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This guide walks you from a fresh Node v1 install to a working photometry observation. It is structured in two stages: a dry run that needs no hardware at all, followed by the steps to connect a real Seestar and enable the full pipeline. If you have not yet installed Node v1, start with the Installation guide first. Every config snippet below uses real keys and default values from config.yaml — nothing is invented.

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Dry-Run (No Hardware Required)

Before touching any hardware, verify that the Flask server starts, the dashboard loads, and all background components initialise cleanly. The minimal config below disables every optional feature so the node starts with only the SafetyManager and dashboard active. Edit config.yaml and confirm these values: 
cloud:
  enabled: false        # must be false — no cloud credentials yet

image_watcher:
  enabled: false        # must be false — don't auto-watch files yet

photometry:
  enabled: false        # must be false — don't auto-run pipeline yet

pier_cam:
  enabled: false        # must be false — optional guide camera

safety:
  enabled: true         # keep this enabled for safe operation

aavso:
  observer_code: ''     # no credentials needed for dry run
  dry_run: true         # if you do test submission, it won't POST to AAVSO
Now start the server: 
python main.py
Open http://localhost:5173. You should see:
  • ✅ Flask server starts (check the console for Running on http://localhost:5173)
  • ✅ Dashboard loads in the browser
  • ✅ Object catalog is browsable (powered by pyongc — no network required)
  • ✅ Configuration panel is editable
  • ✅ Live log panel is streaming with no errors
Even with no Seestar connected, you can click Discover (it will timeout gracefully), browse the NGC/Messier catalog, inspect and edit config.yaml from the browser, and test every API endpoint. This proves the core software is working before any hardware complexity.

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Connect Your Seestar

Once you have confirmed the dry run works, connect your Seestar S50. The telescope must be on the same LAN as the computer running Node v1.
1

Power on and network the Seestar

Ensure the Seestar S50 is powered on and connected to your WiFi network in Station Mode (not Access Point mode). Confirm it is on the same subnet as the node computer.
2

Discover the ALPACA server

In the dashboard, click Discover. Node v1 sends a UDP broadcast on port 32227. Within a few seconds the Seestar’s ALPACA server should appear in the discovered-servers list.
If discovery times out, you can connect manually: enter the Seestar’s IP address and port 32323 directly in the connection fields. The default address in config.yaml is 172.22.6.32:32323 — replace this with your Seestar’s actual IP.
3

Select and connect

Select the discovered server from the list, then click Connect. The dashboard establishes an ALPACA session and polls the telescope, camera, and other configured devices.
4

Unpark the mount

The Seestar S50 ALPACA driver does not implement the Unpark command. You must unpark from within the Seestar iOS/Android app first. After unparking in the app, return to the Node v1 dashboard — the telescope controls (slew, tracking, nudge) will work normally.
Do not attempt to slew before unparking. The SafetyManager gates all motion commands and will reject slews if the mount reports as parked.

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Your First Observation

With the Seestar connected and unparked, enable the photometry pipeline and configure your target. The pipeline runs automatically on every new FITS file delivered by the Seestar.
1

Enable ImageWatcher and set the watch path

Edit config.yaml (or use the dashboard’s config editor modal) to point ImageWatcher at the Seestar’s SMB share:
image_watcher:
  enabled: true
  watch_path: "/mnt/seestar"   # replace with your actual SMB mount point
  debounce_delay: 2.0          # seconds to wait after file write completes
The watch_path is the local filesystem path where the Seestar’s network share is mounted. On macOS this might be /Volumes/Seestar; on Linux /mnt/seestar; on Windows Z:\.
2

Enable the photometry pipeline and set your target

photometry:
  enabled: true
  node_id: "node_001"    # unique identifier for your node — set this before joining the network

  filter_name: "CV"      # AAVSO filter code (CV = broadband, V = Johnson-V)

  target:
    name: "SS Cyg"       # AAVSO VSX name — leave blank to use FITS header values
    ra_deg: 321.7042     # right ascension in decimal degrees (set for your target)
    dec_deg: 43.5861     # declination in decimal degrees

  min_comparison_stars: 3
  snr_threshold: 20
  max_uncertainty: 0.3
  max_airmass: 3.0
In normal operation you can leave target.name, ra_deg, and dec_deg blank — the pipeline reads these from the FITS header written by the Seestar. Fill them in explicitly when you want to override the header or when testing with a manually supplied FITS file.
3

Set your node ID

The photometry.node_id key must be a unique string that identifies your node in the Boundless Skies network. Set it once and do not change it:
photometry:
  node_id: "node_001"
4

Configure AAVSO credentials (or keep dry_run)

For a first test, leave aavso.dry_run: true. The pipeline will format the full AAVSO Extended Format submission and write it to the audit directory, but will not POST to WebObs.When you are ready for live submission:
aavso:
  observer_code: "XXXX"         # your AAVSO OBSCODE — get one at aavso.org
  username: "your_username"
  password: "your_password"
  dry_run: false                 # set to false to submit for real
  submit_poor_quality: false     # only submit good/acceptable quality results
  audit_dir: "aavso_submissions" # audit trail written here regardless of dry_run
5

Take an exposure or wait for a file

You can trigger the pipeline in two ways:From the dashboard: Click Expose in the camera panel. The Seestar captures and saves a FITS file to the watch path. ImageWatcher detects it, runs the pipeline, and results appear in the photometry status panel.Wait for automatic delivery: If the Seestar is already running a scheduled session and writing FITS files to the share, ImageWatcher picks them up automatically — no manual action needed.
6

Watch the live log panel

The log panel streams Server-Sent Events in real time with timestamps and colour-coded log levels. A successful pipeline run looks like:
[INFO]  ImageWatcher: new file detected — seestar_image.fits
[INFO]  Photometry: WCS found in header, skipping plate solve
[INFO]  Photometry: FWHM estimated at 3.8 px (9 stars)
[INFO]  Photometry: 9 comparison stars from AAVSO VSP
[INFO]  Photometry: magnitude 12.341 ± 0.031 (SNR 52.0, quality: good)
[INFO]  AAVSO: dry_run=true — submission saved to aavso_submissions/2025-01-15/

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Reviewing Results

After the pipeline runs, results are visible in two places: Dashboard — Photometry & AAVSO panels: The photometry status panel shows the most recent result: target name, BJD, magnitude, uncertainty, SNR, comparison star count, quality flag, and zero-point scatter. The AAVSO status panel shows whether the last submission was accepted, rejected, dry-run, or skipped. Observation history panel: A thumbnail gallery of completed observations with per-image metadata. Click any thumbnail to see the full measurement record. aavso_submissions/ audit directory: Every pipeline run — including dry runs — writes a full audit trail to aavso_submissions/YYYY-MM-DD/:
  • <target>_<bjd>.txt — the AAVSO Extended Format text that was (or would be) submitted
  • <target>_<bjd>_response.txt — the raw WebObs HTTP response (or a dry-run note)
  • <target>_<bjd>_record.json — a complete JSON record of all measurement fields
Always check *_response.txt if a submission is rejected. The most common causes are an invalid observer code, a target name not in AAVSO VSX, or a date outside the allowed range. Set aavso.dry_run: true to validate the format before going live.

Configuration Reference

Full reference for every key in config.yaml — observatory coordinates, photometry parameters, safety timeouts, and cloud settings.

Photometry Pipeline

Deep-dive into the eight-step pipeline: WCS, FWHM estimation, comparison star retrieval, aperture photometry, differential photometry, and quality flags.

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