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Pandoc's pptx writer was the ceiling on how good a generated deck could be, and the model on top made no difference to it. It maps markdown onto a handful of reference layouts with no per-slide layout, no positioning and no control over how large an image is drawn, which is why every deck came out as bullets on a template — and why autofit had to be injected into its emitted OOXML by hand afterwards, because LibreOffice ignores the autofit pandoc leaves off. scripts/render_pptx.py draws the deck and src/utils/slideSpec.js decides what each slide is. Markdown stays the stored artifact, so "change slide 4" is still a text edit and Word export is untouched — pandoc still writes docx, where its output is good. What that buys, all of it visible in a rendered deck rather than argued for: - 16:9, not pandoc's 4:3. - A pipe table becomes a real table with a header band and banded rows, not eight lines of text with pipes in them. - A list longer than seven items becomes two columns instead of a wall of text. - Text is measured and sized to fit before the file is written, so nothing depends on a renderer honouring autofit. - Wrapped lines hang under the text instead of running back to the margin, which is the clearest single tell that a deck was generated. - An image is drawn at its own aspect ratio, centred, with a caption. Figures now reach the deck at all, which they never did. They were queued and shown on the page, but nothing recorded that they belonged to the resource, so an export could not include them: user_resources.image_ids holds them, a modification adds to that list rather than replacing it, and export fetches the finished ones to a scratch directory. They are spread through the deck rather than appended, because ending on three unexplained pictures is worse than showing each near its material, and a References slide stays last. If the renderer fails for any reason, pandoc still produces a deck — a plainer deck beats a failed download. Verified end to end: a seven-slide request with three figures exported as a 13-page deck; the slides were rendered to PDF, rasterised and looked at. All three formats still download. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Dv6sqaY6Vq3ChZHMem3cnU |
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Ped-AI
Ped-AI is a pediatric clinical documentation, education, and bedside decision-support app. This fork has moved well beyond the original scribe app: it now combines encounter documentation, clinical workflows, Learning Hub CMS, admin controls, MCP-backed clinical assistant integration, Redis-backed operational state, and hardened deployment defaults.
The app runs as an authenticated Express/Postgres service with a browser frontend and optional integrations for LiteLLM, Vertex/Gemini, AWS, OpenAI-compatible APIs, Nextcloud WebDAV, S3-compatible storage, OpenBao, Redis, OIDC, TOTP, and Cloudflare Turnstile.
Current Scope
Clinical Documentation
- Live encounter capture with structured pediatric HPI generation.
- Dictation cleanup for narrative notes.
- SOAP, sick visit, well visit, hospital course, chart review, precharting, and ED encounter workflows.
- Parent-facing education handouts generated from clinician notes, with diagnosis, medication, emergency-care guidance, and preferred-language support.
- Pediatric developmental milestone tooling.
- Templates, physician memory, and per-tab model overrides.
- Server-side speech-to-text routing through configured providers.
Bedside Tools
- Pediatric calculators and emergency dosing helpers.
- PE guide and clinical reference content.
- Vaccines, catch-up schedules, growth/vitals, bilirubin, BSA, GCS, equipment, and resuscitation helpers.
- Mobile-friendly PWA layout for bedside use.
- Per-user phone extension and pager directory with soft-delete, search, ZIP export, and JSON/ZIP import for handoff between users.
Learning Hub
- CMS for articles, clinical pearls, quizzes, and presentations.
- Tiptap article editor, quiz builder, category management, and draft/publish flow.
- AI-assisted content generation from topic text, uploaded files, or connected Nextcloud WebDAV files.
- Marp slide editing with preview and PPTX export.
- Keyword, semantic, and hybrid search using Postgres/pgvector where configured.
Clinical Assistant
- Optional MCP-backed clinical assistant integration.
- Prompt suggestions backed by Redis operational cache.
- No clinical answer response caching.
- Designed to retrieve from indexed clinical material while keeping provider selection explicit.
Admin And Security
- Local auth, role-based access, TOTP 2FA, OIDC/SSO, email verification, and optional Turnstile.
- Admin panel for users, settings, prompts, models, logs, and Learning Hub content.
- Audit, API, access, and client-error logs with redaction hardening.
- OpenBao secret loading support at container startup.
- S3-compatible document storage support.
Removed Browser STT
Browser Whisper has been removed from the runtime. The app should not ship browser Whisper workers, browser-local Whisper model downloads, Transformers.js browser STT, or Browser Whisper setup docs.
Speech-to-text is handled server-side through configured providers such as Google/Gemini, AWS Transcribe, LiteLLM, or OpenAI Whisper. Browser-native Web Speech remains gated behind an explicit user setting when present in the browser.
Quick Start
cp .env.example .env
./scripts/build-image.sh
docker compose up -d --no-build
The default compose exposes the app on 127.0.0.1:3552 and starts:
pediatric-ai-scribefor the Node app.pedscribe-dbfor Postgres with pgvector.ped-ai-redisfor operational Redis state.
Health check:
curl -fsS http://127.0.0.1:3552/api/health
Prometheus metrics are exposed at GET /metrics with the ped_ai_ metric prefix.
The first registered user becomes an admin unless registration has already been configured differently.
Core Environment
Set real values in .env before production use.
APP_URL=https://your-domain.example
JWT_SECRET=<64-char-random-secret>
DB_PASSWORD=<strong-database-password>
AI_PROVIDER=litellm
LITELLM_API_BASE=https://your-litellm.example/v1
LITELLM_API_KEY=<key>
TRANSCRIBE_PROVIDER=litellm
LITELLM_STT_MODEL=whisper-1
REDIS_URL=redis://ped-ai-redis:6379
Supported text AI providers include LiteLLM, OpenRouter, AWS Bedrock, Azure OpenAI, and Google Vertex AI. Supported STT routing includes Google/Gemini, AWS Transcribe, OpenAI Whisper, and LiteLLM. Supported TTS routing includes Google Cloud TTS, LiteLLM/OpenAI-compatible audio, and ElevenLabs where configured.
Admin CLI
docker exec pediatric-ai-scribe node admin-cli.js list-users
docker exec pediatric-ai-scribe node admin-cli.js create-admin admin@example.com password123 "Dr. Admin"
docker exec pediatric-ai-scribe node admin-cli.js make-admin user@example.com
docker exec pediatric-ai-scribe node admin-cli.js reset-password user@example.com newpassword
docker exec pediatric-ai-scribe node admin-cli.js toggle-registration
docker exec pediatric-ai-scribe node admin-cli.js stats
Maintenance
The app checks Postgres collation drift on startup and can reindex text indexes after image or OS-library changes.
docker exec pediatric-ai-scribe npm run maint:check
docker exec pediatric-ai-scribe npm run maint:reindex
Run the reindex command after major Postgres image changes, restoring a dump from another distro, or seeing lookup behavior that suggests collation/index drift.
Testing
Run the Node test suite:
npm test
Run syntax checks for touched files when doing focused backend work:
node --check server.js
node --check src/routes/transcribe.js
Run the Playwright smoke suite against the e2e compose stack:
docker compose -f docker-compose.yml -f docker-compose.e2e.yml up -d pediatric-scribe-e2e
npm run e2e
Deployment Notes
- Put the app behind HTTPS before clinical use.
- Use only AI/STT/TTS providers covered by your BAA and data-processing requirements.
- Configure OIDC/SSO and 2FA for production users.
- Keep
JWT_SECRET, database credentials, provider keys, S3 keys, SMTP credentials, and OpenBao tokens out of git. - Treat logs as sensitive operational data even with redaction enabled.
- Use the Caddy/reverse-proxy layer to expose only intended public routes.
Documentation
Primary references:
docs/ARCHITECTURE.mdfor the current system map and service boundaries.docs/DEVELOPMENT.mdfor day-to-day code-change workflow.docs/SCALING.mdfor scaling priorities and readiness work.docs/CLINICAL_ASSISTANT.mdfor MCP-backed assistant behavior and safety rules.docs/MODULE_CONVENTIONS.mdfor CommonJS, ESM, globals, and rendering rules.docs/architecture.mdfor high-level architecture.docs/api-reference.mdfor API routes.docs/authentication.mdfor auth, OIDC, and security configuration.docs/ai-providers.mdfor model/provider setup.docs/speech.mdfor server-side STT/TTS setup.docs/learning-hub.mdfor the CMS and education workflow.docs/configuration.mdfor environment variables.docs/deployment.mdfor production deployment.docs/mobile-build.mdfor the Capacitor wrapper and app-store build notes.docs/logic/README.mdfor the deeper code walkthrough.
Some deep docs/logic/ files still describe historical implementation details. Prefer runtime code and tests when documentation conflicts with current behavior.
Clinical Safety
Ped-AI is documentation and education support software. It does not replace clinical judgment, local policy, medication verification, or attending review. Validate generated notes, calculations, and recommendations before use in patient care.