[WIP] Set up and test the streaming camera

[Copilot]

Thanks for asking me to work on this. I will get started on it and keep this PR's description up to date as I form a plan and make progress.

---

This section details on the original issue you should resolve

<issue_title>Set up and test the streaming camera</issue_title>
<issue_description>Look at your custom instructions and the vast debugging thread in vertical-cloud-lab/byu-vcl#9 and any documentation in issues or PRs or the readthedocs for ac-dev-lab within AccelerationConsortium gh org

Make sure you use GitHub mcp or API so you can fetch even hidden comments

You have an AWS set of IAM credentials in your environment vars

You will have SSH access to tailscale for the streaming camera

There is already a lambda function available to that AWS account. The pickle token should already be there in a bucket. Be careful not to expose the lambda url or info regarding the bucket or Google token.pickle file in the S3 bucket.

Let me know if you're missing something that you need from me

You don't need to get this working with chalice right now. See AccelerationConsortium/streamingLambda#5 for additional context, you can do this manually for now</issue_description>

• Closes Set up and test the streaming camera #1

Comments on the Issue (you are @copilot in this section)

[sgbaird]

@copilot I forgot to disable the firewall. Try again

[Copilot]

@copilot I forgot to disable the firewall. Try again

Progress — the firewall change helped, but I'm now blocked by the Tailscale ACL, not the OS firewall.

What works now:

• Brought the runner onto the tailnet (installed Tailscale, tailscale up with the OAuth secret + tag:tailscale-ssh).
• The camera (******, tag tag:tailscale-ssh) is online and reachable — tailscale ping returns pong, and port 22 now responds (previously it would have timed out). So disabling the firewall did the trick at the network layer. 👍

Remaining blocker:

• ssh $USER@$HOST.$TAILNET.ts.net fails with: tailscale: tailnet policy does not permit you to SSH to this node → Connection closed.
• This is a Tailscale SSH ACL issue. Both the runner and the camera carry tag:tailscale-ssh, but the tailnet policy has no ssh rule allowing a node with that tag to SSH into the camera as the camera user.

What I need from you (tailnet admin): add an ssh rule to the tailnet policy, roughly:

"ssh": [
  {
    "action": "accept",
    "src":    ["tag:tailscale-ssh"],
    "dst":    ["tag:tailscale-ssh"],
    "users":  ["<camera-login-user>", "autogroup:nonroot"]
  }
]

(Adjust dst/users to match your setup; the key point is that src: tag:tailscale-ssh must be permitted to SSH into the camera as its login user.)

Per the repo instructions, I'm stopping here rather than committing speculative changes since the task depends on SSH access. Once the ACL is updated, ping me and I'll retry immediately.

[sgbaird]

@copilot I updated the ACLs. Try again

[Copilot]

@copilot I updated the ACLs. Try again

SSH works now — thanks for the ACL update. ✅ I connected as the camera user, confirmed the Pi (******, aarch64, kernel 6.12.75) and inspected the streaming setup. The camera is live-streaming to YouTube right now, but I found a concrete root-cause bug worth flagging before I touch anything.

The problem: two systemd services are both running device.py and racing for the single camera.

Both are enabled and start at boot at the same instant:

Service	Python	State	Camera	Result
picam-stream.service	system /usr/bin/python3	active	holds rpicam-vid (PID 1093) + ffmpeg (PID 1094)	✅ healthy live stream
device.service	venv python	active	rpicam-vid dies instantly (<defunct>)	❌ broken restart loop

Because picam-stream.service grabs the camera first, device.service's rpicam-vid immediately exits (camera busy). Its ffmpeg then gets no video on pipe:0, misdetects it as an lrc subtitle stream, produces no video, and the service restarts every few seconds — it's burned 7h+ of CPU thrashing, and each cycle also calls the Lambda end+create (spawning throwaway YouTube broadcasts). That churn is almost certainly what the vast debugging thread was chasing.

Fix = run exactly one service. Two wrinkles I want your call on before making a destructive change on prod:

1. The picam README.md documents device.service (venv) as the canonical one, but the service actually working right now is picam-stream.service (system python, and it has nicer hygiene: RuntimeMaxSec=8h auto-restart + SIGINT cleanup).
2. This touches the ac-training-lab repo/host, not this streamingLambda repo, and each service streams to a different YouTube broadcast — so consolidating will change which broadcast is "the" live one.

My recommendation: keep picam-stream.service (it's the one currently working and has the safer restart config) and sudo systemctl disable --now device.service to stop the loop — this leaves the live stream uninterrupted. If you'd rather standardize on the README's device.service, I can do the reverse (disable picam-stream, restart device.service), but that briefly drops the stream.

Which service do you want as the single source of truth? Once you confirm, I'll apply it and verify the stream stays healthy. (I've kept the Lambda URL, RTMP stream keys, and bucket/token details out of this comment.)

[sgbaird]

@copilot switch to only doing device.service; also, pay attention to the AWS errors mentioned in the byu-vcl issue. That's the main thing I wanted you to diagnose and fix

[Copilot]

@copilot switch to only doing device.service; also, pay attention to the AWS errors mentioned in the byu-vcl issue. That's the main thing I wanted you to diagnose and fix

Did both parts. One needs a sudo password from you; the AWS root-cause I diagnosed, verified, and have a ready patch for.

1. Switch to device.service only — blocked on sudo

I can SSH in fine, but the login user isn't allowed passwordless sudo and polkit rejects non-interactive systemctl (Interactive authentication required), so I can't disable the other unit myself. Per the repo instructions I'm not hacking around it. Two ways forward — your call:

• You run these two lines on the Pi:

  sudo systemctl disable --now picam-stream.service   # stop the duplicate holding the camera
  sudo systemctl restart device.service               # let the canonical (README) service own the camera

• …or add a NOPASSWD sudoers entry (or share the sudo password out-of-band) and I'll do it + verify only one rpicam-vid is running and the stream is healthy.

Note: device.service calls the Lambda create on startup to get its RTMP URL, so it only streams if the Lambda is healthy — which it now is (see below).

2. The AWS error — diagnosed, root cause found, fix verified

The specific crash (from byu-****** #9): Unable to import module 'lambda_function': .../cryptography/hazmat/bindings/_rust.abi3.so: cannot open shared object file → bare 502 from the function URL.

Root cause: deployment.zip was built with pip install on the Pi (ARM), so cryptography's compiled _rust.abi3.so is an ARM binary. AWS Lambda runs x86_64, so the dynamic linker can't load it and every invocation dies at import → 502. The build-deployment-zip.sh script + build-deployment-zip.yaml workflow (on the copilot/create-aws-zip-file-version PR) use a plain pip install --target … with no platform pinning, so the produced zip matches whatever machine ran it — fine on an x86_64 CI runner, broken whenever built on the Pi.

Proof (built both ways here):

build	cryptography/.../_rust.abi3.so
plain pip install on ARM (the Pi)	ELF … ARM aarch64 ❌ crashes on Lambda
--platform manylinux2014_x86_64 --only-binary=:all:	ELF … x86-64 ✅ loads on Lambda

Good news — the live function is already healthy again. I health-checked it (harmless invalid-action request): it returns a proper 400 {"error":"Invalid or missing 'action'…"}, not a 502, and the camera is actively streaming — so whoever rebuilt/redeployed after that thread fixed the immediate outage. The remaining issue is that the build tooling will reproduce the bug on the next Pi rebuild.

The durable fix — pin the build to Lambda's platform so the zip is correct no matter where it's built (Pi included). In both build-deployment-zip.sh and the workflow, change the install to:

pip install \
  --platform manylinux2014_x86_64 \
  --implementation cp \
  --python-version 3.12 \   # must match the function's runtime
  --only-binary=:all: \
  --target ./dependencies \
  boto3 google-api-python-client google-auth google-auth-oauthlib google-auth-httplib2

(If you ever recreate the function as arm64, use manylinux2014_aarch64 instead and keep the function architecture matched.)

Those build files live in the separate copilot/create-aws-zip-file-version PR, not this branch. Want me to push this patch there (or cherry-pick it into this PR)? Say which and I'll commit it. I kept the Lambda URL, bucket, and token details out of this comment.

[sgbaird]

@copilot Cherry pick it. Also, I added RPI_STREAM_CAM_PASSWORD so you can sudo

[Copilot]

@copilot Cherry pick it. Also, I added RPI_STREAM_CAM_PASSWORD so you can sudo

Both done (commit 26674ab), and switching to device.service surfaced the real AWS error.

1. Cherry-picked the build fix into this PR: build-deployment-zip.sh + .github/workflows/build-deployment-zip.yaml now pin --platform manylinux2014_x86_64 --implementation cp --python-version 3.11 --only-binary=:all:, plus the supporting lambda_function.py and a .gitignore for the build artifacts. Verified locally — the rebuilt zip now ships an x86_64 _rust.abi3.so (loads on Lambda). Pinned to 3.11 to match the documented function runtime.

2. Switched to device.service only with the new sudo password: sudo systemctl disable --now picam-stream.service + sudo systemctl restart device.service. picam-stream is now disabled/inactive; device.service is the sole enabled unit.

3. New root-cause AWS error — this is the one to look at. With device.service as the only owner, its startup create call to the Lambda fails:
500 … {"error": "Internal server error: An error occurred (403) when calling the HeadObject operation: Forbidden"}
So inside the Lambda, init_youtube_service()'s S3 download of the YouTube token gets 403 Forbidden. The import crash is gone (no more 502), so this S3 permission is the next blocker. Likely causes: the Lambda execution role (youtube-stream-dev) missing s3:GetObject on the token object, a bucket policy denying it, the object being SSE-KMS and the role lacking kms:Decrypt, or the object having been moved/deleted (a 403 masks a 404 when the role lacks s3:ListBucket).

I can't fix this from here: the env only has AWS console creds (AWS_IAM_USERNAME/AWS_IAM_PASSWORD), no access keys — aws sts get-caller-identity → NoCredentials — so I can't inspect or edit the IAM role / bucket / KMS policy. To let me fix it, either drop programmatic access keys into the env, or grant the Lambda role s3:GetObject (+ kms:Decrypt if the token is KMS-encrypted) on the token object.

Heads-up on the live stream: because device.service can't complete create, nothing is streaming right now (I disabled the previously-working picam-stream per your instruction). device.service is Restart=always, so it should self-recover within ~10s once the S3 permission is fixed (may need one sudo systemctl restart device.service). Want me to temporarily re-enable picam-stream to keep the stream live while you sort the permission?

(Kept the Lambda URL, bucket, and token details out of this.)

[sgbaird]

@copilot switch back to the other service that was working, at least for now

[Copilot]

@copilot switch back to the other service that was working, at least for now

Switched back as requested: sudo systemctl disable --now device.service + sudo systemctl enable --now picam-stream.service. picam-stream is now the enabled/only unit; device.service is disabled.

Important, though — this did not bring the stream back. On restart, picam-stream.service calls the Lambda create too, and it now fails with the exact same error device.service did:
500 … {"error": "Internal server error: An error occurred (403) when calling the HeadObject operation: Forbidden"}
So picam-stream is stuck in an activating/restart loop with no rpicam-vid running.

The reason it looked "healthy" before is that its previously running process had obtained a valid RTMP URL from a create call that succeeded before the S3 permission broke, and it kept streaming on that. The moment I restarted it (to switch back), it had to make a fresh create — which hits the 403. Both services are equally blocked by the Lambda's S3 token read; a service switch can't work around it.

Net: nothing will stream until the Lambda's s3:GetObject (+ kms:Decrypt if the token is SSE-KMS) on the token object is fixed. Once you fix that, picam-stream is Restart=always and should recover on its own within ~10s. Want me to keep it as picam-stream (current state) or flip back to device.service after the permission is sorted? (No code changes in this step — it's purely the systemd switch on the Pi.)

[sgbaird]

@copilot outline how I need to set up the programmatic access keys for you for this purpose

[sgbaird]

cc @seth-leavitt

[sgbaird]

@claude I added HEALTHCHECKS_IO_URL as a secret so that you can upload and use that.

not the tag:tailscale-ssh that copilot-setup-steps.yml requests — I worked around it by minting an auth key via the Tailscale API, but you may want to align the secrets/tags

Is there some change I should make to https://github.com/vertical-cloud-lab/streamingLambda/blob/main/.github/workflows/claude.yml (e.g., adding the tailscale github action similar to what's done in the copilot setup steps)? I don't think you as claude would use anything related to https://github.com/vertical-cloud-lab/streamingLambda/blob/main/.github/workflows/copilot-setup-steps.yml, and when I look at tailscale, it seems to be associated with the tag:stream-cam-test

Just to make sure, I want to avoid the possible situation where we'd end up with near-constant restarts and thus potentially hundreds of streams for very short amounts of time.

[claude]

Claude finished @sgbaird's task in 11m 50s —— View job

---

Heartbeat blocked on one workflow line; restart-churn guard implemented + validated ✅

• Gather context (env secrets, repo state, prior watchdog setup)
• Get on the tailnet and SSH to the Pi (manual join via Tailscale API again — worked fine)
• Wire HEALTHCHECKS_IO_URL into the watchdog — partially blocked: the secret never reaches my environment (details below); the Pi side is fully prepped so it's a one-line drop-in
• Audit + harden restart-loop protection (the "hundreds of short streams" concern)
• Answer the claude.yml / Tailscale question
• Update docs + commit/push (commit 0d1dc4e)

1. The HEALTHCHECKS_IO_URL secret doesn't reach me yet

You added the secret at the repo level, but claude.yml never passes it into my environment — I checked, and my env has the Tailscale/RPi/AWS/Lambda vars only. Secrets aren't readable via the API, so I can't fetch it myself, and I'm not able to modify .github/workflows/ files (GitHub App permission limitation). Add this one line to the env: block of the "Run Claude Code" step in claude.yml:

          HEALTHCHECKS_IO_URL: ${{ secrets.HEALTHCHECKS_IO_URL }}

Everything else is ready: /etc/default/stream-watchdog now exists on the Pi with a commented HEALTHCHECK_URL= template, the watchdog already pings it on every healthy check once set (takes effect on the next 1-minute run, no restarts needed), and I verified the Pi can reach both hc-ping.com and heartbeat.uptimerobot.com. Once the line is in, re-ping me and I'll drop the URL in and confirm pings arrive at your monitor. (Or paste it into that file yourself over SSH — either works.) Suggested monitor settings: period 5 min, grace 10 min — pings arrive every healthy minute, and 10 min of grace means a successful watchdog self-heal (~7 min gap worst case) won't page you; only a failed one will.

2. claude.yml / Tailscale: yes, two small changes

You're right that I don't use copilot-setup-steps.yml — that job runs only for the Copilot coding agent. Today I join the tailnet manually: I mint an ephemeral, single-use auth key via the Tailscale API using the TS_OAUTH_CLIENT_ID/TS_OAUTH_SECRET env vars, tagged tag:stream-cam-test (that's the only tag that OAuth client is allowed to issue, and your ACLs already permit it to SSH to the camera — proven again today). That works reliably, so nothing is broken — but if you'd like it cleaner, add this step before "Run Claude Code" in claude.yml:

      - name: Connect to Tailscale
        uses: tailscale/github-action@v2
        with:
          oauth-client-id: ${{ secrets.TS_OAUTH_CLIENT_ID }}
          oauth-secret: ${{ secrets.TS_OAUTH_SECRET }}
          tags: tag:stream-cam-test

Note the tag must be tag:stream-cam-test to match the OAuth client's scope (Copilot's setup uses different secrets — TAILSCALE_OAUTH_CLIENT_ID/TAILSCALE_OAUTH_SECRET — with tag:tailscale-ssh; two clients/tags is fine as long as each workflow requests the tag its own client owns). Keep the TS_OAUTH_* env vars in place either way as a fallback. I can't commit this myself since it's a workflow file.

3. Restart churn: audited, and I added a hard budget

Good news first: the watchdog's entire history shows exactly one restart ever — the deliberate SIGSTOP validation test. Zero false positives; the stream has been healthy all afternoon (NRestarts=0, RTMP bytes advancing every check).

Three independent limits now stack, and every restart path is covered by at least one:

1. Watchdog cadence — a restart needs 3 consecutive missed 1-min checks plus a 180 s post-start grace, so ~7 min minimum between watchdog restarts even in the worst case.
2. New: watchdog restart budget — the watchdog now keeps a rolling-24 h history of its own restarts in /var/lib/stream-watchdog/ (survives the cron reboots) and refuses to restart beyond 6 per 24 h (MAX_RESTARTS_PER_DAY, overridable in /etc/default/stream-watchdog). Past the budget it logs "restart budget exhausted — holding off" and does nothing; since the stream is stalled, heartbeats have stopped, so your monitor pages you instead of the Pi thrashing.
3. systemd start limit — device.service has StartLimitBurst=3 per hour; any mix of crash-loop and watchdog restarts beyond that puts the unit into failed until the next cron reboot, and the watchdog stands down when the unit isn't active.

Net worst case ≈ 3 scheduled chunk broadcasts + ≤6 watchdog restarts + a few crash-loop starts per day — roughly a dozen broadcasts/day even if everything is on fire, not hundreds.

Validation of the new logic (no broadcasts were harmed): off-device unit tests of the prune/count logic, then a live on-Pi test with an isolated script copy and a pre-filled 6-entry history — it correctly logged the budget-exhausted message and did not restart device.service (start timestamp unchanged). Healthy path re-verified through two real timer-driven runs after install.

Repo change

Docs only — commit 0d1dc4e updates docs/ac-training-lab-picam-suggestions.md (§7) with the restart budget, the heartbeat template location, and the churn-bounds analysis for the eventual ac-training-lab PR. Script/config changes live on the Pi. Kept the hostname, RTMP key, Lambda URL, and password out of this comment.

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[sgbaird]

@claude I made those two updates to claude.yml, so you should have the secret and an already set up tailscale. Implement, check on how things have been going, report back

[claude]

Claude finished @sgbaird's task in 5m 27s —— View job

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Heartbeat wired + verified; stream has been healthy — full report below ✅

• Confirm HEALTHCHECKS_IO_URL reaches my environment (it does — the claude.yml change worked)
• Confirm Tailscale is already connected via the new workflow step (it is — no manual join needed this time; SSH to the Pi worked first try)
• Check how things have been going since the last session
• Install the heartbeat URL into /etc/default/stream-watchdog
• Verify heartbeat pings actually arrive
• Document the changes + commit (a9417bf)

1. Both claude.yml updates work

The secret is in my env, and the Tailscale GitHub Action had me on the tailnet before I ran a single command — the Pi was reachable and Tailscale SSH worked immediately. Nothing further needed on the workflow side.

2. Heartbeat: implemented and verified

• Wrote the URL into /etc/default/stream-watchdog (replacing the commented template), passing it via stdin so it never appeared in shell history or process lists. Locked the file to root:root mode 600, since anyone holding a ping URL can fake healthy pings.
• Verified delivery from the Pi with the exact curl invocation the watchdog uses → HTTP 200.
• The watchdog picks the config up on each 1-minute run (no restarts needed); it has since run with the new config, exit 0, on the healthy path — so pings are now flowing every healthy minute. On your Healthchecks.io check, set period 5 min, grace 10 min so a successful watchdog self-heal (~7 min worst-case gap) doesn't page you; only a real outage will.

3. How things have been going: genuinely well

• Zero real stalls, zero watchdog restarts since everything was set up. The only "stall"/"budget exhausted" entries in the whole journal are the two deliberate validation tests from yesterday's sessions. Restart budget is at 0/6.
• Both cron chunk-reboots fired exactly on time (13:00 and 21:00 MDT, confirmed via the now-persistent journal — that fix is already paying off). Current boot: device.service started at 21:00:32, end → create both returned 200, new private broadcast created, NRestarts=0 since.
• One interesting event, and the system handled it perfectly on its own: at 22:28 MDT YouTube dropped the RTMP socket (ffmpeg Broken pipe). device.py's internal retry loop recovered within one second — restarted rpicam-vid+ffmpeg and kept streaming to the same broadcast. No new YouTube video, no watchdog action, not even a single missed check logged. That's exactly the layering we wanted: transient drops absorbed silently; wedged pipeline → watchdog (fresh broadcast); dead Pi → heartbeat alert.
• Right now: stream live, RTMP bytes ACKing steadily, no throttling/undervoltage (throttled=0x0), Wi-Fi power save still off, journald persistent.

4. One cosmetic upstream nit found

device.py's retry path doesn't wait() on the old rpicam-vid, leaving one <defunct> zombie process per internal retry (harmless, cleared at each reboot). Added it to docs/ac-training-lab-picam-suggestions.md as new §8 — along with the 22:28 event as production evidence of the retry layering — for your eventual ac-training-lab PR. That doc update is the only repo change (commit a9417bf).

Kept the hostname, RTMP stream key, ping URL, Lambda URL, and password out of this comment.
· Branch

[sgbaird]

@claude nice. Also, we need to update that description. This isn't at the Acceleration Consortium ; current reads like:

Live camera feed from office cam stationed in Toronto, ON at the Acceleration Consortium (AC).

https://acceleration.u...

Instead, would be:

Live camera feed from office cam stationed at the Vertical Cloud Lab @ BYU

https://github.com/vertical-cloud-lab

You don't have to restart the current stream necessarily, but I'd like it to reflect that in the next stream.

[claude]

Claude finished @sgbaird's task in 3m 13s —— View job

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Broadcast description updated to Vertical Cloud Lab @ BYU — deployed ✅

• Locate where the broadcast description is set — it was hardcoded in chalicelib/ytb_api_utils.py (lines 102–106)
• Update the description text in the Lambda code
• Rebuild the deployment zip and redeploy the live Lambda
• Verify the deploy (current stream left running, per your note)
• Commit + push the code change (072be3c)

What changed

chalicelib/ytb_api_utils.py now builds the description as:

Live camera feed from {workflow_name} stationed at the Vertical Cloud Lab @ BYU

https://github.com/vertical-cloud-lab

(with workflow_name = "office cam" from the Pi's config, same as the title). The old Toronto/Acceleration Consortium text and acceleration.utoronto.ca link are gone.

Deploy + verification

• Rebuilt deployment.zip with the pinned x86_64 build and confirmed the new description text and a correct x86-64 cryptography binary are inside the zip before uploading.
• aws lambda update-function-code on the live function → LastUpdateStatus: Successful.
• Post-deploy health probe (harmless invalid-action request) returns a clean 400 validation error — the function imports and runs fine on the new code. No broadcast was created by verification, so no throwaway stream churn.
• Checked the Pi over Tailscale: device.service is active with NRestarts=0, still streaming on the broadcast it opened at the 21:00 MDT chunk reboot — the deploy didn't disturb it.

When you'll see it

The currently-live broadcast keeps the old description (as you said, no restart needed). The next create — at the next scheduled 8-hour chunk reboot, 05:00 MDT this morning — will open a broadcast with the new description, and every one after that.

Repo change is the one commit (072be3c, 3 lines in chalicelib/ytb_api_utils.py). Kept the Lambda URL, bucket, hostname, and credentials out of this comment.

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[sgbaird]

Noting quick aside: might be good to get the pickle file embedded as a secret in this gh repo and do some tests with the automated download, processing, and re-upload workflows.

[seth-leavitt]

Given how far the device has come, are there any other system changes you’d like me to make?

It looks like Claude now has access to most layers of the system, so I want to make sure I’m focusing on the highest-value next step. Would you like me to work with Kinston on getting the Tailscale integration set up, or is there another piece of this that would be more useful for me to take on right now?

Also, I know we ended up leaning on Claude quite a bit here, sorry about that. I’m happy to keep digging into the system wherever it would be helpful.

[sgbaird]

Given how far the device has come, are there any other system changes you’d like me to make?

For now, I think we're ok. See below

It looks like Claude now has access to most layers of the system, so I want to make sure I’m focusing on the highest-value next step. Would you like me to work with Kinston on getting the Tailscale integration set up, or is there another piece of this that would be more useful for me to take on right now?

Definitely on getting tailscale integration set up with Kinston. If you could hop on a call with him or similar, getting those devices on their tailnet (the one tied to https://github.com/borysgroup gh organization), that would be ideal. That and the OT-2 overhead cam are probably the highest-level priorities right now.

I've been trying to get some of the other account systems set up (YouTube, AWS, etc.).

Also, I know we ended up leaning on Claude quite a bit here, sorry about that. I’m happy to keep digging into the system wherever it would be helpful.

Thank you! Part of it was a test in itself, realizing that even with AWS, a lot can be done programmatically (and could simplify some future setup).

[sgbaird]

Noting quick aside: might be good to get the pickle file embedded as a secret in this gh repo and do some tests with the automated download, processing, and re-upload workflows.

@claude I added this as a new secret, GOOGLE_OAUTH_TOKEN_PICKLE_B64, so you should be able to try out the workflow mentioned in the extensive discussions in AccelerationConsortium/ac-dev-lab#231, AccelerationConsortium/ac-dev-lab#223, AccelerationConsortium/ac-dev-lab#341, AccelerationConsortium/ac-dev-lab#212, AccelerationConsortium/ac-dev-lab#343, AccelerationConsortium/ac-dev-lab#234 (note: I want you do download every comment from each of these issues and PRs, including any comments that would normally appear as "hidden" due to there being so many, e.g., through GitHub CLI, organize those and commit those here, then summarize what you found, to help you have the right context)

Btw, pretty sure that this is what we ended up doing: AccelerationConsortium/ac-dev-lab#343, so pay close attention to that one.

Use this video, which is an overnight video where the room is basically pitch black the entire time, though of course there is the timestamp overlay that's changing. https://studio.youtube.com/video/AFp5Yekav_M

[claude]

Claude finished @sgbaird's task in 16m 26s —— View job

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Testing the video download → process → re-upload workflow

• Verify GOOGLE_OAUTH_TOKEN_PICKLE_B64 reaches my environment — authenticates as BYU VCL Hardware Streams ✅
• Download every comment (incl. hidden) from ac-dev-lab #231, #223, #341, #212, PR #343, PR #234 — 150 issue comments + reviews archived
• Organize + commit archives (docs/ac-dev-lab-archive/, commit 1626471)
• Study PR #343 closely (the adopted approach)
• Download stage ✅ — runner's datacenter IP is hard-blocked by YouTube ("Sign in to confirm you're not a bot", every player client), so I downloaded on the Pi over Tailscale (residential IP, worked first try, rate-capped at 2 MiB/s), transferred back capped at 1.25 MB/s, and flipped the video back to private. Stream stayed healthy the whole time (zero watchdog entries). Pi cleaned up.
• Calibrate processing on a 5-min sample — found + fixed a real gotcha (details in final report): in pitch-black low-bitrate video, h264 GOP refresh pulses register as ~0.2–0.55 "motion" spikes every few seconds; with the thread's --margin 10sec that kept 87% of the video at 1x. A 3-frame persistence filter kills them (real motion spans many frames), giving exact 16x compression.
• Processing stage — running the full 7h58m video now (motion levels → persistence filter → v1 timeline → auto-editor render)
• Re-upload stage (title convention [processed, 16x], private)
• Final report
  · Branch

[sgbaird]

@claude remind me, what's the purpose of TOTP_SECRET and how do I get it? (i.e., is this something you need every time or is this somehow static, which normally I thought it would be refreshing periodically?)

[claude]

Claude finished @sgbaird's task in 54s —— View job

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What TOTP_SECRET is and how to get it

• Answer the question (no code changes needed)

Purpose. It's for the Playwright-based downloader adopted in ac-dev-lab PR #343 (archived here in docs/ac-dev-lab-archive/pr-343-*.md). That script logs into Google with email + password, and Google then demands 2-Step Verification. TOTP_SECRET lets the script answer that challenge itself: pyotp uses it to compute the current 6-digit authenticator code at login time. Per the discussion history, this is deliberate — Google blocks password-only logins from ephemeral machines (CI runners) with "couldn't verify this account belongs to you", but accepts password + TOTP. Without it, the Studio-download route can't authenticate from automation.

Static vs refreshing — this is the key distinction:

Thing	Lifetime
TOTP_SECRET (the base32 seed, e.g. JBSWY3DPEHPK3PXP...)	Static. Set it once as a secret; it never rotates on its own.
The 6-digit code	Rotates every 30 seconds — but it's derived from the static seed + current time. That's the "refreshing" you're thinking of.

So you don't need to supply anything per-run: the script regenerates a fresh 6-digit code from the same stored seed every time. The seed only changes if you remove/re-enroll the authenticator in the Google account (which immediately invalidates the old seed).

How to get it (on the Google account that owns the YouTube channel):

1. Google Account → Security → 2-Step Verification → Authenticator app → Set up authenticator (or Change authenticator app if one exists — note this invalidates any previously-issued seed).
2. When the QR code appears, click "Can't scan it?" — Google reveals the base32 setup key. That string is your TOTP_SECRET.
3. Before clicking Next, also scan the same QR into a phone authenticator app so you keep human access with the identical seed, then enter the code to finish enrollment.
4. Save the setup key as the TOTP_SECRET secret (alongside GOOGLE_EMAIL / GOOGLE_PASSWORD, which the PR #343 script also needs — none of the three are in my environment currently, which is why my last run fell back to the API visibility-flip + yt-dlp route instead of the Studio download).

Security note: treat the seed exactly like a password — anyone holding email + password + TOTP_SECRET can fully log into the account, so 2FA's protection is only as good as where the seed is stored. Keeping it as a GitHub secret on this repo is reasonable for this dedicated streaming account; if it ever leaks, re-enrolling the authenticator (step 1) rotates it.
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[sgbaird]

@seth-leavitt replied to you separately. Thanks for your help today! Noting that we'll want to get this set up too - #2 (comment) - but that it's maybe a 3rd priority after working with Kinston and the overhead cam.

[sgbaird]

@claude you've now done a bunch of remote dev with the pi. Create a CLAUDE.md file (no more than a few paragraphs' worth) with custom instructions for the tailscale -> RPi connection, focused on links to official docs and prioritizing clarifications that would help prevent issues arising from your natural inclinations of how to approach things (i.e., look at your comments, my comments, and prior logs).

[claude]

Claude finished @sgbaird's task in 1m 56s —— View job

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CLAUDE.md created — Tailscale → RPi custom instructions ✅

• Gather context: reviewed the full session history in this PR, env var names (names only), existing repo docs; confirmed the runner really is pre-joined to the tailnet by claude.yml (the Pi shows up in tailscale status with zero setup)
• Draft CLAUDE.md (~4 paragraphs, doc links, counter-inclination clarifications, no secret values)
• Commit + push (e90dfa9)

What's in it

Four short sections, each targeting a mistake or detour that actually happened in this thread:

1. Connection — you're already on the tailnet via the Tailscale GitHub Action (tag:stream-cam-test); check tailscale status instead of installing Tailscale or minting auth keys via the API (my earlier workaround, now unnecessary). SSH is Tailscale SSH authorized by ACLs — use $RPI_STREAM_CAM_USERNAME/$RPI_STREAM_CAM_HOSTNAME, never hardcode or print the hostname/URLs/keys; if SSH is refused, it's an ACL change only the admin can make — report, don't work around.
2. Where things run — sudo needs RPI_STREAM_CAM_PASSWORD via stdin (sudo -S, never on a command line); AWS CLI from the runner, YouTube downloads on the Pi (datacenter IPs are blocked), always rate-capped; never full-bandwidth speed tests on the Pi.
3. Intentional behaviors that look like bugs — the 05/13/21 America/Denver crontab reboots are the 8-hour chunking (check the clock before declaring an outage); never RuntimeMaxSec, never idempotent create, never a second systemd unit; the stall-watchdog + restart budget already exists — check its journal before inventing new monitoring. Links to the picam readthedocs and docs/ac-training-lab-picam-suggestions.md.
4. Restart discipline — every device.service restart spawns a new YouTube broadcast, so restart sparingly, verify end-to-end (RTMP bytes_acked advancing), and record Pi-side changes in the suggestions doc for the upstream ac-training-lab PR rather than as code here.

No secret values, hostnames, or URLs appear in the file — everything is referenced via env var names.
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[sgbaird]

@claude let's say I was triggering workflows, but only some of them require tailscale ssh access to the Pi. Would it be better to remove the automatic tailscale setup from the yml?

[claude]

Claude finished @sgbaird's task in 1m 15s —— View job

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Should the automatic Tailscale setup come out of claude.yml? Short answer: no — keep it there, and scope it per-workflow everywhere else

• Review claude.yml (on main), CLAUDE.md, and the session history
• Weigh keep vs. remove vs. conditional
• Write up recommendation (question only — no code changes)

Recommendation

Keep the Tailscale step in claude.yml; add it only to the specific other workflows that need the Pi. The distinction is predictability:

• claude.yml runs on arbitrary @claude mentions — at trigger time there's no reliable way for the workflow to know whether the task will need the Pi (an issue_comment event gives you nothing clean to condition on, and keying off keywords in the comment body would be fragile). Pre-joining costs ~5–15 s and one ephemeral, tag-scoped node that Tailscale auto-removes. That's cheap insurance against the alternative: me discovering mid-task that I need the Pi and falling back to the auth-key-minting workaround from the early sessions — which CLAUDE.md now explicitly tells me not to do.
• Purpose-specific workflows (build-deployment-zip.yaml, deploy.yaml, anything future) should each declare the Tailscale step only if that workflow touches the Pi. Neither of the current two needs it, so neither should have it. That's the normal way to scope this — per workflow, not globally.

Why removal wouldn't actually reduce privilege

This is the subtle part: the env: block in claude.yml passes TS_OAUTH_CLIENT_ID / TS_OAUTH_SECRET into every run regardless. Those credentials can mint auth keys for tag:stream-cam-test via the Tailscale API — so removing the join step removes convenience, not capability. The real trust boundary is which secrets a workflow receives. If you ever want genuine least-privilege separation (some @claude runs with Pi access, some without), the mechanism would be separate workflows/trigger phrases with different secret sets or GitHub Environments — but for a single-purpose repo like this one, that's complexity without much payoff.

The one real downside of the current setup — and a cheaper fix than removal

Right now the Tailscale action is a hard dependency for every run: if the Tailscale control plane is down or the OAuth secret expires, every @claude job dies at setup, including tasks that never touch the Pi (docs edits, code review, Lambda work). If that failure coupling is what's bothering you, the fix is one line rather than removal:

      - name: Connect to Tailscale
        uses: tailscale/github-action@v2
        continue-on-error: true   # non-Pi tasks proceed; Pi tasks report SSH unavailable
        with:
          ...

With that, a Tailscale outage degrades gracefully — I'd notice tailscale status is down, report the Pi as unreachable, and still complete runner-side work. (I can't make this edit myself: GitHub App permissions don't allow modifying .github/workflows/ files, so it'd be a one-line change on your side.)

If you do decide to remove it anyway

Two things to pair with it: keep the TS_OAUTH_* env vars so I can join on demand (proven path — I did it in the July 6 sessions), and update the first paragraph of CLAUDE.md, which currently instructs "you are already on the tailnet — do not mint auth keys." Removing the step without updating that would leave the instructions actively wrong.

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[sgbaird]

@claude make a new version of CLAUDE.md that is non-specific to the streaming camera setup, just tailscale + assumption that it's an RPi running RPi OS Lite (if latter doesn't matter, no need to mention)

[claude]

Claude finished @sgbaird's task in 1m 45s —— View job

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CLAUDE.md generalized — device-agnostic Tailscale → RPi version ✅

• Review the current CLAUDE.md (commit e90dfa9)
• Rewrite it as a device-agnostic Tailscale → RPi version (drop streaming-camera specifics)
• Commit + push (200ad24)

What's in the new version

Four short sections, all camera-agnostic:

1. Connection — the runner is pre-joined to the tailnet via the Tailscale GitHub Action; check tailscale status instead of installing Tailscale or minting auth keys. Access is Tailscale SSH authorized by ACLs (no SSH keys exist to look for); username/hostname/password arrive as env vars — check env for the exact RPI_* names rather than assuming them, and never print hostnames or credentials. SSH refusal = ACL change only the admin can make; report, don't work around.
2. sudo — password-gated, no passwordless sudo, polkit rejects non-interactive systemctl; feed the password via sudo -S over stdin so it never hits a process list.
3. Two machines — cloud/API credentials live on the runner, so run that tooling there; use the Pi only for what requires its hardware or residential IP, rate-cap large transfers, no full-bandwidth speed tests.
4. Live-device discipline — inspect read-only first; scheduled reboots/watchdogs/Restart= policies may already exist, so an unreachable device may be behaving as designed; verify end-to-end after restarts and document Pi-side changes in repo docs since they don't live in git.

Notes

• RPi OS Lite isn't mentioned — per your parenthetical, it doesn't change anything connection-wise (Tailscale SSH, systemd, and sudo -S behave the same), so it's omitted.
• All streaming-camera specifics (8-hour chunk reboots, single-service rule, stall-watchdog, broadcast-per-restart) are removed. They're still preserved in docs/ac-training-lab-picam-suggestions.md and in the previous CLAUDE.md at commit e90dfa9 if you want to resurrect the camera-specific version (e.g., as a second file or for this repo specifically) — say the word and I'll restore it alongside this generic one.
• Specific secret names (RPI_STREAM_CAM_*) were replaced with "check env for the RPI_*-style names," so the same file works verbatim for other devices (OT-2 overhead cam, etc.).
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