Jyotisha/deploy/README.md

Production deployment and maintenance

This file is the operational source of truth for the current Jyotisha demo deployment.

Current production

Item	Value
Public domain	https://jyotisha.chat
DNS	Spaceship nameservers (launch1.spaceship.net, launch2.spaceship.net)
Server	Hong Kong VPS, Ubuntu 22.04 x86_64
Public host	103.117.123.53
SSH	port 22000, public-key authentication only
Capacity	1 vCPU / 2 GB RAM / 40 GB disk / 5 Mbps
App directory	/opt/jyotisha-app
Environment file	/opt/jyotisha-app/.env.production (0600)
Source repository	https://github.com/jesse-ux/Jyotisha.git
Supabase project	vtvnfqmonbfuxmqkqdlc

This machine is suitable for a client demo and low concurrency. Supabase and the model provider stay managed externally; do not self-host them on this VPS.

Architecture

Spaceship DNS
  -> Caddy :80/:443
     -> web:3000 (Next.js + Mastra, Docker-private)
        -> api:5200 (Python Jyotish API, Docker-private)
           -> Swiss Ephemeris / local engine
           -> VedAstro gateway with local fallback
     -> Supabase Cloud
     -> external OpenAI-compatible model API

Only Caddy publishes host ports. Ports 3000 and 5200 must remain private.

DNS and Supabase Auth

Spaceship resource records:

A      @      103.117.123.53
CNAME  www    jyotisha.chat

Supabase Authentication URL Configuration:

Site URL:      https://jyotisha.chat
Redirect URLs: https://jyotisha.chat/**
               https://www.jyotisha.chat/**

Before changing Caddy to the domain, verify the authoritative DNS result:

dig +short @launch1.spaceship.net A jyotisha.chat

It must return 103.117.123.53. Caddy provisions and renews HTTPS automatically after DNS resolves.

Production environment

.env.production combines the backend and frontend server variables. Required groups:

SITE_ADDRESS=https://jyotisha.chat
JYOTISH_API_BASE=http://api:5200

NEXT_PUBLIC_SUPABASE_URL=...
NEXT_PUBLIC_SUPABASE_ANON_KEY=...
SUPABASE_SERVICE_ROLE_KEY=...
ADMIN_EMAILS=...

# Recommended multi-model catalog. The JSON references server-only keys.
LLM_DEFAULT_MODEL_ID=deepseek-pro
LLM_MODELS_JSON='[{"id":"deepseek-pro","label":"DeepSeek V4 Pro","description":"更适合复杂分析","provider":"openai-compatible","baseURL":"https://api.deepseek.com","apiKeyEnv":"DEEPSEEK_API_KEY","model":"deepseek-v4-pro","creditCost":1},{"id":"gpt-5-mini","label":"ChatGPT 5 Mini","description":"响应稳定、速度均衡","provider":"openai","apiKeyEnv":"OPENAI_API_KEY","model":"openai/gpt-5-mini","creditCost":1}]'
DEEPSEEK_API_KEY=<server-secret>
OPENAI_API_KEY=<server-secret>

# Legacy single-model OpenAI configuration remains supported:
# OPENAI_API_KEY=<server-secret>
# MASTRA_MODEL=openai/gpt-5-mini

# Legacy single OpenAI-compatible provider remains supported:
# LLM_BASE_URL=https://provider.example/v1
# LLM_API_KEY=<server-secret>
# LLM_MODEL=provider-model-id

# Required VedAstro server-side upstream for chart creation and rectification:
VEDASTRO_GATEWAY_MODE=official_first
VEDASTRO_API_ENDPOINT=https://api.vedastro.org/api
VEDASTRO_ENABLE_NETWORK=1
VEDASTRO_TIMEOUT_SECONDS=20
VEDASTRO_API_KEY=<server-secret>

Never commit .env.production, SUPABASE_SERVICE_ROLE_KEY, model keys, user JWTs, SSH private keys or passwords. NEXT_PUBLIC_SUPABASE_ANON_KEY is intentionally public; authorization is enforced by Supabase RLS and server-side checks.

After changing VedAstro variables, restart the API and verify the configuration without printing credentials:

docker compose --env-file .env.production -f deploy/docker-compose.server.yml up -d --build api
docker compose --env-file .env.production -f deploy/docker-compose.server.yml exec api python3 scripts/diagnose_vedastro_mode.py

The report must show mode: official_extended and network_enabled: true. A missing raw response remains an upstream response boundary, not a successful external verification.

Connect and inspect

ssh -p 22000 root@103.117.123.53
cd /opt/jyotisha-app
COMPOSE='docker compose --env-file .env.production -f deploy/docker-compose.server.yml'
$COMPOSE ps
$COMPOSE logs --tail=100 api web caddy
free -h
docker stats --no-stream

The server has a persistent 2 GB /swapfile. UFW permits only SSH 22000/tcp, HTTP 80/tcp, HTTPS 443/tcp, and the pre-existing WireGuard 51820/udp rule.

Manual deployment with GitHub Actions

Pushes and pull requests do not start GitHub Actions automatically. Run the required validation workflows from the Actions page, then manually start .github/workflows/deploy-production.yml for the tested branch. The deployment workflow syncs that revision with rsync, preserves /opt/jyotisha-app/.env.production, rebuilds both Docker services, and verifies the public login route, logged-out account response, and private Python health endpoint.

Required GitHub Actions secret:

PRODUCTION_SSH_PRIVATE_KEY = dedicated production deploy private key

The workflow pins the VPS Ed25519 host key and serializes deployments with the production concurrency group.

Staging deployment

Staging is isolated from production:

Item	Value
URL	https://staging.jyotisha.chat
Host	118.26.111.127
Path	/opt/jyotisha-staging
Runtime env	/opt/jyotisha-staging/.env.staging (0600)
Supabase	separate Jyotisha Staging project
GitHub Environment	staging

The GitHub Environment contains STAGING_SSH_PRIVATE_KEY and the variables STAGING_HOST, STAGING_PORT, STAGING_USER, STAGING_PATH, STAGING_URL, and STAGING_KNOWN_HOSTS. Its deployment branch policy allows the main controller branch: GitHub's workflow_run event executes from the default branch while the workflow separately requires the successfully tested upstream branch to be staging. The staging key, database, Supabase keys, and model-provider keys must not be shared with production.

A push to branch staging runs Jyotish Skill CI. A successful push run triggers .github/workflows/deploy-staging.yml, which deploys the tested SHA and verifies the login route, logged-out account response, deployment SHA, and private Python health endpoint.

The staging env file must include these non-secret selectors so Compose cannot fall back to production paths:

APP_ENV_FILE=../.env.staging
CADDYFILE_PATH=./Caddyfile.staging
SITE_ADDRESS=https://staging.jyotisha.chat

After source sync and before up, the workflow validates .env.staging mode/selectors, explicitly pins the three staging selectors against ambient shell overrides, and runs docker compose --env-file .env.staging -f deploy/docker-compose.server.yml config --quiet. For later manual inspections, run the same checks only after the tracked deployment files exist on the server. The first deployment should be manual:

1. Confirm /opt/jyotisha-staging/.env.staging exists, has mode 0600, and contains the three selectors above.
2. Open GitHub Actions -> Jyotish Skill CI -> Run workflow, using workflow from main.
3. Wait for success and copy that run's exact 40-character commit SHA.
4. Open GitHub Actions -> Deploy staging -> Run workflow, using workflow from main, and enter the SHA in git_sha.
5. Confirm https://staging.jyotisha.chat/api/health reports that SHA.
6. Only after the manual deployment passes, push a reviewed revision to branch staging to validate automatic deployment.

Application rollback uses the same workflow: manually dispatch Deploy staging from main with a previous known-good full SHA that has a successful CI run. Database migrations are separate and are not rolled back by an application deployment. Restore a staging database backup before running any destructive migration rehearsal.

Inspect staging without printing secrets:

ssh -i ~/.ssh/jyotisha-staging deploy@118.26.111.127
cd /opt/jyotisha-staging
docker compose --env-file .env.staging -f deploy/docker-compose.server.yml ps
docker compose --env-file .env.staging -f deploy/docker-compose.server.yml logs --tail=100 api web caddy
curl -fsS https://staging.jyotisha.chat/api/health

The normal application deployment workflow never runs database migrations. Apply migrations to the separate staging project first, verify them, and only then deploy application code that depends on them.

Manual deployment fallback

If GitHub Actions is unavailable, deploy the tracked tree without copying local secrets:

cd /Users/jesse/Downloads/Copse/astrology/yinduzhanxing
git status --short --branch
rsync -az --delete \
  --exclude='.git/' \
  --exclude='.env.production' \
  --exclude='frontend/node_modules/' \
  --exclude='frontend/.next/' \
  -e 'ssh -p 22000' \
  ./ root@103.117.123.53:/opt/jyotisha-app/
ssh -p 22000 root@103.117.123.53 \
  'cd /opt/jyotisha-app && docker compose --env-file .env.production -f deploy/docker-compose.server.yml up -d --build --remove-orphans'

The excluded .env.production remains only on the VPS.

Verification

curl -fsS https://jyotisha.chat/login >/dev/null
curl -fsS -o /dev/null -w '%{http_code}\n' https://jyotisha.chat/api/account

The second command should return 401 while logged out. Verify the private Python API from inside the web container:

ssh -p 22000 root@103.117.123.53 \
  'cd /opt/jyotisha-app && docker compose --env-file .env.production -f deploy/docker-compose.server.yml exec -T web node -e "fetch(\"http://api:5200/api/health\").then(async r=>{console.log(r.status); console.log(await r.text())})"'

Expected: HTTP 200, "status": "ok", and "swisseph_available": true. Public access to 103.117.123.53:5200 must fail.

Before deploying application code that depends on any new Supabase migration (columns, tables, grants, policies, or RPCs), run cd frontend && npx supabase db push --linked; the GitHub deployment workflow does not apply database migrations. Multi-model chat specifically requires 20260717010000_chat_session_model.sql before the new web image is deployed. Then manually verify: OTP login, onboarding/profile persistence, per-session model_id persistence, code redemption, admin code generation, authenticated /api/models returns only sanitized public metadata, invalid model IDs are rejected before charging, each configured model can answer, the 2.5-second free undo window, streaming response, one-credit charge, refund before the first output chunk, and charged stop with partial output preserved after streaming starts.

For the July 2026 new-user profile save fix, either run the manual GitHub Action Apply Supabase profile migrations after adding SUPABASE_DB_URL or DATABASE_URL to /opt/jyotisha-app/.env.production, or execute these five SQL migrations in the Supabase SQL Editor with a project member account:

• 20260718010000_recover_missing_profile_rows.sql
• 20260718020000_profiles_service_role_upsert_grants.sql
• 20260718050000_profiles_service_role_upsert_grants.sql
• 20260718070000_profiles_service_role_upsert_id.sql
• 20260718080000_profiles_service_role_account_upsert_selects.sql

Do not treat a green app deployment as proof this database step ran. If the SQL Editor shows You do not have access to this project, use the correct Supabase organization account or invite the current GitHub user to project vtvnfqmonbfuxmqkqdlc before retrying.

Common operations

# Restart without rebuilding
docker compose --env-file .env.production -f deploy/docker-compose.server.yml up -d

# Rebuild only the web container
docker compose --env-file .env.production -f deploy/docker-compose.server.yml up -d --build web caddy

# Rebuild only the Python API
docker compose --env-file .env.production -f deploy/docker-compose.server.yml up -d --build api

# Follow logs
docker compose --env-file .env.production -f deploy/docker-compose.server.yml logs -f --tail=100 api web caddy

Optional Railway deployment

Railway is not the current production target. If needed, create web and api services from the same repository using deploy/railway-web.Dockerfile and deploy/railway-api.Dockerfile; keep api private and set the web service's JYOTISH_API_BASE to Railway's private API hostname.