morning-signal 0.1.1rc5

Auto-generated daily briefing podcast: Claude + web search → script → Polly TTS → S3 + RSS

Morning Signal

Auto-generated daily briefing podcast. A scheduler fires at 5 AM (and optionally 5 PM) Pacific, Claude with web search writes the script, Amazon Polly converts it to audio, and the MP3 + RSS feed publish to S3. Subscribe in any podcast app — episodes just show up on your phone.

How it works

Scheduler (systemd timer / cron / launchd)
  │
  ├─ 1. Load prompt + config (from local files OR SSM Parameter Store)
  ├─ 2. Call Claude with web search → ~2,000-word script
  ├─ 3. Call Amazon Polly → synthesize speech, ffmpeg speed-adjust
  ├─ 4. Upload MP3 + regenerate RSS feed → S3
  ├─ 5. Email success/failure notification (optional, via SES)
  │
  └─ Episode appears in your podcast app within minutes

Two production deployment styles are supported:

• Local CLI (Mac/Linux dev) — reads config.yaml, prompt.md, and .env from disk. Schedule with cron or launchd.
• Cloud deploy — runs on a long-lived EC2 instance under systemd, reads config + prompt + secrets from AWS SSM Parameter Store, assumes a dedicated IAM role for Polly + S3 + SSM + SES. Survives laptop sleep, supports DST-aware scheduling, and surfaces failures by email.

Project structure

morning-signal/
├── generate_episode.py    Main script — generates and publishes one episode
├── feed.py                RSS feed builder (Apple-compatible)
├── config.yaml.example    Configuration template
├── prompt.md              YOUR PODCAST — segments, sources, tone, length cap
├── run.sh                 Local-dev launcher (sources .env + venv → python)
├── pyproject.toml         Build + dependency manifest (single source of truth)
├── artwork.jpg            Podcast cover art (3000×3000 recommended)
├── tests/                 pytest suite (run via `pytest --cov`)
├── episodes/              Generated MP3s + metadata JSON (gitignored)
├── scripts/               Generated transcripts (gitignored)
└── feed.xml               Generated RSS (gitignored; also lives on S3)

Quick start (local CLI)

1. Install

git clone https://github.com/cipher813/morning-signal.git && cd morning-signal
python3 -m venv .venv && .venv/bin/pip install -e .

2. Configure

cp config.yaml.example config.yaml
$EDITOR config.yaml          # set s3_bucket + base_url + podcast metadata
$EDITOR prompt.md            # set segments, tickers, sources
echo 'ANTHROPIC_API_KEY=sk-ant-...' > .env

3. Create the S3 bucket

BUCKET=morning-signal-podcast  # or your name
REGION=us-west-2

aws s3 mb "s3://$BUCKET" --region "$REGION"
aws s3api put-public-access-block --bucket "$BUCKET" \
  --public-access-block-configuration BlockPublicAcls=false,IgnorePublicAcls=false,BlockPublicPolicy=false,RestrictPublicBuckets=false
aws s3api put-bucket-policy --bucket "$BUCKET" --policy "$(cat <<EOF
{"Version":"2012-10-17","Statement":[{"Effect":"Allow","Principal":"*","Action":"s3:GetObject","Resource":"arn:aws:s3:::$BUCKET/*"}]}
EOF
)"

The bucket must be publicly readable so podcast apps can fetch the episodes.

4. Verify

.venv/bin/python generate_episode.py --script-only   # Claude only, no TTS, no upload
.venv/bin/python generate_episode.py --no-publish    # Add Polly, no upload
.venv/bin/python generate_episode.py                 # Full pipeline

5. Subscribe in Apple Podcasts (or any podcast app)

Once the first episode publishes successfully:

• Apple Podcasts: Library → ··· → "Follow a Show by URL…" → paste your feed URL
• Overcast / Pocket Casts: "Add URL" → paste

Your feed URL is <base_url>/feed.xml.

Cloud deploy (recommended for reliability)

The local CLI is fine for testing, but a laptop that sleeps at 5 AM won't run the cron. For dependable daily delivery, deploy on a long-lived host with systemd.

The pipeline supports two environment-variable knobs that turn on production behavior:

• MORNING_SIGNAL_RUNNER_ROLE_ARN=<role-arn> — at startup, call sts:AssumeRole and use that role's credentials for all subsequent boto3 clients. Lets you keep secrets/perms scoped to a dedicated runtime identity instead of the host's instance profile.
• MORNING_SIGNAL_USE_SSM=1 — fetch config.yaml, prompt.md, and ANTHROPIC_API_KEY from AWS SSM Parameter Store paths /morning-signal/config-yaml, /morning-signal/prompt-md, /morning-signal/anthropic-api-key (SecureString). Override the region with MORNING_SIGNAL_SSM_REGION (default us-east-1).

If neither is set, the script behaves as the local CLI — reads from disk, uses the default boto3 credential chain.

A representative systemd unit:

# /etc/systemd/system/morning-signal.service
[Unit]
Description=Morning Signal podcast generator
Wants=network-online.target
After=network-online.target

[Service]
Type=oneshot
User=ec2-user
WorkingDirectory=/home/ec2-user/morning-signal
Environment="MORNING_SIGNAL_RUNNER_ROLE_ARN=arn:aws:iam::ACCOUNT_ID:role/morning-signal-runner-role"
Environment="MORNING_SIGNAL_USE_SSM=1"
Environment="MORNING_SIGNAL_SSM_REGION=us-east-1"
ExecStart=/home/ec2-user/morning-signal/.venv/bin/python generate_episode.py
TimeoutStartSec=600
PrivateTmp=true

# /etc/systemd/system/morning-signal.timer
[Unit]
Description=Morning Signal — 5 AM + 5 PM Pacific (DST-aware)

[Timer]
Unit=morning-signal.service
OnCalendar=*-*-* 05:00:00 America/Los_Angeles
OnCalendar=*-*-* 17:00:00 America/Los_Angeles
Persistent=true

[Install]
WantedBy=timers.target

Persistent=true catches missed firings — e.g., if the host was rebooting at the calendar moment, the run fires when the host comes back up. America/Los_Angeles automatically tracks PDT/PST.

Two editions per day

When the --edition flag is unset, it's inferred from the Pacific clock (am if local hour < 12, else pm). Filenames carry the suffix: 2026-05-14-am.mp3, 2026-05-14-pm.mp3. Each edition is told via the prompt to cover only news that has broken since the prior edition (~12-hour window), avoiding duplicated content.

To run one edition daily, just omit the second OnCalendar line in the timer.

CLI reference

# Default: generate today's edition + publish (edition inferred from clock)
python generate_episode.py

# Specific edition / date
python generate_episode.py --edition pm
python generate_episode.py --date 2026-05-13 --edition am

# Re-generate an episode that already exists (overrides front-door dedup)
python generate_episode.py --force

# Script only — free; no TTS, no upload
python generate_episode.py --script-only

# Generate locally, skip S3
python generate_episode.py --no-publish

# Rebuild feed only (no Claude / Polly call), republish to S3
python generate_episode.py --publish-only

Customizing your podcast

Everything is controlled by two files:

prompt.md — Content + segments

This is the production prompt sent to Claude. Edit freely:

• Add / remove / reorder segments
• Pin specific sources, tickers, or themes
• Tune the word-count cap (the supplied prompt targets ~2,000 words ≈ 9 min audio at 1.5× playback)
• Adjust the news-window instruction if you want one or two editions

config.yaml — Infrastructure + metadata

• TTS voice + engine + playback speed
• S3 bucket + base URL
• Podcast title / description / category
• Max episodes in the feed
• SES notification recipients (optional)

Cost

For two editions per day (5 AM + 5 PM Pacific):

Component	Per episode	Monthly (60 episodes)
Claude Sonnet + web search	~$0.03	~$1.80
Amazon Polly neural (~10 KB chars)	~$0.04	~$2.40
S3 storage + transfer	~$0.01	~$0.30
Total	~$0.08	~$4.50

One edition per day is half that. Add an always-on EC2 t3.micro (~$8/month) if you don't already have a host; serverless options (Lambda + EventBridge, Fly scheduled Machine) come in cheaper but require a container image because ffmpeg is needed for the speed adjustment.

Tests

.venv/bin/pip install -e .[dev]
.venv/bin/pytest --cov

The suite uses moto for boto3 mocking and an inline anthropic mock — no real API calls. Coverage target: 80%+.

Alpha disclaimer

v0.1.x is an alpha release. The CLI surface, config schema, and SSM/IAM hooks may change in breaking ways before v1.0.0. Pin to a specific version (pip install morning-signal==0.1.0) if you're depending on a stable interface; otherwise expect to read the CHANGELOG when bumping.

Troubleshooting

Episodes not appearing in podcast app

• Verify the feed URL returns HTTP 200: curl -I <feed_url>
• Check the bucket policy allows public reads on s3:GetObject
• Apple Podcasts can take 10–15 minutes to poll a new feed; Overcast / Pocket Casts are usually faster

TTS chunking artifacts (slight pauses mid-script)

• Polly's neural engine has a 3000-char per-request limit; the script chunks at sentence boundaries and concatenates. Try a different voice or polly_engine: "standard" in config.yaml if it bothers you.

Re-publish everything

python generate_episode.py --publish-only

Skip a dedup

python generate_episode.py --force

Releasing to PyPI

The .github/workflows/publish.yml workflow runs on any push of a tag matching v*.*.*. It builds an sdist + wheel, validates them with twine check, then publishes to PyPI via OIDC trusted publishing (no API token in repo secrets).

One-time PyPI setup (do this once on PyPI's web UI before tagging v0.1.0):

1. Sign in at https://pypi.org/.
2. Account → Publishing → "Add a new pending publisher".
3. Fill in:
   • PyPI project name: morning-signal
   • Owner: cipher813
   • Repository name: morning-signal
   • Workflow filename: publish.yml
   • Environment name: pypi
4. Save.

Cutting a release:

# 1. Bump __version__ in src/morning_signal/__init__.py (e.g., "0.1.0")
# 2. Update CHANGELOG.md (move Unreleased entries into a dated version section)
# 3. Commit + push the version bump to main
# 4. Tag + push the tag — the workflow takes it from there
git tag v0.1.0
git push origin v0.1.0

Within ~2 minutes the package appears at https://pypi.org/project/morning-signal/ and pip install morning-signal works for anyone.

License

MIT — see LICENSE.