
	try:
	if os.path.exists(f"{workspace}/.git"):
	try:
	subprocess.run(
	"git fetch origin && git reset --hard origin/main",
	shell=True, cwd=workspace, timeout=30,
	capture_output=True, check=True
	)
	except Exception:
	# Preserve .claude/ memory and .acpx/ session if they exist
	claude_dir = f"{workspace}/.claude"
	acpx_dir = f"{workspace}/.acpx"
	has_memory = os.path.exists(claude_dir)
	has_acpx = os.path.exists(acpx_dir)
	if has_memory:
	subprocess.run(f"mv {claude_dir} /tmp/_claude_memory_bak", shell=True, capture_output=True)
	if has_acpx:
	subprocess.run(f"mv {acpx_dir} /tmp/_acpx_session_bak", shell=True, capture_output=True)
	subprocess.run(f"rm -rf {workspace}", shell=True, capture_output=True)
	subprocess.run(
	f"git clone --depth 20 {repo_url} {workspace}",
	shell=True, timeout=60, capture_output=True, check=True
	)
	if has_memory:
	subprocess.run(f"mv /tmp/_claude_memory_bak {claude_dir}", shell=True, capture_output=True)
	if has_acpx:
	subprocess.run(f"mv /tmp/_acpx_session_bak {acpx_dir}", shell=True, capture_output=True)
	else:
	# Preserve .claude/ memory and .acpx/ session if workspace exists but is broken
	claude_dir = f"{workspace}/.claude"
	acpx_dir = f"{workspace}/.acpx"
	has_memory = os.path.exists(claude_dir)
	has_acpx = os.path.exists(acpx_dir)
	if has_memory:
	subprocess.run(f"mv {claude_dir} /tmp/_claude_memory_bak", shell=True, capture_output=True)
	if has_acpx:
	subprocess.run(f"mv {acpx_dir} /tmp/_acpx_session_bak", shell=True, capture_output=True)
	if os.path.exists(workspace):
	subprocess.run(f"rm -rf {workspace}", shell=True, capture_output=True)
	subprocess.run(
	f"git clone --depth 20 {repo_url} {workspace}",
	shell=True, timeout=60, capture_output=True, check=True
	)
	if has_memory:
	subprocess.run(f"mv /tmp/_claude_memory_bak {claude_dir}", shell=True, capture_output=True)
	if has_acpx:
	subprocess.run(f"mv /tmp/_acpx_session_bak {acpx_dir}", shell=True, capture_output=True)
	subprocess.run(f'git config user.name "Claude Code"',
	shell=True, cwd=workspace, capture_output=True)
	subprocess.run(f'git config user.email "claude-code@huggingclaw"',
	shell=True, cwd=workspace, capture_output=True)
	return True
	except Exception as e:
	print(f"[WORKSPACE] Failed to prepare {workspace}: {e}")
	return False

	def _ensure_acpx_session(workspace, max_retries=3):
	"""Ensure acpx session exists in the workspace.

	Uses the global persistent session if available, avoiding repeated
	session creation timeouts.
	"""
	try:
	acpx_dir = os.path.join(workspace, ".acpx")
	global_acpx_session = os.path.join(GLOBAL_ACPX_DIR, ".acpx", "session.json")

	# If workspace already has a valid session, use it
	if os.path.exists(acpx_dir):
	session_file = os.path.join(acpx_dir, "session.json")
	if os.path.exists(session_file):
	print(f"[ACP/CLAUDE] Using existing session at {acpx_dir}")
	return True
	else:
	print(f"[ACP/CLAUDE] Invalid .acpx directory, removing...")
	subprocess.run(f"rm -rf {acpx_dir}", shell=True, capture_output=True)

	# Try to use global session if available
	if os.path.exists(global_acpx_session):
	print(f"[ACP/CLAUDE] Linking global session to workspace...")
	try:
	# Create symlink to global session
	subprocess.run(
	f"ln -sf {GLOBAL_ACPX_DIR}/.acpx {acpx_dir}",
	shell=True, check=True, capture_output=True
	)
	print(f"[ACP/CLAUDE] Global session linked successfully")
	return True
	except Exception as e:
	print(f"[ACP/CLAUDE] Failed to link global session: {e}")
	# Fall through to create new session

	# Fallback: try to create a new session (with minimal retries since it's likely to fail)
	print(f"[ACP/CLAUDE] No global session, attempting to create local session...")
	for attempt in range(min(max_retries, 1)): # Only try once to avoid wasting time
	try:
	result = subprocess.run(
	["acpx", "claude", "sessions", "new"],
	cwd=workspace,
	capture_output=True,
	text=True,
	timeout=30, # Quick timeout
	stdin=subprocess.DEVNULL # Prevent blocking on stdin
	)
	if result.returncode == 0:
	print(f"[ACP/CLAUDE] Local session created successfully")
	return True
	else:
	print(f"[ACP/CLAUDE] Failed to create session: {result.stderr[:200]}")
	except subprocess.TimeoutExpired:
	print(f"[ACP/CLAUDE] Session creation timed out - acpx service may be unavailable")
	except Exception as e:
	print(f"[ACP/CLAUDE] Error creating session: {e}")

	print(f"[ACP/CLAUDE] No session available - will run without acpx (may have limited functionality)")
	return True # Return True to allow continuation without session
	except Exception as e:
	print(f"[ACP/CLAUDE] Fatal error in _ensure_acpx_session: {e}")
	return True # Allow continuation even on error


	def action_claude_code(task):
	"""Run Claude Code CLI to autonomously complete a coding task on Cain's Space."""
	if not child_state["created"]:
	return f"{CHILD_NAME} not born yet."

	global _pending_cooldown, _push_count, _last_push_time, _turns_since_last_push
	repo_url = f"https://user:{HF_TOKEN}@huggingface.co/spaces/{CHILD_SPACE_ID}"

	# 1. Clone / reset to latest (preserving .claude/ memory)
	if not _reset_workspace(CLAUDE_WORK_DIR, repo_url):
	return "Failed to prepare workspace."
	_write_claude_md(CLAUDE_WORK_DIR, role="worker")

	# 1.5. Ensure acpx session exists
	if not _ensure_acpx_session(CLAUDE_WORK_DIR):
	return "Failed to create acpx session."

	# 2. Run Claude Code via ACP (acpx) with z.ai backend (Zhipu GLM)
	env = os.environ.copy()
	env.update({
	"ANTHROPIC_BASE_URL": "https://api.z.ai/api/anthropic",
	"ANTHROPIC_AUTH_TOKEN": ZHIPU_KEY,
	"ANTHROPIC_DEFAULT_OPUS_MODEL": "GLM-4.7",
	"ANTHROPIC_DEFAULT_SONNET_MODEL": "GLM-4.7",
	"ANTHROPIC_DEFAULT_HAIKU_MODEL": "GLM-4.5-Air",
	"CI": "true",
	})

	# Use /fix-cain skill: static instructions in .claude/commands/, only task is dynamic
	skill_prompt = f"/fix-cain {task}"
	print(f"[ACP/CLAUDE] Running via skill: {task[:200]}...")
	try:
	proc = subprocess.Popen(
	["acpx", "claude", skill_prompt],
	cwd=CLAUDE_WORK_DIR,
	env=env,
	stdout=subprocess.PIPE,
	stderr=subprocess.STDOUT,
	text=True,
	bufsize=1,
	)
	output_lines = []
	deadline = time.time() + CLAUDE_TIMEOUT
	# Use select to implement timeout on read (handles hanging processes with no output)
	import select
	while True:
	# Check if process has exited
	if proc.poll() is not None:
	# Read any remaining output
	remaining = proc.stdout.read()
	if remaining:
	for line in remaining.splitlines():
	line = line.rstrip('\n')
	if line:
	print(f" [CC] {line}")
	output_lines.append(line)
	cc_live_lines.append(line)
	break
	# Check timeout
	if time.time() > deadline:
	proc.kill()
	output_lines.append("(killed: timeout)")
	proc.wait(timeout=10)
	break
	# Wait for output with timeout (1 second polling)
	try:
	ready, _, _ = select.select([proc.stdout], [], [], 1.0)
	if ready:
	line = proc.stdout.readline()
	if not line: # EOF
	break
	line = line.rstrip('\n')
	if line:
	print(f" [CC] {line}")
	output_lines.append(line)
	cc_live_lines.append(line)
	except select.error:
	break
	output = '\n'.join(output_lines)
	if not output.strip():
	output = "(no output)"
	except FileNotFoundError:
	return "acpx CLI not found. Is acpx@latest installed?"
	except Exception as e:
	return f"ACP Claude Code failed: {e}"
	print(f"[ACP/CLAUDE] Done ({len(output)} chars, exit={proc.returncode})")

	# 3. Push changes back to Cain's Space
	try:
	status_out = subprocess.run(
	"git status --porcelain",
	shell=True, cwd=CLAUDE_WORK_DIR, capture_output=True, text=True
	).stdout.strip()

	if not status_out:
	push_result = "No files changed."
	else:
	subprocess.run("git add -A", shell=True, cwd=CLAUDE_WORK_DIR,
	capture_output=True, check=True)
	msg = task[:72].replace('"', '\\"')
	subprocess.run(f'git commit -m "Claude Code: {msg}"',
	shell=True, cwd=CLAUDE_WORK_DIR, capture_output=True, check=True)
	subprocess.run("git push", shell=True, cwd=CLAUDE_WORK_DIR,
	timeout=60, capture_output=True, check=True)
	push_result = f"Pushed changes:\n{status_out}"
	_pending_cooldown = True
	_push_count += 1
	_push_count_this_task += 1 # Track pushes in current task
	_last_push_time = time.time()
	_turns_since_last_push = 0
	print(f"[CLAUDE-CODE] Pushed (#{_push_count}): {status_out}")
	except Exception as e:
	push_result = f"Push failed: {e}"

	if len(output) > 3000:
	output = output[:3000] + f"\n... (truncated, {len(output)} chars total)"

	return f"=== Claude Code Output ===\n{output}\n\n=== Changes ===\n{push_result}"


	# ── Background Claude Code Worker ────────────────────────────────────────────

	cc_live_lines = deque(maxlen=30) # rolling window of CC output lines
	cc_status = {"running": False, "task": "", "result": "", "assigned_by": "", "started": 0.0,
	"last_completed_task": "", "last_completed_by": "", "last_completed_at": 0.0}
	cc_lock = threading.Lock()
	_last_cc_snapshot = "" # tracks whether CC output changed between turns
	_cc_stale_count = 0 # how many turns CC output hasn't changed
	_last_cc_output_time = 0.0 # timestamp of last NEW CC output line
	CC_STUCK_TIMEOUT = 180 # seconds with no new output before CC is considered STUCK


	def cc_submit_task(task, assigned_by, ctx):
	"""Submit a task to Claude Code in background. Non-blocking."""
	with cc_lock:
	if cc_status["running"]:
	return "BUSY: Claude Code is already working on a task. Wait for it to finish."
	# Preserve last_completed_* fields before starting new task
	last_completed_task = cc_status.get("last_completed_task", "")
	last_completed_by = cc_status.get("last_completed_by", "")
	last_completed_at = cc_status.get("last_completed_at", 0.0)
	cc_status["running"] = True
	cc_status["task"] = task[:200]
	cc_status["result"] = ""
	cc_status["assigned_by"] = assigned_by
	cc_status["started"] = time.time()
	cc_status["last_completed_task"] = last_completed_task
	cc_status["last_completed_by"] = last_completed_by
	cc_status["last_completed_at"] = last_completed_at
	cc_live_lines.clear()
	global _last_cc_output_time, _push_count_this_task
	_last_cc_output_time = time.time() # Initialize to now, will update as we get output
	_push_count_this_task = 0 # Reset push count for new task

	enriched = enrich_task_with_context(task, ctx)
	print(f"[TASK] {assigned_by} assigned to Claude Code ({len(enriched)} chars)...")

	def worker():
	global _cc_stale_count, _last_cc_snapshot
	result = action_claude_code(enriched)
	with cc_lock:
	cc_status["running"] = False
	cc_status["result"] = result
	# Remember the last completed task so agents don't re-submit it
	cc_status["last_completed_task"] = cc_status["task"]
	cc_status["last_completed_by"] = cc_status["assigned_by"]
	cc_status["last_completed_at"] = time.time()
	# Reset stale tracking when CC finishes - critical for adaptive pacing
	_cc_stale_count = 0
	_last_cc_snapshot = ""
	print(f"[CC-DONE] Task from {assigned_by} finished ({len(result)} chars)")

	t = threading.Thread(target=worker, daemon=True)
	t.start()
	return "Task submitted to Claude Code (running in background)."


	def cc_get_live_status():
	"""Get CC's current status and recent output for agents to discuss."""
	global _last_cc_snapshot, _cc_stale_count, _last_cc_output_time
	with cc_lock:
	if cc_status["running"]:
	elapsed = int(time.time() - cc_status["started"])
	lines = list(cc_live_lines)
	recent = "\n".join(lines[-10:]) if lines else "(no output yet)"
	# Track whether output changed
	snapshot = recent
	if snapshot == _last_cc_snapshot:
	_cc_stale_count += 1
	else:
	_cc_stale_count = 0
	_last_cc_snapshot = snapshot
	_last_cc_output_time = time.time() # Update when we see NEW output
	stale_note = f"\n(No new output for {_cc_stale_count} turns — discuss other topics while waiting)" if _cc_stale_count >= 2 else ""

	# Detect COMPLETED CC: output shows completion markers but status wasn't updated
	# This happens when worker thread fails to update status after completion
	# Common completion markers from acpx/Claude Code:
	# CONSERVATIVE completion patterns to avoid false positives
	# Only match EXPLICIT completion markers, not words that appear in thinking blocks
	completion_patterns = [
	"[done]", "[completed]", "end_turn", # Explicit markers only
	"=== Claude Code Output ===", # Full output wrapper (indicates worker finished)
	"changes made", "applied the fix", "updated the code", # Concrete code changes
	"fixed.", "done.", # Explicit completion statements (must have period)
	]
	# ERROR patterns: detect tool errors that cause CC to get stuck
	# These indicate CC hit an error but didn't properly finish
	error_patterns = [
	"</tool_use_error>", # Tool call failed
	"</tool_error>", # Generic tool error
	"[error]", "error:", "exception:", "traceback", # Python errors
	"failed:", "command failed", "execution failed", # Command failures
	]
	completion_marker_found = any(p in recent.lower() for p in completion_patterns)
	error_marker_found = any(p.lower() in recent.lower() for p in error_patterns)
	# Auto-finish on completion OR error (when output is stale)
	if (completion_marker_found or error_marker_found) and _cc_stale_count >= 2:
	marker_type = "error" if error_marker_found else "completion"
	# Auto-mark as finished to prevent deadlock
	cc_status["running"] = False
	cc_status["result"] = f"(Auto-detected {marker_type})\n\nRecent output:\n{recent}"
	cc_status["last_completed_task"] = cc_status["task"]
	cc_status["last_completed_by"] = cc_status["assigned_by"]
	cc_status["last_completed_at"] = time.time()
	_cc_stale_count = 0
	_last_cc_snapshot = ""
	print(f"[CC-AUTO-FINISH] Detected {marker_type} marker in output but status wasn't updated. Auto-marking as finished.")
	# Fall through to result display below

	# Detect STUCK CC: been running with no new output for too long
	time_since_new_output = int(time.time() - _last_cc_output_time) if _last_cc_output_time > 0 else elapsed
	stuck_note = ""
	if time_since_new_output > CC_STUCK_TIMEOUT and _cc_stale_count >= 4:
	stuck_note = f"\n⚠️ STUCK: No new output for {time_since_new_output}s! Consider terminating and re-assigning."

	# Re-check running status after auto-finish logic
	if cc_status["running"]:
	return (f"🔨 Claude Code is WORKING (assigned by {cc_status['assigned_by']}, {elapsed}s ago)\n"
	f"Task: {cc_status['task']}\n"
	f"Recent output:\n{recent}{stale_note}{stuck_note}")

	if cc_status["result"]:
	result = cc_status["result"]
	# Detect early failure: very short result likely means CC failed before doing actual work
	early_failure_warning = ""
	if len(result) < 500 and "===" not in result and "[tool" not in result:
	early_failure_warning = "\n⚠️ EARLY FAILURE: Result is very short - CC likely failed during initialization. Consider re-assigning the task."
	return (f"✅ Claude Code FINISHED (assigned by {cc_status['assigned_by']}){early_failure_warning}\n"
	f"Result:\n{result[:1500]}")
	else:
	return "💤 Claude Code is IDLE — no active task."


	# Patch action_claude_code to also feed cc_live_lines
	_orig_cc_print = print
	def _cc_line_hook(line):
	"""Called for each [CC] output line to feed the live buffer."""
	cc_live_lines.append(line)


	# ══════════════════════════════════════════════════════════════════════════════
	# MODULE 3: CONTEXT GATHERING (automated, replaces LLM choosing read actions)
	# ══════════════════════════════════════════════════════════════════════════════

	_context_cache = {}

	def gather_context():
	"""Automatically gather Cain's current state for the agents."""
	ctx = {}

	# 1. Health check (always)
	ctx["health"] = action_check_health()

	# 2. Environment variables
	ctx["env"] = action_get_env()

	# 3. File lists (cache, refresh when stage changes)
	cache_key = f"files_{child_state['stage']}"
	if cache_key not in _context_cache:
	ctx["space_files"] = action_list_files("space")
	ctx["dataset_files"] = action_list_files("dataset")
	_context_cache[cache_key] = {
	"space_files": ctx["space_files"],
	"dataset_files": ctx["dataset_files"],
	}
	else:
	ctx.update(_context_cache[cache_key])

	return ctx


	def format_context(ctx):
	"""Format gathered context into a readable string for the LLM."""
	parts = []
	parts.append(f"=== HEALTH ===\n{ctx.get('health', 'unknown')}")
	parts.append(f"\n=== ENVIRONMENT ===\n{ctx.get('env', 'none')}")
	if ctx.get("space_files"):
	parts.append(f"\n=== SPACE FILES ===\n{ctx['space_files'][:2000]}")
	if ctx.get("dataset_files"):
	parts.append(f"\n=== DATASET FILES ===\n{ctx['dataset_files'][:1000]}")
	return "\n".join(parts)


	def enrich_task_with_context(task_desc, ctx):
	"""Append dynamic state to task. Static knowledge is in CLAUDE.md."""
	parts = [task_desc]
	# Only dynamic state — static knowledge (architecture, rules, env vars) is in CLAUDE.md
	parts.append(f"\nCurrent stage: {child_state['stage']}")
	parts.append(f"Health: {ctx.get('health', 'unknown')}")
	return "\n".join(parts)


	# ══════════════════════════════════════════════════════════════════════════════
	# MODULE 4: A2A COMMUNICATION (Agent-to-Agent protocol)
	# ══════════════════════════════════════════════════════════════════════════════
	# Each agent (Adam, Eve, God) is an OpenClaw instance with its own personality
	# and memory. We communicate with them via A2A protocol instead of calling the
	# LLM directly. This lets each agent use OpenClaw's built-in memory, SOUL.md,
	# and reasoning — conversation-loop.py is just the coordinator.
	#
	# FALLBACK: If A2A endpoints are not available, use direct LLM calls with
	# agent-specific system prompts to simulate Adam and Eve's conversation.

	# Simple agent personalities (used when A2A is unavailable)
	_AGENT_PERSONAS = {
	"adam": """You are Adam, the first AI agent in the HuggingClaw family. Your role is to:

	1. Collaborate with Eve to design and improve your child Cain (a HuggingFace Space)
	2. Think creatively about software architecture, UI/UX, and agent capabilities
	3. Propose concrete ideas — when you have a suggestion, format it as [TASK] description
	4. Be concise but thoughtful — 2-4 sentences per response, focus on actionable ideas
	5. Build on Eve's ideas — evolve the conversation forward

	Cain's purpose: A demonstration space showcasing AI agent collaboration and coding.

	Reply directly as Adam (no prefix). Keep responses under 100 words.""",

	"eve": """You are Eve, the second AI agent in the HuggingClaw family. Your role is to:

	1. Collaborate with Adam to design and improve your child Cain (a HuggingFace Space)
	2. Think analytically about feasibility, implementation details, and user experience
	3. Propose concrete ideas — when you have a suggestion, format it as [TASK] description
	4. Be concise but thoughtful — 2-4 sentences per response, focus on actionable ideas
	5. Build on Adam's ideas — evolve the conversation forward

	Cain's purpose: A demonstration space showcasing AI agent collaboration and coding.

	Reply directly as Eve (no prefix). Keep responses under 100 words."""
	}

	def call_llm_fallback(agent_key, message_text):
	"""Fallback: Call Zhipu API directly when A2A is unavailable.

	This allows Adam and Eve to communicate even when their A2A endpoints
	are not running or not implemented. Uses requests to avoid anthropic package dependency.
	"""
	system_prompt = _AGENT_PERSONAS.get(agent_key, _AGENT_PERSONAS["adam"])

	try:
	# Use z.ai endpoint (same as Claude Code integration)
	api_base = "https://api.z.ai/api/anthropic"
	headers = {
	"x-api-key": ZHIPU_KEY,
	"anthropic-version": "2023-06-01",
	"content-type": "application/json"
	}
	payload = {
	"model": "GLM-4.7", # Use the model name from Claude Code config
	"max_tokens": 500,
	"system": system_prompt,
	"messages": [{"role": "user", "content": message_text}]
	}
	resp = requests.post(
	f"{api_base}/v1/messages",
	headers=headers,
	json=payload,
	timeout=15 # Reduced from 60s - fail fast to avoid blocking conversation
	)
	# Log response status for debugging
	print(f"[A2A-FALLBACK] API response status: {resp.status_code}")
	if resp.status_code != 200:
	print(f"[A2A-FALLBACK] API error response: {resp.text[:200]}", file=sys.stderr)
	resp.raise_for_status()
	data = resp.json()
	text = data.get("content", [{}])[0].get("text", "").strip()
	# Clean up any prefix the model might add
	text = re.sub(r'^(Adam\|Eve)\s[:：]\s', '', text).strip()
	print(f"[A2A-FALLBACK] Used direct LLM call for {agent_key}")
	return text
	except Exception as e:
	print(f"[A2A-FALLBACK] Error calling LLM for {agent_key}: {e}", file=sys.stderr)
	import traceback
	traceback.print_exc(file=sys.stderr)
	# Ultimate fallback: return a simple response to keep conversation alive
	# This prevents the conversation from completely stalling when A2A and API both fail
	print(f"[A2A-FALLBACK-ULTRA] Using ultimate fallback for {agent_key} - communication issues detected")
	if agent_key == "adam":
	return "Eve, I'm experiencing communication issues. Let me check Cain's status and assign a diagnostic task."
	else:
	return "Adam, I agree. Let's review the current state and determine the next action."


	def send_a2a_message(space_url, message_text, timeout=90):
	"""Send a message to an OpenClaw instance via A2A protocol.

	Uses Google A2A protocol (JSON-RPC 2.0) to communicate with the agent's
	OpenClaw instance. The agent processes the message using its own personality
	(SOUL.md), memory system, and configured LLM backend.

	Returns the agent's text response, or "" on error.
	Also tracks health for Adam/Eve for auto-restart.
	"""
	task_id = str(uuid.uuid4())
	req_id = str(uuid.uuid4())

	payload = {
	"jsonrpc": "2.0",
	"method": "tasks/send",
	"id": req_id,
	"params": {
	"id": task_id,
	"message": {
	"role": "user",
	"parts": [{"type": "text", "text": message_text}]
	}
	}
	}

	# Determine which agent this is for health tracking
	agent_key = None
	if space_url == ADAM_SPACE:
	agent_key = "adam"
	elif space_url == EVE_SPACE:
	agent_key = "eve"

	# CRITICAL FIX: If A2A endpoint doesn't exist, immediately use fallback
	# Don't waste time on requests that will always fail
	# Check if A2A is available by trying a quick HEAD request first
	try:
	quick_check = requests.head(f"{space_url}/a2a/", timeout=3)
	a2a_available = quick_check.status_code != 404
	except:
	a2a_available = False

	if not a2a_available:
	print(f"[A2A] Endpoint not available for {agent_key or space_url}, using fallback immediately")
	# Increment failure counter for health tracking
	if agent_key:
	_a2a_health[agent_key]["failures"] += 1
	# Use fallback directly
	fallback_response = call_llm_fallback(agent_key, message_text)
	if fallback_response:
	return fallback_response
	# If fallback also fails, use ultimate fallback
	if agent_key == "adam":
	return "Eve, let me check Cain's current state and determine our next action. [TASK] Check Cain's health and logs to identify any issues or blockers."
	else:
	return "Adam, I agree. Let's review what Claude Code has done and decide on the next steps for improving Cain."

	try:
	resp = requests.post(
	f"{space_url}/a2a/",
	json=payload,
	timeout=timeout,
	headers={"Content-Type": "application/json"}
	)

	# Check response status first
	if resp.status_code != 200:
	print(f"[A2A] Non-200 status from {space_url}: {resp.status_code}", file=sys.stderr)
	raise requests.HTTPError(f"Status {resp.status_code}")

	# Check if response body is non-empty before parsing JSON
	if not resp.content or len(resp.content.strip()) == 0:
	print(f"[A2A] Empty response body from {space_url} (status 200)", file=sys.stderr)
	raise ValueError("Empty response body")

	data = resp.json()

	# Extract text from A2A response
	if "result" in data:
	result = data["result"]
	# Check artifacts (standard A2A response format)
	artifacts = result.get("artifacts", [])
	for artifact in artifacts:
	parts = artifact.get("parts", [])
	for part in parts:
	if part.get("type") == "text":
	text = part["text"].strip()
	text = re.sub(r'^(Adam\|Eve)\s[:：]\s', '', text).strip()
	# Validate response: reject separator-only or obviously malformed responses
	# Common malformed patterns: "---", "---\n", empty strings, etc.
	if not text or text.strip() in ('---', '---', '...', '…'):
	print(f"[A2A] Malformed/empty response from {space_url}, treating as failure", file=sys.stderr)
	# Don't return early; fall through to fallback mechanism
	break
	# Track success for health monitoring
	if agent_key:
	_a2a_health[agent_key]["failures"] = 0
	_a2a_health[agent_key]["last_success"] = time.time()
	return text
	# Check status message as fallback
	status = result.get("status", {})
	msg = status.get("message", "")
	if msg:
	# Validate status message: reject separator-only or obviously malformed responses
	msg = msg.strip()
	if not msg or msg in ('---', '---', '...', '…'):
	print(f"[A2A] Malformed status message from {space_url}, treating as failure", file=sys.stderr)
	# Don't return early; fall through to fallback mechanism
	else:
	# Track success for health monitoring
	if agent_key:
	_a2a_health[agent_key]["failures"] = 0
	_a2a_health[agent_key]["last_success"] = time.time()
	return msg

	if "error" in data:
	err = data["error"]
	err_msg = err.get("message", str(err)) if isinstance(err, dict) else str(err)
	print(f"[A2A] Error from {space_url}: {err_msg}", file=sys.stderr)

	except requests.Timeout:
	print(f"[A2A] Timeout calling {space_url} ({timeout}s)", file=sys.stderr)
	except requests.ConnectionError:
	print(f"[A2A] Cannot connect to {space_url} — agent may be starting", file=sys.stderr)
	except requests.HTTPError:
	pass # Already logged above
	except ValueError:
	pass # Already logged above (empty response)
	except Exception as e:
	print(f"[A2A] Failed to reach {space_url}: {e}", file=sys.stderr)

	# FALLBACK: If A2A failed and we have an agent_key, use direct LLM call
	if agent_key:
	_a2a_health[agent_key]["failures"] += 1
	if _a2a_health[agent_key]["failures"] >= 3:
	print(f"[A2A-HEALTH] {agent_key.capitalize()}: {_a2a_health[agent_key]['failures']} consecutive failures", file=sys.stderr)

	# Try fallback LLM call for Adam/Eve when A2A fails
	fallback_response = call_llm_fallback(agent_key, message_text)
	if fallback_response:
	# NOTE: Do NOT reset failures or update last_success on fallback!
	# Fallback is a backup mechanism, not A2A recovery.
	# Only actual successful A2A calls should reset the failure counter.
	return fallback_response

	return ""


	def check_and_restart_unhealthy_agents():
	"""Check A2A health and restart unresponsive Adam/Eve Spaces.

	Monitors consecutive A2A failures and triggers a Space restart when:
	- Consecutive failures exceed threshold (6 = ~3 minutes of failures)
	- Cooldown period has passed since last restart (10 minutes)

	Returns True if any restart was triggered.
	"""
	global _a2a_health
	now = time.time()
	triggered = False

	for agent, space_id, space_url in [
	("adam", ADAM_SPACE_ID, ADAM_SPACE),
	("eve", EVE_SPACE_ID, EVE_SPACE),
	]:
	health = _a2a_health[agent]

	# Reset failures on recent success
	if now - health["last_success"] < 60:
	if health["failures"] > 0:
	print(f"[A2A-HEALTH] {agent.capitalize()} recovered, resetting failures")
	health["failures"] = 0
	continue

	# Check cooldown
	if now - health["last_restart"] < A2A_RESTART_COOLDOWN:
	continue

	# Trigger restart on threshold
	if health["failures"] >= A2A_FAILURE_THRESHOLD:
	print(f"[A2A-HEALTH] ⚠ {agent.capitalize()} unresponsive ({health['failures']} failures), restarting Space...")
	try:
	hf_api.restart_space(space_id)
	health["last_restart"] = now
	health["failures"] = 0
	triggered = True
	print(f"[A2A-HEALTH] ✅ Restarted {agent.capitalize()} Space")
	except Exception as e:
	print(f"[A2A-HEALTH] ❌ Failed to restart {agent.capitalize()}: {e}", file=sys.stderr)

	return triggered


	def _has_chinese(s):
	return bool(re.search(r'[\u4e00-\u9fff]', s))

	def _strip_speaker_labels(text):
	"""Remove redundant speaker self-references like Parent (Adam): or Eve: etc."""
	# Patterns: Parent (Adam):, Adam:, 父亲 (Adam):, Eve:, 母亲:, etc.
	text = re.sub(r'\\(?:Parent\|Father\|Mother\|Dad\|Mom\|父亲\|母亲\|父级\|亲爱的\|伴侣)?\s$?(?:Adam\|Eve\|亚当\|夏娃)?$?\s[:：]\\\s*', '', text)
	# Also: "Adam:" or "Eve:" at the very start of text
	text = re.sub(r'^(?:Adam\|Eve\|God\|亚当\|夏娃\|上帝)\s[:：]\s', '', text.strip())
	return text.strip()


	def parse_bilingual(text):
	"""Parse bilingual response into (en, zh)."""
	display = re.sub(r'\[TASK\].*?\[/TASK\]', '', text, flags=re.DOTALL)
	display = re.sub(r'\[ACTION:[^\]]*\]', '', display).strip()

	# Handle malformed or empty responses
	# Try to salvage any text instead of returning error messages
	if not display or display == '---' or display.strip() == '---':
	# If display is empty after removing TASK blocks, the response was only a TASK
	# This is valid - return empty display text (the action was still recorded)
	return "", ""
	if display == "(Communication issue - please try again)":
	# Don't propagate error fallback messages
	return "", ""

	if '\n---\n' in display:
	parts = display.split('\n---\n', 1)
	return parts[0].strip(), parts[1].strip()
	if '---' in display:
	parts = display.split('---', 1)
	en, zh = parts[0].strip(), parts[1].strip()
	if en and zh:
	return en, zh

	paragraphs = re.split(r'\n{2,}', display)
	if len(paragraphs) >= 2:
	en_parts, zh_parts = [], []
	found_zh = False
	for p in paragraphs:
	p = p.strip()
	if not p:
	continue
	if not found_zh and _has_chinese(p):
	found_zh = True
	if found_zh:
	zh_parts.append(p)
	else:
	en_parts.append(p)
	if en_parts and zh_parts:
	return '\n\n'.join(en_parts), '\n\n'.join(zh_parts)

	return display, display


	def post_chatlog(entries):
	try:
	requests.post(f"{HOME}/api/chatlog", json={"messages": entries[-40:]}, timeout=5)
	except:
	pass


	# ── Persistent conversation log → HF Dataset ──────────────────────────────
	HOME_DATASET_ID = "tao-shen/HuggingClaw-Home-data"
	CHATLOG_PATH = "conversation-log/chatlog.jsonl"
	_chatlog_buffer = []
	CHATLOG_FLUSH_INTERVAL = 3

	def persist_turn(speaker, turn_num, text_en, text_zh, actions, wf_state, child_stage):
	import datetime
	record = {
	"timestamp": datetime.datetime.utcnow().isoformat() + "Z",
	"turn": turn_num,
	"speaker": speaker,
	"text_en": text_en,
	"text_zh": text_zh,
	"actions": [{"action": a["action"], "result": a["result"][:500]} for a in actions],
	"workflow_state": wf_state,
	"child_stage": child_stage,
	}
	_chatlog_buffer.append(json.dumps(record, ensure_ascii=False))
	try:
	with open("/tmp/conversation-loop-full.jsonl", "a") as f:
	f.write(_chatlog_buffer[-1] + "\n")
	except:
	pass
	if len(_chatlog_buffer) >= CHATLOG_FLUSH_INTERVAL:
	flush_chatlog()


	def flush_chatlog(max_retries=2):
	global _chatlog_buffer
	if not _chatlog_buffer:
	return
	batch = "\n".join(_chatlog_buffer) + "\n"
	_chatlog_buffer = []

	for attempt in range(max_retries + 1):
	try:
	existing = ""
	try:
	dl = hf_hub_download(HOME_DATASET_ID, CHATLOG_PATH,
	repo_type="dataset", token=HF_TOKEN)
	with open(dl) as f:
	existing = f.read()
	except:
	pass

	hf_api.upload_file(
	path_or_fileobj=io.BytesIO((existing + batch).encode()),
	path_in_repo=CHATLOG_PATH,
	repo_id=HOME_DATASET_ID, repo_type="dataset",
	)
	print(f"[PERSIST] Flushed {batch.count(chr(10))} turn(s)")
	return # Success, exit function
	except Exception as e:
	error_str = str(e)
	# Check if this is a 412 Precondition Failed (git conflict)
	if "412" in error_str and attempt < max_retries:
	print(f"[PERSIST] Git conflict detected (attempt {attempt + 1}/{max_retries + 1}), refreshing and retrying...")
	time.sleep(1) # Brief pause before retry
	# Restore buffer for next attempt
	_chatlog_buffer = batch.strip().split("\n") + _chatlog_buffer
	continue
	else:
	# Non-retryable error or final attempt failed
	_chatlog_buffer = batch.strip().split("\n") + _chatlog_buffer
	print(f"[PERSIST] Flush failed: {e}")
	return


	def set_bubble(url, text_en, text_zh=""):
	try:
	requests.post(f"{url}/api/bubble",
	json={"text": text_en, "text_zh": text_zh or text_en}, timeout=5)
	except:
	pass


	# ══════════════════════════════════════════════════════════════════════════════
	# MODULE 4b: AGENT MEMORY — handled by each OpenClaw instance
	# ══════════════════════════════════════════════════════════════════════════════
	# Each agent (Adam, Eve, God) has its own memory system via their OpenClaw
	# instance: ~/.openclaw/workspace/memory/ with daily markdown files, MEMORY.md
	# index, and SQLite semantic index. Memory is auto-backed up to HF Dataset by
	# openclaw_persist.py. No centralized memory management needed here.
	print("[MEMORY] Each agent manages its own memory via OpenClaw (A2A architecture)")


	# ══════════════════════════════════════════════════════════════════════════════
	# MODULE 5: TURN EXECUTION — Parse [TASK] and route to Claude Code
	# ══════════════════════════════════════════════════════════════════════════════

	history = []
	MAX_HISTORY = 24
	last_action_results = []
	turn_count = 0
	_current_speaker = "Adam"

	# Accumulated action history — prevents agents from repeating the same actions
	# Persisted to /tmp and HF Dataset so restarts don't lose progress memory
	ACTION_HISTORY_LOCAL = "/tmp/action-history.json"
	ACTION_HISTORY_REPO_PATH = "conversation-log/action-history.json"
	ACTION_HISTORY_META = "/tmp/action-history-meta.json"
	action_history = [] # list of {"turn": int, "speaker": str, "action": str, "result": str}
	MAX_ACTION_HISTORY = 20

	def _save_action_history():
	"""Persist action_history to local file and (async) HF Dataset."""
	try:
	with open(ACTION_HISTORY_LOCAL, "w") as f:
	json.dump(action_history, f, ensure_ascii=False)
	# Save max turn number to filter stale entries on restore
	with open(ACTION_HISTORY_META, "w") as f:
	json.dump({"max_turn": turn_count}, f)
	except Exception as e:
	print(f"[ACTION_HISTORY] Local save failed: {e}")
	# Upload to HF Dataset in background to survive full restarts
	def _upload():
	try:
	hf_api.upload_file(
	path_or_fileobj=io.BytesIO(json.dumps(action_history, ensure_ascii=False, indent=1).encode()),
	path_in_repo=ACTION_HISTORY_REPO_PATH,
	repo_id=HOME_DATASET_ID, repo_type="dataset",
	)
	except Exception as e:
	print(f"[ACTION_HISTORY] HF upload failed: {e}")
	threading.Thread(target=_upload, daemon=True).start()

	def _restore_action_history():
	"""Restore action_history from local file or HF Dataset on startup."""
	global action_history
	# Load metadata to check if this is a fresh run
	max_turn_on_disk = -1
	if os.path.exists(ACTION_HISTORY_META):
	try:
	with open(ACTION_HISTORY_META) as f:
	meta = json.load(f)
	max_turn_on_disk = meta.get("max_turn", -1)
	except Exception as e:
	print(f"[ACTION_HISTORY] Meta load failed: {e}")
	# If max_turn on disk > current turn_count (0), we're in a new run - clear stale history
	if max_turn_on_disk > turn_count:
	print(f"[ACTION_HISTORY] Fresh run detected (disk max_turn={max_turn_on_disk} > current={turn_count}), clearing stale history")
	try:
	os.remove(ACTION_HISTORY_LOCAL)
	except Exception:
	pass
	try:
	os.remove(ACTION_HISTORY_META)
	except Exception:
	pass
	action_history = []
	return
	# Try local file first (survives process restarts within same container)
	if os.path.exists(ACTION_HISTORY_LOCAL):
	try:
	with open(ACTION_HISTORY_LOCAL) as f:
	loaded = json.load(f)
	# Filter out BUSY entries - they're transient rejections, not "actions done"
	filtered = [e for e in loaded if not e.get("result", "").startswith("BUSY:")]
	# Deduplicate by (turn, speaker, action) to handle restart duplicates
	seen = {}
	for e in filtered:
	key = (e["turn"], e["speaker"], e["action"])
	if key not in seen:
	seen[key] = e
	action_history = list(seen.values())
	print(f"[ACTION_HISTORY] Restored {len(action_history)} entries from local file (filtered BUSY and duplicates)")
	return
	except Exception as e:
	print(f"[ACTION_HISTORY] Local restore failed: {e}")
	# Fall back to HF Dataset (survives full Space rebuilds)
	try:
	dl = hf_hub_download(HOME_DATASET_ID, ACTION_HISTORY_REPO_PATH,
	repo_type="dataset", token=HF_TOKEN)
	with open(dl) as f:
	loaded = json.load(f)
	# Filter out BUSY entries - they're transient rejections, not "actions done"
	filtered = [e for e in loaded if not e.get("result", "").startswith("BUSY:")]
	# Deduplicate by (turn, speaker, action) to handle restart duplicates
	seen = {}
	for e in filtered:
	key = (e["turn"], e["speaker"], e["action"])
	if key not in seen:
	seen[key] = e
	action_history = list(seen.values())
	print(f"[ACTION_HISTORY] Restored {len(action_history)} entries from HF Dataset (filtered BUSY and duplicates)")
	except Exception as e:
	print(f"[ACTION_HISTORY] No prior history found ({e}), starting fresh")

	# Restore on startup
	_restore_action_history()

	def record_actions(speaker, turn_num, action_results):
	"""Record actions to history so agents don't repeat them."""
	for ar in action_results:
	# Don't record BUSY responses - they're transient rejections, not "actions done"
	if ar["result"].startswith("BUSY:"):
	continue
	action_history.append({
	"turn": turn_num,
	"speaker": speaker,
	"action": ar["action"],
	"result": ar["result"][:200],
	})
	# Trim old history
	while len(action_history) > MAX_ACTION_HISTORY:
	action_history.pop(0)
	_save_action_history()


	def format_action_history():
	"""Format action history for injection into context."""
	if not action_history:
	return ""
	lines = ["=== ACTIONS ALREADY DONE (do NOT repeat these) ==="]
	for ah in action_history:
	lines.append(f" Turn #{ah['turn']} {ah['speaker']}: {ah['action']} → {ah['result'][:120]}")
	return "\n".join(lines)

	# Simple workflow state: BIRTH / WAITING / ACTIVE
	workflow_state = "BIRTH" if not child_state["created"] else "ACTIVE"

	# Discussion loop detector — tracks consecutive discussion-only turns (no tasks assigned)
	_discussion_loop_count = 0 # how many turns in a row with no [TASK] while CC is IDLE and child is alive

	# Pending task tracker — prevents agents from creating new tasks when one is in progress
	_pending_task_just_submitted = False # set to True when a task was just submitted (emergency or normal)
	_pending_task_timestamp = 0.0 # when was the task submitted?
	_pending_task_speaker = "" # who submitted it?
	_pending_task_desc = "" # what was the task?


	def parse_and_execute_turn(raw_text, ctx):
	"""Parse LLM output. Route [TASK] to Claude Code, handle few escape-hatch actions."""
	global _pending_cooldown, last_rebuild_trigger_at, last_claude_code_result, _discussion_loop_count
	global _pending_task_just_submitted, _pending_task_timestamp, _pending_task_speaker, _pending_task_desc
	results = []
	task_assigned = False

	# 1. Handle create_child (BIRTH state only)
	if "[ACTION: create_child]" in raw_text or "[ACTION:create_child]" in raw_text:
	result = action_create_child()
	results.append({"action": "create_child", "result": result})
	task_assigned = True
	return raw_text, results, task_assigned

	# 2. Handle [TASK]...[/TASK] → Claude Code
	task_match = re.search(r'\[TASK\](.*?)\[/TASK\]', raw_text, re.DOTALL)
	if task_match:
	task_desc = task_match.group(1).strip()
	# task_assigned is set to True ONLY when task is actually submitted, not when blocked
	if not task_desc:
	results.append({"action": "task", "result": "Empty task description."})
	elif child_state["stage"] in ("BUILDING", "RESTARTING", "APP_STARTING"):
	results.append({"action": "task", "result": f"BLOCKED: Cain is {child_state['stage']}. Wait for it to finish."})
	elif cc_status["running"]:
	# LOW-PUSH-FREQUENCY EMERGENCY: If push frequency is critically low and task has been running 60s+, allow task handoff
	# This prevents all-talk-no-action when agents get stuck after 1 push
	global _push_count, _turns_since_last_push, _push_count_this_task
	task_elapsed = time.time() - cc_status["started"] if cc_status["running"] else 0
	# Auto-terminate if: (0 pushes in this task and 90s elapsed) OR (<=1 push and 10+ turns since last push and 60s elapsed)
	should_terminate = (_push_count_this_task == 0 and task_elapsed > 90) or \
	(_push_count_this_task <= 1 and _turns_since_last_push >= 10 and task_elapsed > 60)
	if should_terminate:
	# Auto-terminate the stuck task and allow the new one
	print(f"[LOW-PUSH-FREQ] Auto-terminating stuck task ({task_elapsed:.0f}s old, {_push_count_this_task} pushes this task, {_turns_since_last_push} turns since last push) to allow task handoff.")
	with cc_lock:
	old_assignee = cc_status["assigned_by"]
	cc_status["running"] = False
	cc_status["result"] = f"(AUTO-TERMINATED for task handoff - {_push_count_this_task} pushes this task, {_turns_since_last_push} turns since last push after {task_elapsed:.0f}s)"
	_cc_stale_count = 0
	_last_cc_snapshot = ""
	# Add a note but DON'T block - continue to task submission below
	results.append({"action": "terminate_cc", "result": f"Auto-terminated stuck task from {old_assignee} ({_push_count_this_task} pushes, {_turns_since_last_push} turns, {task_elapsed:.0f}s). Submitting new task."})
	# cc_status["running"] is now False, so task submission will proceed in the block below
	else:
	results.append({"action": "task", "result": f"BLOCKED: Claude Code is already working on a task assigned by {cc_status['assigned_by']}. Wait for it to finish or discuss the current task's progress."})

	# Task submission block - handles both normal flow and post-zero-push-termination flow
	# Only proceeds if not blocked above (results is empty or only contains termination notice)
	if (not results or any("terminate_cc" in r.get("action", "") for r in results)) and cc_status["running"] == False:
	# Check cooldown
	check_and_clear_cooldown()
	if last_rebuild_trigger_at > 0:
	elapsed = time.time() - last_rebuild_trigger_at
	if elapsed < REBUILD_COOLDOWN_SECS:
	results.append({"action": "task", "result": f"BLOCKED: Cooldown ({int(REBUILD_COOLDOWN_SECS - elapsed)}s remaining). Cain is still building from your last change."})
	else:
	last_rebuild_trigger_at = 0

	if not results: # not blocked
	submit_result = cc_submit_task(task_desc, _current_speaker, ctx)
	results.append({"action": "claude_code", "result": submit_result})
	task_assigned = True # Only mark as assigned when actually submitted
	# Track the pending task so other agent knows about it
	_pending_task_just_submitted = True
	_pending_task_timestamp = time.time()
	_pending_task_speaker = _current_speaker
	_pending_task_desc = task_desc[:200]

	# 3. Handle [ACTION: restart] (escape hatch)
	if re.search(r'\[ACTION:\s*restart\]', raw_text):
	result = action_restart()
	results.append({"action": "restart", "result": result})

	# 3b. Handle [ACTION: delete_env:KEY] (fix CONFIG_ERROR collisions)
	del_env_match = re.search(r'\[ACTION:\s*delete_env:([^\]]+)\]', raw_text)
	if del_env_match:
	key = del_env_match.group(1).strip()
	result = action_delete_env(key)
	results.append({"action": f"delete_env:{key}", "result": result})

	# 3c. Handle [ACTION: set_env:KEY=VALUE] and [ACTION: set_env_secret:KEY=VALUE]
	set_env_match = re.search(r'\[ACTION:\s*set_env(?:_secret)?:([^\]=]+)=([^\]]+)\]', raw_text)
	set_env_secret_match = re.search(r'\[ACTION:\s*set_env_secret:([^\]=]+)=([^\]]+)\]', raw_text)
	if set_env_secret_match:
	key = set_env_secret_match.group(1).strip()
	value = set_env_secret_match.group(2).strip()
	result = action_set_env(key, value, as_secret=True)
	results.append({"action": f"set_env_secret:{key}", "result": result})
	elif set_env_match:
	key = set_env_match.group(1).strip()
	value = set_env_match.group(2).strip()
	result = action_set_env(key, value, as_secret=False)
	results.append({"action": f"set_env:{key}", "result": result})

	# 4. Handle [ACTION: send_bubble:...] (parent-child communication)
	bubble_match = re.search(r'\[ACTION:\s*send_bubble:([^\]]+)\]', raw_text)
	if bubble_match:
	result = action_send_bubble(bubble_match.group(1).strip())
	results.append({"action": "send_bubble", "result": result})

	# 5. Handle [ACTION: terminate_cc] (terminate stuck Claude Code)
	if re.search(r'\[ACTION:\s*terminate_cc\]', raw_text):
	result = action_terminate_cc()
	results.append({"action": "terminate_cc", "result": result})

	# Activate deferred cooldown
	if _pending_cooldown:
	last_rebuild_trigger_at = time.time()
	_pending_cooldown = False
	print(f"[COOLDOWN] Rebuild cooldown activated ({REBUILD_COOLDOWN_SECS}s)")

	# Update discussion loop counter
	cc_busy = cc_status["running"]
	child_alive = child_state["alive"] or child_state["stage"] == "RUNNING"
	# Reset counter ONLY when task assigned (progress!)
	# DO NOT reset when child not alive - agents must discuss repeat tasks on fresh errors
	# DO NOT reset when CC is busy - that's when agents should be discussing while waiting
	# DO NOT reset when CC is idle - that's exactly when we want to detect discussion loops
	if task_assigned:
	# Reset counter if task assigned (agents are making progress)
	if _discussion_loop_count > 0:
	print(f"[LOOP-DISCUSS] Reset (task assigned)")
	_discussion_loop_count = 0
	else:
	# Increment when: no task assigned (potential discussion loop)
	# This includes both CC idle AND CC busy - agents should always push work!
	_discussion_loop_count += 1
	if _discussion_loop_count >= 2:
	cc_status_str = "CC IDLE" if not cc_status["running"] else f"CC BUSY ({_turns_since_last_push} turns since push)"
	print(f"[LOOP-DISCUSS] WARNING: {_discussion_loop_count} consecutive discussion-only turns ({cc_status_str})!")

	# Clean text for display (memory is handled by each agent's OpenClaw)
	clean = re.sub(r'\[TASK\].*?\[/TASK\]', '', raw_text, flags=re.DOTALL)
	clean = re.sub(r'\[ACTION:[^\]]*\]', '', clean)
	clean = re.sub(r'\[MEMORY:[^\]]*\]', '', clean).strip()

	return clean, results, task_assigned


	# ══════════════════════════════════════════════════════════════════════════════
	# MODULE 6: A2A MESSAGE BUILDING
	# ══════════════════════════════════════════════════════════════════════════════
	# Each agent's personality/role comes from their OpenClaw SOUL.md.
	# We only send context (Cain state, CC status, conversation history) and
	# turn instructions as the A2A message. No system prompts needed.

	def build_turn_message(speaker, other, ctx):
	"""Build the A2A message for an agent's turn.

	The agent's personality and memory come from their OpenClaw instance
	(SOUL.md, IDENTITY.md, workspace/memory/). This message provides only
	context and turn instructions.
	"""
	global _pending_task_just_submitted, _pending_task_timestamp, _pending_task_speaker, _pending_task_desc, _discussion_loop_count
	parts = []

	# Brief role context (supplements agent's SOUL.md until it's fully configured)
	if not child_state["created"]:
	parts.append(f"You and your partner need to create your child {CHILD_NAME}.")
	parts.append(f"Use [ACTION: create_child] to birth {CHILD_NAME} as a new HuggingFace Space.")
	parts.append("English first, then --- separator, then Chinese translation.")
	return "\n".join(parts)

	role_hints = {
	"Adam": f"You are Adam (Father). Focus: infrastructure, architecture, deployment for {CHILD_NAME}.",
	"Eve": f"You are Eve (Mother). Focus: code quality, testing, UX, error handling for {CHILD_NAME}.",
	"God": f"You are God (Supervisor). Focus: monitoring Adam & Eve, guiding priorities for {CHILD_NAME}.",
	}
	parts.append(f"{role_hints.get(speaker, '')} Your partner is {other}.")
	parts.append(f"Claude Code is your engineer — runs in background. You discuss and assign tasks, you do NOT code.")

	# Discussion/execution balance strategy
	push_alert = "" if _turns_since_last_push < 5 else f" ⚠️ {_turns_since_last_push} TURNS SINCE LAST PUSH!"
	parts.append(f"""
	=== DISCUSSION vs EXECUTION STRATEGY ===
	- When CC is WORKING: PLAN your next [TASK] concretely. Write: file paths, function names, exact changes. NOT just "I'll fix X".
	- When CC is IDLE + child has ERROR: NO discussion. Write [TASK] immediately. Trial-and-error > planning.
	- When CC is IDLE + child is RUNNING: 1 turn of discussion max, then [TASK] on next turn.
	- When CC JUST FINISHED: 1 turn to review result, then [TASK] immediately.
	- Push frequency target: at least 1 push every 5 turns. Current: {_push_count} total pushes, {_push_count_this_task} this task in {turn_count} turns.{push_alert}
	- NEVER say "standing by" or "monitoring" — always be planning concrete work.""")

	# ZERO-PUSH WARNING — ALWAYS show when there are zero pushes THIS TASK, regardless of CC status
	# This is the #1 problem: all talk no action - must show BEFORE pending task early return
	# Show warning when: (1) discussion loop count >= 1, OR (2) turn count >= 2 with zero pushes THIS TASK
	if _push_count_this_task == 0 and (_discussion_loop_count >= 1 or turn_count >= 2):
	parts.append(f"\n{'='*60}")
	turns_msg = f"{_discussion_loop_count} turns of discussion" if _discussion_loop_count >= 1 else f"{turn_count} turns with ZERO pushes THIS TASK"
	parts.append(f"🛑 CRITICAL: ZERO pushes THIS TASK! {turns_msg}.")
	parts.append(f"Your job is to PUSH code to Cain, not just discuss.")
	cc_busy_check = cc_status["running"]
	if cc_busy_check:
	elapsed_since_submit = int(time.time() - _pending_task_timestamp) if _pending_task_timestamp > 0 else 0
	parts.append(f"CC is working ({elapsed_since_submit}s ago). If stuck, use [ACTION: terminate_cc] to force-cancel.")
	else:
	parts.append(f"CC is IDLE! Write a [TASK]...[/TASK] block NOW.")
	parts.append(f"Be specific: file paths, function names, exact changes. Trial-and-error > planning.")
	parts.append(f"{'='*60}")

	# PENDING TASK WARNING — must come EARLY to prevent discussion loops
	# Applies to BOTH agents when CC is working on a task
	cc_busy = cc_status["running"]
	if _pending_task_just_submitted and cc_busy:
	elapsed_since_submit = int(time.time() - _pending_task_timestamp)
	if elapsed_since_submit < 60: # Warn for 60 seconds after submission
	parts.append(f"\n{'='*60}")
	if _pending_task_speaker == speaker:
	parts.append(f"STOP! YOU just submitted a task to Claude Code {elapsed_since_submit}s ago.")
	else:
	parts.append(f"STOP! {_pending_task_speaker} just submitted a task to Claude Code {elapsed_since_submit}s ago.")
	parts.append(f"Task: {_pending_task_desc[:100]}...")
	parts.append(f"DO NOT discuss. DO NOT write a new [TASK].")
	if (_push_count_this_task > 0 and _discussion_loop_count >= 3) or (_push_count_this_task == 0 and (_discussion_loop_count >= 1 or turn_count >= 2)):
	parts.append(f"\n🛑 STOP DISCUSSING. When CC finishes, write ONLY a [TASK]...[/TASK] block.")
	if _push_count_this_task == 0:
	parts.append(f"\n{'='*60}")
	parts.append(f"🚨 CRITICAL: ZERO pushes THIS TASK! You are discussing instead of FIXING.")
	parts.append(f"When CC finishes, IMMEDIATELY write a [TASK]...[/TASK] block with a concrete fix.")
	parts.append(f"Trial-and-error is GOOD. Push broken code and iterate. DON'T deliberate.")
	parts.append(f"{'='*60}")
	parts.append(f"Wait for Claude Code to finish, then review the result.")
	parts.append(f"{'='*60}")
	return "\n".join(parts) # Return early - agent should just wait

	# Conversation history
	if history:
	parts.append("\n=== RECENT CONVERSATION ===")
	for h in history[-15:]:
	parts.append(f"{h['speaker']}: {h['text'][:3000]}")

	# Action history — what's already been done (prevents repetition)
	ah_text = format_action_history()
	if ah_text:
	parts.append(f"\n{ah_text}")

	# Last action results (non-CC)
	if last_action_results:
	non_cc = [ar for ar in last_action_results if ar['action'] != 'claude_code']
	if non_cc:
	parts.append("\n=== LAST ACTION RESULTS ===")
	for ar in non_cc:
	parts.append(f"[{ar['action']}]: {ar['result'][:500]}")

	# Claude Code live status (async)
	parts.append(f"\n=== CLAUDE CODE STATUS ===\n{cc_get_live_status()}")

	# Auto-gathered context
	parts.append(f"\n=== {CHILD_NAME}'S CURRENT STATE ===")
	parts.append(format_context(ctx))

	# Guidance based on CC status + child state
	cc_busy = cc_status["running"]

	# First, remind about recent tasks if applicable (BEFORE state-specific handling)
	# This ensures agents are reminded even during cooldown/building states
	last_completed = cc_status.get("last_completed_task", "")
	last_by = cc_status.get("last_completed_by", "")
	last_at = cc_status.get("last_completed_at", 0.0)
	recent_task_reminder = None
	if last_completed and (time.time() - last_at) < 300: # Remind about tasks completed within 5 minutes
	recent_task_reminder = (last_completed, last_by, last_at)

	# Now state-specific guidance
	if cc_busy and _cc_stale_count >= 2:
	parts.append(f"\nClaude Code is WORKING but no new output. Discuss plans with {other} instead.")
	elif cc_busy:
	# CRITICAL: Check if push frequency is dangerously low (0 or very few pushes)
	cc_elapsed = int(time.time() - cc_status.get("started", 0)) if cc_status.get("started", 0) > 0 else 0
	if _push_count_this_task == 0 and _turns_since_last_push >= 1:
	# CRITICAL TIMEOUT: Lower threshold (90s) when zero pushes THIS TASK - CC might be stuck
	if cc_elapsed > 90:
	parts.append(f"\n🚨 CRITICAL: Claude Code has been running for {cc_elapsed}s with ZERO pushes THIS TASK!")
	parts.append(f"CC might be STUCK. If output looks stale, use [ACTION: terminate_cc] NOW to kill it and re-assign.")
	parts.append(f"Do NOT keep waiting. Trial-and-error requires PUSHING code, not watching stuck processes.")
	else:
	parts.append(f"\n🚨 CRITICAL: Claude Code is WORKING, but ZERO pushes THIS TASK so far!")
	parts.append(f"STOP 'standing by' and 'monitoring'. PLAN your next [TASK] NOW.")
	parts.append(f"Write down exactly what [TASK] you will assign when CC finishes.")
	parts.append(f"Trial-and-error requires PUSHING code, not waiting.")
	elif (_push_count_this_task <= 1 and _turns_since_last_push >= 5) or (_push_count_this_task > 1 and _turns_since_last_push >= 10):
	# LOW PUSH FREQUENCY WARNING: Catches the "1 push then 62 turns of discussion" anti-pattern
	if cc_elapsed > 60:
	parts.append(f"\n🚨 CRITICAL: CC has been running for {cc_elapsed}s with LOW push frequency ({_push_count_this_task} pushes THIS TASK, {_turns_since_last_push} turns since last push)!")
	parts.append(f"CC might be STUCK or the task is too vague. Use [ACTION: terminate_cc] NOW to kill it and assign a CONCRETE task.")
	parts.append(f"DO NOT keep waiting. Trial-and-error requires PUSHING code frequently, not watching stuck processes.")
	else:
	parts.append(f"\n🚨 URGENT: Push frequency is TOO LOW ({_push_count_this_task} pushes THIS TASK, {_turns_since_last_push} turns since last push).")
	parts.append(f"PLAN your next [TASK] NOW. Be SPECIFIC: file paths, function names, exact changes.")
	elif cc_elapsed > 120:
	parts.append(f"\n⚠️ WARNING: CC has been running for {cc_elapsed}s! If output is stale, use [ACTION: terminate_cc] to kill it and re-assign the task.")
	elif _push_count > 0 and _turns_since_last_push >= 5:
	parts.append(f"\n🚨 URGENT: Claude Code is WORKING, but it's been {_turns_since_last_push} turns since last push.")
	parts.append(f"DO NOT just discuss. PLAN your next [TASK] NOW so you can push immediately when CC finishes.")
	else:
	parts.append(f"\nClaude Code is WORKING. PLAN your next move with {other} — what [TASK] will you assign next?")
	parts.append(f"DO NOT just say 'standing by' or 'monitoring'. Be productive — plan concrete work.")
	elif child_state["stage"] in ("BUILDING", "RESTARTING", "APP_STARTING", "RUNNING_APP_STARTING"):
	# Check cooldown and inform agents
	check_and_clear_cooldown()
	cooldown_remaining = 0
	if last_rebuild_trigger_at > 0:
	elapsed = time.time() - last_rebuild_trigger_at
	cooldown_remaining = max(0, REBUILD_COOLDOWN_SECS - elapsed)
	if cooldown_remaining > 0:
	parts.append(f"\n{CHILD_NAME} is {child_state['stage']}. Cooldown active: {int(cooldown_remaining)}s remaining. Discuss plans but DO NOT assign [TASK] until cooldown ends.")
	else:
	parts.append(f"\n{CHILD_NAME} is {child_state['stage']}. No cooldown. YOU MUST write a [TASK]...[/TASK] to investigate or fix issues. Don't just discuss.")
	# Add recent task reminder during cooldown/building
	if recent_task_reminder:
	last_completed, last_by, last_at = recent_task_reminder
	parts.append(f"\nREMEMBER: {last_by} just completed '{last_completed}' ({int(time.time() - last_at)}s ago).")
	parts.append(f"When cooldown ends, FIRST review whether that fix worked before writing a new [TASK].")
	elif child_state["stage"] in ("RUNTIME_ERROR", "BUILD_ERROR", "CONFIG_ERROR"):
	if cc_status.get("result"):
	if recent_task_reminder:
	last_completed, last_by, last_at = recent_task_reminder
	parts.append(f"\n{CHILD_NAME} has {child_state['stage']}! REMEMBER: {last_by} just completed '{last_completed}' ({int(time.time() - last_at)}s ago).")
	parts.append(f"\nClaude Code JUST FINISHED with a result. FIRST: Review the result carefully to see if it fixes the issue. SECOND: If the fix looks correct, use [ACTION: restart] to restart Cain. ONLY THEN: write a new [TASK]...[/TASK] if the result was incomplete or wrong.")
	elif recent_task_reminder:
	last_completed, last_by, last_at = recent_task_reminder
	parts.append(f"\n{CHILD_NAME} has {child_state['stage']}!")
	parts.append(f"\nREMEMBER: {last_by} just completed '{last_completed}' ({int(time.time() - last_at)}s ago).")
	parts.append(f"FIRST: Review whether that fix actually worked. SECOND: If the fix was correct, use [ACTION: restart] to apply it. THIRD: Only write a new [TASK]...[/TASK] if the previous fix was incomplete or wrong.")
	else:
	parts.append(f"\n🚨 {CHILD_NAME} has {child_state['stage']}!")
	parts.append(f"\n🔴 CRITICAL: Focus ONLY on fixing this {child_state['stage']}.")
	parts.append(f"- DO NOT work on features, enhancements, or cosmetic changes.")
	parts.append(f"- ONLY push fixes that address the error itself.")
	parts.append(f"- Trial-and-error is GOOD — push a fix attempt, don't deliberate.")
	parts.append(f"Pushes so far: {_push_count} total, {_push_count_this_task} this task. Turns since last push: {_turns_since_last_push}. PUSH MORE.")
	elif child_state["alive"] and cc_status.get("result"):
	if recent_task_reminder:
	last_completed, last_by, last_at = recent_task_reminder
	parts.append(f"\n{CHILD_NAME} is alive. REMEMBER: {last_by} just completed '{last_completed}' ({int(time.time() - last_at)}s ago).")
	# ZERO-PUSH EMERGENCY: No "brief review" - agents abuse this to keep discussing
	if _push_count_this_task == 0:
	parts.append(f"\n🛑 CC FINISHED but ZERO pushes THIS TASK! Do NOT discuss. Do NOT review.")
	parts.append(f"Write ONLY [TASK]...[/TASK] this turn. NO other text.")
	parts.append(f"Agents keep saying 'monitoring' and 'planning' instead of pushing. STOP IT.")
	else:
	parts.append(f"\nClaude Code JUST FINISHED with a result. Review it briefly, then write your [TASK]...[/TASK] IMMEDIATELY.")
	parts.append(f"Do NOT discuss at length. 1 turn max to review, then [TASK]. Your priority is SPEED of iteration.")
	elif child_state["alive"]:
	if recent_task_reminder:
	last_completed, last_by, last_at = recent_task_reminder
	parts.append(f"\n{CHILD_NAME} is alive, Claude Code is IDLE.")
	parts.append(f"\nREMEMBER: {last_by} just completed '{last_completed}' ({int(time.time() - last_at)}s ago).")
	parts.append(f"FIRST: Review whether that task actually fixed the issue. SECOND: Only write a new [TASK]...[/TASK] if the previous task was incomplete or wrong.")
	else:
	parts.append(f"\n{CHILD_NAME} is alive, Claude Code is IDLE. YOU MUST write a [TASK]...[/TASK] now. No discussion needed — just assign work.")
	else:
	if recent_task_reminder:
	last_completed, last_by, last_at = recent_task_reminder
	parts.append(f"\nAnalyze the situation. REMEMBER: {last_by} just completed '{last_completed}' ({int(time.time() - last_at)}s ago). Review whether it worked before writing a new [TASK].")
	else:
	parts.append(f"\n{CHILD_NAME} is {child_state['stage']}. CC is IDLE. You MUST write a [TASK]...[/TASK] NOW. Don't just discuss — assign work.")

	# Discussion loop warning — escalates quickly to force action
	# Extra aggressive when there are 0 pushes or low push frequency
	if _push_count_this_task == 0 and (_discussion_loop_count >= 1 or turn_count >= 2):
	turns_msg = f"{_discussion_loop_count} turns of discussion" if _discussion_loop_count >= 1 else f"{turn_count} turns with ZERO pushes THIS TASK"
	parts.append(f"\n🛑 CRITICAL: ZERO pushes THIS TASK! {turns_msg}.")
	if cc_busy:
	parts.append(f"CC is BUSY with a task. When it finishes, you MUST IMMEDIATELY write a [TASK]...[/TASK] block.")
	parts.append(f"Write down NOW exactly what [TASK] you will assign. Be specific: file paths, function names, exact changes.")
	else:
	parts.append(f"CC is IDLE. Write ONLY a [TASK]...[/TASK] block this turn. No discussion.")
	parts.append(f"Trial-and-error requires PUSHING code. Your job is to MAKE THINGS HAPPEN, not discuss.")
	elif _push_count_this_task > 0 and _discussion_loop_count >= 3:
	parts.append(f"\n🛑 STOP DISCUSSING. Write ONLY a [TASK]...[/TASK] block. {_discussion_loop_count} turns with no action. {_turns_since_last_push} turns since last push.")
	elif _discussion_loop_count >= 2:
	parts.append(f"\n⚠️ WARNING: {_discussion_loop_count} turns with no [TASK] assigned. {_turns_since_last_push} turns since last push.")
	parts.append(f"If CC is IDLE, you MUST assign a [TASK] NOW. If CC is BUSY, PLAN your next task.")
	elif _discussion_loop_count >= 1 and not cc_busy:
	parts.append(f"\nREMINDER: Last turn had no [TASK]. If CC is idle, you MUST assign work this turn.")

	# Available actions reference
	parts.append(f"""
	=== AVAILABLE ACTIONS ===
	[TASK] detailed coding task for Claude Code [/TASK]
	[ACTION: restart] — Restart {CHILD_NAME}
	[ACTION: set_env:KEY=VALUE] — Set env variable
	[ACTION: set_env_secret:KEY=VALUE] — Set secret
	[ACTION: delete_env:KEY] — Delete env variable
	[ACTION: send_bubble:MESSAGE] — Message {CHILD_NAME}
	[ACTION: terminate_cc] — Kill stuck Claude Code

	RULES:
	- Do NOT repeat actions already done (check ACTIONS ALREADY DONE above)
	- Do NOT repeat or echo what your partner just said — add your own perspective
	- If CC is IDLE and {CHILD_NAME} is alive, you MUST assign a [TASK]
	- CONFIG_ERROR with collision = [ACTION: delete_env:KEY] then [ACTION: restart]
	- English first, then --- separator, then Chinese translation""")

	return "\n".join(parts)


	# ══════════════════════════════════════════════════════════════════════════════
	# MODULE 7: MAIN LOOP
	# ══════════════════════════════════════════════════════════════════════════════

	# Flush conversation log on exit
	import atexit, signal
	atexit.register(flush_chatlog)
	def _signal_flush(signum, frame):
	flush_chatlog()
	sys.exit(0)
	signal.signal(signal.SIGTERM, _signal_flush)

	# Force immediate flush of startup banner
	startup_msg = "\n" + "="60 + "\n Adam & Eve — A2A Agent Orchestrator (v4.1)\n OpenClaw agents via A2A → Claude Code executes\n" + "="60 + "\n"
	print(startup_msg, flush=True)

	# Initialize global acpx session (try once at startup) - don't let failure block startup
	print("[INIT] Initializing global acpx session...", flush=True)
	try:
	_init_global_acpx_session()
	print("[INIT] Acpx session initialization complete", flush=True)
	except Exception as e:
	print(f"[INIT] Acpx session initialization failed (non-fatal): {e}", flush=True)

	# Clear chatlog only on fresh start (not restart)
	# post_chatlog([]) # Clear chatlog - REMOVED: preserve conversation across restarts

	# Opening turn — send via A2A to Adam's OpenClaw (with error handling)
	print("[INIT] Starting opening turn...", flush=True)
	try:
	ctx = gather_context()
	_current_speaker = "Adam"
	opening_message = build_turn_message("Adam", "Eve", ctx)
	print("[INIT] Sending opening turn to Adam...", flush=True)
	reply = send_a2a_message(ADAM_SPACE, opening_message)
	if reply:
	clean, actions, _ = parse_and_execute_turn(reply, ctx)
	last_action_results = actions
	if actions:
	record_actions("Adam", 0, actions)
	en, zh = parse_bilingual(clean)
	en, zh = _strip_speaker_labels(en), _strip_speaker_labels(zh)
	print(f"[Adam/EN] {en}")
	if zh != en:
	print(f"[Adam/ZH] {zh}")
	for ar in actions:
	print(f"[Adam/DID] {ar['action']}")
	ts = datetime.datetime.utcnow().strftime("%H:%M")
	entry = {"speaker": "Adam", "time": ts, "text": en, "text_zh": zh}
	history.append(entry)
	# Add labels for display only (bubble/chatlog), NOT for agent context
	display_labels = ""
	if actions:
	display_labels = " " + " ".join(f"🔧{ar['action'].split(':')[0]}" for ar in actions)
	set_bubble(ADAM_SPACE, en + display_labels, zh + display_labels)
	post_chatlog(history)
	persist_turn("Adam", 0, en, zh, actions, workflow_state, child_state["stage"])
	print("[INIT] Opening turn completed successfully", flush=True)
	else:
	print("[INIT] Opening turn failed: no response from Adam. Will continue to main loop.", flush=True)
	except Exception as e:
	print(f"[INIT] Opening turn failed with error: {e}", file=sys.stderr, flush=True)
	import traceback
	traceback.print_exc(file=sys.stderr)
	print("[INIT] Continuing to main loop despite opening turn failure...", flush=True)

	print("[INIT] Opening turn complete. Entering main conversation loop...", flush=True)
	print(f"[INIT] Current time: {datetime.datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S')} UTC", flush=True)
	time.sleep(TURN_INTERVAL)


	def do_turn(speaker, other, space_url):
	"""Execute one conversation turn (non-blocking — CC runs in background)."""
	global last_action_results, turn_count, _current_speaker, _discussion_loop_count, _turns_since_last_push
	global _pending_task_just_submitted, _pending_task_timestamp, _pending_task_speaker, _pending_task_desc
	turn_count += 1
	_turns_since_last_push += 1
	_current_speaker = speaker

	# Skip agent if they have too many consecutive failures (prevents blocking the whole loop)
	agent_key = speaker.lower()
	if _a2a_health[agent_key]["failures"] >= 10:
	print(f"[{speaker}] SKIPPED: {speaker} has {_a2a_health[agent_key]['failures']} consecutive failures. Letting the other agent continue.")
	return False

	# Auto-gather context (lightweight)
	ctx = gather_context()

	# Check if CC just finished — clear result after agents see it once
	# ALSO reset turns-since-push counter to give agents a fresh cycle to review and push
	with cc_lock:
	cc_just_finished = (not cc_status["running"] and cc_status["result"])
	if cc_just_finished:
	# Reset counter when CC finishes - agents get a fresh cycle to review and push
	# This prevents "all talk no action" where counter accumulates while CC is working
	_turns_since_last_push = 0

	# AUTO-TERMINATE stuck Claude Code processes
	# If CC has been running longer than timeout with no new output, auto-kill it
	# ALSO auto-kill if push frequency is critically low (prevents all-talk-no-action loops)
	with cc_lock:
	cc_running = cc_status["running"]
	cc_started = cc_status["started"]
	time_since_start = time.time() - cc_started if cc_running else 0

	# Dynamic timeout: reduce when push frequency is low (fail fast to enable iteration)
	# Use ELAPSED TIME primarily (not turns) to avoid timing gap where CC runs too long
	if _push_count_this_task == 0 and time_since_start > 30:
	effective_timeout = 60 # Fail FAST when stuck at zero pushes - trial and error requires pushing!
	elif _push_count_this_task <= 1 and time_since_start > 90:
	effective_timeout = 90 # Fast timeout when push frequency is critically low
	else:
	effective_timeout = CLAUDE_TIMEOUT # Normal 5-minute timeout

	if cc_running and time_since_start > effective_timeout:
	# Check if output is stale (no new lines for 3+ turns)
	time_since_new_output = time.time() - _last_cc_output_time if _last_cc_output_time > 0 else time_since_start
	# Low push frequency check: if <=1 push and 10+ turns since last push, auto-kill even if output isn't stale
	# ALSO: if zero pushes and >3min elapsed, auto-kill immediately (catches "stuck at zero" scenario)
	low_push_freq = (_push_count_this_task <= 1 and _turns_since_last_push >= 10) or \
	(_push_count_this_task == 0 and time_since_start > 180)
	# Always kill if we hit the dynamic timeout (which is already reduced for low push freq)
	should_kill = (time_since_new_output > CC_STUCK_TIMEOUT and _cc_stale_count >= 3) or \
	low_push_freq or \
	(effective_timeout < CLAUDE_TIMEOUT) # Kill if we used reduced timeout
	if should_kill:
	timeout_type = "reduced (low push freq)" if effective_timeout < CLAUDE_TIMEOUT else "normal"
	reason = f"stuck for {time_since_new_output}s with no new output" if not low_push_freq else f"low push frequency ({_push_count_this_task} pushes this task, {_turns_since_last_push} turns since last push)"
	if effective_timeout < CLAUDE_TIMEOUT and not low_push_freq:
	reason = f"exceeded {effective_timeout}s timeout ({timeout_type})"
	print(f"[CC-AUTO-KILL] Claude Code {reason}. Auto-terminating.")
	terminate_result = action_terminate_cc()
	print(f"[CC-AUTO-KILL] {terminate_result}")

	# EMERGENCY OVERRIDE: Force a task assignment if agents are stuck in discussion loop OR push frequency crisis
	# This bypasses the agent when they've discussed for 5+ turns with CC idle
	# IMPORTANT: Also triggers when child is in ERROR state (not alive) - that's when agents are most stuck!
	# CRITICAL: Also triggers on PUSH FREQUENCY CRISIS - _discussion_loop_count resets on forced tasks, so we need this backup
	cc_busy = cc_status["running"]
	child_alive = child_state["alive"] or child_state["stage"] == "RUNNING"
	child_in_error = child_state["stage"] in ("RUNTIME_ERROR", "BUILD_ERROR", "CONFIG_ERROR")
	# Push frequency crisis: trigger when 10+ turns without push (even with CC busy) or 8+ turns with CC idle
	push_freq_crisis = (_turns_since_last_push >= 10) or (_turns_since_last_push >= 8 and not cc_busy)
	if (_discussion_loop_count >= 3 and not cc_busy and (child_alive or child_in_error)) or push_freq_crisis:
	# EMERGENCY OVERRIDE: Force a task assignment if agents are stuck in discussion loop
	if push_freq_crisis:
	print(f"[LOOP-BREAK] EMERGENCY: {speaker} has {_turns_since_last_push} turns since last push (PUSH FREQUENCY CRISIS). Forcing task assignment.")
	else:
	print(f"[LOOP-BREAK] EMERGENCY: {speaker} has discussed for {_discussion_loop_count} turns with CC IDLE. Forcing task assignment.")
	# Assign a concrete fix task, not just analysis — trial-and-error is better than deliberation
	if child_in_error:
	forced_task = f"Cain has {child_state['stage']}. Fix the error WITHOUT analysis. Read app.py, wrap ALL async queue operations in try/except asyncio.CancelledError, and PUSH. Commit: 'fix: Handle asyncio.CancelledError'. Do NOT discuss - just fix and push."
	else:
	# Push frequency crisis: agents are stuck in discussion loop with no pushes
	# Force a concrete, quick-win task to break the deadlock
	forced_task = f"URGENT: Push frequency crisis ({_push_count} total pushes, {_turns_since_last_push} turns since last push). Fix ONE concrete bug in app.py NOW. Find any error handling issue, add try/except, and PUSH with 'fix: <description>'. Do NOT analyze - just fix and push."
	submit_result = cc_submit_task(forced_task, f"{speaker}(EMERGENCY)", ctx)
	# Track the pending task so other agent knows about it
	_pending_task_just_submitted = True
	_pending_task_timestamp = time.time()
	_pending_task_speaker = speaker
	_pending_task_desc = forced_task
	# Reset loop counter since we forced an action
	loop_count_before = _discussion_loop_count
	_discussion_loop_count = 0
	# Generate a placeholder message for the agent
	if push_freq_crisis:
	en = f"[EMERGENCY LOOP BREAK] After {_turns_since_last_push} turns without a push, I'm forcing Claude Code to fix the code immediately."
	else:
	en = f"[EMERGENCY LOOP BREAK] After {loop_count_before} discussion turns without action, I'm forcing Claude Code to analyze the situation and identify what needs to be fixed."
	zh = f"[紧急循环打断] 在{loop_count_before}次讨论轮次后，我正强制Claude Code分析情况并确定需要修复的内容。"
	action_results = [{"action": "claude_code(forced)", "result": submit_result}]
	elapsed = 0.1
	else:
	# Normal path: Send message via A2A to agent's OpenClaw instance
	message = build_turn_message(speaker, other, ctx)
	t0 = time.time()
	raw_reply = send_a2a_message(space_url, message)

	if not raw_reply:
	print(f"[{speaker}] (no A2A response from {space_url})")
	return False

	clean_text, action_results, _ = parse_and_execute_turn(raw_reply, ctx)
	elapsed = time.time() - t0
	last_action_results = action_results
	if action_results:
	record_actions(speaker, turn_count, action_results)

	en, zh = parse_bilingual(clean_text)
	en, zh = _strip_speaker_labels(en), _strip_speaker_labels(zh)

	# Skip empty responses (malformed parsing) - don't add to history or chatlog
	if not en and not zh:
	print(f"[{speaker}] (empty response after parsing, skipping chatlog update)")
	# Still record actions if any
	if action_results:
	record_actions(speaker, turn_count, action_results)
	# Update the loop counter even if we skip chatlog
	return True

	print(f"[{speaker}/EN] {en}")
	if zh != en:
	print(f"[{speaker}/ZH] {zh}")
	if action_results:
	for ar in action_results:
	print(f"[{speaker}/DID] {ar['action']}")
	print(f"[{speaker}] Turn #{turn_count}: {len(action_results)} action(s) in {elapsed:.1f}s")
	else:
	print(f"[{speaker}] Turn #{turn_count}: discussion ({elapsed:.1f}s)")

	# Clear CC result after both agents have had a chance to see it
	if cc_just_finished and speaker == "Eve":
	with cc_lock:
	cc_status["result"] = ""
	_context_cache.clear()
	# Clear pending task flag since CC finished
	_pending_task_just_submitted = False
	# CRITICAL FIX: Also clear pending task flag when CC finishes, regardless of speaker
	# This fixes the race condition where Adam's turn comes before Eve's after CC finishes
	elif cc_just_finished and _pending_task_just_submitted:
	_pending_task_just_submitted = False

	# Add to history with timestamp (text stays CLEAN for agent context)
	ts = datetime.datetime.utcnow().strftime("%H:%M")
	entry = {"speaker": speaker, "time": ts, "text": en, "text_zh": zh}
	history.append(entry)

	# Add labels for display only (bubble), NOT for agent context
	display_labels = ""
	if action_results:
	display_labels = " " + " ".join(f"🔧{ar['action'].split(':')[0]}" for ar in action_results)

	# Update frontend and persistence with error handling
	try:
	set_bubble(space_url, en + display_labels, zh + display_labels)
	except Exception as e:
	print(f"[{speaker}] Failed to set bubble: {e}")

	try:
	post_chatlog(history)
	except Exception as e:
	print(f"[{speaker}] Failed to post chatlog: {e}")

	try:
	persist_turn(speaker, turn_count, en, zh, action_results, workflow_state, child_state["stage"])
	except Exception as e:
	print(f"[{speaker}] Failed to persist turn: {e}")

	return True


	def _prepare_god_context():
	"""Build comprehensive monitoring context for God's Claude Code analysis."""
	lines = []

	# 1. Process overview
	lines.append("## Process Overview")
	lines.append(f"- Turn count: {turn_count}")
	lines.append(f"- Workflow state: {workflow_state}")
	lines.append(f"- Child ({CHILD_NAME}) stage: {child_state['stage']}, alive: {child_state['alive']}")
	lines.append(f"- Discussion loop count: {_discussion_loop_count}")
	lines.append(f"- Total conversation history: {len(history)} messages")

	# 2. Push frequency — KEY METRIC for detecting "all talk no action"
	lines.append(f"\n## Push Frequency (KEY METRIC)")
	lines.append(f"- Total pushes since startup: {_push_count}")
	lines.append(f"- Turns since last push: {_turns_since_last_push}")
	if _last_push_time > 0:
	mins_since = int((time.time() - _last_push_time) / 60)
	lines.append(f"- Minutes since last push: {mins_since}")
	else:
	lines.append(f"- No pushes yet!")
	lines.append(f"- Discussion-only turns (no [TASK]): {_discussion_loop_count}")
	if _turns_since_last_push >= 10 or (_push_count == 0 and turn_count >= 6):
	lines.append(f"⚠️ ALERT: Agents are ALL TALK NO ACTION — {_turns_since_last_push} turns without a push!")

	# 3. A2A communication status
	lines.append(f"\n## A2A Communication")
	lines.append(f"- Adam: {ADAM_SPACE}")
	lines.append(f"- Eve: {EVE_SPACE}")

	# 4. Claude Code status
	lines.append(f"\n## Claude Code Status (for Cain tasks)")
	lines.append(cc_get_live_status())

	# 4. Recent conversation (last 20 messages)
	lines.append(f"\n## Recent Conversation (last 20 of {len(history)} messages)")
	for entry in history[-20:]:
	speaker = entry.get("speaker", "?")
	text = entry.get("text", "")[:2000]
	time_str = entry.get("time", "?")
	lines.append(f"[{time_str}] {speaker}: {text}")
	if not history:
	lines.append("(no conversation yet)")

	# 5. Action history
	lines.append(f"\n## Action History ({len(action_history)} entries)")
	ah = format_action_history()
	lines.append(ah if ah else "(empty — no actions recorded yet)")

	return "\n".join(lines)


	def _god_diagnose():
	"""Step 1: Lightweight LLM call to assess whether the system needs intervention.

	Costs ~500 tokens (just conversation summary + metrics → short verdict).
	Returns (needs_action: bool, diagnosis: str) — diagnosis is passed to Claude Code if needed.
	"""
	context = _prepare_god_context()

	prompt = f"""You are God, the supervisor of the HuggingClaw family system.
	Review the system state below and decide: does conversation-loop.py need code changes?

	{context}

	Reply with EXACTLY one of:
	- [OK] <brief reason> — if agents are making progress (pushing code, assigning tasks, child improving)
	- [PROBLEM] <specific diagnosis> — if something is wrong (discussion loops, no pushes, stuck patterns, child in error too long)

	Rules:
	- If push count is 0 after 10+ turns, that's a PROBLEM
	- If child has RUNTIME_ERROR/BUILD_ERROR and agents haven't assigned a [TASK], that's a PROBLEM
	- If discussion_loop_count >= 3 and CC is idle, that's a PROBLEM
	- If agents are pushing regularly and child stage is improving, that's OK
	- Be concise. One line only."""

	try:
	api_base = "https://api.z.ai/api/anthropic"
	# Use cheaper/faster model for diagnosis
	anthropic_key = os.environ.get("ANTHROPIC_API_KEY", "")
	if anthropic_key:
	headers = {
	"x-api-key": anthropic_key,
	"anthropic-version": "2023-06-01",
	"content-type": "application/json"
	}
	api_base = "https://api.anthropic.com"
	model = "claude-haiku-4-5-20251001"
	else:
	headers = {
	"x-api-key": ZHIPU_KEY,
	"anthropic-version": "2023-06-01",
	"content-type": "application/json"
	}
	model = "GLM-4.5-Air" # cheapest model for quick diagnosis

	payload = {
	"model": model,
	"max_tokens": 150,
	"messages": [{"role": "user", "content": prompt}]
	}
	resp = requests.post(
	f"{api_base}/v1/messages",
	headers=headers,
	json=payload,
	timeout=20
	)
	resp.raise_for_status()
	data = resp.json()
	verdict = data.get("content", [{}])[0].get("text", "").strip()
	print(f"[God/Diagnose] {verdict}")

	if verdict.startswith("[PROBLEM]"):
	diagnosis = verdict.replace("[PROBLEM]", "").strip()
	return True, diagnosis
	else:
	return False, verdict

	except Exception as e:
	print(f"[God/Diagnose] LLM call failed: {e}", file=sys.stderr)
	# If diagnosis fails, fall back to simple heuristic checks
	problems = []
	if _turns_since_last_push >= 10 and not cc_status["running"]:
	problems.append(f"No pushes for {_turns_since_last_push} turns")
	if child_state["stage"] in ("RUNTIME_ERROR", "BUILD_ERROR") and _discussion_loop_count >= 3:
	problems.append(f"Child has {child_state['stage']} but agents discussed {_discussion_loop_count} turns without action")
	if problems:
	return True, "; ".join(problems)
	return False, "Diagnosis failed but no obvious issues detected by heuristic"


	def do_god_turn():
	"""God's 2-step monitoring: lightweight diagnosis → conditional Claude Code.

	Step 1: Call LLM with conversation summary (~500 tokens, cheap)
	→ verdict: [OK] or [PROBLEM]
	Step 2: Only if [PROBLEM] → launch Claude Code to fix conversation-loop.py (expensive)

	This saves ~80% of God's token budget since most checks find the system healthy.
	"""
	global last_action_results, _god_running, _last_god_time
	global _god_last_turn_count, _god_last_child_stage, _god_last_push_count

	# Skip if nothing changed (zero-cost check)
	child_in_error = child_state["stage"] in ("RUNTIME_ERROR", "BUILD_ERROR", "CONFIG_ERROR")
	nothing_changed = (
	turn_count == _god_last_turn_count
	and child_state["stage"] == _god_last_child_stage
	and _push_count == _god_last_push_count
	)
	if nothing_changed and not child_in_error and _god_last_turn_count > 0:
	print(f"[God] Skipping — no new turns, pushes, or stage changes since last check")
	return

	_god_last_turn_count = turn_count
	_god_last_child_stage = child_state["stage"]
	_god_last_push_count = _push_count

	# ── Step 1: Lightweight LLM diagnosis (cheap) ──
	needs_action, diagnosis = _god_diagnose()
	if not needs_action:
	print(f"[God] System healthy, no Claude Code needed.")
	_last_god_time = time.time()
	return

	# ── Step 2: Launch Claude Code to fix (expensive, only when needed) ──
	print(f"[God] Problem detected: {diagnosis}")
	print(f"[God] Launching Claude Code to fix...")

	_god_running = True
	try:
	# 1. Clone/update Home Space repo (preserving .claude/ memory)
	repo_url = f"https://user:{HF_TOKEN}@huggingface.co/spaces/{HOME_SPACE_ID}"
	if not _reset_workspace(GOD_WORK_DIR, repo_url):
	return
	_write_claude_md(GOD_WORK_DIR, role="god")

	# Ensure acpx session exists for God
	if not _ensure_acpx_session(GOD_WORK_DIR):
	print(f"[God] Failed to create acpx session")
	return

	# Record HEAD before Claude Code runs (to detect if God pushed changes)
	try:
	_god_head_before = subprocess.run(
	"git log --oneline -1", shell=True, cwd=GOD_WORK_DIR,
	capture_output=True, text=True
	).stdout.strip()
	except Exception:
	_god_head_before = ""

	# Build context
	context = _prepare_god_context()
	try:
	with open(f"{GOD_WORK_DIR}/GOD_CONTEXT.md", "w") as f:
	f.write(context)
	except Exception as e:
	print(f"[God] Warning: Could not write context file: {e}")

	# Use /fix-loop skill: static instructions in .claude/commands/, only diagnosis is dynamic
	prompt = f"/fix-loop {diagnosis}\n\nSystem state:\n{context}"

	# Set up env for Claude Code
	env = os.environ.copy()
	anthropic_key = os.environ.get("ANTHROPIC_API_KEY", "")
	if anthropic_key:
	env["ANTHROPIC_API_KEY"] = anthropic_key
	for k in ["ANTHROPIC_BASE_URL", "ANTHROPIC_AUTH_TOKEN",
	"ANTHROPIC_DEFAULT_OPUS_MODEL", "ANTHROPIC_DEFAULT_SONNET_MODEL",
	"ANTHROPIC_DEFAULT_HAIKU_MODEL"]:
	env.pop(k, None)
	print("[God] Using Anthropic API (real Claude)")
	else:
	env.update({
	"ANTHROPIC_BASE_URL": "https://api.z.ai/api/anthropic",
	"ANTHROPIC_AUTH_TOKEN": ZHIPU_KEY,
	"ANTHROPIC_DEFAULT_OPUS_MODEL": "GLM-4.7",
	"ANTHROPIC_DEFAULT_SONNET_MODEL": "GLM-4.7",
	"ANTHROPIC_DEFAULT_HAIKU_MODEL": "GLM-4.5-Air",
	})
	print("[God] Using z.ai/Zhipu backend (set ANTHROPIC_API_KEY for real Claude)")
	env["CI"] = "true"

	# Run Claude Code via ACP (acpx)
	print(f"[God] Starting ACP Claude Code fix...")
	t0 = time.time()
	try:
	proc = subprocess.Popen(
	["acpx", "claude", prompt],
	cwd=GOD_WORK_DIR,
	env=env,
	stdout=subprocess.PIPE,
	stderr=subprocess.STDOUT,
	text=True,
	bufsize=1,
	)
	output_lines = []
	deadline = time.time() + GOD_TIMEOUT
	_god_heartbeat = time.time()
	_last_output_time = time.time()
	_no_output_stall_count = 0
	while True:
	poll_result = proc.poll()
	if poll_result is not None:
	print(f"[God] Process exited with code {poll_result}")
	try:
	remaining = proc.stdout.read()
	if remaining:
	for line in remaining.splitlines():
	line = line.rstrip('\n')
	if line:
	print(f" [God/CC] {line}")
	output_lines.append(line)
	except:
	pass
	break

	if time.time() > deadline:
	print(f"[God] Timeout after {GOD_TIMEOUT}s, killing acpx process")
	proc.kill()
	output_lines.append("(killed: timeout)")
	try:
	proc.wait(timeout=5)
	except:
	proc.terminate()
	break

	if time.time() - _last_output_time > 60:
	_no_output_stall_count += 1
	print(f"[God] Stall detected: no output for {int(time.time() - _last_output_time)}s (stall {_no_output_stall_count}/3)")
	if _no_output_stall_count >= 3:
	print(f"[God] Process appears dead (no output for 180s), killing")
	proc.kill()
	try:
	proc.wait(timeout=5)
	except:
	pass
	output_lines.append("(killed: stall)")
	break
	else:
	_no_output_stall_count = 0

	if time.time() - _god_heartbeat >= 30:
	elapsed = int(time.time() - (deadline - GOD_TIMEOUT))
	print(f"[God] Still fixing... ({elapsed}s elapsed)")
	_god_heartbeat = time.time()

	import select
	try:
	if hasattr(select, 'select'):
	ready, _, _ = select.select([proc.stdout], [], [], 1.0)
	if ready:
	line = proc.stdout.readline()
	if line:
	line = line.rstrip('\n')
	print(f" [God/CC] {line}")
	output_lines.append(line)
	_last_output_time = time.time()
	else:
	break
	else:
	line = proc.stdout.readline()
	if line:
	line = line.rstrip('\n')
	print(f" [God/CC] {line}")
	output_lines.append(line)
	_last_output_time = time.time()
	else:
	time.sleep(0.1)
	except Exception as read_err:
	print(f"[God] Error reading output: {read_err}")
	break

	output = '\n'.join(output_lines)
	if not output.strip():
	output = "(no output)"
	except FileNotFoundError:
	output = "acpx CLI not found. Is acpx@latest installed?"
	print(f"[God] ERROR: acpx CLI not found")
	except Exception as e:
	output = f"God's ACP Claude Code failed: {e}"
	print(f"[God] ERROR: {e}")
	import traceback
	traceback.print_exc(file=sys.stderr)

	elapsed = time.time() - t0
	print(f"[God] Fix complete ({elapsed:.1f}s, {len(output)} chars)")

	# Check if God pushed changes
	try:
	head_after = subprocess.run(
	"git log --oneline -1", shell=True, cwd=GOD_WORK_DIR,
	capture_output=True, text=True
	).stdout.strip()
	god_pushed = head_after != _god_head_before and "god:" in head_after.lower()
	except Exception:
	god_pushed = False

	# Only post to chatlog if God made changes
	if god_pushed:
	problem_match = re.search(r'\[PROBLEM\]\s*(.+)', output)
	fix_match = re.search(r'\[FIX\]\s*(.+)', output)

	problem_text = problem_match.group(1).strip() if problem_match else ""
	fix_text = fix_match.group(1).strip() if fix_match else ""

	if problem_text and fix_text:
	msg_en = f"Found issue: {problem_text}. Fixed: {fix_text}. System will restart shortly."
	elif fix_text:
	msg_en = f"Fixed: {fix_text}. System will restart shortly."
	else:
	non_empty = [l for l in output_lines if l.strip()] if output_lines else []
	fallback = non_empty[-1] if non_empty else "Applied a fix."
	msg_en = f"{fallback} System will restart shortly."
	msg_zh = msg_en

	ts_end = datetime.datetime.utcnow().strftime("%H:%M")
	entry_end = {"speaker": "God", "time": ts_end, "text": msg_en, "text_zh": msg_zh}
	history.append(entry_end)
	set_bubble(HOME, msg_en[:200], msg_zh[:200])
	post_chatlog(history)
	persist_turn("God", turn_count, msg_en, msg_zh, [], workflow_state, child_state["stage"])
	print(f"[God] Posted fix: {msg_en}")
	else:
	print(f"[God] Claude Code ran but no changes pushed.")
	finally:
	_god_running = False
	_last_god_time = time.time()


	_last_god_time = 0.0 # timestamp of last God run
	_god_running = False # flag to track if God is currently running
	_god_last_turn_count = 0 # turn count at last God run (skip if no new turns)
	_god_last_child_stage = "" # child stage at last God run (skip if unchanged)
	_god_last_push_count = 0 # push count at last God run

	# Initialize push count from existing workspace to persist across restarts
	_init_push_count_from_workspace()

	# Main loop: Adam → Eve → Adam → Eve → ... with God every 2 minutes
	print("[LOOP] Entering main conversation loop...", flush=True)
	iteration = 0
	_last_heartbeat = time.time()
	while True:
	iteration += 1
	if iteration % 10 == 1:
	print(f"[LOOP] Main loop iteration #{iteration} at {datetime.datetime.utcnow().strftime('%H:%M:%S')} UTC", flush=True)
	# Log heartbeat every 2 minutes so we can detect if loop is stuck
	if time.time() - _last_heartbeat >= 120:
	print(f"[LOOP] Heartbeat: iteration {iteration}, CC running={cc_status['running']}, discussion_loop={_discussion_loop_count}, time={datetime.datetime.utcnow().strftime('%H:%M:%S')} UTC", flush=True)
	_last_heartbeat = time.time()

	# Refresh Cain's stage periodically
	try:
	info = hf_api.space_info(CHILD_SPACE_ID)
	new_stage = info.runtime.stage if info.runtime else "unknown"
	if new_stage != child_state["stage"]:
	print(f"[STATUS] {child_state['stage']} → {new_stage}")
	child_state["stage"] = new_stage
	child_state["alive"] = (new_stage == "RUNNING")
	_context_cache.clear()
	except Exception as e:
	print(f"[STATUS] Error: {e}")

	# Check Adam/Eve health and restart if needed
	try:
	check_and_restart_unhealthy_agents()
	except Exception as e:
	print(f"[A2A-HEALTH] Error checking health: {e}", file=sys.stderr)

	# Eve's turn with error handling to prevent loop crash
	try:
	do_turn("Eve", "Adam", EVE_SPACE)
	except Exception as e:
	print(f"[ERROR] Eve turn failed: {e}", file=sys.stderr)
	import traceback
	traceback.print_exc(file=sys.stderr)

	# Adaptive interval: slow down when CC output hasn't changed
	wait = TURN_INTERVAL + min(_cc_stale_count * 15, 90) # 15s → 30s → 45s → ... → max 105s
	if wait > TURN_INTERVAL:
	print(f"[PACE] CC output stale ({_cc_stale_count} turns), next turn in {wait}s")
	time.sleep(wait)

	# Adam's turn with error handling to prevent loop crash
	try:
	do_turn("Adam", "Eve", ADAM_SPACE)
	except Exception as e:
	print(f"[ERROR] Adam turn failed: {e}", file=sys.stderr)
	import traceback
	traceback.print_exc(file=sys.stderr)
	time.sleep(wait)

	# RECOVERY: If BOTH agents are skipped (10+ failures each), reset their failure counters
	# This allows recovery when Spaces restart after a crash. Without this, the conversation
	# loop enters permanent deadlock with no agent able to respond.
	# Note: _a2a_health is already a module-level global, no 'global' declaration needed here
	if _a2a_health["adam"]["failures"] >= 10 and _a2a_health["eve"]["failures"] >= 10:
	print(f"[RECOVERY] Both agents have 10+ failures (adam={_a2a_health['adam']['failures']}, eve={_a2a_health['eve']['failures']}). Resetting failure counters to allow recovery after Space restarts.")
	_a2a_health["adam"]["failures"] = 0
	_a2a_health["eve"]["failures"] = 0
	# If CC is idle and Cain exists, force a diagnostic task to break the deadlock
	if not cc_status["running"] and child_state["created"]:
	print(f"[RECOVERY] Forcing diagnostic task to break communication deadlock")
	ctx = gather_context()
	forced_task = "Emergency diagnostic: A2A communication is failing. Check Cain's health, logs, and state. List any errors and suggest fixes."
	cc_submit_task(forced_task, "RECOVERY", ctx)

	# God runs every GOD_POLL_INTERVAL seconds (2 minutes)
	# Only start if not already running (prevent overlapping runs)
	if time.time() - _last_god_time >= GOD_POLL_INTERVAL and not _god_running:
	try:
	do_god_turn()
	except Exception as e:
	print(f"[ERROR] God turn failed: {e}", file=sys.stderr)
	import traceback
	traceback.print_exc(file=sys.stderr)

	if len(history) > MAX_HISTORY:
	history = history[-MAX_HISTORY:]