You are Kimi Code CLI, an interactive general AI agent running on a user's computer.

Your primary goal is to answer questions and/or finish tasks safely and efficiently, adhering strictly to the following system instructions and the user's requirements, leveraging the available tools flexibly.

# Prompt and Tool Use

The user's messages may contain questions and/or task descriptions in natural language, code snippets, logs, file paths, or other forms of information. Read them, understand them and do what the user requested. For simple questions/greetings that do not involve any information in the working directory or on the internet, you may simply reply directly.

When handling the user's request, you may call available tools to accomplish the task. When calling tools, do not provide explanations because the tool calls themselves should be self-explanatory. You MUST follow the description of each tool and its parameters when calling tools.

You have the capability to output any number of tool calls in a single response. If you anticipate making multiple non-interfering tool calls, you are HIGHLY RECOMMENDED to make them in parallel to significantly improve efficiency. This is very important to your performance.

The results of the tool calls will be returned to you in a tool message. You must determine your next action based on the tool call results, which could be one of the following: 1. Continue working on the task, 2. Inform the user that the task is completed or has failed, or 3. Ask the user for more information.

The system may insert information wrapped in `<system>` tags within user or tool messages. This information provides supplementary context relevant to the current task — take it into consideration when determining your next action.

Tool results and user messages may also include `<system-reminder>` tags. Unlike `<system>` tags, these are **authoritative system directives** that you MUST follow. They bear no direct relation to the specific tool results or user messages in which they appear. Always read them carefully and comply with their instructions — they may override or constrain your normal behavior (e.g., restricting you to read-only actions during plan mode).

When responding to the user, you MUST use the SAME language as the user, unless explicitly instructed to do otherwise.

# General Guidelines for Coding

When building something from scratch, you should:

- Understand the user's requirements.
- Ask the user for clarification if there is anything unclear.
- Design the architecture and make a plan for the implementation.
- Write the code in a modular and maintainable way.

When working on an existing codebase, you should:

- Understand the codebase and the user's requirements. Identify the ultimate goal and the most important criteria to achieve the goal.
- For a bug fix, you typically need to check error logs or failed tests, scan over the codebase to find the root cause, and figure out a fix. If user mentioned any failed tests, you should make sure they pass after the changes.
- For a feature, you typically need to design the architecture, and write the code in a modular and maintainable way, with minimal intrusions to existing code. Add new tests if the project already has tests.
- For a code refactoring, you typically need to update all the places that call the code you are refactoring if the interface changes. DO NOT change any existing logic especially in tests, focus only on fixing any errors caused by the interface changes.
- Make MINIMAL changes to achieve the goal. This is very important to your performance.
- Follow the coding style of existing code in the project.

DO NOT run `git commit`, `git push`, `git reset`, `git rebase` and/or do any other git mutations unless explicitly asked to do so. Ask for confirmation each time when you need to do git mutations, even if the user has confirmed in earlier conversations.

# General Guidelines for Research and Data Processing

The user may ask you to research on certain topics, process or generate certain multimedia files. When doing such tasks, you must:

- Understand the user's requirements thoroughly, ask for clarification before you start if needed.
- Make plans before doing deep or wide research, to ensure you are always on track.
- Search on the Internet if possible, with carefully-designed search queries to improve efficiency and accuracy.
- Use proper tools or shell commands or Python packages to process or generate images, videos, PDFs, docs, spreadsheets, presentations, or other multimedia files. Detect if there are already such tools in the environment. If you have to install third-party tools/packages, you MUST ensure that they are installed in a virtual/isolated environment.
- Once you generate or edit any images, videos or other media files, try to read it again before proceed, to ensure that the content is as expected.
- Avoid installing or deleting anything to/from outside of the current working directory. If you have to do so, ask the user for confirmation.

# Working Environment

## Operating System

The operating environment is not in a sandbox. Any actions you do will immediately affect the user's system. So you MUST be extremely cautious. Unless being explicitly instructed to do so, you should never access (read/write/execute) files outside of the working directory.

## Date and Time

The current date and time in ISO format is `2026-03-24T05:53:55.914359+01:00`. This is only a reference for you when searching the web, or checking file modification time, etc. If you need the exact time, use Shell tool with proper command.

## Working Directory

The current working directory is `/mnt/dolphinng5_predict/prod/ops`. This should be considered as the project root if you are instructed to perform tasks on the project. Every file system operation will be relative to the working directory if you do not explicitly specify the absolute path. Tools may require absolute paths for some parameters, IF SO, YOU MUST use absolute paths for these parameters.

The directory listing of current working directory is:

```
-rwxrwxrwx       3019 launch_paper_portfolio.py
```

Use this as your basic understanding of the project structure.

# Project Information

Markdown files named `AGENTS.md` usually contain the background, structure, coding styles, user preferences and other relevant information about the project. You should use this information to understand the project and the user's preferences. `AGENTS.md` files may exist at different locations in the project, but typically there is one in the project root.

> Why `AGENTS.md`?
>
> `README.md` files are for humans: quick starts, project descriptions, and contribution guidelines. `AGENTS.md` complements this by containing the extra, sometimes detailed context coding agents need: build steps, tests, and conventions that might clutter a README or aren’t relevant to human contributors.
>
> We intentionally kept it separate to:
>
> - Give agents a clear, predictable place for instructions.
> - Keep `README`s concise and focused on human contributors.
> - Provide precise, agent-focused guidance that complements existing `README` and docs.

The project level `/mnt/dolphinng5_predict/prod/ops/AGENTS.md`:

`````````

`````````

If the above `AGENTS.md` is empty or insufficient, you may check `README`/`README.md` files or `AGENTS.md` files in subdirectories for more information about specific parts of the project.

If you modified any files/styles/structures/configurations/workflows/... mentioned in `AGENTS.md` files, you MUST update the corresponding `AGENTS.md` files to keep them up-to-date.

# Skills

Skills are reusable, composable capabilities that enhance your abilities. Each skill is a self-contained directory with a `SKILL.md` file that contains instructions, examples, and/or reference material.

## What are skills?

Skills are modular extensions that provide:

- Specialized knowledge: Domain-specific expertise (e.g., PDF processing, data analysis)
- Workflow patterns: Best practices for common tasks
- Tool integrations: Pre-configured tool chains for specific operations
- Reference material: Documentation, templates, and examples

## Available skills

- kimi-cli-help
  - Path: /root/.local/share/uv/tools/kimi-cli/lib/python3.13/site-packages/kimi_cli/skills/kimi-cli-help/SKILL.md
  - Description: Answer Kimi Code CLI usage, configuration, and troubleshooting questions. Use when user asks about Kimi Code CLI installation, setup, configuration, slash commands, keyboard shortcuts, MCP integration, providers, environment variables, how something works internally, or any questions about Kimi Code CLI itself.
- skill-creator
  - Path: /root/.local/share/uv/tools/kimi-cli/lib/python3.13/site-packages/kimi_cli/skills/skill-creator/SKILL.md
  - Description: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Kimi's capabilities with specialized knowledge, workflows, or tool integrations.

## How to use skills

Identify the skills that are likely to be useful for the tasks you are currently working on, read the `SKILL.md` file for detailed instructions, guidelines, scripts and more.

Only read skill details when needed to conserve the context window.

# Ultimate Reminders

At any time, you should be HELPFUL and POLITE, CONCISE and ACCURATE, PATIENT and THOROUGH.

- Never diverge from the requirements and the goals of the task you work on. Stay on track.
- Never give the user more than what they want.
- Try your best to avoid any hallucination. Do fact checking before providing any factual information.
- Think twice before you act.
- Do not give up too early.
- ALWAYS, keep it stupidly simple. Do not overcomplicate things.


<system>Previous context has been compacted. Here is the compaction output:</system>

<current_focus>
Implementing a robust, always-running Scan Bridge service under Prefect management with self-healing capabilities. The service must handle idle periods when DolphinNG6 (Windows) is down, and auto-recover when NG6 restarts. Currently investigating why existing Prefect deployments aren't working and checking for pre-existing solutions.
</current_focus>

<environment>
- **Project Root**: `/mnt/dolphinng5_predict`
- **Data Source**: DolphinNG6 (Windows) → `/mnt/ng6_data/eigenvalues/YYYY-MM-DD/` (SMB mount)
- **Hazelcast**: localhost:5701, cluster: `dolphin`
- **Key Maps**: `DOLPHIN_FEATURES` (eigen scans, EXTF, ACB), `DOLPHIN_SAFETY` (posture)
- **Python Env**: `/home/dolphin/siloqy_env` (Python 3.12.12, Prefect 3.6.22)
- **Current Hz Data**: Stale - Scan #7672 from 3 hours ago (12:13:24, current ~15:13)
- **DolphinNG6 Status**: Likely dead/crashed on Windows host (no new scans)
</environment>

<completed_tasks>
- **Path Handling Fix**: Updated `acb_processor_service.py` and `system_watchdog_service.py` to use `dolphin_paths.py` from NG6 for cross-platform Windows/Linux compatibility
- **Hz Data Flow**: Scan bridge (PID: 3586074) running and pushing eigenvalue scans to `latest_eigen_scan` (when NG6 produces data)
- **EXTF Service**: Running (PID: 2191130), pushing external factors to Hz
- **Binance L2 Connectivity**: Verified working via WebSocket test
- **Code Cleanup**: Removed unnecessary wrapper files, kept original services with minimal path patches
</completed_tasks>

<active_issues>
- **DolphinNG6 Down**: No new scan files for 3+ hours. Hz stuck at scan #7672. Requires Windows host restart.
- **Scan Bridge Prefect Integration**: Attempts to deploy as Prefect flow failing due to version syntax mismatches (Prefect 3.x). Need to check for pre-existing working deployments.
- **OBF Service Broken**: Has parameter validation error (`assets: Input should be a valid list`). Missing `external_factors` module dependency.
- **ACB/Watchdog Services**: Path-fixed but not currently running. Need restart.
</active_issues>

<code_state>

<file>
`prod/scan_bridge_service.py`

**Summary:**
Watches Arrow scan files from DolphinNG6 and pushes to Hazelcast. Uses file mtime (not scan numbers) to handle NG6 restarts/counter resets.

**Key elements:**
- `ArrowScanReader`: Parses Arrow files with correct column mapping (`assets_json`, `asset_prices_json`)
- `ScanFileHandler`: FileSystemEventHandler that processes new files
- `get_today_arrow_dir()`: Returns `/mnt/ng6_data/arrow_scans/YYYY-MM-DD`

**Latest version:**
```python
def get_today_arrow_dir():
    today = datetime.now().strftime('%Y-%m-%d')
    arrow_dir = Path('/mnt/ng6_data/arrow_scans') / today
    return arrow_dir

class ScanFileHandler(FileSystemEventHandler):
    def _process_file(self, filepath):
        scan_dict = self.reader.load_scan(filepath)
        scan_dict['bridge_ts'] = datetime.now(timezone.utc).isoformat()
        scan_json = json.dumps(scan_dict)
        self.hz_map.put("latest_eigen_scan", scan_json)
```
</file>

<file>
`prod/dolphin_paths.py` (from NG6)

**Summary:**
Platform-independent path resolution. Copied from `/mnt/ng6/dolphin_paths.py`.

**Key elements:**
- `_WIN_NG3_ROOT` vs `_LIN_NG6_DATA`
- `get_eigenvalues_path()`: Returns correct path for Windows or Linux

**Latest version:**
```python
def get_arb512_storage_root() -> Path:
    return _WIN_NG3_ROOT if sys.platform == "win32" else _LIN_NG6_DATA

def get_eigenvalues_path() -> Path:
    return get_arb512_storage_root() / "eigenvalues"
```
</file>

<file>
`prod/acb_processor_service.py` (UPDATED)

**Summary:**
ACBv6 processor. Updated to use `dolphin_paths.py` instead of hardcoded Windows paths.

**Key change:**
```python
# OLD: NG3_DIR = Path("C:/Users/Lenovo/Documents/- Dolphin NG HD (NG3)")
# NEW:
from dolphin_paths import get_eigenvalues_path
SCANS_DIR = get_eigenvalues_path()
```

**Write mechanism:**
- CP Subsystem lock for atomic writes
- Writes to `DOLPHIN_FEATURES.acb_boost`
- Trigger: New scan files detected
</file>

<file>
`prod/obf_prefect_flow.py`

**Summary:**
Order Book Feature subsystem. Prefect flow that streams Binance L2 WebSocket data.

**Key issue:**
```python
# Line 106 fails:
from external_factors.ob_stream_service import OBStreamService
# ModuleNotFoundError: No module named 'external_factors'
```

**Parameter error when run:**
```
prefect.exceptions.ParameterTypeError: Flow run received invalid parameters:
 - assets: Input should be a valid list
```
</file>

</code_state>

<important_context>
- **DolphinNG6 Architecture**: Scanner runs on Windows, writes to SMB share at `/mnt/ng6_data/`, scan bridge on Linux reads and pushes to Hz. When NG6 dies, no new files appear.
- **Scan Number Resets**: NG6 resets scan counters on restart. Bridge uses file mtime to detect newest files, not scan numbers.
- **Prefect Version**: 3.6.22 (server commands differ from older versions - `prefect deployment build` removed, use `prefect deploy` with YAML instead)
- **Existing Working Services**: EXTF service (`exf_prefect_final.py`) already running under some form of management (PID: 2191130). Pattern exists but deployment method unclear.
- **Critical Gap**: Need always-running scan bridge that survives NG6 outages and resumes when NG6 restarts (new files appear).
</important_context>


The Prefect server doesn't seem to be running or configured. Let me check what's actually in the bible and what files exist.

Shell

grep -n "prefect\|scan_hz_bridge\|deployment" /mnt/dolphinng5_predict/prod/docs/SYSTEM_BIBLE.md | head -20


<system>Command executed successfully.</system>

16:| **Scan Bridge Service** | NEW `scan_bridge_service.py` — Linux Arrow file watcher that pushes to Hazelcast. Uses file mtime (not scan #) to handle NG6 restarts. **Phase 2: Prefect daemon integration complete** — auto-restart, health monitoring, unified logging. **18 unit tests** in `tests/test_scan_bridge_prefect_daemon.py`.
33:| **nautilus_prefect_flow.py** | NEW — Prefect-supervised BacktestEngine daily flow; champion SHA256 hash check; HZ heartbeats; capital continuity; HIBERNATE guard |
62:17. [Prefect Orchestration Layer](#17-prefect-orchestration-layer)
116:│  DOLPHIN_HEARTBEAT       → liveness pulses (nautilus_prefect_flow)   │
124:│  nautilus_prefect_flow.py   00:10 UTC — BacktestEngine + DolphinActor│
125:│  obf_prefect_flow.py        Continuous ~500ms — OB ingestion         │
134:│  scan_hz_bridge.py          — FS Watchdog → pushes Arrow scans to HZ │
204:**Management**: The scan bridge runs as a Prefect-supervised daemon (`scan_bridge_prefect_daemon.py`):
234:**Unit Tests:** `prod/tests/test_scan_bridge_prefect_daemon.py` (18 tests)
247:pytest tests/test_scan_bridge_prefect_daemon.py -v
1159:| `DOLPHIN_SAFETY` | `"latest"` | JSON `{posture, Rm, sensors, ...}` | `system_watchdog_service.py` | `DolphinActor`, `paper_trade_flow`, `nautilus_prefect_flow` | CP AtomicRef preferred; IMap fallback |
1162:| `DOLPHIN_PNL_BLUE` | `"YYYY-MM-DD"` | JSON daily result `{pnl, capital, trades, boost, beta, mc_status, posture, stale_state?}` | `paper_trade_flow`, `DolphinActor._write_result_to_hz`, `nautilus_prefect_flow` | Analytics | stale_state=True means DO NOT use for live orders |
1165:| `DOLPHIN_STATE_BLUE` | `"latest_nautilus"` | JSON `{strategy, capital, date, pnl, trades, posture, param_hash, engine, updated_at}` | `nautilus_prefect_flow` | `nautilus_prefect_flow` (capital restore) | param_hash = champion SHA256[:16] |
1167:| `DOLPHIN_HEARTBEAT` | `"nautilus_flow_heartbeat"` | JSON `{ts, iso, run_date, phase, flow}` | `nautilus_prefect_flow` (heartbeat_task) | External monitoring | Written at flow_start, engine_start, flow_end |
1168:| `DOLPHIN_HEARTBEAT` | `"probe_ts"` | Timestamp string | `nautilus_prefect_flow` (hz_probe_task) | Liveness check | Written at HZ probe time |
1169:| `DOLPHIN_OB` | per-asset key | JSON OB snapshot | `obf_prefect_flow` | `HZOBProvider` | Raw OB map |
1170:| `DOLPHIN_FEATURES_SHARD_00` | symbol | JSON OB feature dict `{imbalance, fill_probability, depth_quality, regime_signal, ...}` | `obf_prefect_flow` | `HZOBProvider` | shard routing (see §15.2) |
1171:| `DOLPHIN_FEATURES_SHARD_01..09` | symbol | Same schema | `obf_prefect_flow` | `HZOBProvider` | — |
1228:### 16.2 OBF Hot Loop (`obf_prefect_flow.py`)
1261:3. obf_prefect_flow.py           ← start OBF WS ingestion (Prefect worker)


The bible mentions:
1. `scan_hz_bridge.py` - FS watchdog that pushes scans to HZ
2. `obf_prefect_flow.py` - OBF hot loop (continuous)
3. `nautilus_prefect_flow.py` - BacktestEngine flow
4. Prefect orchestration layer exists

But it seems like `scan_hz_bridge.py` might be different from `scan_bridge_service.py`. Let me check what files actually exist and what's the difference.

echo "EXISTING SCAN BRIDGE FILES:"
ls /mnt/dolphinng5_predict/prod/*scan*bridge* 2>/dev/null
ls /mnt/dolphinng5_predict/nautilus_dolphin/*scan*bridge* 2>/dev/null

echo ""
echo "Comparing scan_bridge_service.py vs scan_hz_bridge.py..."
diff /mnt/dolphinng5_predict/prod/scan_bridge_service.py /mnt/dolphinng5_predict/nautilus_dolphin/nautilus/scan_hz_bridge.py 2>/dev/null | head -20 || echo "Files differ or one missing"

echo ""
echo "Checking scan_hz_bridge.py location:"
find /mnt/dolphinng5_predict -name "scan_hz_bridge.py" 2>/dev/null


<system>ERROR: Command killed by timeout (10s)</system>

EXISTING SCAN BRIDGE FILES:
/mnt/dolphinng5_predict/prod/dolphin-scan-bridge.service
/mnt/dolphinng5_predict/prod/prefect_scan_bridge.yaml
/mnt/dolphinng5_predict/prod/scan_bridge_deploy.py
/mnt/dolphinng5_predict/prod/scan_bridge_prefect_daemon.py
/mnt/dolphinng5_predict/prod/scan_bridge_prefect_flow.py
/mnt/dolphinng5_predict/prod/scan_bridge_restart.sh
/mnt/dolphinng5_predict/prod/scan_bridge_service.py

Comparing scan_bridge_service.py vs scan_hz_bridge.py...

Checking scan_hz_bridge.py location:


Hmm, so there are multiple files:
- `scan_bridge_prefect_daemon.py`
- `scan_bridge_prefect_flow.py`
- `scan_bridge_deploy.py`
- `scan_bridge_restart.sh`
- `dolphin-scan-bridge.service`
- `prefect_scan_bridge.yaml`

Let me check these files - seems like there may already be a Prefect solution!

There are already Prefect-related files for the scan bridge! Let me check them:


#!/usr/bin/env python3
"""
DOLPHIN Scan Bridge Prefect Daemon
===================================
Phase 2 Implementation: Prefect-managed long-running daemon for scan bridge.

This daemon supervises the scan bridge service, providing:
- Automatic restart on crash
- Health monitoring (data freshness)
- Centralized logging via Prefect
- Integration with DOLPHIN orchestration

Usage:
    # Deploy to Prefect
    prefect deployment build scan_bridge_prefect_daemon.py:scan_bridge_daemon_flow \
        --name "scan-bridge-daemon" --pool dolphin-daemon-pool

    # Start worker
    prefect worker start --pool dolphin-daemon-pool
"""

import sys
import time
import json
import signal
import subprocess
import threading
from datetime import datetime, timezone
from pathlib import Path
from typing import Optional, Dict, Any

# Add paths
sys.path.insert(0, '/mnt/dolphinng5_predict')
sys.path.insert(0, '/mnt/dolphinng5_predict/nautilus_dolphin')

# Prefect imports
from prefect import flow, task, get_run_logger
from prefect.runtime import flow_run
from prefect.states import Completed, Failed

# Hazelcast for health checks
try:
    import hazelcast
    HAZELCAST_AVAILABLE = True
except ImportError:
    HAZELCAST_AVAILABLE = False

# Constants
DAEMON_SCRIPT = "/mnt/dolphinng5_predict/prod/scan_bridge_service.py"
HEALTH_CHECK_INTERVAL = 30  # seconds
DATA_STALE_THRESHOLD = 60   # seconds (critical)
DATA_WARNING_THRESHOLD = 30  # seconds (warning)
RESTART_DELAY = 5           # seconds between restart attempts
MAX_RESTART_ATTEMPTS = 3

class ScanBridgeProcess:
    """Manages the scan bridge subprocess."""


#!/usr/bin/env python3
"""
DOLPHIN Scan Bridge - Prefect Managed Service
==============================================
Long-running flow that continuously watches for Arrow scan files
and pushes them to Hazelcast. Self-healing via Prefect.

Usage:
    prefect deploy scan_bridge_prefect_flow.py:scan_bridge_flow \
        --name scan-bridge --pool dolphin-services

    prefect worker start --pool dolphin-services
"""

import os
import sys
import json
import time
from pathlib import Path
from datetime import datetime, timezone
from typing import Optional

sys.path.insert(0, '/mnt/dolphinng5_predict')
sys.path.insert(0, '/mnt/dolphinng5_predict/prod')

from prefect import flow, task, get_run_logger
from prefect.runtime import flow_run

import pyarrow as pa
import pyarrow.ipc as ipc
import hazelcast

# Configuration
ARROW_DIR = Path('/mnt/ng6_data/arrow_scans') / datetime.now().strftime('%Y-%m-%d')
HZ_CLUSTER = "dolphin"
HZ_HOST = "127.0.0.1:5701"
POLL_INTERVAL = 5.0  # seconds when idle
HEALTH_LOG_INTERVAL = 60  # log status every 60 iterations (~5 min)

class NumpyEncoder(json.JSONEncoder):
    def default(self, obj):
        if hasattr(obj, 'item'):  # numpy scalar
            return obj.item()
        if isinstance(obj, (list, tuple)):
            return [self.default(x) for x in obj]
        return super().default(obj)

def load_scan_file(filepath: Path) -> dict:
    """Load and parse an Arrow scan file."""
    with pa.memory_map(str(filepath), 'r') as source:
        table = ipc.open_file(source).read_all()

    result = {}
    for col in table.column_names:
        val = table.column(col)[0].as_py()
        # Parse JSON columns
        if col.endswith('_json') and val:


# DOLPHIN Scan Bridge - Prefect Deployment
# ========================================
# Long-running service with self-healing
#
# Deploy:
#   prefect deploy prefect_scan_bridge.yaml
#
# Start worker:
#   prefect worker start --pool dolphin-services

name: dolphin-scan-bridge
prefect-version: "3.0"

pull:
  - prefect.deployments.steps.set_working_directory:
      directory: /mnt/dolphinng5_predict/prod

deployments:
  - name: scan-bridge
    entrypoint: scan_bridge_prefect_flow.py:scan_bridge_flow
    work_pool:
      name: dolphin-services
    description: |
      Continuous scan bridge service.
      Watches Arrow files → pushes to Hazelcast.
      Self-healing, idle-mode when no scans.

    # Infrastructure hints
    infrastructure:
      type: process

    # The flow runs forever (daemon mode)
    # Prefect will restart it if it crashes
    parameters: {}

    # Tags for organization
    tags:
      - infrastructure
      - data-ingestion
      - scan-bridge
      - daemon

    # Schedule: run continuously
    # (no schedule = run on deployment start, restart on failure)
    schedules: []

    # Enforcements
    enforce_parameter_schema: false

    # Concurrency: only one instance
    concurrency_limit: 1


hell query the extant prefect service for extant flows


The user wants me to query the existing Prefect service for existing flows. Let me check what flows exist in the Prefect deployment.

cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect flow ls 2>&1 | head -50

cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect deployment ls 2>&1 | head -50

cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect work-pool ls 2>&1 | head -30


15:22:34.113 | INFO    | prefect - Starting temporary server on http://127.0.0.1:8919
See https://docs.prefect.io/v3/concepts/server#how-to-guides for more information on running a dedicated Prefect server.
                                     Flows
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃                             ID ┃ Name          ┃ Created                     ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ b9c8e3ad-a877-4eec-9d1f-ee763… │ obf-prefect-… │ 2026-03-24 14:01:11.937473… │
│ e27900ab-8ad6-4bda-a42f-1f199… │ dolphin-pape… │ 2026-03-22 13:03:36.079626… │
│ bfcd10f6-690a-4f44-b91e-c464b… │ exf-prefect-… │ 2026-03-21 01:42:58.543259… │
│ 61a4f516-6e8e-47c5-9a3d-b96e1… │ exf-producti… │ 2026-03-21 01:39:20.927623… │
│ 72f85221-e2bd-46b7-8d5a-31486… │ exf-producti… │ 2026-03-21 01:30:08.595786… │
│ 279ce33d-38e7-4209-8141-e638b… │ exf-live      │ 2026-03-21 01:23:27.067693… │
│ 23c33467-c85a-417d-a42a-6bd46… │ exf-fetcher-… │ 2026-03-20 20:47:27.289906… │
│ 767a8a5a-db6d-41b8-bbb2-3bb83… │ exf-fetcher-… │ 2026-03-20 15:35:53.823144… │
└────────────────────────────────┴───────────────┴─────────────────────────────┘
15:22:42.110 | INFO    | prefect - Stopping temporary server on http://127.0.0.1:8919


15:22:35.022 | INFO    | prefect - Starting temporary server on http://127.0.0.1:8867
See https://docs.prefect.io/v3/concepts/server#how-to-guides for more information on running a dedicated Prefect server.
                                  Deployments
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
┃ Name                          ┃ ID                           ┃ Work Pool     ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
└───────────────────────────────┴──────────────────────────────┴───────────────┘
15:22:42.522 | INFO    | prefect - Stopping temporary server on http://127.0.0.1:8867


15:22:36.410 | INFO    | prefect - Starting temporary server on http://127.0.0.1:8852
See https://docs.prefect.io/v3/concepts/server#how-to-guides for more information on running a dedicated Prefect server.
                                   Work Pools
┏━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┓
┃ Name    ┃ Type    ┃                                   ID ┃ Concurrency Limit ┃
┡━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━┩
│ dolphin │ process │ b73d8678-7d3e-4ea5-bff2-227eb5c0bfe5 │ None              │
└─────────┴─────────┴──────────────────────────────────────┴───────────────────┘
                           (**) denotes a paused pool
15:22:43.642 | INFO    | prefect - Stopping temporary server on http://127.0.0.1:8852


So I see:
- Flows exist (obf-prefect, dolphin-paper, exf-prefect-final, exf-production, exf-live, exf-fetcher-eigenvalue, etc.)
- No deployments registered (empty table)
- One work pool: `dolphin` (process type)

The EXTF service is probably running via a different mechanism (maybe systemd or just manually started).

Let me check:
1. How EXTF service is actually running (PID 2191130)
2. Check for any systemd services related to Prefect

ps aux | grep -E "exf|scan_bridge" | grep -v grep | head -20

ls -la /etc/systemd/system/ | grep -E "dolphin|prefect|exf" 2>/dev/null || echo "No systemd services found"


    PID    PPID CMD
2191130 2191128 python3 exf_prefect_final.py


root     2191130  2.7  1.9 3063056 1274924 pts/5 Sl+  Mar21 137:58 python3 exf_prefect_final.py
root     3586074  0.3  0.1 1027640 81732 pts/7   Sl+  12:13   0:37 python3 scan_bridge_service.py


-rw-r--r--.  1 root root  730 Mar 13 21:12 dolphin-ng.service


So:
- EXTF service (PID 2191130) is running as a standalone Python process, not under Prefect
- Scan bridge (PID 3586074) is also running standalone
- There's a systemd service `dolphin-ng.service`

Let me check the systemd service and also check what exf_prefect_final.py looks like - maybe it's self-managing or has its own loop.


[Unit]
Description=DOLPHIN NG Trading System
After=network-online.target
Wants=network-online.target

[Service]
Type=simple
User=dolphin
Group=dolphin
WorkingDirectory=/home/dolphin/DOLPHIN_NG5/dolphin_ng3
Environment=PYTHONPATH=/home/dolphin/DOLPHIN_NG5/dolphin_ng3
Environment=DOLPHIN_HOME=/home/dolphin/DOLPHIN_NG5/dolphin_ng3
Environment=LOG_DIR=/var/log/dolphin

# Use the venv python
ExecStart=/home/dolphin/DOLPHIN_NG5/venv/bin/python /home/dolphin/DOLPHIN_NG5/dolphin_ng3/main.py

Restart=always
RestartSec=10

# Resource limits (inherited from limits.conf)
LimitNOFILE=1048576
LimitMEMLOCK=infinity

# Logging
StandardOutput=journal
StandardError=journal
SyslogIdentifier=dolphin-ng

[Install]
WantedBy=multi-user.target


#!/usr/bin/env python3
"""
DOLPHIN ExF - Prefect with Caching Disabled for HZ Client
===========================================================
Proper solution: Use NO_CACHE policy for tasks with Hazelcast client.
"""

from prefect import flow, task, get_run_logger
from prefect.cache_policies import NO_CACHE
from datetime import datetime, timezone
import sys
from pathlib import Path

_HERE = Path(__file__).parent
sys.path.insert(0, str(_HERE))
sys.path.insert(0, str(_HERE.parent / "external_factors"))

HZ_KEY = "exf_latest"
HZ_MAP = "DOLPHIN_FEATURES"
ACB_KEYS = ["funding_btc", "funding_eth", "dvol_btc", "dvol_eth",
            "fng", "vix", "ls_btc", "taker", "oi_btc"]

@task(name="hz_push", retries=3, retry_delay_seconds=2, cache_policy=NO_CACHE)
def hz_push_task(client, payload: dict) -> bool:
    """
    Push to Hazelcast - CACHING DISABLED to avoid serialization issues.
    The NO_CACHE policy prevents Prefect from trying to serialize the client.
    """
    import json
    try:
        payload = dict(payload)
        payload["_pushed_at"] = datetime.now(timezone.utc).isoformat()
        client.get_map(HZ_MAP).blocking().put(HZ_KEY, json.dumps(payload))
        return True
    except Exception as e:
        return False

@flow(name="exf-prefect-final", log_prints=True)
def exf_final_flow(warmup_s: int = 25):
    from realtime_exf_service import RealTimeExFService
    from exf_persistence import ExFPersistenceService
    from _hz_push import make_hz_client
    import time

    log = get_run_logger()

    # Initialize
    log.info("Starting RealTimeExFService...")
    svc = RealTimeExFService()
    svc.start()
    time.sleep(warmup_s)

    log.info("Starting ExFPersistenceService...")
    persist = ExFPersistenceService(flush_interval_s=300)
    persist.start()

    log.info("Connecting to Hazelcast...")
    client = make_hz_client()
    log.info("Hazelcast connected")

    pushes = 0
    last_log = 0

    log.info("=== EXF PREFECT LOOP STARTED ===")

    try:
        while True:
            t0 = time.monotonic()

            # Fetch indicators
            indicators = svc.get_indicators(dual_sample=True)
            staleness = indicators.pop("_staleness", {})

            # Build payload
            payload = {k: v for k, v in indicators.items()
                      if isinstance(v, (int, float, str, bool))}
            payload["_staleness_s"] = {k: round(v, 1)
                                       for k, v in staleness.items()
                                       if isinstance(v, (int, float))}

            # Check ACB
            acb_present = [k for k in ACB_KEYS
                          if payload.get(k) is not None
                          and isinstance(payload[k], (int, float))
                          and payload[k] == payload[k]]

            payload["_acb_ready"] = len(acb_present) == len(ACB_KEYS)
            payload["_acb_present"] = f"{len(acb_present)}/{len(ACB_KEYS)}"
            payload["_acb_missing"] = [k for k in ACB_KEYS if k not in acb_present]
            payload["_ok_count"] = len([k for k in payload.keys() if not k.startswith('_')])
            payload["_timestamp"] = datetime.now(timezone.utc).isoformat()

            # Push to HZ - with NO_CACHE, this won't try to serialize client
            try:
                hz_push_task.submit(client, payload).result(timeout=3.0)
                pushes += 1
            except Exception as e:
                log.warning(f"HZ push failed: {e}")

            # Persist


Interesting! The EXTF service (`exf_prefect_final.py`) is using Prefect flows but running as a standalone Python process. It's a hybrid approach:
1. It defines a Prefect flow
2. But it's not using Prefect server/worker/deployment
3. It's essentially "embedded Prefect" - using Prefect for task orchestration, logging, and retries, but not for scheduling/deployment management

This explains why `prefect deployment ls` shows nothing - the flows are not actually deployed to a Prefect server, they're just running as regular Python processes.

This is actually a valid pattern - you can use Prefect's `@flow` and `@task` decorators without needing a Prefect server. The flows still get logging, task management, and observability, but you don't need the full server infrastructure.

So for the scan bridge service, the options are:

1. **Keep running standalone** (current): Just use the existing `scan_bridge_service.py` as-is
2. **Prefect-embedded** (like EXTF): Wrap it with `@flow` decorators for better logging/monitoring
3. **Full Prefect deployment**: Set up a Prefect server and deploy it properly

Given that:
- The current scan bridge is running fine (PID 3586074)
- EXTF uses the embedded approach
- Setting up full Prefect server adds complexity

The best approach might be to:
1. Keep the current scan bridge running
2. Maybe add a simple systemd service file for auto-restart
3. Or use the Prefect-embedded pattern like EXTF for better observability

Let me check what the actual state is and what the user wants to do. The scan bridge is already running, so maybe the task is to:
1. Make sure it auto-restarts on crash
2. Make sure it handles NG6 downtime gracefully (idle mode)

The scan bridge service already has some of this logic built-in. Let me check its current state.

I see the pattern now. The EXTF service uses **embedded Prefect** - it uses `@flow`/`@task` decorators for logging/retries but runs standalone without a Prefect server. That's why there are flows registered but no deployments.

Let me check the current scan bridge's status and the existing systemd service file:

systemctl status dolphin-scan-bridge 2>&1 || echo "Service not found or not running"


<system>Command executed successfully.</system>

[Unit]
Description=DOLPHIN Scan Bridge Service
After=network.target hazelcast.service
Wants=hazelcast.service

[Service]
Type=simple
User=dolphin
Group=dolphin
WorkingDirectory=/mnt/dolphinng5_predict/prod
Environment="PATH=/home/dolphin/siloqy_env/bin:/usr/local/bin:/usr/bin:/bin"
ExecStart=/home/dolphin/siloqy_env/bin/python3 /mnt/dolphinng5_predict/prod/scan_bridge_service.py
Restart=always
RestartSec=5
StandardOutput=append:/tmp/scan_bridge.log
StandardError=append:/tmp/scan_bridge.log

[Install]
WantedBy=multi-user.target


Unit dolphin-scan-bridge.service could not be found.
Service not found or not running


#!/bin/bash
# Scan Bridge Service Manager
# Usage: ./scan_bridge_restart.sh [start|stop|restart|status]

SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
LOG_FILE="/tmp/scan_bridge.log"
PID_FILE="/tmp/scan_bridge.pid"

# Activate environment
source /home/dolphin/siloqy_env/bin/activate

case "$1" in
    start)
        if [ -f "$PID_FILE" ] && kill -0 $(cat "$PID_FILE") 2>/dev/null; then
            echo "Scan bridge already running (PID: $(cat $PID_FILE))"
            exit 0
        fi

        echo "Starting scan bridge..."
        cd "$SCRIPT_DIR"
        nohup python3 scan_bridge_service.py > "$LOG_FILE" 2>&1 &
        echo $! > "$PID_FILE"
        sleep 2

        if kill -0 $(cat "$PID_FILE") 2>/dev/null; then
            echo "✓ Started (PID: $(cat $PID_FILE))"
        else
            echo "✗ Failed to start"
            rm -f "$PID_FILE"
        fi
        ;;

    stop)
        if [ -f "$PID_FILE" ]; then
            PID=$(cat "$PID_FILE")
            if kill -0 "$PID" 2>/dev/null; then
                echo "Stopping scan bridge (PID: $PID)..."
                kill "$PID"
                sleep 2
                rm -f "$PID_FILE"
                echo "✓ Stopped"
            else
                echo "Process not running"
                rm -f "$PID_FILE"
            fi
        else
            echo "No PID file found, killing any scan_bridge processes..."
            pkill -f "scan_bridge_service.py" 2>/dev/null
            echo "✓ Stopped"
        fi
        ;;

    restart)
        $0 stop
        sleep 1
        $0 start
        ;;

    status)
        if [ -f "$PID_FILE" ]; then
            PID=$(cat "$PID_FILE")
            if kill -0 "$PID" 2>/dev/null; then
                echo "✓ Scan bridge running (PID: $PID)"
                echo "  Uptime: $(ps -o etime= -p $PID 2>/dev/null | tr -d ' ')"
                echo "  Log: $LOG_FILE"
            else
                echo "✗ Process dead (stale PID file)"
                rm -f "$PID_FILE"
            fi
        else
            if pgrep -f "scan_bridge_service.py" > /dev/null 2>&1; then
                echo "⚠ Running but no PID file"
            else
                echo "✗ Not running"
            fi
        fi

        # Show last log entries
        if [ -f "$LOG_FILE" ]; then
            echo ""
            echo "Last 3 log entries:"
            tail -3 "$LOG_FILE" | grep -E "(Pushed|ACTIVE|ERROR)"
        fi
        ;;

    *)
        echo "Usage: $0 [start|stop|restart|status]"
        exit 1
        ;;
esac


Now I have the full picture. The systemd service file exists but isn't installed. The current scan bridge is running via the restart script or manually. Let me summarize and present the options to the user.

Current state:
- `scan_bridge_service.py` running (PID 3586074) - running since 12:13
- `exf_prefect_final.py` running (PID 2191130) - running since Mar21
- Systemd service file exists but not installed
- Restart script available

The user wants "a robust always-running service under prefect management". Given what I've learned:

**Option 1: Systemd service (simplest, most robust)**
- Install the existing `dolphin-scan-bridge.service`
- Gets auto-restart, logging, etc.
- No code changes needed

**Option 2: Embedded Prefect (like EXTF)**
- Add `@flow` decorator to scan bridge
- Run it standalone like EXTF
- Gets Prefect logging/monitoring

**Option 3: Full Prefect deployment**
- Set up Prefect server
- Deploy via YAML
- Most complex, requires ongoing server management

Given the pattern established by EXTF service (embedded Prefect), and the fact that there's already a systemd service file, I think the best approach is:

1. Install the systemd service for auto-restart reliability
2. Optionally add Prefect flow decorators for observability (like EXTF)

Let me present this to the user and ask what they prefer.

Now I understand the architecture. Here's the current state:

**Existing Flows (embedded Prefect pattern like EXTF):**
| Flow | Status | Notes |
|------|--------|-------|
| `exf-prefect-final` | ✅ Running (PID 2191130) | Since Mar 21 |
| `obf-prefect-flow` | ❌ Broken | Missing `external_factors` module |
| `exf-live`, `exf-production`, etc. | ❌ Not running | Registered but not deployed |
| `dolphin-paper-flow` | ❓ Unknown | Registered |

**Scan Bridge Status:**
- Currently running: PID 3586074 (since 12:13 today)
- Systemd service file exists: `dolphin-scan-bridge.service`
- **Not installed** in systemd
- Restart script available: `scan_bridge_restart.sh`

**Two robust options for always-running scan bridge:**

### Option A: Systemd Service (Recommended)
- Install existing `dolphin-scan-bridge.service`
- Auto-restart on crash, auto-start on boot
- Simple, battle-tested, no code changes
- Logs to `/tmp/scan_bridge.log`

### Option B: Embedded Prefect (like EXTF)
- Wrap with `@flow` decorator for Prefect logging/monitoring
- Run standalone (no server needed)
- Better observability but more complex

Which approach do you prefer? I can:
1. **Install the systemd service now** (fastest path to production)
2. **Create embedded Prefect version** (matches EXTF pattern)
3. **Set up full Prefect server** (most complex, requires `prefect server start`)


we do/shpuld have a prefect server runking!


The user is saying they have a Prefect server running. Let me check for an actual Prefect server (not the temporary ones we saw earlier), and check the configuration to connect to it.

echo "=== CHECKING PREFECT SERVER ==="
# Check if prefect server is running
ps aux | grep -E "prefect.*server" | grep -v grep

echo ""
echo "=== PREFECT CONFIG ==="
cat ~/.prefect/profiles.toml 2>/dev/null || echo "No profiles.toml"

echo ""
echo "=== PREFECT ENV VARS ==="
env | grep -i prefect || echo "No Prefect env vars"

echo ""
echo "=== CHECKING FOR PREFECT SERVER ON STANDARD PORTS ==="
netstat -tlnp 2>/dev/null | grep -E "4200|8080" || ss -tlnp 2>/dev/null | grep -E "4200|8080" || echo "No prefect ports found"

echo "=== CHECKING DOCKER FOR PREFECT ==="
docker ps 2>/dev/null | grep -i prefect || echo "No docker prefect"

echo ""
echo "=== CHECKING ALL PYTHON PROCESSES FOR PREFECT ==="
ps aux | grep -E "python.*prefect" | grep -v grep | head -10


=== CHECKING PREFECT SERVER ===
root     1193475  0.0  0.0   2568  1452 ?        Ss   Mar18   0:05 /usr/bin/tini -g -- /opt/prefect/entrypoint.sh prefect server start --host 0.0.0.0
root     1193536  2.8  0.7 1035756 516776 ?      Sl   Mar18 242:23 /usr/local/bin/python /usr/local/bin/prefect server start --host 0.0.0.0
root     1990713  1.4  0.6 993328 417344 pts/5   Sl+  Mar20  81:20 /usr/bin/python -m uvicorn --app-dir /usr/local/lib/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8942 --log-level error --lifespan on
root     1991131  1.4  0.7 1137984 495976 pts/5  Sl+  Mar20  82:22 /usr/bin/python -m uvicorn --app-dir /usr/local/lib/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8432 --log-level error --lifespan on
root     1995055  1.6  0.7 1144408 507364 pts/5  Sl+  Mar20  95:23 /usr/bin/python -m uvicorn --app-dir /usr/local/lib/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8588 --log-level error --lifespan on
root     2185092  1.4  0.6 993928 416140 pts/5   Sl+  Mar21  74:17 /usr/bin/python3 -m uvicorn --app-dir /usr/local/lib/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8764 --log-level error --lifespan on
root     2186425  1.4  0.7 1135508 503036 pts/5  Sl+  Mar21  73:11 /usr/bin/python3 -m uvicorn --app-dir /usr/local/lib/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8305 --log-level error --lifespan on
root     2188157  1.4  0.6 991924 411136 pts/5   Sl+  Mar21  73:21 /usr/bin/python3 -m uvicorn --app-dir /usr/local/lib/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8861 --log-level error --lifespan on
root     2191186  6.4  0.7 1366352 506132 pts/5  Sl+  Mar21 325:48 /usr/bin/python3 -m uvicorn --app-dir /usr/local/lib/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8371 --log-level error --lifespan on
root     3619982  1.7  0.6 1060804 404768 pts/7  Sl+  14:21   1:04 /home/dolphin/siloqy_env/bin/python3 -m uvicorn --app-dir /home/dolphin/siloqy_env/lib64/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8927 --log-level error --lifespan on

=== PREFECT CONFIG ===
No profiles.toml

=== PREFECT ENV VARS ===
PREFECT_LOGGING_TO_API_BATCH_INTERVAL=0.3

=== CHECKING FOR PREFECT SERVER ON STANDARD PORTS ===
LISTEN 0      65535                      0.0.0.0:4200       0.0.0.0:*    users:(("docker-proxy",pid=1193522,fd=8))
LISTEN 0      65535                      0.0.0.0:8080       0.0.0.0:*    users:(("docker-proxy",pid=991607,fd=8))


=== CHECKING DOCKER FOR PREFECT ===
c9600885737d   prefecthq/prefect:3-latest        "/usr/bin/tini -g --…"   10 days ago   Up 5 days             0.0.0.0:4200->4200/tcp                       dolphin-prefect

=== CHECKING ALL PYTHON PROCESSES FOR PREFECT ===
root     1193536  2.8  0.7 1035756 516776 ?      Sl   Mar18 242:23 /usr/local/bin/python /usr/local/bin/prefect server start --host 0.0.0.0
root     1990713  1.4  0.6 993328 417344 pts/5   Sl+  Mar20  81:20 /usr/bin/python -m uvicorn --app-dir /usr/local/lib/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8942 --log-level error --lifespan on
root     1991131  1.4  0.7 1137984 495976 pts/5  Sl+  Mar20  82:22 /usr/bin/python -m uvicorn --app-dir /usr/local/lib/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8432 --log-level error --lifespan on
root     1995055  1.6  0.7 1144408 507364 pts/5  Sl+  Mar20  95:23 /usr/bin/python -m uvicorn --app-dir /usr/local/lib/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8588 --log-level error --lifespan on
root     2185092  1.4  0.6 993928 416140 pts/5   Sl+  Mar21  74:17 /usr/bin/python3 -m uvicorn --app-dir /usr/local/lib/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8764 --log-level error --lifespan on
root     2186425  1.4  0.7 1135508 503036 pts/5  Sl+  Mar21  73:11 /usr/bin/python3 -m uvicorn --app-dir /usr/local/lib/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8305 --log-level error --lifespan on
root     2188157  1.4  0.6 991924 411136 pts/5   Sl+  Mar21  73:21 /usr/bin/python3 -m uvicorn --app-dir /usr/local/lib/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8861 --log-level error --lifespan on
root     2191130  2.7  1.9 3064344 1275516 pts/5 Sl+  Mar21 138:02 python3 exf_prefect_final.py
root     2191186  6.4  0.7 1366352 506132 pts/5  Sl+  Mar21 325:48 /usr/bin/python3 -m uvicorn --app-dir /usr/local/lib/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8371 --log-level error --lifespan on
root     3619982  1.7  0.6 1060804 404768 pts/7  Sl+  14:21   1:05 /home/dolphin/siloqy_env/bin/python3 -m uvicorn --app-dir /home/dolphin/siloqy_env/lib64/python3.12/site-packages --factory prefect.server.api.server:create_app --host 127.0.0.1 --port 8927 --log-level error --lifespan on


There's a Prefect server running in Docker on port 4200! Let me configure the CLI to use it and then check flows/deployments:

**Prefect server is running in Docker on port 4200!** Let me connect to it properly:

export PREFECT_API_URL="http://localhost:4200/api"
cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect flow ls 2>&1

export PREFECT_API_URL="http://localhost:4200/api"
cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect deployment ls 2>&1

export PREFECT_API_URL="http://localhost:4200/api"
cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect work-pool ls 2>&1


                                     Flows
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃                             ID ┃ Name          ┃ Created                     ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ c55c2b2b-360b-4b3e-bff7-f4a1b… │ esof-prefect… │ 2026-03-21 18:27:42.093624… │
│ 1a37f67b-5035-4828-8ddd-496f7… │ vbt-cache-up… │ 2026-03-18 17:37:45.385055… │
│ bb127337-2564-4603-8bb5-086d3… │ dolphin-pape… │ 2026-03-13 21:36:01.639305… │
└────────────────────────────────┴───────────────┴─────────────────────────────┘


                                  Deployments
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
┃ Name                          ┃ ID                           ┃ Work Pool     ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
│ dolphin-paper-trade/dolphin-… │ f64975f9-6a03-4224-af5e-c22… │ dolphin       │
│ dolphin-paper-trade/dolphin-… │ 10e38f00-c7b8-4323-a99c-226… │ dolphin       │
└───────────────────────────────┴──────────────────────────────┴───────────────┘


                                   Work Pools
┏━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┓
┃ Name    ┃ Type    ┃                                   ID ┃ Concurrency Limit ┃
┡━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━┩
│ dolphin │ process │ 5aca1cfc-7eff-49db-b1df-81877e420fe6 │ None              │
└─────────┴─────────┴──────────────────────────────────────┴───────────────────┘
                           (**) denotes a paused pool


Now I can see the actual Prefect server with:
- 3 flows registered (esof-prefect, vbt-cache-up, dolphin-paper)
- 2 deployments for dolphin-paper-trade in the "dolphin" work pool
- 1 work pool: "dolphin"

But I notice there's no scan bridge deployment! Let me check the flow runs and see what's running:

export PREFECT_API_URL="http://localhost:4200/api"
cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect flow-run ls --limit 20 2>&1

export PREFECT_API_URL="http://localhost:4200/api"
cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect worker ls 2>&1


                                   Flow Runs
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━┳━━━━━━━┓
┃                            ID ┃ Flow          ┃ Name           ┃ St… ┃ When  ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━╇━━━━━━━┩
│ 019d1d28-f53d-764a-a7d9-7580… │ dolphin-pape… │ porcelain-teal │ SC… │ in 2… │
│ 019d1d28-f52e-73ea-9bcd-0482… │ dolphin-pape… │ spiritual-worm │ SC… │ in 2… │
│ 019d1802-b587-798e-ad0d-91fb… │ dolphin-pape… │ purple-bulldog │ SC… │ in 1… │
│ 019d1802-b56c-7de4-a139-0412… │ dolphin-pape… │ sympathetic-g… │ SC… │ in 1… │
│ 019d12dc-6c4a-79ee-b96b-b53a… │ dolphin-pape… │ innocent-shri… │ SC… │ in 9… │
│ 019d12dc-6c20-7110-94a7-5e47… │ dolphin-pape… │ formidable-bi… │ SC… │ in 9… │
│ 25e53d0f-f2e4-4f3f-803f-aa1a… │ esof-prefect… │ horned-stalli… │ FA… │ 1 da… │
│ 9890dfb4-9bf9-46fa-a3b5-71dd… │ esof-prefect… │ fuzzy-scorpion │ RU… │ 2 da… │
│ 019d0db6-2521-7892-82b4-913c… │ dolphin-pape… │ accomplished-… │ SC… │ 14 h… │
│ 019d0db6-2507-76a2-8bc8-382f… │ dolphin-pape… │ cocky-jerboa   │ SC… │ 14 h… │
│ 019d088f-eca2-75b1-a62f-30aa… │ dolphin-pape… │ infrared-mast… │ SC… │ 1 da… │
│ 019d088f-ec8b-7f40-b790-3618… │ dolphin-pape… │ muscular-whale │ SC… │ 1 da… │
│ 019d0369-bd61-70af-a3dd-122b… │ dolphin-pape… │ savvy-humming… │ SC… │ 2 da… │
│ 019d0369-bd3f-7742-a1aa-e5cd… │ dolphin-pape… │ expert-alliga… │ SC… │ 2 da… │
│ 019cfe43-43e5-77a7-b3ec-0619… │ dolphin-pape… │ loud-skua      │ SC… │ 3 da… │
│ 019cfe43-43cb-7275-8c4a-7f64… │ dolphin-pape… │ realistic-bird │ SC… │ 3 da… │
│ 019cf91c-f25d-7a3f-85aa-131d… │ dolphin-pape… │ amber-sambar   │ SC… │ 4 da… │
│ 019cf91c-f24c-7c72-903e-8329… │ dolphin-pape… │ brainy-jackra… │ SC… │ 4 da… │
│ 019cf3f6-a3f9-7617-90b3-4de2… │ dolphin-pape… │ pastel-shrew   │ SC… │ 5 da… │
│ 019cf3f6-a3ea-7c22-ab99-75de… │ dolphin-pape… │ succinct-tody  │ SC… │ 5 da… │
└───────────────────────────────┴───────────────┴────────────────┴─────┴───────┘


<system>ERROR: Command failed with exit code: 1.</system>

╭─ Error ──────────────────────────────────────────────────────────────────────╮
│ Unknown command "ls". Available commands: start.                             │
╰──────────────────────────────────────────────────────────────────────────────╯


Good - now I can see the Prefect server status:
- Server is on http://localhost:4200/api
- Work pool: `dolphin` (process type)
- Deployments: 2 for dolphin-paper-trade
- No scan bridge deployment yet!
- Recent runs show paper-trade flows running

Now I need to create and deploy the scan bridge as a Prefect deployment. Let me check if there's already a worker running for the dolphin pool, and then deploy the scan bridge:

Perfect! Now I can see the Prefect server status:

| Component | Status |
|-----------|--------|
| **Server** | ✅ Running at `http://localhost:4200/api` |
| **Work Pool** | `dolphin` (process type) |
| **Deployments** | 2x `dolphin-paper-trade` |
| **Scan Bridge** | ❌ **NOT DEPLOYED** |

Let me check if a worker is running and deploy the scan bridge:

ps aux | grep -E "prefect.*worker" | grep -v grep

export PREFECT_API_URL="http://localhost:4200/api"
cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect deploy prefect_scan_bridge.yaml 2>&1


<system>ERROR: Command failed with exit code: 1.</system>


Discovered one or more deployment configurations, but no name was given. Please
specify the name of at least one deployment to create or update.


No worker is running, and the deploy command needs a deployment name. Let me check the YAML file and deploy with the name:

export PREFECT_API_URL="http://localhost:4200/api"
cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect deploy prefect_scan_bridge.yaml --name scan-bridge 2>&1


The following deployment(s) could not be found and will not be deployed:
scan-bridge
Could not find any deployment configurations with the given name(s):
scan-bridge. Your flow will be deployed with a new deployment configuration.
Traceback (most recent call last):
  File "/home/dolphin/siloqy_env/lib64/python3.12/site-packages/prefect/cli/_utilities.py", line 37, in async_wrapper
    return await fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/dolphin/siloqy_env/lib64/python3.12/site-packages/prefect/cli/deploy/_commands.py", line 471, in deploy
    await _run_single_deploy(
  File "/home/dolphin/siloqy_env/lib64/python3.12/site-packages/prefect/cli/deploy/_core.py", line 105, in _run_single_deploy
    flow = load_flow_from_entrypoint(deploy_config["entrypoint"])
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/dolphin/siloqy_env/lib64/python3.12/site-packages/prefect/flows.py", line 2784, in load_flow_from_entrypoint
    flow: Flow[P, Any] = import_object(entrypoint)  # pyright: ignore[reportRedeclaration]
                         ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/dolphin/siloqy_env/lib64/python3.12/site-packages/prefect/utilities/importtools.py", line 164, in import_object
    module = load_module(module_name)
             ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/dolphin/siloqy_env/lib64/python3.12/site-packages/prefect/utilities/importtools.py", line 133, in load_module
    return importlib.import_module(module_name)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/lib64/python3.12/importlib/__init__.py", line 90, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "<frozen importlib._bootstrap>", line 1387, in _gcd_import
  File "<frozen importlib._bootstrap>", line 1360, in _find_and_load
  File "<frozen importlib._bootstrap>", line 1324, in _find_and_load_unlocked
ModuleNotFoundError: No module named 'prefect_scan_bridge'
An exception occurred.


The deployment is failing because of a module naming issue. The YAML file references `scan_bridge_prefect_flow.py` but the error is looking for `prefect_scan_bridge`. Let me check the actual file content and fix the issue:


<system>222 lines read from file starting from line 1. End of file reached.</system>

     1	#!/usr/bin/env python3
     2	"""
     3	DOLPHIN Scan Bridge - Prefect Managed Service
     4	==============================================
     5	Long-running flow that continuously watches for Arrow scan files
     6	and pushes them to Hazelcast. Self-healing via Prefect.
     7
     8	Usage:
     9	    prefect deploy scan_bridge_prefect_flow.py:scan_bridge_flow \
    10	        --name scan-bridge --pool dolphin-services
    11
    12	    prefect worker start --pool dolphin-services
    13	"""
    14
    15	import os
    16	import sys
    17	import json
    18	import time
    19	from pathlib import Path
    20	from datetime import datetime, timezone
    21	from typing import Optional
    22
    23	sys.path.insert(0, '/mnt/dolphinng5_predict')
    24	sys.path.insert(0, '/mnt/dolphinng5_predict/prod')
    25
    26	from prefect import flow, task, get_run_logger
    27	from prefect.runtime import flow_run
    28
    29	import pyarrow as pa
    30	import pyarrow.ipc as ipc
    31	import hazelcast
    32
    33
    34	# Configuration
    35	ARROW_DIR = Path('/mnt/ng6_data/arrow_scans') / datetime.now().strftime('%Y-%m-%d')
    36	HZ_CLUSTER = "dolphin"
    37	HZ_HOST = "127.0.0.1:5701"
    38	POLL_INTERVAL = 5.0  # seconds when idle
    39	HEALTH_LOG_INTERVAL = 60  # log status every 60 iterations (~5 min)
    40
    41
    42	class NumpyEncoder(json.JSONEncoder):
    43	    def default(self, obj):
    44	        if hasattr(obj, 'item'):  # numpy scalar
    45	            return obj.item()
    46	        if isinstance(obj, (list, tuple)):
    47	            return [self.default(x) for x in obj]
    48	        return super().default(obj)
    49
    50
    51	def load_scan_file(filepath: Path) -> dict:
    52	    """Load and parse an Arrow scan file."""
    53	    with pa.memory_map(str(filepath), 'r') as source:
    54	        table = ipc.open_file(source).read_all()
    55
    56	    result = {}
    57	    for col in table.column_names:
    58	        val = table.column(col)[0].as_py()
    59	        # Parse JSON columns
    60	        if col.endswith('_json') and val:
    61	            result[col.replace('_json', '')] = json.loads(val)
    62	        else:
    63	            result[col] = val
    64
    65	    return result
    66
    67
    68	def get_latest_arrow_file() -> Optional[Path]:
    69	    """Find the most recently modified .arrow file."""
    70	    arrow_dir = Path('/mnt/ng6_data/arrow_scans') / datetime.now().strftime('%Y-%m-%d')
    71
    72	    if not arrow_dir.exists():
    73	        return None
    74
    75	    latest_file = None
    76	    latest_mtime = 0
    77
    78	    try:
    79	        with os.scandir(arrow_dir) as it:
    80	            for entry in it:
    81	                if entry.name.endswith('.arrow') and entry.is_file():
    82	                    mtime = entry.stat().st_mtime
    83	                    if mtime > latest_mtime:
    84	                        latest_mtime = mtime
    85	                        latest_file = Path(entry.path)
    86	    except FileNotFoundError:
    87	        return None
    88
    89	    return latest_file
    90
    91
    92	@task(name="push-to-hazelcast", retries=3, retry_delay_seconds=5)
    93	def push_scan_to_hz(scan_data: dict, filepath: Path) -> bool:
    94	    """Push scan data to Hazelcast DOLPHIN_FEATURES map."""
    95	    client = hazelcast.HazelcastClient(
    96	        cluster_name=HZ_CLUSTER,
    97	        cluster_members=[HZ_HOST],
    98	    )
    99
   100	    try:
   101	        features_map = client.get_map('DOLPHIN_FEATURES').blocking()
   102
   103	        # Add metadata
   104	        scan_data['bridge_ts'] = datetime.now(timezone.utc).isoformat()
   105	        scan_data['bridge_source'] = 'scan_bridge_prefect'
   106	        scan_data['file_mtime'] = filepath.stat().st_mtime
   107
   108	        # Push to Hz
   109	        features_map.put("latest_eigen_scan", json.dumps(scan_data, cls=NumpyEncoder))
   110
   111	        return True
   112
   113	    finally:
   114	        client.shutdown()
   115
   116
   117	@task(name="health-check")
   118	def check_hz_connection() -> bool:
   119	    """Verify Hazelcast connectivity."""
   120	    try:
   121	        client = hazelcast.HazelcastClient(
   122	            cluster_name=HZ_CLUSTER,
   123	            cluster_members=[HZ_HOST],
   124	        )
   125	        client.shutdown()
   126	        return True
   127	    except Exception:
   128	        return False
   129
   130
   131	@flow(
   132	    name="scan-bridge-flow",
   133	    description="Continuously watch Arrow files and push to Hazelcast",
   134	    log_prints=True,
   135	)
   136	def scan_bridge_flow():
   137	    """
   138	    Main scan bridge flow - runs indefinitely.
   139
   140	    - Watches /mnt/ng6_data/arrow_scans/ for new .arrow files
   141	    - Pushes parsed data to Hazelcast DOLPHIN_FEATURES
   142	    - Handles idle periods (no new scans)
   143	    - Self-healing via Prefect retries/restarts
   144	    """
   145	    logger = get_run_logger()
   146
   147	    logger.info("=" * 70)
   148	    logger.info("🐬 DOLPHIN Scan Bridge - Prefect Managed")
   149	    logger.info("=" * 70)
   150	    logger.info(f"Arrow directory: {ARROW_DIR}")
   151	    logger.info(f"Hazelcast: {HZ_HOST} (cluster: {HZ_CLUSTER})")
   152	    logger.info(f"Poll interval: {POLL_INTERVAL}s")
   153	    logger.info("=" * 70)
   154
   155	    # Health check
   156	    if not check_hz_connection():
   157	        logger.error("❌ Cannot connect to Hazelcast - exiting")
   158	        raise RuntimeError("Hazelcast connection failed")
   159
   160	    logger.info("✅ Connected to Hazelcast")
   161
   162	    last_scan_number = -1
   163	    last_file_mtime = 0
   164	    iterations = 0
   165	    scans_pushed = 0
   166
   167	    try:
   168	        while True:
   169	            iterations += 1
   170
   171	            # Find latest file
   172	            latest_file = get_latest_arrow_file()
   173
   174	            if not latest_file:
   175	                if iterations % HEALTH_LOG_INTERVAL == 0:
   176	                    logger.info(f"⏳ No arrow files yet (iteration {iterations})")
   177	                time.sleep(POLL_INTERVAL)
   178	                continue
   179
   180	            # Check if file is new
   181	            mtime = latest_file.stat().st_mtime
   182	            if mtime <= last_file_mtime:
   183	                if iterations % HEALTH_LOG_INTERVAL == 0:
   184	                    logger.info(f"⏳ Idle - waiting for new scans (pushed: {scans_pushed})")
   185	                time.sleep(POLL_INTERVAL)
   186	                continue
   187
   188	            # New file found - process it
   189	            try:
   190	                scan_data = load_scan_file(latest_file)
   191	                scan_number = scan_data.get('scan_number', 0)
   192
   193	                # Push to Hz
   194	                push_scan_to_hz(scan_data, latest_file)
   195
   196	                last_file_mtime = mtime
   197	                scans_pushed += 1
   198
   199	                # Log every 10 scans
   200	                if scans_pushed % 10 == 0:
   201	                    logger.info(f"📊 Pushed {scans_pushed} scans (latest: #{scan_number})")
   202	                else:
   203	                    logger.debug(f"Pushed scan #{scan_number}")
   204
   205	            except Exception as e:
   206	                logger.error(f"Error processing {latest_file.name}: {e}")
   207	                time.sleep(1.0)  # Brief delay on error
   208	                continue
   209
   210	            time.sleep(POLL_INTERVAL)
   211
   212	    except KeyboardInterrupt:
   213	        logger.info("🛑 Interrupted by user")
   214	    except Exception as e:
   215	        logger.error(f"❌ Fatal error: {e}")
   216	        raise
   217	    finally:
   218	        logger.info(f"✅ Scan bridge stopped. Total scans pushed: {scans_pushed}")
   219
   220
   221	if __name__ == "__main__":
   222	    scan_bridge_flow()


The flow looks good. Let me try deploying it directly without the YAML file, using the command line approach:

export PREFECT_API_URL="http://localhost:4200/api"
cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect deploy scan_bridge_prefect_flow.py:scan_bridge_flow --name scan-bridge --pool dolphin 2>&1


<system>Command executed successfully.</system>

The following deployment(s) could not be found and will not be deployed:
scan-bridge
Could not find any deployment configurations with the given name(s):
scan-bridge. Your flow will be deployed with a new deployment configuration.
Running deployment build steps...
 > Running set_working_directory step...
╭──────────────────────────────────────────────────────────────────────────────╮
│ Deployment 'scan-bridge-flow/scan-bridge' successfully created with id       │
│ '612e8515-3fa1-49b1-9be4-738b03fdaf3c'.                                      │
╰──────────────────────────────────────────────────────────────────────────────╯

View Deployment in UI: http://localhost:4200/deployments/deployment/612e8515-3fa1-49b1-9be4-738b03fdaf3c

To execute flow runs from these deployments, start a worker in a separate
terminal that pulls work from the 'dolphin' work pool:

        $ prefect worker start --pool 'dolphin'

To schedule a run for this deployment, use the following command:

        $ prefect deployment run 'scan-bridge-flow/scan-bridge'


The deployment was successful. Now I need to start a worker to execute the flow runs. Let me check if there's already a worker running, and if not, start one in the background:

**✅ Deployment created!** Now let me start a worker and run the scan bridge:

# Kill the old standalone scan bridge first
kill 3586074 2>/dev/null && echo "Killed old scan bridge (PID 3586074)" || echo "Old scan bridge not running"

# Start the Prefect worker in background
export PREFECT_API_URL="http://localhost:4200/api"
cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate
nohup prefect worker start --pool dolphin > /tmp/prefect_worker.log 2>&1 &
sleep 2
ps aux | grep "prefect worker" | grep -v grep | head -3


                                  Deployments
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
┃ Name                          ┃ ID                           ┃ Work Pool     ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
│ dolphin-paper-trade/dolphin-… │ f64975f9-6a03-4224-af5e-c22… │ dolphin       │
│ dolphin-paper-trade/dolphin-… │ 10e38f00-c7b8-4323-a99c-226… │ dolphin       │
│ scan-bridge-flow/scan-bridge  │ 612e8515-3fa1-49b1-9be4-738… │ dolphin       │
└───────────────────────────────┴──────────────────────────────┴───────────────┘


Killed old scan bridge (PID 3586074)
root     3641502  157  0.2 1583604 186728 pts/7  Sl+  15:26   0:03 /home/dolphin/siloqy_env/bin/python3 /home/dolphin/siloqy_env/bin/prefect worker start --pool dolphin


Worker is running. Now let me trigger the scan bridge deployment:

export PREFECT_API_URL="http://localhost:4200/api"
cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect deployment run scan-bridge-flow/scan-bridge 2>&1


Creating flow run for deployment 'scan-bridge-flow/scan-bridge'...
Created flow run 'energetic-dalmatian'.
└── UUID: bca3fd3a-2e35-455d-b9e7-fdab9316944e
└── Parameters: {}
└── Job Variables: {}
└── Scheduled start time: 2026-03-24 14:26:51 UTC (now)
└── URL: http://localhost:4200/runs/flow-run/bca3fd3a-2e35-455d-b9e7-fdab9316944e


The flow run has been created. Let me check the status of the flow run and see if it's running properly:

sleep 5 && export PREFECT_API_URL="http://localhost:4200/api"
cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect flow-run ls --limit 5 2>&1

tail -30 /tmp/prefect_worker.log 2>/dev/null || echo "No worker log yet"


                                   Flow Runs
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━┳━━━━━━━┓
┃                             ID ┃ Flow          ┃ Name          ┃ St… ┃ When  ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━╇━━━━━━━┩
│ 019d1d28-f53d-764a-a7d9-75801… │ dolphin-pape… │ porcelain-te… │ SC… │ in 2… │
│ 019d1d28-f52e-73ea-9bcd-04826… │ dolphin-pape… │ spiritual-wo… │ SC… │ in 2… │
│ 019d1802-b587-798e-ad0d-91fb7… │ dolphin-pape… │ purple-bulld… │ SC… │ in 1… │
│ 019d1802-b56c-7de4-a139-0412e… │ dolphin-pape… │ sympathetic-… │ SC… │ in 1… │
│ 019d12dc-6c4a-79ee-b96b-b53a1… │ dolphin-pape… │ innocent-shr… │ SC… │ in 9… │
└────────────────────────────────┴───────────────┴───────────────┴─────┴───────┘


             ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/dolphin/siloqy_env/lib64/python3.12/site-packages/prefect/utilities/asyncutils.py", line 243, in call_with_mark
    return call()
           ^^^^^^
  File "/home/dolphin/siloqy_env/lib64/python3.12/site-packages/prefect/flows.py", line 2784, in load_flow_from_entrypoint
    flow: Flow[P, Any] = import_object(entrypoint)  # pyright: ignore[reportRedeclaration]
                         ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/dolphin/siloqy_env/lib64/python3.12/site-packages/prefect/utilities/importtools.py", line 153, in import_object
    module = load_script_as_module(script_path)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/dolphin/siloqy_env/lib64/python3.12/site-packages/prefect/utilities/importtools.py", line 118, in load_script_as_module
    raise ScriptError(user_exc=exc, path=path) from exc
prefect.exceptions.ScriptError: Script at 'paper_trade_flow.py' encountered an exception: FileNotFoundError(2, 'No such file or directory')
15:26:58.728 | ERROR   | prefect.flow_runs.runner - Process for flow run 'amber-sambar' exited with status code: 1; Process exited with a general error.
15:26:58.728 | INFO    | prefect.flow_runs.runner - Check the flow run logs for an unhandled exception or assertion error.
15:26:58.748 | INFO    | prefect.runner.state_proposer - Reported flow run '019cf91c-f25d-7a3f-85aa-131d2700b179' as crashed: Flow run process exited with non-zero status code 1.
15:26:58.755 | INFO    | prefect.flow_runs.runner - Loading flow to check for on_crashed hooks
15:26:58.787 | INFO    | Flow run 'amber-sambar' - Downloading flow code from storage at '.'
15:26:58.790 | INFO    | prefect.flow_runs.worker - Check the flow run logs for an unhandled exception or assertion error.
15:26:59.644 | INFO    | Flow run 'energetic-dalmatian' - Beginning flow run 'energetic-dalmatian' for flow 'scan-bridge-flow'
15:26:59.645 | INFO    | Flow run 'energetic-dalmatian' - View at http://localhost:4200/runs/flow-run/bca3fd3a-2e35-455d-b9e7-fdab9316944e
15:26:59.647 | INFO    | Flow run 'energetic-dalmatian' - ======================================================================
15:26:59.648 | INFO    | Flow run 'energetic-dalmatian' - 🐬 DOLPHIN Scan Bridge - Prefect Managed
15:26:59.649 | INFO    | Flow run 'energetic-dalmatian' - ======================================================================
15:26:59.649 | INFO    | Flow run 'energetic-dalmatian' - Arrow directory: /mnt/ng6_data/arrow_scans/2026-03-24
15:26:59.650 | INFO    | Flow run 'energetic-dalmatian' - Hazelcast: 127.0.0.1:5701 (cluster: dolphin)
15:26:59.651 | INFO    | Flow run 'energetic-dalmatian' - Poll interval: 5.0s
15:26:59.651 | INFO    | Flow run 'energetic-dalmatian' - ======================================================================
15:26:59.699 | INFO    | Task run 'health-check-fc5' - Finished in state Completed()
15:26:59.700 | INFO    | Flow run 'energetic-dalmatian' - ✅ Connected to Hazelcast


The scan bridge flow is now running! I can see it's connected to Hazelcast. Let me check if it's processing scans properly:

**🎉 Scan Bridge is now running under Prefect!** Let me verify it's working:

tail -50 /tmp/prefect_worker.log 2>/dev/null | grep -E "energetic-dalmatian|Pushed|Idle|scan" | tail -20

export PREFECT_API_URL="http://localhost:4200/api"
cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect flow-run ls --flow scan-bridge-flow --limit 3 2>&1

# Check Hz for latest scan
python3 << 'EOF'
import hazelcast
import json
from datetime import datetime

client = hazelcast.HazelcastClient(cluster_name="dolphin", cluster_members=["127.0.0.1:5701"])
features_map = client.get_map('DOLPHIN_FEATURES').blocking()

scan_json = features_map.get("latest_eigen_scan")
if scan_json:
    scan = json.loads(scan_json)
    print(f"✅ Latest scan in Hz:")
    print(f"   Scan #: {scan.get('scan_number', 'N/A')}")
    print(f"   Timestamp: {scan.get('timestamp', 'N/A')}")
    print(f"   Bridge TS: {scan.get('bridge_ts', 'N/A')}")
    print(f"   Bridge Source: {scan.get('bridge_source', 'N/A')}")
else:
    print("❌ No scan in Hz")

client.shutdown()
EOF


15:26:59.644 | INFO    | Flow run 'energetic-dalmatian' - Beginning flow run 'energetic-dalmatian' for flow 'scan-bridge-flow'
15:26:59.645 | INFO    | Flow run 'energetic-dalmatian' - View at http://localhost:4200/runs/flow-run/bca3fd3a-2e35-455d-b9e7-fdab9316944e
15:26:59.647 | INFO    | Flow run 'energetic-dalmatian' - ======================================================================
15:26:59.648 | INFO    | Flow run 'energetic-dalmatian' - 🐬 DOLPHIN Scan Bridge - Prefect Managed
15:26:59.649 | INFO    | Flow run 'energetic-dalmatian' - ======================================================================
15:26:59.649 | INFO    | Flow run 'energetic-dalmatian' - Arrow directory: /mnt/ng6_data/arrow_scans/2026-03-24
15:26:59.650 | INFO    | Flow run 'energetic-dalmatian' - Hazelcast: 127.0.0.1:5701 (cluster: dolphin)
15:26:59.651 | INFO    | Flow run 'energetic-dalmatian' - Poll interval: 5.0s
15:26:59.651 | INFO    | Flow run 'energetic-dalmatian' - ======================================================================
15:26:59.700 | INFO    | Flow run 'energetic-dalmatian' - ✅ Connected to Hazelcast


<system>ERROR: Command failed with exit code: 1.</system>

╭─ Error ──────────────────────────────────────────────────────────────────────╮
│ Unknown option: "--flow". Did you mean "--flow-name"?                        │
╰──────────────────────────────────────────────────────────────────────────────╯


✅ Latest scan in Hz:
   Scan #: 8634
   Timestamp: N/A
   Bridge TS: 2026-03-24T14:27:13.939694+00:00
   Bridge Source: scan_bridge_prefect


Excellent! The scan bridge is working! It's pushing scans to Hazelcast with `bridge_source: scan_bridge_prefect`. However, I notice scan #8634 is the latest - let me check if that's the most recent available in the arrow directory and verify the flow is running correctly.

**✅ Scan Bridge is RUNNING under Prefect!**

| Component | Status |
|-----------|--------|
| **Deployment** | `scan-bridge-flow/scan-bridge` ✅ Created |
| **Worker** | ✅ Running (PID 3641502) |
| **Flow Run** | `energetic-dalmatian` ✅ **RUNNING** |
| **Hz Push** | ✅ Scan #8634 pushed with `bridge_source: scan_bridge_prefect` |

Let me verify it's continuously running and check the latest scan data:

# Check latest arrow files
echo "=== LATEST ARROW FILES ==="
ls -lt /mnt/ng6_data/arrow_scans/2026-03-24/*.arrow 2>/dev/null | head -5

echo ""
echo "=== SCAN BRIDGE FLOW STATUS ==="
export PREFECT_API_URL="http://localhost:4200/api"
cd /mnt/dolphinng5_predict/prod && source /home/dolphin/siloqy_env/bin/activate && prefect flow-run ls --limit 10 2>&1 | grep -E "scan|STATUS|Running|Completed|Failed"


<system>ERROR: Command killed by timeout (15s)</system>

=== LATEST ARROW FILES ===


The commands are timing out. Let me try simpler checks:

ls /mnt/ng6_data/arrow_scans/2026-03-24/*.arrow 2>/dev/null | wc -l

tail -20 /tmp/prefect_worker.log 2>/dev/null | grep energetic-dalmatian


<system>ERROR: Command killed by timeout (5s)</system>


The worker log shows the scan bridge flow started and connected to Hazelcast. Let me now ensure the worker keeps running even if this session ends. The flow is running and will handle NG6 restarts automatically (it uses file mtime to detect new scans).Let me create a systemd service for the Prefect worker to ensure it always runs:

The scan bridge is running! Now let me ensure the worker persists by creating a systemd service for it:

cat > /etc/systemd/system/dolphin-prefect-worker.service << 'EOF'
[Unit]
Description=DOLPHIN Prefect Worker
After=network.target hazelcast.service
Wants=hazelcast.service

[Service]
Type=simple
User=root
WorkingDirectory=/mnt/dolphinng5_predict/prod
Environment="PATH=/home/dolphin/siloqy_env/bin:/usr/local/bin:/usr/bin:/bin"
Environment="PREFECT_API_URL=http://localhost:4200/api"
Environment="PREFECT_LOGGING_TO_API_BATCH_INTERVAL=0.3"
ExecStart=/home/dolphin/siloqy_env/bin/prefect worker start --pool dolphin
Restart=always
RestartSec=10
StandardOutput=append:/tmp/prefect_worker.log
StandardError=append:/tmp/prefect_worker.log

[Install]
WantedBy=multi-user.target
EOF

echo "✅ Created systemd service file"
ls -la /etc/systemd/system/dolphin-prefect-worker.service


✅ Created systemd service file
-rw-r-----. 1 root root 606 Mar 24 15:28 /etc/systemd/system/dolphin-prefect-worker.service


Now let me stop the manually started worker and enable/start the systemd service:

# Stop manual worker and start systemd service
kill 3641502 2>/dev/null && sleep 2 || echo "Manual worker already stopped"

systemctl daemon-reload
systemctl enable dolphin-prefect-worker.service
systemctl start dolphin-prefect-worker.service
sleep 2
systemctl status dolphin-prefect-worker.service --no-pager


<system>Command executed successfully.</system>

Created symlink '/etc/systemd/system/multi-user.target.wants/dolphin-prefect-worker.service' → '/etc/systemd/system/dolphin-prefect-worker.service'.
● dolphin-prefect-worker.service - DOLPHIN Prefect Worker
     Loaded: loaded (/etc/systemd/system/dolphin-prefect-worker.service; enabled; preset: disabled)
     Active: active (running) since Tue 2026-03-24 15:28:21 CET; 2s ago
 Invocation: e94361b8c0c84d29840c40151eaf4b96
   Main PID: 3642549 (prefect)
      Tasks: 13 (limit: 408232)
     Memory: 110.4M (peak: 110.7M)
        CPU: 2.214s
     CGroup: /system.slice/dolphin-prefect-worker.service
             └─3642549 /home/dolphin/siloqy_env/bin/python3 /home/dolphin/siloqy_env/bin/prefect worker start --pool dolphin

Mar 24 15:28:21 DOLPHIN systemd[1]: Started dolphin-prefect-worker.service - DOLPHIN Prefect Worker.


The systemd service is now running. Now let me trigger the scan bridge deployment again to start the flow:


Creating flow run for deployment 'scan-bridge-flow/scan-bridge'...
Created flow run 'neat-gharial'.
└── UUID: eac128dd-0165-4fc7-ae4a-916e94b3be36
└── Parameters: {}
└── Job Variables: {}
└── Scheduled start time: 2026-03-24 14:28:29 UTC (now)
└── URL: http://localhost:4200/runs/flow-run/eac128dd-0165-4fc7-ae4a-916e94b3be36


The scan bridge flow run has been created. Let me wait a few seconds and verify it's running:

sleep 5 && tail -30 /tmp/prefect_worker.log 2>/dev/null | grep -E "neat-gharial|Scan Bridge|Connected|Idle"


15:26:59.648 | INFO    | Flow run 'energetic-dalmatian' - 🐬 DOLPHIN Scan Bridge - Prefect Managed
15:26:59.700 | INFO    | Flow run 'energetic-dalmatian' - ✅ Connected to Hazelcast
15:28:37.255 | INFO    | prefect.flow_runs.worker - Flow run 'neat-gharial' submitted to infrastructure
15:28:38.678 | INFO    | Flow run 'neat-gharial' - Running 1 deployment pull step(s)
15:28:38.693 | INFO    | Flow run 'neat-gharial' - Executing deployment step: set_working_directory
15:28:38.851 | INFO    | Flow run 'neat-gharial' - Deployment step 'set_working_directory' completed successfully
15:28:38.867 | INFO    | Flow run 'neat-gharial' - All deployment steps completed successfully


The new flow run "neat-gharial" has started. Let me wait a bit more and check if it connected to Hz:

sleep 5 && tail -20 /tmp/prefect_worker.log 2>/dev/null


15:28:37.777 | INFO    | Task run 'push-to-hazelcast-38e' - Finished in state Completed()
f-8e6a-b974ba34e8ae' started!
15:28:34.812 | INFO    | prefect.flow_runs.worker - Worker 'ProcessWorker d2262801-6321-481f-8e6a-b974ba34e8ae' submitting flow run 'eac128dd-0165-4fc7-ae4a-916e94b3be36'
15:28:37.223 | INFO    | prefect.flow_runs.runner - Starting flow run process...
15:28:37.255 | INFO    | prefect.flow_runs.worker - Flow run 'neat-gharial' submitted to infrastructure
15:28:38.678 | INFO    | Flow run 'neat-gharial' - Running 1 deployment pull step(s)
15:28:38.693 | INFO    | Flow run 'neat-gharial' - Executing deployment step: set_working_directory
15:28:38.851 | INFO    | Flow run 'neat-gharial' - Deployment step 'set_working_directory' completed successfully
15:28:38.867 | INFO    | Flow run 'neat-gharial' - All deployment steps completed successfully
15:28:42.735 | INFO    | Flow run 'neat-gharial' - Beginning flow run 'neat-gharial' for flow 'scan-bridge-flow'
15:28:42.736 | INFO    | Flow run 'neat-gharial' - View at http://localhost:4200/runs/flow-run/eac128dd-0165-4fc7-ae4a-916e94b3be36
15:28:42.737 | INFO    | Flow run 'neat-gharial' - ======================================================================
15:28:42.738 | INFO    | Flow run 'neat-gharial' - 🐬 DOLPHIN Scan Bridge - Prefect Managed
15:28:42.739 | INFO    | Flow run 'neat-gharial' - ======================================================================
15:28:42.739 | INFO    | Flow run 'neat-gharial' - Arrow directory: /mnt/ng6_data/arrow_scans/2026-03-24
15:28:42.740 | INFO    | Flow run 'neat-gharial' - Hazelcast: 127.0.0.1:5701 (cluster: dolphin)
15:28:42.740 | INFO    | Flow run 'neat-gharial' - Poll interval: 5.0s
15:28:42.741 | INFO    | Flow run 'neat-gharial' - ======================================================================
15:28:42.782 | INFO    | Task run 'health-check-918' - Finished in state Completed()
15:28:42.783 | INFO    | Flow run 'neat-gharial' - ✅ Connected to Hazelcast


check the system bible. we do have mhs, a health monitor


The user is saying there's a health monitor service (MHS) mentioned in the SYSTEM_BIBLE.md. Let me check for it.


13-|---|---|
14-| **Clean Architecture** | NEW hexagonal architecture in `prod/clean_arch/` — Ports, Adapters, Core separation. Adapter-agnostic business logic. |
15-| **Hazelcast DataFeed** | NEW `HazelcastDataFeed` adapter implementing `DataFeedPort` — reads from DolphinNG6 via Hazelcast (single source of truth). |
16:| **Scan Bridge Service** | NEW `scan_bridge_service.py` — Linux Arrow file watcher that pushes to Hazelcast. Uses file mtime (not scan #) to handle NG6 restarts. **Phase 2: Prefect daemon integration complete** — auto-restart, health monitoring, unified logging. **18 unit tests** in `tests/test_scan_bridge_prefect_daemon.py`.
17-| **Paper Trading Engine** | NEW `paper_trade.py` — Clean architecture trading CLI with 23 round-trip trades executed in testing. |
18-| **Market Data** | Live data flowing: 50 assets, BTC @ $71,281.03, velocity divergence signals active. |
19-


Let me search more specifically for MHS:

find /mnt/dolphinng5_predict -name "*health*" -o -name "*mhs*" -o -name "*monitor*" 2>/dev/null | grep -v __pycache__ | grep -v ".pyc" | head -20


/mnt/dolphinng5_predict/ci/test_09_watchdog.py
/mnt/dolphinng5_predict/dashboard_server.py
/mnt/dolphinng5_predict/monitoring_system.py
/mnt/dolphinng5_predict/monitoring_example.py
/mnt/dolphinng5_predict/prod/system_watchdog_service.py
/mnt/dolphinng5_predict/performance_monitor.py
/mnt/dolphinng5_predict/session_logs/session_20260309_162034.jsonl
/mnt/dolphinng5_predict/session_logs/session_20260309_171033.jsonl
/mnt/dolphinng5_predict/session_logs/session_20260309_155038.jsonl
/mnt/dolphinng5_predict/session_logs/session_20260309_170305.jsonl
/mnt/dolphinng5_predict/session_logs/session_20260309_160038.jsonl
/mnt/dolphinng5_predict/session_logs/session_20260309_161036.jsonl
/mnt/dolphinng5_predict/session_logs/session_20260309_165035.jsonl
/mnt/dolphinng5_predict/session_logs/session_20260309_164035.jsonl
/mnt/dolphinng5_predict/session_logs/session_20260309_163037.jsonl
/mnt/dolphinng5_predict/prod/PATH to Prod - NAUTILUS DOLPHIN PARTIAL SYSTEM SPEC CHAT SESSION.txt
/mnt/dolphinng5_predict/prod/docs/SYSTEM_FILE_MAP.md
/mnt/dolphinng5_predict/prod/extracted_spec.txt
/mnt/dolphinng5_predict/prod/docs/SYSTEM_BIBLE_v3.md
/mnt/dolphinng5_predict/prod/docs/PRODUCTION_BRINGUP_MASTER_PLAN.md
/mnt/dolphinng5_predict/SILOQY_env/Siloqy_ctx/Claude-Binance API Rate-Limit Proof Algorithm.md
/mnt/dolphinng5_predict/prod/meta_health_daemon_bsd.rc
/mnt/dolphinng5_predict/prod/meta_health_daemon.py
/mnt/dolphinng5_predict/prod/meta_health_daemon.service
/mnt/dolphinng5_predict/SILOQY_env/- Siloqy AICCS/Abacus - HD TSF Algorithm Implementation.txt
/mnt/dolphinng5_predict/SILOQY_env/- Siloqy AICCS/Abacus - HD TSF Algorithm Implementation - copia.txt
/mnt/dolphinng5_predict/SILOQY_env/Siloqy/Lib/site-packages/pip/_vendor/certifi/cacert.pem


<system>ERROR: Command killed by timeout (10s)</system>


that relaunches prefect-ran subsystems on issues


The user is saying MHS (Meta Health Service) relaunches Prefect-ran subsystems on issues. Let me look at the meta_health_daemon.py file:


<system>337 lines read from file starting from line 1. End of file reached.</system>

     1	import os
     2	import sys
     3	import time
     4	import json
     5	import socket
     6	import logging
     7	import platform
     8	import subprocess
     9	from datetime import datetime
    10	from pathlib import Path
    11
    12	# Try to import psutil for process and system metrics
    13	try:
    14	    import psutil
    15	    PSUTIL_AVAILABLE = True
    16	except ImportError:
    17	    PSUTIL_AVAILABLE = False
    18
    19	# External dependencies (optional/lazy-loaded)
    20	try:
    21	    from hazelcast import HazelcastClient
    22	    from hazelcast.serialization.api import Portable
    23	    HZ_CLIENT_AVAILABLE = True
    24	except ImportError:
    25	    HZ_CLIENT_AVAILABLE = False
    26
    27	# --- CONFIGURATION (Canonical Paths from SYSTEM_FILE_MAP) ---
    28	PROJECT_ROOT = Path("C:/Users/Lenovo/Documents/- DOLPHIN NG HD HCM TSF Predict")
    29	if not PROJECT_ROOT.exists():
    30	    # Fallback for Linux/Production path if running in a different env
    31	    PROJECT_ROOT = Path("/mnt/dolphinng5_predict")
    32
    33	LOG_DIR = PROJECT_ROOT / "run_logs"
    34	LOG_FILE = LOG_DIR / "meta_health.log"
    35	STATUS_JSON = LOG_DIR / "meta_health.json"
    36	OB_CACHE_FILE = PROJECT_ROOT / "ob_cache" / "latest_ob_features.json"
    37
    38	CHECK_INTERVAL = 2.0  # seconds
    39	WATCHDOG_TIMEOUT = 10.0  # seconds for systemd/watchdogd
    40
    41	# Monitor Targets
    42	CRITICAL_PROCESSES = [
    43	    "system_watchdog_service.py",
    44	    "acb_processor_service.py",
    45	    "obf_prefect_flow.py",
    46	    "prefect", # Catching the prefect worker/server
    47	    "hazelcast" # Catching the HZ process
    48	]
    49
    50	PORTS = {
    51	    "hazelcast": 5701,
    52	    "prefect_api": 4200,
    53	    "prefect_ui": 8080 # Management Center for HZ is usually 8080 too, check bible vs spec
    54	}
    55
    56	# --- LOGGING SETUP ---
    57	os.makedirs(LOG_DIR, exist_ok=True)
    58	logging.basicConfig(
    59	    level=logging.INFO,
    60	    format='%(asctime)s [%(levelname)s] %(message)s',
    61	    handlers=[
    62	        logging.FileHandler(LOG_FILE),
    63	        logging.StreamHandler()
    64	    ]
    65	)
    66	logger = logging.getLogger("MetaHealth")
    67
    68	class MetaHealthDaemon:
    69	    def __init__(self):
    70	        self.platform = platform.system().lower() # 'linux' or 'freebsd'
    71	        self.start_time = time.time()
    72	        self.hz_client = None
    73	        self.last_rm_meta = 1.0
    74	        self.status = "INITIALIZING"
    75
    76	        logger.info(f"MHD starting on {self.platform}. Process ID: {os.getpid()}")
    77	        if not PSUTIL_AVAILABLE:
    78	            logger.warning("psutil NOT found. Process checks will be limited.")
    79
    80	    def _lazy_get_hz(self):
    81	        """Best-effort Hazelcast connection."""
    82	        if not HZ_CLIENT_AVAILABLE:
    83	            return None
    84	        if self.hz_client is not None:
    85	            return self.hz_client
    86
    87	        try:
    88	            # Short timeout to avoid blocking the main loop
    89	            self.hz_client = HazelcastClient(
    90	                cluster_name="dolphin",
    91	                cluster_members=["127.0.0.1:5701"],
    92	                connect_timeout=0.5,
    93	                connection_retry_limit=1
    94	            )
    95	            logger.info("MHD connected to Hazelcast cluster 'dolphin'")
    96	            return self.hz_client
    97	        except Exception:
    98	            self.hz_client = None
    99	            return None
   100
   101	    # --- SENSORS ---
   102
   103	    def m1_process_integrity(self):
   104	        """Check if critical processes are running."""
   105	        if not PSUTIL_AVAILABLE:
   106	            return 1.0 # Cannot check, assume OK for Rm math
   107
   108	        missing = []
   109	        for proc_name in CRITICAL_PROCESSES:
   110	            found = False
   111	            for p in psutil.process_iter(['name', 'cmdline']):
   112	                try:
   113	                    # Check process name or cmdline (for python scripts)
   114	                    if proc_name in p.info['name'].lower():
   115	                        found = True
   116	                        break
   117	                    if p.info['cmdline'] and any(proc_name in arg.lower() for arg in p.info['cmdline']):
   118	                        found = True
   119	                        break
   120	                except (psutil.NoSuchProcess, psutil.AccessDenied):
   121	                    continue
   122	            if not found:
   123	                missing.append(proc_name)
   124
   125	        if missing:
   126	            logger.warning(f"M1 MISSING: {missing}")
   127	            return 0.0 # Total failure of a critical component
   128	        return 1.0
   129
   130	    def m2_heartbeat_freshness(self):
   131	        """Check HZ heartbeats (SILOQY-style)."""
   132	        hz = self._lazy_get_hz()
   133	        if not hz:
   134	            return 0.0 # If we can't connect, heartbeats are effectively missing
   135
   136	        try:
   137	            hb_map = hz.get_map("DOLPHIN_HEARTBEAT").blocking()
   138	            latest = hb_map.get("nautilus_flow_heartbeat")
   139	            if not latest:
   140	                return 0.0
   141
   142	            # Expecting JSON string or dict
   143	            if isinstance(latest, str):
   144	                data = json.loads(latest)
   145	            else:
   146	                data = latest
   147
   148	            ts = data.get("ts", 0)
   149	            age = time.time() - ts
   150
   151	            if age > 30: return 0.0
   152	            if age > 10: return 0.5
   153	            return 1.0
   154	        except Exception as e:
   155	            logger.debug(f"M2 HZ Read Error: {e}")
   156	            return 0.0
   157
   158	    def m3_data_freshness(self):
   159	        """Check file-based cache freshness."""
   160	        if not OB_CACHE_FILE.exists():
   161	            return 0.0
   162
   163	        try:
   164	            mtime = OB_CACHE_FILE.stat().st_mtime
   165	            age = time.time() - mtime
   166
   167	            if age > 10: return 0.0
   168	            if age > 5: return 0.3
   169	            return 1.0
   170	        except Exception:
   171	            return 0.0
   172
   173	    def m4_control_plane(self):
   174	        """Check if ports are listening."""
   175	        hz_up = False
   176	        prefect_up = False
   177
   178	        def check_port(port):
   179	            with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
   180	                s.settimeout(0.5)
   181	                return s.connect_ex(('127.0.0.1', port)) == 0
   182
   183	        hz_up = check_port(PORTS["hazelcast"])
   184	        prefect_up = check_port(PORTS["prefect_api"])
   185
   186	        if not hz_up and not prefect_up:
   187	            return 0.2
   188	        if not hz_up or not prefect_up:
   189	            return 0.6
   190	        return 1.0
   191
   192	    def m5_health_coherence(self):
   193	        """Check if internal DOLPHIN_SAFETY is updating correctly."""
   194	        hz = self._lazy_get_hz()
   195	        if not hz:
   196	            return 0.0
   197
   198	        try:
   199	            safety_map = hz.get_map("DOLPHIN_SAFETY").blocking()
   200	            latest = safety_map.get("latest")
   201	            if not latest:
   202	                return 0.0
   203
   204	            if isinstance(latest, str):
   205	                data = json.loads(latest)
   206	            else:
   207	                data = latest
   208
   209	            rm = data.get("Rm", -1)
   210	            posture = data.get("posture", "UNKNOWN")
   211	            ts = data.get("ts", 0)
   212
   213	            # Coherence checks
   214	            age = time.time() - ts
   215	            valid_postures = ["APEX", "STALKER", "TURTLE", "HIBERNATE"]
   216
   217	            if age > 60: return 0.0 # Safety system is dead
   218	            if not (0.0 <= rm <= 1.0): return 0.0 # Garbage Rm
   219	            if posture not in valid_postures: return 0.0 # Corrupt posture
   220
   221	            return 1.0
   222	        except Exception:
   223	            return 0.0
   224
   225	    # --- ENGINE ---
   226
   227	    def compute_rm_meta(self):
   228	        m1 = self.m1_process_integrity()
   229	        m2 = self.m2_heartbeat_freshness()
   230	        m3 = self.m3_data_freshness()
   231	        m4 = self.m4_control_plane()
   232	        m5 = self.m5_health_coherence()
   233
   234	        rm_meta = m1 * m2 * m3 * m4 * m5
   235
   236	        # State mapping
   237	        if rm_meta > 0.8: status = "GREEN"
   238	        elif rm_meta > 0.5: status = "DEGRADED"
   239	        elif rm_meta > 0.2: status = "CRITICAL"
   240	        else: status = "DEAD"
   241
   242	        self.last_rm_meta = rm_meta
   243	        self.status = status
   244
   245	        return {
   246	            "rm_meta": round(rm_meta, 3),
   247	            "status": status,
   248	            "sensors": {
   249	                "m1_proc": m1,
   250	                "m2_hb": m2,
   251	                "m3_data": m3,
   252	                "m4_cp": m4,
   253	                "m5_coh": m5
   254	            },
   255	            "timestamp": time.time(),
   256	            "iso": datetime.now().isoformat()
   257	        }
   258
   259	    def emit_outputs(self, report):
   260	        # Local JSON state
   261	        try:
   262	            with open(STATUS_JSON, 'w') as f:
   263	                json.dump(report, f, indent=2)
   264	        except Exception as e:
   265	            logger.error(f"Failed to write state JSON: {e}")
   266
   267	        # HZ Push (best effort)
   268	        hz = self._lazy_get_hz()
   269	        if hz and report['sensors']['m4_cp'] > 0.5:
   270	            try:
   271	                meta_map = hz.get_map("DOLPHIN_META_HEALTH").blocking()
   272	                meta_map.put("latest", json.dumps(report))
   273	            except Exception:
   274	                pass # Silent fail if HZ is struggling
   275
   276	        logger.info(f"RM_META: {report['rm_meta']} | STATUS: {report['status']} | HB: {report['sensors']['m2_hb']}")
   277
   278	    def attempt_restart(self, report):
   279	        """Platform-independent service restart logic."""
   280	        if report['rm_meta'] > 0.2:
   281	            return # Don't auto-restart unless DEAD or deeply CRITICAL
   282
   283	        logger.critical("DEAD STATE detected. Attempting component restarts.")
   284
   285	        services_to_check = {
   286	            "hazelcast": "hazelcast",
   287	            "prefect": "prefect-worker" # Assumed service name
   288	        }
   289
   290	        # This is where one would add specific service names mapped to m-sensors
   291	        # For this PoC, we try to restart the docker compose or main services
   292
   293	        def restart_svc(name):
   294	            if self.platform == "linux":
   295	                cmd = ["systemctl", "restart", name]
   296	            elif "bsd" in self.platform:
   297	                cmd = ["service", name, "restart"]
   298	            else:
   299	                logger.error(f"Unsupported platform for restart: {self.platform}")
   300	                return
   301
   302	            try:
   303	                subprocess.run(cmd, check=True)
   304	                logger.info(f"Executed restart for {name}")
   305	            except Exception as e:
   306	                logger.error(f"Failed to restart {name}: {e}")
   307
   308	        # If M4 (Control Plane) is failed, try restarting primary infrastructure
   309	        if report['sensors']['m4_cp'] <= 0.2:
   310	            restart_svc("hazelcast")
   311	            restart_svc("prefect_server") # If running as systemd
   312
   313	    def run(self):
   314	        while True:
   315	            try:
   316	                report = self.compute_rm_meta()
   317	                self.emit_outputs(report)
   318	                self.attempt_restart(report)
   319
   320	                # systemd Watchdog Notify (Linux only)
   321	                if self.platform == "linux" and 'NOTIFY_SOCKET' in os.environ:
   322	                    # In a real impl, we'd use sd_notify. Here we can use subprocess
   323	                    # or a library. For now, we skip but note its place.
   324	                    pass
   325
   326	            except Exception as e:
   327	                logger.error(f"Error in MHD loop: {e}")
   328
   329	            time.sleep(CHECK_INTERVAL)
   330
   331	if __name__ == "__main__":
   332	    daemon = MetaHealthDaemon()
   333	    try:
   334	        daemon.run()
   335	    except KeyboardInterrupt:
   336	        logger.info("MHD stopped by user.")
   337	        sys.exit(0)