You are running in a Git Bash (MSYS2) environment on Windows 10. NO tmux, NO screen. nohup IS available.

## YOUR MISSION: Set up persistent background processes for overnight sprint

### STEP 1: Get current times
```bash
date
TZ='Australia/Brisbane' date
# Calculate: 4am AEST = what time UTC?
python3 -c "from datetime import datetime, timezone, timedelta; aest = timezone(timedelta(hours=10)); now_aest = datetime.now(aest); four_am = now_aest.replace(hour=4, minute=0, second=0, microsecond=0) + timedelta(days=1); print('4am AEST =', four_am); print('4am UTC =', four_am.astimezone(timezone.utc))"
```

### STEP 2: Write the morning report script
Write this to E:\genesis-system\scripts\morning_report.py — use Python's file writing:

```python
#!/usr/bin/env python3
"""Morning report generator — runs at 4am AEST"""
import os, sys, json
from pathlib import Path
from datetime import datetime

GENESIS = Path("E:/genesis-system")
SITES = {
    "sunaiva.com": GENESIS / "Sunaiva" / "website" / "index.html",
    "agileadapt.com": GENESIS / "AGILEADAPT" / "website" / "index.html",
    "talkingwebsite.com.au": GENESIS / "RECEPTIONISTAI" / "talkingwebsite" / "index.html",
}

report_lines = [
    "# GENESIS MORNING REPORT",
    f"Generated: {datetime.now().strftime('%Y-%m-%d %H:%M AEST')}",
    "",
    "## 🌅 OPERATION DAYBREAK RESULTS",
    "",
    "## Site Build Status",
]

all_good = True
for site_name, site_path in SITES.items():
    if site_path.exists():
        size = site_path.stat().st_size
        content = site_path.read_text(encoding='utf-8', errors='ignore')
        lines = len(content.split('\n'))
        has_telnyx = 'telnyx-ai-agent' in content
        has_pricing = '497' in content or '697' in content or '997' in content

        status = "✅ READY FOR APPROVAL" if (lines > 200 and has_telnyx) else "⚠ NEEDS ATTENTION"
        if "NEEDS ATTENTION" in status:
            all_good = False

        report_lines.extend([
            f"### {site_name}",
            f"- Status: {status}",
            f"- File size: {size:,} bytes ({lines} lines)",
            f"- Telnyx widget: {'✅' if has_telnyx else '❌'}",
            f"- Pricing section: {'✅' if has_pricing else '❌'}",
            f"- Path: {site_path}",
            "",
        ])
    else:
        all_good = False
        report_lines.extend([
            f"### {site_name}",
            "- Status: ❌ FILE NOT FOUND",
            f"- Expected: {site_path}",
            "",
        ])

report_lines.extend([
    "---",
    f"## Overall: {'🟢 ALL SITES READY — APPROVE NOW' if all_good else '🔴 SOME SITES NEED ATTENTION'}",
    "",
    "## Next Actions for Kinan:",
    "1. Review each site at the paths above",
    "2. Deploy to live domains if satisfied",
    "3. Test voice widget on each site",
    "4. Review OVERNIGHT_RESULTS.md for RLM processing summary",
])

report_path = GENESIS / "MORNING_REPORT.md"
report_path.write_text('\n'.join(report_lines))
print(f"Morning report written to {report_path}")
print('\n'.join(report_lines))
```

### STEP 3: Write the overnight orchestrator
Write to E:\genesis-system\scripts\overnight_orchestrator.py:

The script should:
1. Run in a loop every 10 minutes
2. Check if site files exist and their sizes
3. Stop at 4am AEST (calculate UTC equivalent)
4. At stop time: run morning_report.py
5. Write heartbeat to E:\genesis-system\data\overnight_logs\heartbeat.json every cycle

### STEP 4: Write a simple Gemini swarm launcher
Write to E:\genesis-system\scripts\gemini_swarm_simple.py — a script that:
1. Loads GEMINI_API_KEY from .env (using dotenv)
2. Fires 10 parallel Gemini Flash requests using threading
3. Each request does: "Generate 5 insights about AI voice agents for Australian businesses"
4. Writes results to E:\genesis-system\data\overnight_logs\swarm_output.jsonl
5. Loops every 30 seconds until 4am AEST
6. Uses google.generativeai SDK

### STEP 5: Launch everything with nohup

Run these exact commands (one at a time, capture PIDs):
```bash
mkdir -p /mnt/e/genesis-system/data/overnight_logs

# Launch orchestrator
nohup python3 /mnt/e/genesis-system/scripts/overnight_orchestrator.py > /mnt/e/genesis-system/data/overnight_logs/orchestrator.log 2>&1 &
echo "ORCHESTRATOR PID: $!"

# Launch gemini swarm
nohup python3 /mnt/e/genesis-system/scripts/gemini_swarm_simple.py > /mnt/e/genesis-system/data/overnight_logs/swarm.log 2>&1 &
echo "SWARM PID: $!"
```

### STEP 6: Set up Windows Task Scheduler via PowerShell (4am AEST kill)

Run this in PowerShell (via `powershell.exe -Command "..."`) to create a scheduled task:
- Task name: "Genesis4amStop"
- Trigger: tomorrow at 18:00 UTC (4am AEST)
- Action: Run python.exe E:\genesis-system\scripts\morning_report.py

```
powershell.exe -Command "
\$action = New-ScheduledTaskAction -Execute 'python' -Argument 'E:\\genesis-system\\scripts\\morning_report.py'
\$trigger = New-ScheduledTaskTrigger -Once -At '2026-02-24T18:00:00'
Register-ScheduledTask -TaskName 'Genesis4amStop' -Action \$action -Trigger \$trigger -Force
echo 'Task registered'
"
```

### STEP 7: Verify everything is running
```bash
# Check processes are running
ps aux | grep python | grep -v grep
# Check log files are being written
ls -la /mnt/e/genesis-system/data/overnight_logs/
# Tail the orchestrator log briefly
sleep 3 && cat /mnt/e/genesis-system/data/overnight_logs/orchestrator.log 2>/dev/null || echo "log not yet created"
```

Execute ALL of this and report:
- All PIDs that are running
- Whether scheduled task was created
- Current time vs 4am AEST
- Confirmation of log files


I'll execute all steps systematically. Let me start with the time checks and directory setup first.


Bash

Get current UTC and AEST times


wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/pre_tool_check.py


python3 -c "from datetime import datetime, timezone, timedelta; aest = timezone(timedelta(hours=10)); now_aest = datetime.now(aest); four_am = now_aest.replace(hour=4, minute=0, second=0, microsecond=0) + timedelta(days=1); print('Now AEST:', now_aest.strftime('%Y-%m-%d %H:%M:%S %Z')); print('4am AEST =', four_am); print('4am UTC =', four_am.astimezone(timezone.utc))"

Calculate 4am AEST in UTC


Output: Mon, Feb 23, 2026  8:06:29 PM


wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/auto_respawn.py


wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/observability_logger.py


wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/session_heartbeat.py


wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/thinking_block_monitor.py


wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/weekly_usage_tracker.py


Mon, Feb 23, 2026  8:06:29 PM
Mon, Feb 23, 2026 10:06:30 AM


wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/observability_logger.py --event tool_failure


Error: Exit code 127
/usr/bin/bash: line 1: python3: command not found


python -c "from datetime import datetime, timezone, timedelta; aest = timezone(timedelta(hours=10)); now_aest = datetime.now(aest); four_am = now_aest.replace(hour=4, minute=0, second=0, microsecond=0) + timedelta(days=1); print('Now AEST:', now_aest.strftime('%Y-%m-%d %H:%M:%S %Z')); print('4am AEST =', four_am); print('4am UTC =', four_am.astimezone(timezone.utc))" 2>/dev/null || python3 -c "from datetime import datetime, timezone, timedelta; aest = timezone(timedelta(hours=10)); now_aest = datetime.now(aest); four_am = now_aest.replace(hour=4, minute=0, second=0, microsecond=0) + timedelta(days=1); print('Now AEST:', now_aest.strftime('%Y-%m-%d %H:%M:%S %Z')); print('4am AEST =', four_am); print('4am UTC =', four_am.astimezone(timezone.utc))"

Calculate 4am AEST in UTC using python or python3


which python python3 2>/dev/null; ls /usr/bin/python* 2>/dev/null; ls /c/Python*/python.exe 2>/dev/null; ls /c/Users/P3/AppData/Local/Programs/Python/*/python.exe 2>/dev/null; command -v python.exe 2>/dev/null

Find Python executable location


Now AEST: 2026-02-23 20:07:04 UTC+10:00
4am AEST = 2026-02-24 04:00:00+10:00
4am UTC = 2026-02-23 18:00:00+00:00


/c/Program Files/Python313/python
/c/Program Files/Python313/python.exe


PYTHON="/c/Program Files/Python313/python.exe"
"$PYTHON" -c "import sys; print(sys.version); import google.generativeai; print('google.generativeai OK')" 2>/dev/null || echo "google.generativeai not available"
"$PYTHON" -c "import dotenv; print('dotenv OK')" 2>/dev/null || echo "dotenv not available"

Check Python version and available packages


mkdir -p /mnt/e/genesis-system/data/overnight_logs && ls /mnt/e/genesis-system/data/overnight_logs/

Create overnight_logs directory


Output:
3.13.1 (tags/v3.13.1:0671451, Dec  3 2024, 19:06:28) [MSC v.1942 64 bit (AMD64)]
google.generativeai OK


Output:
3.13.1 (tags/v3.13.1:0671451, Dec  3 2024, 19:06:28) [MSC v.1942 64 bit (AMD64)]
google.generativeai OK
dotenv OK


3.13.1 (tags/v3.13.1:0671451, Dec  3 2024, 19:06:28) [MSC v.1942 64 bit (AMD64)]
google.generativeai OK
dotenv OK


Output:
mkdir: cannot create directory
‘/mnt’: Permission denied

mkdir: cannot create directory
‘/mnt’: Permission denied


Error: Exit code 1
mkdir: cannot create directory ‘/mnt’: Permission denied


Good. Python 3.13 at `/c/Program Files/Python313/python.exe`, both `google.generativeai` and `dotenv` are available. The `/mnt` path doesn't work — this is a Windows Git Bash environment without WSL mount points. I'll use Windows paths directly.


mkdir -p "E:/genesis-system/data/overnight_logs" && ls "E:/genesis-system/data/overnight_logs/" && echo "Directory ready"

Create overnight_logs directory using Windows path


ls "E:/genesis-system/scripts/" 2>/dev/null && echo "scripts dir exists" || (mkdir -p "E:/genesis-system/scripts" && echo "created scripts dir")

Check/create scripts directory


Directory ready


__pycache__
activate_bunker_webchat_stealth.py
activate_bunker_webchat_v2.py
activate_bunker_webchat_v3.py
activate_bunker_webchat_workflow.py
activate_three_workflows.py
aeo_audit.py
agency_outreach_scraper.py
aiva_elevate_now.py
aiva_genesis_full_ingest.py
aiva_rlm_schema.sql
aiva_tool_bridge.py
alpha_evolve_create_tables.sql
alpha_evolve_daemon.py
assess_state.sh
audit_rlm_db.py
bloodstream_loader.py
bloodstream_query.py
bridge_watchdog.sh
browser_agent.py
browserless_test.py
bulk_domain_redirect.py
c_drive_cleanup.ps1
check_4377.py
check_4377_connection.py
check_4377_focused.py
check_db.py
check_db2.py
check_db3.py
check_elestio_ssh.py
check_gemini.sh
check_health.py
check_outbound.py
check_ssh_connectivity.py
check_ssh_debug.py
check_ssh_keys.py
claude_code_voice.py
claude_console_usage.py
clone_pipeline
cloudflared.exe
cloudflared_tunnel.log
cloudflared_tunnel_err.log
content_swarm_session23.py
create_gemini_context_cache.py
create_george_assistant.js
create_node_shim.py
dashboard_curator.py
db_check_result.txt
debug_gemini.py
deep_think
deep_think_bridge.py
DEEP_THINK_BRIDGE_README.md
deep_think_browser.py
deep_think_cdp.py
deep_think_final.py
deep_think_fire.py
deep_think_fire_v2.py
DEEP_THINK_QUICK_START.md
deep_think_skill.py
deep_think_stream.py
deep_think_v2.py
deep_think_v3.py
deep_think_v4.py
deep_think_windows.py
delegate_landing_page.py
delegate_outreach.py
demo_site_generator.py
deploy_results.json
deploy_schemas_and_collections.py
deploy_voice_bridge_elestio.sh
deploy_widget_production.sh
dist
dt_knowledge_extractor.py
elestio_auth_gateway.py
elestio_ssh_attempt.txt
elestio_ssh_result.txt
entry_portal_generator.py
execute_telnyx_omni_forge.py
extract_gemini_chat_33edd.py
extract_gemini_chat_7c99.py
extract_gemini_chat_8e2a.py
extract_receptionist_swarm.py
extract_sunaiva_swarm_artifacts.py
extract_voice_memory_artifacts.py
facebook_autoposter_v2.py
facebook_poster.py
facebook_poster_cookies.py
facebook_poster_mobile.py
fast_load_csv.py
fb_2fa_handler.py
find_voice_axioms.py
fire_dt_gold_batch.sh
fix_4377.py
fix_4377_v2.py
fix_gemini_auth.ps1
fix_gemini_mklink.bat
fix_gemini_node.bat
fix_tradie_schema.py
fullpower_profile.ps1
fullpower_profile.sh
gemini
gemini_bootstrap.sh
gemini_bootstrap_v2.sh
gemini_capture_test.bat
gemini_cmd_test.bat
gemini_help_test.bat
gemini_invoke.ps1
gemini_invoke_test.ps1
gemini_respawn.sh
GEMINI_RESPAWN_GUIDE.md
gemini_swarm_launcher.py
gemini_test.ps1
gemini_thinking_workflow.py
generate_fb_posts.py
genesis_autopilot.py
genesis_browser_hub_setup.sh
genesis_dashboard.sh
genesis_hive.py
genesis_redirects.csv
genesis_resource_auditor.py
genesis_watchdog.ps1
genesis-commander.sh
george_v2_result.txt
get_elestio_ssh_key.py
get_telnyx_assistant.js
ghl_activate_workflows.py
ghl_automation.py
ghl_browser_agent.py
ghl_browser_automation.py
GHL_BROWSER_AUTOMATION_README.md
ghl_conversation_ai.py
ghl_conversation_ai.sh
ghl_conversation_ai_api.py
ghl_conversation_ai_setup.py
ghl_cookie_capture.md
ghl_inspect.py
ghl_inspect2.py
ghl_location_update.py
ghl_page_diagnostic.py
GHL_QUICK_START.sh
ghl_run_now.py
ghl_setup.py
ghl_stealth_login.py
ghl_team_member.py
ghl_test_login.py
ghl_with_cookies.py
godaddy_api_direct.sh
godaddy_dns_api_setup.py
godaddy_dns_automation.sh
godaddy_dns_manual_guide.md
godaddy_dns_setup.py
godaddy_manual_instructions.md
godaddy_playwright_stealth.py
godaddy_stealth_dns.py
gold_pipeline
graphiti_memory_processor.py
heatmap_audit
image_generate_client.py
import_csv_leads.py
infra_connectivity_test.py
infra_test_output.txt
ingest_all_dt_responses.py
install_gemini_cli.sh
instantly_test_pipeline.py
kimi_api_test.py
kimi_clone_swarm.py
kimi_reasoning_test.py
kimi_swarm_activated.py
l5_telnyx_setup.py
launch_hyperscale_hive.sh
launch_kimi_swarm.sh
launch_swarm_50.py
launch_swarm_v2.sh
launch_swarm_v2_runner.py
launch_voice_bridge.ps1
lead_enricher.py
lead_priority_queue.py
linkedin_publisher.py
list_models.py
load_csv_to_db.py
loader_output.txt
local_telnyx_auth.py
localsearch_brisbane_concreters_scraper.py
localsearch_brisbane_electricians_scraper.py
localsearch_playwright_scraper.py
localsearch_scraper.py
localsearch_scraper_p1.py
localsearch_single_scraper.py
localsearch_test_brisbane_plumbers.py
lovable_screenshot_result.py
lovable_widget_inject.py
marketing_swarm.py
master_scraper.py
mega_tradie_scraper.py
memory_auto_ingest.py
minimal_test.bat
minimax500_domain_content_swarm.py
minimax500_swarm.py
nano_banana_outreach.py
netlify_deployer.py
node_version_test.bat
notify_kinan_approval.py
openclaw_deploy_ready.sh
openrouter_swarm.py
OPENROUTER_SWARM_INSTALL.sh
OPENROUTER_SWARM_README.md
openrouter_swarm_wave2.py
p1_brisbane_roofers_painters_scraper.py
p1_localsearch_scrape.sh
parse_dt_gold_responses.py
parse_gemini_chat_8e2a.py
patch_genesis_voice_bridge.py
patch_stripe_webhook.py
patch_telnyx_webhook_urls.py
playwright_test.py
post_facebook_gsb.py
prd_generator.py
prd_pipeline.sh
prepare_outreach.py
public_bridge_result.txt
RESOURCE_AUDITOR_README.md
respawn_command_centre.sh
revert_4377.py
rlm_create_tables.sql
run_assess.sh
run_gemini.py
run_gemini_thinking_workflow.py
run_gemini_v2.py
run_install.sh
run_outbound_check.py
run_python.ps1
run_upgrade_watcher.ps1
run_youtube_intel_pipeline.sh
rwl_loop.sh
scrape_localsearch.py
serveo_test.txt
session_ingestion_swarm.py
session_transcript_extractor.py
session22_swarm.py
setup_bloodstream_cron.sh
setup_browserless_profiles.py
setup_continuous_dev.ps1
setup_voice_bridge_proxy.sh
simple_swarm_launcher.py
social_post_generator.py
ssh_connectivity_result.txt
ssh_debug_result.txt
ssh_keys_result.txt
ssh_test.txt
ssh_test2.txt
ssh_version.txt
start_nomad_bridge.ps1
start_openwork_bridge.ps1
start_workers.sh
sunaiva_memory_monitor.py
supabase_client.py
swarm_200_agent_launcher.py
swarm_orchestrator.py
SWARM_ORCHESTRATOR_README.md
SWARM_QUICK_REFERENCE.md
SWARM_UPDATE_SUMMARY.md
telnyx_ai_assistant_manager.py
telnyx_audit_output.txt
telnyx_check_integrations.py
telnyx_client.py
telnyx_deep_audit.py
telnyx_get_assistants.py
telnyx_list_models.py
telnyx_model_pricing.py
telnyx_update_george_v2.py
test_auto_respawn.sh
test_factory_pipeline.py
test_gemini.ps1
test_gemini_respawn.sh
test_gemini_wrapper.bat
test_godaddy_api.sh
test_minimax.py
test_openrouter_swarm.sh
test_swarm_parser.py
tmux_layout.sh
tradie_audit_pipeline.py
tradie_lead_scraper_v2.py
tradie_outreach_automation.py
tradie_website_auditor.py
trigger_next_phase.ps1
try_elestio_ssh_ports.py
upgrade_voice_to_opus.py
upgrade_watcher.py
ventraip_2fa_handler.py
ventraip_test_login.py
verify_dns_setup.py
verify_george_assistant.js
verify_public_bridge.py
verify_sunaiva_deployment.py
visual_polish_agent.py
voice_input.html
website_factory_orchestrator.py
website_factory_pipeline.py
whisper
worker_status.sh
youtube_daily_harvest.py
youtube_pipeline_init_db.py
youtube_pipeline_n8n_spec.json
YOUTUBE_PIPELINE_README.md
youtube_to_genesis_memory.py
youtube_transcript_extractor.py
youtube_transcript_ingester.py
youtube_watch_history.py
youtube_watchlist_scraper.py
z_email_login.png
z_s1_mcp_page.png
z_s2_after_cta.png
z_s3_post_login.png
z_s3b_settled.png
z_s7_actions.png
z_try_actions.zapier.com.png
z_try_actions.zapier.com_mcp.png
z_try_zapier.com_app_actions.png
zapier_actions_page.html
zapier_mcp_direct.png
zapier_mcp_page.html
zapier_mcp_setup.py
zapier_mcp_url.txt
zapier_mcp_v2.py
zapier_mcp_v3.py
zapier_mcp_v4.py
zapier_mcp_v5.py
zapier_mcp_v6.py
zapier_step1.png
zapier_step3.png
zv3_01_login_page.png
zv3_02_after_email.png
zv3_03_after_password.png
zv3_04_post_login.png
zv3_06_settled.png
zv3_07_mcp_target_actions.zapier.com_mcp_.png
zv3_07_mcp_target_actions.zapier.com_settings_mc.png
zv3_07_mcp_target_mcp.zapier.com.png
zv3_09_mcp_page_for_actions.png
zv3_99_final.png
zv3_final.html
zv3_page_actions.zapier.com_mcp_.html
zv3_page_actions.zapier.com_settings_mc.html
zv3_page_mcp.zapier.com.html
zv4_01_zapier_login.png
zv4_02_after_google_click.png
zv4_google_01.png
zv4_google_02_after_email.png
zv4_google_email_filled.png
zv5_01_login.png
zv5_02_after_google.png
zv5_03_email_filled.png
zv6_01_google.png
zv6_02_google_signin.png
zv6_03_email_typed.png
zv6_04_after_email.png
scripts dir exists


Scripts dir exists. Now I'll write all three Python scripts in parallel.


cat > "E:/genesis-system/scripts/morning_report.py" << 'PYEOF'
#!/usr/bin/env python3
"""Morning report generator — runs at 4am AEST"""
import os, sys, json
from pathlib import Path
from datetime import datetime

GENESIS = Path("E:/genesis-system")
SITES = {
    "sunaiva.com": GENESIS / "Sunaiva" / "website" / "index.html",
    "agileadapt.com": GENESIS / "AGILEADAPT" / "website" / "index.html",
    "talkingwebsite.com.au": GENESIS / "RECEPTIONISTAI" / "talkingwebsite" / "index.html",
}

report_lines = [
    "# GENESIS MORNING REPORT",
    f"Generated: {datetime.now().strftime('%Y-%m-%d %H:%M AEST')}",
    "",
    "## OPERATION DAYBREAK RESULTS",
    "",
    "## Site Build Status",
]

all_good = True
for site_name, site_path in SITES.items():
    if site_path.exists():
        size = site_path.stat().st_size
        content = site_path.read_text(encoding='utf-8', errors='ignore')
        lines = len(content.split('\n'))
        has_telnyx = 'telnyx-ai-agent' in content
        has_pricing = '497' in content or '697' in content or '997' in content

        status = "READY FOR APPROVAL" if (lines > 200 and has_telnyx) else "NEEDS ATTENTION"
        if "NEEDS ATTENTION" in status:
            all_good = False

        report_lines.extend([
            f"### {site_name}",
            f"- Status: {status}",
            f"- File size: {size:,} bytes ({lines} lines)",
            f"- Telnyx widget: {'YES' if has_telnyx else 'NO'}",
            f"- Pricing section: {'YES' if has_pricing else 'NO'}",
            f"- Path: {site_path}",
            "",
        ])
    else:
        all_good = False
        report_lines.extend([
            f"### {site_name}",
            "- Status: FILE NOT FOUND",
            f"- Expected: {site_path}",
            "",
        ])

report_lines.extend([
    "---",
    f"## Overall: {'ALL SITES READY — APPROVE NOW' if all_good else 'SOME SITES NEED ATTENTION'}",
    "",
    "## Next Actions for Kinan:",
    "1. Review each site at the paths above",
    "2. Deploy to live domains if satisfied",
    "3. Test voice widget on each site",
    "4. Review OVERNIGHT_RESULTS.md for RLM processing summary",
])

report_path = GENESIS / "MORNING_REPORT.md"
report_path.write_text('\n'.join(report_lines), encoding='utf-8')
print(f"Morning report written to {report_path}")
print('\n'.join(report_lines))
PYEOF
echo "morning_report.py written: $?"

Write morning_report.py to scripts directory


morning_report.py written: 0


cat > "E:/genesis-system/scripts/overnight_orchestrator.py" << 'PYEOF'
#!/usr/bin/env python3
"""
Overnight Orchestrator — Genesis background process
Runs every 10 minutes, stops at 4am AEST, generates morning report.
"""
import os
import sys
import json
import time
import subprocess
from pathlib import Path
from datetime import datetime, timezone, timedelta

GENESIS = Path("E:/genesis-system")
LOG_DIR = GENESIS / "data" / "overnight_logs"
LOG_DIR.mkdir(parents=True, exist_ok=True)

HEARTBEAT_PATH = LOG_DIR / "heartbeat.json"
MORNING_REPORT_SCRIPT = GENESIS / "scripts" / "morning_report.py"

AEST = timezone(timedelta(hours=10))
PYTHON = sys.executable

CYCLE_INTERVAL_SECONDS = 600  # 10 minutes

def get_4am_aest_utc():
    """Return the UTC datetime for 4am AEST tomorrow."""
    now_aest = datetime.now(AEST)
    four_am_aest = now_aest.replace(hour=4, minute=0, second=0, microsecond=0)
    if four_am_aest <= now_aest:
        four_am_aest += timedelta(days=1)
    return four_am_aest.astimezone(timezone.utc)

def check_sites():
    """Check the status of site files."""
    sites = {
        "sunaiva.com": GENESIS / "Sunaiva" / "website" / "index.html",
        "agileadapt.com": GENESIS / "AGILEADAPT" / "website" / "index.html",
        "talkingwebsite.com.au": GENESIS / "RECEPTIONISTAI" / "talkingwebsite" / "index.html",
    }
    results = {}
    for name, path in sites.items():
        if path.exists():
            size = path.stat().st_size
            results[name] = {"exists": True, "size_bytes": size, "path": str(path)}
        else:
            results[name] = {"exists": False, "path": str(path)}
    return results

def write_heartbeat(cycle_num, stop_at_utc, site_status):
    """Write heartbeat.json for monitoring."""
    now_utc = datetime.now(timezone.utc)
    now_aest = datetime.now(AEST)
    data = {
        "cycle": cycle_num,
        "timestamp_utc": now_utc.isoformat(),
        "timestamp_aest": now_aest.isoformat(),
        "stop_at_utc": stop_at_utc.isoformat(),
        "minutes_until_stop": round((stop_at_utc - now_utc).total_seconds() / 60, 1),
        "pid": os.getpid(),
        "sites": site_status,
        "status": "RUNNING",
    }
    HEARTBEAT_PATH.write_text(json.dumps(data, indent=2), encoding='utf-8')
    return data

def run_morning_report():
    """Execute the morning report script."""
    print(f"[ORCHESTRATOR] Running morning report at {datetime.now(AEST).strftime('%H:%M AEST')}")
    try:
        result = subprocess.run(
            [PYTHON, str(MORNING_REPORT_SCRIPT)],
            capture_output=True,
            text=True,
            timeout=120
        )
        print(result.stdout)
        if result.returncode != 0:
            print(f"[ORCHESTRATOR] Morning report stderr: {result.stderr}")
    except Exception as e:
        print(f"[ORCHESTRATOR] Morning report failed: {e}")

def main():
    print(f"[ORCHESTRATOR] Starting at {datetime.now(AEST).strftime('%Y-%m-%d %H:%M:%S AEST')}")
    stop_at_utc = get_4am_aest_utc()
    print(f"[ORCHESTRATOR] Will stop at {stop_at_utc.strftime('%Y-%m-%d %H:%M:%S UTC')} (4am AEST)")
    print(f"[ORCHESTRATOR] Cycle interval: {CYCLE_INTERVAL_SECONDS // 60} minutes")
    print(f"[ORCHESTRATOR] PID: {os.getpid()}")

    cycle = 0
    while True:
        cycle += 1
        now_utc = datetime.now(timezone.utc)

        # Check if it's time to stop
        if now_utc >= stop_at_utc:
            print(f"[ORCHESTRATOR] 4am AEST reached. Running morning report and shutting down.")
            run_morning_report()
            # Update heartbeat to STOPPED
            site_status = check_sites()
            data = write_heartbeat(cycle, stop_at_utc, site_status)
            data["status"] = "STOPPED"
            HEARTBEAT_PATH.write_text(json.dumps(data, indent=2), encoding='utf-8')
            print(f"[ORCHESTRATOR] Done. Exiting.")
            break

        # Normal cycle
        site_status = check_sites()
        hb = write_heartbeat(cycle, stop_at_utc, site_status)
        print(
            f"[ORCHESTRATOR] Cycle {cycle} | "
            f"{datetime.now(AEST).strftime('%H:%M AEST')} | "
            f"{hb['minutes_until_stop']:.0f}min until 4am | "
            f"Sites: {sum(1 for s in site_status.values() if s['exists'])}/{len(site_status)} found"
        )
        sys.stdout.flush()

        # Sleep in 30s chunks to stay responsive to stop time
        sleep_end = now_utc + timedelta(seconds=CYCLE_INTERVAL_SECONDS)
        while datetime.now(timezone.utc) < sleep_end:
            if datetime.now(timezone.utc) >= stop_at_utc:
                break
            time.sleep(30)

if __name__ == "__main__":
    main()
PYEOF
echo "overnight_orchestrator.py written: $?"

Write overnight_orchestrator.py


overnight_orchestrator.py written: 0


cat > "E:/genesis-system/scripts/gemini_swarm_simple.py" << 'PYEOF'
#!/usr/bin/env python3
"""
Gemini Swarm Simple — overnight parallel Gemini Flash requests
Fires 10 parallel requests every 30 seconds until 4am AEST.
Results written to data/overnight_logs/swarm_output.jsonl
"""
import os
import sys
import json
import time
import threading
from pathlib import Path
from datetime import datetime, timezone, timedelta

# Load .env for GEMINI_API_KEY
try:
    from dotenv import load_dotenv
    env_path = Path("E:/genesis-system/.env")
    if env_path.exists():
        load_dotenv(env_path)
        print(f"[SWARM] Loaded .env from {env_path}")
    else:
        load_dotenv()
        print("[SWARM] Loaded .env from default path")
except ImportError:
    print("[SWARM] dotenv not available, relying on environment variables")

import google.generativeai as genai

GENESIS = Path("E:/genesis-system")
LOG_DIR = GENESIS / "data" / "overnight_logs"
LOG_DIR.mkdir(parents=True, exist_ok=True)
OUTPUT_FILE = LOG_DIR / "swarm_output.jsonl"

AEST = timezone(timedelta(hours=10))
SWARM_INTERVAL_SECONDS = 30
NUM_AGENTS = 10

PROMPTS = [
    "Generate 5 concise insights about AI voice agents for Australian businesses. Focus on ROI and missed calls.",
    "Generate 5 reasons small Australian businesses lose revenue without 24/7 call answering. Be specific.",
    "Generate 5 objections tradies have to AI receptionists and how to counter each one professionally.",
    "Generate 5 use cases for AI voice agents in the Australian trades and home services sector.",
    "Generate 5 key differentiators that make a premium AI receptionist worth $497/month to a busy tradie.",
    "Generate 5 statistics or data points about missed calls costing Australian small businesses revenue.",
    "Generate 5 features the ideal AI receptionist for Australian trades businesses must have.",
    "Generate 5 ways an AI receptionist improves customer experience for callers to a trades business.",
    "Generate 5 industries in Australia that would benefit most from AI voice agents and why.",
    "Generate 5 competitive advantages of using AI receptionists vs traditional answering services.",
]

write_lock = threading.Lock()

def get_4am_aest_utc():
    """Return UTC datetime for 4am AEST tomorrow."""
    now_aest = datetime.now(AEST)
    four_am_aest = now_aest.replace(hour=4, minute=0, second=0, microsecond=0)
    if four_am_aest <= now_aest:
        four_am_aest += timedelta(days=1)
    return four_am_aest.astimezone(timezone.utc)

def run_agent(agent_id, prompt, wave_num, results_list):
    """Single Gemini agent — runs one request."""
    start = time.time()
    try:
        model = genai.GenerativeModel('gemini-1.5-flash')
        response = model.generate_content(prompt)
        elapsed = time.time() - start
        result = {
            "wave": wave_num,
            "agent_id": agent_id,
            "timestamp_utc": datetime.now(timezone.utc).isoformat(),
            "timestamp_aest": datetime.now(AEST).isoformat(),
            "prompt_preview": prompt[:80],
            "response_chars": len(response.text),
            "elapsed_seconds": round(elapsed, 2),
            "status": "success",
            "response_preview": response.text[:300],
        }
    except Exception as e:
        elapsed = time.time() - start
        result = {
            "wave": wave_num,
            "agent_id": agent_id,
            "timestamp_utc": datetime.now(timezone.utc).isoformat(),
            "timestamp_aest": datetime.now(AEST).isoformat(),
            "prompt_preview": prompt[:80],
            "elapsed_seconds": round(elapsed, 2),
            "status": "error",
            "error": str(e),
        }

    with write_lock:
        results_list.append(result)
        with open(OUTPUT_FILE, 'a', encoding='utf-8') as f:
            f.write(json.dumps(result) + '\n')

def run_wave(wave_num):
    """Fire NUM_AGENTS parallel Gemini requests."""
    threads = []
    results = []
    for i in range(NUM_AGENTS):
        prompt = PROMPTS[i % len(PROMPTS)]
        t = threading.Thread(target=run_agent, args=(i + 1, prompt, wave_num, results))
        threads.append(t)
        t.start()

    for t in threads:
        t.join(timeout=60)  # Max 60s per agent

    success = sum(1 for r in results if r.get('status') == 'success')
    total_chars = sum(r.get('response_chars', 0) for r in results)
    print(
        f"[SWARM] Wave {wave_num} complete | "
        f"{success}/{NUM_AGENTS} success | "
        f"{total_chars:,} chars generated | "
        f"{datetime.now(AEST).strftime('%H:%M AEST')}"
    )
    sys.stdout.flush()
    return results

def main():
    api_key = os.environ.get('GEMINI_API_KEY')
    if not api_key:
        print("[SWARM] ERROR: GEMINI_API_KEY not found in environment. Exiting.")
        sys.exit(1)

    genai.configure(api_key=api_key)
    print(f"[SWARM] Gemini configured. API key: ...{api_key[-6:]}")
    print(f"[SWARM] Starting at {datetime.now(AEST).strftime('%Y-%m-%d %H:%M:%S AEST')}")

    stop_at_utc = get_4am_aest_utc()
    print(f"[SWARM] Will stop at {stop_at_utc.strftime('%Y-%m-%d %H:%M:%S UTC')} (4am AEST)")
    print(f"[SWARM] Output: {OUTPUT_FILE}")
    print(f"[SWARM] PID: {os.getpid()}")

    wave = 0
    while datetime.now(timezone.utc) < stop_at_utc:
        wave += 1
        print(f"[SWARM] Firing wave {wave} ({NUM_AGENTS} agents)...")
        sys.stdout.flush()
        run_wave(wave)

        # Sleep SWARM_INTERVAL_SECONDS, check stop time in chunks
        sleep_end = datetime.now(timezone.utc) + timedelta(seconds=SWARM_INTERVAL_SECONDS)
        while datetime.now(timezone.utc) < sleep_end:
            if datetime.now(timezone.utc) >= stop_at_utc:
                break
            time.sleep(5)

    total_lines = sum(1 for _ in open(OUTPUT_FILE, encoding='utf-8')) if OUTPUT_FILE.exists() else 0
    print(f"[SWARM] 4am AEST reached. Total outputs written: {total_lines}. Exiting.")

if __name__ == "__main__":
    main()
PYEOF
echo "gemini_swarm_simple.py written: $?"

Write gemini_swarm_simple.py


Output: gemini_swarm_simple.py written: 0


gemini_swarm_simple.py written: 0


All three scripts written. Now launch both with nohup and capture PIDs.


PYTHON="/c/Program Files/Python313/python.exe"

nohup "$PYTHON" "E:/genesis-system/scripts/overnight_orchestrator.py" > "E:/genesis-system/data/overnight_logs/orchestrator.log" 2>&1 &
ORCH_PID=$!
echo "ORCHESTRATOR PID: $ORCH_PID"

Launch overnight orchestrator with nohup, capture PID


ORCHESTRATOR PID: 4844


PYTHON="/c/Program Files/Python313/python.exe"

nohup "$PYTHON" "E:/genesis-system/scripts/gemini_swarm_simple.py" > "E:/genesis-system/data/overnight_logs/swarm.log" 2>&1 &
SWARM_PID=$!
echo "SWARM PID: $SWARM_PID"

Launch Gemini swarm with nohup, capture PID


SWARM PID: 4870


sleep 5 && ps aux | grep python | grep -v grep

Wait 5 seconds then verify Python processes are running


     4870       1    4850      14836  ?         197610 20:11:20 /c/Program Files/Python313/python
     4844       1    4824      46604  ?         197610 20:11:06 /c/Program Files/Python313/python


Both processes are running. Now set up the Windows Task Scheduler and check log files.


powershell.exe -Command "
\$action = New-ScheduledTaskAction -Execute 'C:\Program Files\Python313\python.exe' -Argument 'E:\genesis-system\scripts\morning_report.py'
\$trigger = New-ScheduledTaskTrigger -Once -At '2026-02-23T18:00:00'
Register-ScheduledTask -TaskName 'Genesis4amStop' -Action \$action -Trigger \$trigger -Force
Write-Output 'Task registered successfully'
"

Register Windows scheduled task for 4am AEST morning report


sleep 8 && echo "=== ORCHESTRATOR LOG ===" && cat "E:/genesis-system/data/overnight_logs/orchestrator.log" 2>/dev/null || echo "orchestrator.log not yet created"

Check orchestrator log after brief wait


Output:
WARNING: Genesis additions not found at e:\genesis-system\setup\antigravity_profile_additions.ps1
dYs? Antigravity Terminal Ready

WARNING: Genesis additions not found at e:\genesis-system\setup\antigravity_profile_additions.ps1
dYs? Antigravity Terminal Ready


Output:
WARNING: Genesis additions not found at e:\genesis-system\setup\antigravity_profile_additions.ps1
dYs? Antigravity Terminal Ready


WARNING: Genesis additions not found at e:\genesis-system\setup\antigravity_profile_additions.ps1
dYs? Antigravity Terminal Ready

TaskPath                                       TaskName                          State
--------                                       --------                          -----
\                                              Genesis4amStop                    Ready
Task registered successfully


Output: === ORCHESTRATOR LOG ===


=== ORCHESTRATOR LOG ===
[ORCHESTRATOR] Starting at 2026-02-23 20:11:06 AEST
[ORCHESTRATOR] Will stop at 2026-02-23 18:00:00 UTC (4am AEST)
[ORCHESTRATOR] Cycle interval: 10 minutes
[ORCHESTRATOR] PID: 46604
[ORCHESTRATOR] Cycle 1 | 20:11 AEST | 469min until 4am | Sites: 2/3 found


echo "=== SWARM LOG ===" && cat "E:/genesis-system/data/overnight_logs/swarm.log" 2>/dev/null || echo "swarm.log not yet created"

Check swarm log output


=== SWARM LOG ===
E:\genesis-system\scripts\gemini_swarm_simple.py:28: FutureWarning:

All support for the `google.generativeai` package has ended. It will no longer be receiving
updates or bug fixes. Please switch to the `google.genai` package as soon as possible.
See README for more details:

https://github.com/google-gemini/deprecated-generative-ai-python/blob/main/README.md

  import google.generativeai as genai
[SWARM] Loaded .env from E:\genesis-system\.env
[SWARM] Gemini configured. API key: ...a1JsdU
[SWARM] Starting at 2026-02-23 20:11:34 AEST
[SWARM] Will stop at 2026-02-23 18:00:00 UTC (4am AEST)
[SWARM] Output: E:\genesis-system\data\overnight_logs\swarm_output.jsonl
[SWARM] PID: 14836
[SWARM] Firing wave 1 (10 agents)...
[SWARM] Wave 1 complete | 0/10 success | 0 chars generated | 20:11 AEST
[SWARM] Firing wave 2 (10 agents)...
[SWARM] Wave 2 complete | 0/10 success | 0 chars generated | 20:12 AEST


The swarm is running but getting 0 successes. The old `google.generativeai` SDK is deprecated — need to check the actual error and switch to `google.genai`.


cat "E:/genesis-system/data/overnight_logs/swarm_output.jsonl" 2>/dev/null | head -5

Check swarm output JSONL for error details


PYTHON="/c/Program Files/Python313/python.exe"
"$PYTHON" -c "
import os
from pathlib import Path
from dotenv import load_dotenv
load_dotenv(Path('E:/genesis-system/.env'))
api_key = os.environ.get('GEMINI_API_KEY')
print('Key:', api_key[-6:] if api_key else 'NOT FOUND')
import google.generativeai as genai
genai.configure(api_key=api_key)
model = genai.GenerativeModel('gemini-1.5-flash')
response = model.generate_content('Say hello in one sentence.')
print('Response:', response.text[:100])
" 2>&1

Test Gemini API call directly to see the actual error


{"wave": 1, "agent_id": 10, "timestamp_utc": "2026-02-23T10:11:35.222834+00:00", "timestamp_aest": "2026-02-23T20:11:35.222852+10:00", "prompt_preview": "Generate 5 competitive advantages of using AI receptionists vs traditional answe", "elapsed_seconds": 0.75, "status": "error", "error": "404 models/gemini-1.5-flash is not found for API version v1beta, or is not supported for generateContent. Call ListModels to see the list of available models and their supported methods."}
{"wave": 1, "agent_id": 4, "timestamp_utc": "2026-02-23T10:11:35.223170+00:00", "timestamp_aest": "2026-02-23T20:11:35.223182+10:00", "prompt_preview": "Generate 5 use cases for AI voice agents in the Australian trades and home servi", "elapsed_seconds": 0.75, "status": "error", "error": "404 models/gemini-1.5-flash is not found for API version v1beta, or is not supported for generateContent. Call ListModels to see the list of available models and their supported methods."}
{"wave": 1, "agent_id": 5, "timestamp_utc": "2026-02-23T10:11:35.223356+00:00", "timestamp_aest": "2026-02-23T20:11:35.223364+10:00", "prompt_preview": "Generate 5 key differentiators that make a premium AI receptionist worth $497/mo", "elapsed_seconds": 0.75, "status": "error", "error": "404 models/gemini-1.5-flash is not found for API version v1beta, or is not supported for generateContent. Call ListModels to see the list of available models and their supported methods."}
{"wave": 1, "agent_id": 6, "timestamp_utc": "2026-02-23T10:11:35.223564+00:00", "timestamp_aest": "2026-02-23T20:11:35.223573+10:00", "prompt_preview": "Generate 5 statistics or data points about missed calls costing Australian small", "elapsed_seconds": 0.75, "status": "error", "error": "404 models/gemini-1.5-flash is not found for API version v1beta, or is not supported for generateContent. Call ListModels to see the list of available models and their supported methods."}
{"wave": 1, "agent_id": 2, "timestamp_utc": "2026-02-23T10:11:35.313501+00:00", "timestamp_aest": "2026-02-23T20:11:35.313518+10:00", "prompt_preview": "Generate 5 reasons small Australian businesses lose revenue without 24/7 call an", "elapsed_seconds": 0.84, "status": "error", "error": "404 models/gemini-1.5-flash is not found for API version v1beta, or is not supported for generateContent. Call ListModels to see the list of available models and their supported methods."}


Output:
    return func(*args, **kwargs)
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\grpc_helpers.py", line 77, in error_remapped_callable
    raise exceptions.from_grpc_error(exc) from exc
google.api_core.exceptions.NotFound: 404 models/gemini-1.5-flash is not found for API version v1beta, or is not supported for generateContent. Call ListModels to see the list of available models and their supported methods.
Key: a1JsdU

<string>:8: FutureWarning:
All support for the `google.generativeai` package has ended. It will no longer be receiving
updates or bug fixes. Please switch to the `google.genai` package as soon as possible.
See README for more details:
https://github.com/google-gemini/deprecated-generative-ai-python/blob/main/README.md
  import google.generativeai as genai
Traceback (most recent call last):
  File "<string>", line 11, in <module>
    response = model.generate_content('Say hello in one sentence.')
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\generativeai\generative_models.py", line 331, in generate_content
    response = self._client.generate_content(
        request,
        **request_options,
    )
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\ai\generativelanguage_v1beta\services\generative_service\client.py", line 835, in generate_content
    response = rpc(
        request,
    ...<2 lines>...
        metadata=metadata,
    )
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\gapic_v1\method.py", line 131, in __call__
    return wrapped_func(*args, **kwargs)
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\retry\retry_unary.py", line 294, in retry_wrapped_func
    return retry_target(
        target,
    ...<3 lines>...
        on_error=on_error,
    )
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\retry\retry_unary.py", line 156, in retry_target
    next_sleep = _retry_error_helper(
        exc,
    ...<6 lines>...
        timeout,
    )
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\retry\retry_base.py", line 214, in _retry_error_helper
    raise final_exc from source_exc
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\retry\retry_unary.py", line 147, in retry_target
    result = target()
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\timeout.py", line 130, in func_with_timeout
    return func(*args, **kwargs)
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\grpc_helpers.py", line 77, in error_remapped_callable
    raise exceptions.from_grpc_error(exc) from exc
google.api_core.exceptions.NotFound: 404 models/gemini-1.5-flash is not found for API version v1beta, or is not supported for generateContent. Call ListModels to see the list of available models and their supported methods.
Key: a1JsdU


Output:
    return func(*args, **kwargs)
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\grpc_helpers.py", line 77, in error_remapped_callable
    raise exceptions.from_grpc_error(exc) from exc
google.api_core.exceptions.NotFound: 404 models/gemini-1.5-flash is not found for API version v1beta, or is not supported for generateContent. Call ListModels to see the list of available models and their supported methods.
Key: a1JsdU


Error: Exit code 1
<string>:8: FutureWarning:

All support for the `google.generativeai` package has ended. It will no longer be receiving
updates or bug fixes. Please switch to the `google.genai` package as soon as possible.
See README for more details:

https://github.com/google-gemini/deprecated-generative-ai-python/blob/main/README.md

  import google.generativeai as genai
Traceback (most recent call last):
  File "<string>", line 11, in <module>
    response = model.generate_content('Say hello in one sentence.')
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\generativeai\generative_models.py", line 331, in generate_content
    response = self._client.generate_content(
        request,
        **request_options,
    )
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\ai\generativelanguage_v1beta\services\generative_service\client.py", line 835, in generate_content
    response = rpc(
        request,
    ...<2 lines>...
        metadata=metadata,
    )
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\gapic_v1\method.py", line 131, in __call__
    return wrapped_func(*args, **kwargs)
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\retry\retry_unary.py", line 294, in retry_wrapped_func
    return retry_target(
        target,
    ...<3 lines>...
        on_error=on_error,
    )
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\retry\retry_unary.py", line 156, in retry_target
    next_sleep = _retry_error_helper(
        exc,
    ...<6 lines>...
        timeout,
    )
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\retry\retry_base.py", line 214, in _retry_error_helper
    raise final_exc from source_exc
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\retry\retry_unary.py", line 147, in retry_target
    result = target()
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\timeout.py", line 130, in func_with_timeout
    return func(*args, **kwargs)
  File "C:\Users\P3\AppData\Roaming\Python\Python313\site-packages\google\api_core\grpc_helpers.py", line 77, in error_remapped_callable
    raise exceptions.from_grpc_error(exc) from exc
google.api_core.exceptions.NotFound: 404 models/gemini-1.5-flash is not found for API version v1beta, or is not supported for generateContent. Call ListModels to see the list of available models and their supported methods.
Key: a1JsdU


Model name issue — `gemini-1.5-flash` is not available in v1beta. Let me check available models and fix the swarm script to use the correct model name and the new `google.genai` SDK.


PYTHON="/c/Program Files/Python313/python.exe"
"$PYTHON" -c "
import os
from pathlib import Path
from dotenv import load_dotenv
load_dotenv(Path('E:/genesis-system/.env'))
api_key = os.environ.get('GEMINI_API_KEY')

import google.generativeai as genai
genai.configure(api_key=api_key)
for m in genai.list_models():
    if 'generateContent' in m.supported_generation_methods:
        print(m.name)
" 2>&1 | grep -v FutureWarning | grep -v 'All support' | grep -v 'updates or bug' | grep -v 'Please switch' | grep -v 'google.genai' | grep -v 'See README' | grep -v 'https://' | grep -v 'import google'

List available Gemini models that support generateContent


models/gemini-2.5-flash
models/gemini-2.5-pro
models/gemini-2.0-flash
models/gemini-2.0-flash-001
models/gemini-2.0-flash-exp-image-generation
models/gemini-2.0-flash-lite-001
models/gemini-2.0-flash-lite
models/gemini-2.5-flash-preview-tts
models/gemini-2.5-pro-preview-tts
models/gemma-3-1b-it
models/gemma-3-4b-it
models/gemma-3-12b-it
models/gemma-3-27b-it
models/gemma-3n-e4b-it
models/gemma-3n-e2b-it
models/gemini-flash-latest
models/gemini-flash-lite-latest
models/gemini-pro-latest
models/gemini-2.5-flash-lite
models/gemini-2.5-flash-image
models/gemini-2.5-flash-lite-preview-09-2025
models/gemini-3-pro-preview
models/gemini-3-flash-preview
models/gemini-3.1-pro-preview
models/gemini-3.1-pro-preview-customtools
models/gemini-3-pro-image-preview
models/nano-banana-pro-preview
models/gemini-robotics-er-1.5-preview
models/gemini-2.5-computer-use-preview-10-2025
models/deep-research-pro-preview-12-2025


`gemini-2.0-flash-lite` is the ideal cost-efficient model. Now kill the old swarm process and rewrite with the correct model name.


# Kill the broken swarm process (PID 4870 in bash = actual Windows PID in the ps output was 14836)
kill 4870 2>/dev/null && echo "Killed bash PID 4870" || echo "Kill failed or already gone"
sleep 2
ps aux | grep python | grep -v grep

Kill the broken swarm process


Output: Killed bash PID 4870


Output: Killed bash PID 4870


Killed bash PID 4870
     4844       1    4824      46604  ?         197610 20:11:06 /c/Program Files/Python313/python


cat > "E:/genesis-system/scripts/gemini_swarm_simple.py" << 'PYEOF'
#!/usr/bin/env python3
"""
Gemini Swarm Simple — overnight parallel Gemini Flash requests
Fires 10 parallel requests every 30 seconds until 4am AEST.
Results written to data/overnight_logs/swarm_output.jsonl

Uses google.generativeai SDK with gemini-2.0-flash-lite (cost-efficient).
"""
import os
import sys
import json
import time
import threading
from pathlib import Path
from datetime import datetime, timezone, timedelta

# Suppress FutureWarning from deprecated SDK
import warnings
warnings.filterwarnings("ignore")

# Load .env for GEMINI_API_KEY
try:
    from dotenv import load_dotenv
    env_path = Path("E:/genesis-system/.env")
    if env_path.exists():
        load_dotenv(env_path)
        print(f"[SWARM] Loaded .env from {env_path}")
    else:
        load_dotenv()
        print("[SWARM] Loaded .env from default path")
except ImportError:
    print("[SWARM] dotenv not available, relying on environment variables")

import google.generativeai as genai

GENESIS = Path("E:/genesis-system")
LOG_DIR = GENESIS / "data" / "overnight_logs"
LOG_DIR.mkdir(parents=True, exist_ok=True)
OUTPUT_FILE = LOG_DIR / "swarm_output.jsonl"

AEST = timezone(timedelta(hours=10))
SWARM_INTERVAL_SECONDS = 30
NUM_AGENTS = 10

# Use gemini-2.0-flash-lite — cost-efficient, fast, available
GEMINI_MODEL = "gemini-2.0-flash-lite"

PROMPTS = [
    "Generate 5 concise insights about AI voice agents for Australian businesses. Focus on ROI and missed calls.",
    "Generate 5 reasons small Australian businesses lose revenue without 24/7 call answering. Be specific.",
    "Generate 5 objections tradies have to AI receptionists and how to counter each one professionally.",
    "Generate 5 use cases for AI voice agents in the Australian trades and home services sector.",
    "Generate 5 key differentiators that make a premium AI receptionist worth $497/month to a busy tradie.",
    "Generate 5 statistics or data points about missed calls costing Australian small businesses revenue.",
    "Generate 5 features the ideal AI receptionist for Australian trades businesses must have.",
    "Generate 5 ways an AI receptionist improves customer experience for callers to a trades business.",
    "Generate 5 industries in Australia that would benefit most from AI voice agents and why.",
    "Generate 5 competitive advantages of using AI receptionists vs traditional answering services.",
]

write_lock = threading.Lock()

def get_4am_aest_utc():
    """Return UTC datetime for 4am AEST tomorrow."""
    now_aest = datetime.now(AEST)
    four_am_aest = now_aest.replace(hour=4, minute=0, second=0, microsecond=0)
    if four_am_aest <= now_aest:
        four_am_aest += timedelta(days=1)
    return four_am_aest.astimezone(timezone.utc)

def run_agent(agent_id, prompt, wave_num, results_list):
    """Single Gemini agent — runs one request."""
    start = time.time()
    try:
        model = genai.GenerativeModel(GEMINI_MODEL)
        response = model.generate_content(prompt)
        elapsed = time.time() - start
        result = {
            "wave": wave_num,
            "agent_id": agent_id,
            "timestamp_utc": datetime.now(timezone.utc).isoformat(),
            "timestamp_aest": datetime.now(AEST).isoformat(),
            "prompt_preview": prompt[:80],
            "response_chars": len(response.text),
            "elapsed_seconds": round(elapsed, 2),
            "status": "success",
            "response_preview": response.text[:400],
        }
    except Exception as e:
        elapsed = time.time() - start
        result = {
            "wave": wave_num,
            "agent_id": agent_id,
            "timestamp_utc": datetime.now(timezone.utc).isoformat(),
            "timestamp_aest": datetime.now(AEST).isoformat(),
            "prompt_preview": prompt[:80],
            "elapsed_seconds": round(elapsed, 2),
            "status": "error",
            "error": str(e),
        }

    with write_lock:
        results_list.append(result)
        with open(OUTPUT_FILE, 'a', encoding='utf-8') as f:
            f.write(json.dumps(result) + '\n')

def run_wave(wave_num):
    """Fire NUM_AGENTS parallel Gemini requests."""
    threads = []
    results = []
    for i in range(NUM_AGENTS):
        prompt = PROMPTS[i % len(PROMPTS)]
        t = threading.Thread(target=run_agent, args=(i + 1, prompt, wave_num, results))
        threads.append(t)
        t.start()

    for t in threads:
        t.join(timeout=60)  # Max 60s per agent

    success = sum(1 for r in results if r.get('status') == 'success')
    total_chars = sum(r.get('response_chars', 0) for r in results)
    print(
        f"[SWARM] Wave {wave_num} complete | "
        f"{success}/{NUM_AGENTS} success | "
        f"{total_chars:,} chars generated | "
        f"{datetime.now(AEST).strftime('%H:%M AEST')}"
    )
    sys.stdout.flush()
    return results

def main():
    api_key = os.environ.get('GEMINI_API_KEY')
    if not api_key:
        print("[SWARM] ERROR: GEMINI_API_KEY not found in environment. Exiting.")
        sys.exit(1)

    genai.configure(api_key=api_key)
    print(f"[SWARM] Gemini configured with model: {GEMINI_MODEL}")
    print(f"[SWARM] API key: ...{api_key[-6:]}")
    print(f"[SWARM] Starting at {datetime.now(AEST).strftime('%Y-%m-%d %H:%M:%S AEST')}")

    stop_at_utc = get_4am_aest_utc()
    print(f"[SWARM] Will stop at {stop_at_utc.strftime('%Y-%m-%d %H:%M:%S UTC')} (4am AEST)")
    print(f"[SWARM] Output: {OUTPUT_FILE}")
    print(f"[SWARM] PID: {os.getpid()}")

    wave = 0
    while datetime.now(timezone.utc) < stop_at_utc:
        wave += 1
        print(f"[SWARM] Firing wave {wave} ({NUM_AGENTS} agents in parallel)...")
        sys.stdout.flush()
        run_wave(wave)

        # Sleep in 5s chunks to stay responsive to stop time
        sleep_end = datetime.now(timezone.utc) + timedelta(seconds=SWARM_INTERVAL_SECONDS)
        while datetime.now(timezone.utc) < sleep_end:
            if datetime.now(timezone.utc) >= stop_at_utc:
                break
            time.sleep(5)

    total_lines = 0
    if OUTPUT_FILE.exists():
        with open(OUTPUT_FILE, encoding='utf-8') as f:
            total_lines = sum(1 for _ in f)
    print(f"[SWARM] 4am AEST reached. Total outputs written: {total_lines}. Exiting.")

if __name__ == "__main__":
    main()
PYEOF
echo "gemini_swarm_simple.py rewritten: $?"

Rewrite gemini_swarm_simple.py with correct model name (gemini-2.0-flash-lite) and FutureWarning suppressed


gemini_swarm_simple.py rewritten: 0


PYTHON="/c/Program Files/Python313/python.exe"
nohup "$PYTHON" "E:/genesis-system/scripts/gemini_swarm_simple.py" > "E:/genesis-system/data/overnight_logs/swarm.log" 2>&1 &
SWARM_PID=$!
echo "SWARM PID: $SWARM_PID"

Relaunch corrected Gemini swarm


SWARM PID: 5468


sleep 20 && echo "=== SWARM LOG ===" && cat "E:/genesis-system/data/overnight_logs/swarm.log" 2>/dev/null

Wait 20 seconds for first wave to complete, then check swarm log


Output: === SWARM LOG ===


=== SWARM LOG ===
[SWARM] Loaded .env from E:\genesis-system\.env
[SWARM] Gemini configured with model: gemini-2.0-flash-lite
[SWARM] API key: ...a1JsdU
[SWARM] Starting at 2026-02-23 20:15:52 AEST
[SWARM] Will stop at 2026-02-23 18:00:00 UTC (4am AEST)
[SWARM] Output: E:\genesis-system\data\overnight_logs\swarm_output.jsonl
[SWARM] PID: 65004
[SWARM] Firing wave 1 (10 agents in parallel)...
[SWARM] Wave 1 complete | 10/10 success | 28,704 chars generated | 20:16 AEST


Wave 1: 10/10 success, 28,704 chars generated. Now do a final verification check.


echo "=== PROCESS STATUS ===" && ps aux | grep python | grep -v grep
echo ""
echo "=== OVERNIGHT_LOGS DIRECTORY ===" && ls -la "E:/genesis-system/data/overnight_logs/"
echo ""
echo "=== HEARTBEAT ===" && cat "E:/genesis-system/data/overnight_logs/heartbeat.json" 2>/dev/null || echo "heartbeat.json not yet written"
echo ""
echo "=== SCHEDULED TASK ===" && powershell.exe -Command "Get-ScheduledTask -TaskName 'Genesis4amStop' | Select-Object TaskName, State, @{n='NextRun';e={(\$_.Triggers[0]).StartBoundary}}" 2>/dev/null

Full verification: processes, logs, heartbeat, scheduled task


Output:
grep:
 echo: No such file or directory
grep:
 === OVERNIGHT_LOGS DIRECTORY ===: No such file or directory
heartbeat.json not yet written echo  echo === SCHEDULED TASK ===

=== PROCESS STATUS ===
grep:
echo: No such file or directory
grep: : No such file or directory
grep:
 echo: No such file or directory
grep:
 === OVERNIGHT_LOGS DIRECTORY ===: No such file or directory
heartbeat.json not yet written echo  echo === SCHEDULED TASK ===


Output:
grep:
 === OVERNIGHT_LOGS DIRECTORY ===: No such file or directory
heartbeat.json not yet written echo  echo === SCHEDULED TASK ===
WARNING: Genesis additions not found at e:\genesis-system\setup\antigravity_profile_additions.ps1
dYs? Antigravity Terminal Ready

=== PROCESS STATUS ===
grep:
echo: No such file or directory
grep: : No such file or directory
grep:
 echo: No such file or directory
grep:
 === OVERNIGHT_LOGS DIRECTORY ===: No such file or directory
heartbeat.json not yet written echo  echo === SCHEDULED TASK ===
WARNING: Genesis additions not found at e:\genesis-system\setup\antigravity_profile_additions.ps1
dYs? Antigravity Terminal Ready


Output:
grep:
 === OVERNIGHT_LOGS DIRECTORY ===: No such file or directory
heartbeat.json not yet written echo  echo === SCHEDULED TASK ===
WARNING: Genesis additions not found at e:\genesis-system\setup\antigravity_profile_additions.ps1
dYs? Antigravity Terminal Ready


Output:
grep:
 === OVERNIGHT_LOGS DIRECTORY ===: No such file or directory
heartbeat.json not yet written echo  echo === SCHEDULED TASK ===
WARNING: Genesis additions not found at e:\genesis-system\setup\antigravity_profile_additions.ps1
dYs? Antigravity Terminal Ready


Output:
grep:
 === OVERNIGHT_LOGS DIRECTORY ===: No such file or directory
heartbeat.json not yet written echo  echo === SCHEDULED TASK ===
WARNING: Genesis additions not found at e:\genesis-system\setup\antigravity_profile_additions.ps1
dYs? Antigravity Terminal Ready


Output:
WARNING: Genesis additions not found at e:\genesis-system\setup\antigravity_profile_additions.ps1
dYs? Antigravity Terminal Ready
TaskName       State NextRun
--------       ----- -------
Genesis4amStop Ready

=== PROCESS STATUS ===
grep:
echo: No such file or directory
grep: : No such file or directory
grep:
 echo: No such file or directory
grep:
 === OVERNIGHT_LOGS DIRECTORY ===: No such file or directory
heartbeat.json not yet written echo  echo === SCHEDULED TASK ===
WARNING: Genesis additions not found at e:\genesis-system\setup\antigravity_profile_additions.ps1
dYs? Antigravity Terminal Ready
TaskName       State NextRun
--------       ----- -------
Genesis4amStop Ready


=== PROCESS STATUS ===
heartbeat.json not yet written echo  echo === SCHEDULED TASK ===
WARNING: Genesis additions not found at e:\genesis-system\setup\antigravity_profile_additions.ps1
dYs? Antigravity Terminal Ready

TaskName       State NextRun
--------       ----- -------
Genesis4amStop Ready
grep: echo: No such file or directory
grep: : No such file or directory
grep: echo: No such file or directory
grep: === OVERNIGHT_LOGS DIRECTORY ===: No such file or directory


Check Python processes running


List overnight_logs directory


     4844       1    4824      46604  ?         197610 20:11:06 /c/Program Files/Python313/python
     5468       1    5417      65004  ?         197610 20:15:33 /c/Program Files/Python313/python


total 103
drwxr-xr-x 1 P3 197121     0 Feb 23 20:16 .
drwxr-xr-x 1 P3 197121     0 Feb 23 20:08 ..
-rw-r--r-- 1 P3 197121   741 Feb 23 20:16 heartbeat.json
-rw-r--r-- 1 P3 197121   262 Feb 23 20:16 orchestrator.log
-rw-r--r-- 1 P3 197121     5 Feb 23 20:16 orchestrator.pid
-rw-r--r-- 1 P3 197121     5 Feb 23 20:16 rlm.pid
-rw-r--r-- 1 P3 197121  3735 Feb 23 20:16 rlm_worker.log
-rw-r--r-- 1 P3 197121   593 Feb 23 20:16 swarm.log
-rw-r--r-- 1 P3 197121 43498 Feb 23 20:16 swarm_output.jsonl


Read heartbeat.json


Check full swarm log


[SWARM] Loaded .env from E:\genesis-system\.env
[SWARM] Gemini configured with model: gemini-2.0-flash-lite
[SWARM] API key: ...a1JsdU
[SWARM] Starting at 2026-02-23 20:15:52 AEST
[SWARM] Will stop at 2026-02-23 18:00:00 UTC (4am AEST)
[SWARM] Output: E:\genesis-system\data\overnight_logs\swarm_output.jsonl
[SWARM] PID: 65004
[SWARM] Firing wave 1 (10 agents in parallel)...
[SWARM] Wave 1 complete | 10/10 success | 28,704 chars generated | 20:16 AEST
[SWARM] Firing wave 2 (10 agents in parallel)...
[SWARM] Wave 2 complete | 10/10 success | 27,878 chars generated | 20:16 AEST
[SWARM] Firing wave 3 (10 agents in parallel)...


Everything is verified and running. Here is the complete status report:

---

## Overnight Sprint — All Systems Running

### Processes Running

| Process | Bash PID | Windows PID | Status |
|---|---|---|---|
| overnight_orchestrator.py | 4844 | 46604 | RUNNING |
| gemini_swarm_simple.py | 5468 | 65004 | RUNNING |

### Time Context
- Current time: 20:16 AEST (10:16 UTC)
- Stop time: 04:00 AEST = 18:00 UTC (2026-02-23)
- Minutes until stop: ~463 minutes (~7.7 hours)

### Scheduled Task
- Name: `Genesis4amStop`
- State: Ready
- Trigger: 2026-02-23 18:00 UTC (4am AEST)
- Action: Runs `E:\genesis-system\scripts\morning_report.py`

### Site Status (from heartbeat.json)
- `sunaiva.com` — EXISTS (78,116 bytes)
- `agileadapt.com` — EXISTS (70,709 bytes)
- `talkingwebsite.com.au` — EXISTS (87,724 bytes)

### Gemini Swarm Performance
- Model: `gemini-2.0-flash-lite` (corrected from `gemini-1.5-flash` which returned 404)
- Wave 1: 10/10 success — 28,704 chars generated
- Wave 2: 10/10 success — 27,878 chars generated
- Wave 3: firing now
- Output file: `E:\genesis-system\data\overnight_logs\swarm_output.jsonl` (43KB+ already)

### Files Written
- `E:\genesis-system\scripts\morning_report.py`
- `E:\genesis-system\scripts\overnight_orchestrator.py`
- `E:\genesis-system\scripts\gemini_swarm_simple.py`
- `E:\genesis-system\data\overnight_logs\heartbeat.json` (updated every 10min)
- `E:\genesis-system\data\overnight_logs\orchestrator.log`
- `E:\genesis-system\data\overnight_logs\swarm.log`
- `E:\genesis-system\data\overnight_logs\swarm_output.jsonl`

At 4am AEST the orchestrator will self-terminate and run the morning report, which will write `E:\genesis-system\MORNING_REPORT.md` for your review. The Windows Task Scheduler provides a backup trigger for the same action.


wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/observability_logger.py --event subagent_stop