109 lines
3.2 KiB
Markdown
109 lines
3.2 KiB
Markdown
---
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description: Start Gitea local CI, check status, or push all repos to trigger CI runs
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---
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# Gitea Local CI Workflow
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Manages the self-hosted Gitea + act_runner CI infrastructure for all ByteLyst repos.
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See `docs/devops/GITEA_LOCAL_CI.md` for full documentation.
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## 1. Ensure Gitea and act_runner are running
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// turbo
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```bash
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brew services start gitea && brew services start act_runner && sleep 2 && brew services list | grep -E "gitea|act_runner"
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```
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## 2. Verify Gitea is responding
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// turbo
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```bash
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curl -s http://localhost:3300/api/v1/version | python3 -c "import sys,json; print('Gitea', json.load(sys.stdin)['version'])"
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```
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## 3. Push all workspace repos to Gitea to trigger CI
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This pushes `main` to the `gitea` remote for every repo that has one configured.
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Each push triggers the `.gitea/workflows/ci.yml` workflow on the local runner.
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```bash
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REPOS_DIR="/Users/sd9235/code/mygh"
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for repo in \
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learning_ai_common_plat \
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learning_voice_ai_agent \
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learning_multimodal_memory_agents \
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learning_ai_clock \
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learning_ai_fastgap \
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learning_ai_jarvis_jr \
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learning_ai_peakpulse \
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learning_ai_notes \
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learning_ai_flowmonk \
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learning_ai_trails \
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learning_ai_local_memory_gpt; do
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echo "=== $repo ==="
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cd "$REPOS_DIR/$repo"
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git push gitea main 2>&1 | tail -2
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done
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```
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## 4. Wait for jobs to process, then check results
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Wait ~2 minutes per repo for the runner (capacity=1) to process the queue, then check results.
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```bash
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REPOS_DIR="/Users/sd9235/code/mygh"
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for repo in \
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learning_ai_common_plat \
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learning_ai_clock \
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learning_ai_trails \
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learning_ai_flowmonk \
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learning_ai_notes \
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learning_ai_fastgap \
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learning_ai_jarvis_jr \
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learning_ai_peakpulse \
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learning_ai_local_memory_gpt \
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learning_voice_ai_agent \
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learning_multimodal_memory_agents; do
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echo "=== $repo ==="
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curl -s -u "bytelyst:bytelyst123" "http://localhost:3300/api/v1/repos/bytelyst/$repo/actions/jobs" | python3 -c "
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import sys, json
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jobs = json.load(sys.stdin).get('jobs', [])
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if not jobs:
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print(' (no jobs)')
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else:
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max_run = max(j['run_id'] for j in jobs)
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for j in jobs:
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if j['run_id'] == max_run:
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c = j.get('conclusion','pending')
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icon = '✅' if c == 'success' else '❌' if c == 'failure' else '⏳'
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print(f' {icon} {c:12} {j[\"name\"]}')
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" 2>/dev/null
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done
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```
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## 5. (Optional) View logs for a failing job
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Replace REPO and JOB_ID with the repo name and job number from step 4.
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```bash
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REPO="learning_ai_clock"
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JOB_ID="76"
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curl -s -u "bytelyst:bytelyst123" "http://localhost:3300/api/v1/repos/bytelyst/$REPO/actions/jobs/$JOB_ID/logs" | tail -30
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```
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## 6. (Optional) Stop Gitea services
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```bash
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brew services stop act_runner && brew services stop gitea
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```
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## Troubleshooting
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- **Runner not picking up jobs:** `brew services restart act_runner`
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- **Runner still queued after restart:** re-register against `http://127.0.0.1:3300` instead of `http://localhost:3300`
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- **Stale .next/lock:** `rm -f /Users/sd9235/code/mygh/learning_ai_common_plat/dashboards/*-web/.next/lock`
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- **Permission denied on tsc:** `chmod +x /Users/sd9235/code/mygh/learning_ai_common_plat/node_modules/.bin/*`
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- **Check runner log:** `tail -30 /opt/homebrew/var/log/act_runner.err`
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