Timmy the Talking Turd

A working mobile-first bowel diary with an optional photo-first AI assist: “Your intelligent pooping pal.”

Build a gated review release

python3 scripts/build_release.py

The builder clones the committed main tree into an isolated directory, runs unit/security and both mobile acceptance suites, audits dependencies, checks syntax and secrets, excludes model weights and sensitive/generated media, records a vertical feature demonstration from the working app, fully decodes and probes that MP4, and writes checksummed source/video artifacts plus manifest.json under /root/timmy-releases/. It refuses dirty or non-main source trees.

Run with the self-hosted open-weight path

npm install

git clone --depth 1 https://github.com/ggml-org/llama.cpp /root/model-spikes/llama.cpp
cmake -S /root/model-spikes/llama.cpp -B /root/model-spikes/llama.cpp/build -DCMAKE_BUILD_TYPE=Release
cmake --build /root/model-spikes/llama.cpp/build -j4 --target llama-server

hf download ggml-org/SmolVLM2-2.2B-Instruct-GGUF \
  SmolVLM2-2.2B-Instruct-Q4_K_M.gguf \
  mmproj-SmolVLM2-2.2B-Instruct-Q8_0.gguf \
  --local-dir /root/model-spikes/models/smolvlm2-2.2b

TIMMY_MODEL_PORT=8080 scripts/run_selfhost_smolvlm.sh

# In another terminal
TIMMY_VISION_PROFILE=selfhost npm start
# open http://localhost:4173

The selected bootstrap model is SmolVLM2-2.2B-Instruct using the official Apache-2.0 GGUF conversion. The default self-hosted endpoint is loopback-only at http://127.0.0.1:8080/v1. Override paths, host, port, threads, model ID, or endpoint with the TIMMY_MODEL_* and TIMMY_VISION_* environment variables.

Run with a hosted provider

hermes proxy start --provider nous --host 127.0.0.1 --port 8645
npm start

Hosted remains the default compatibility profile. To make it explicit, set TIMMY_VISION_PROFILE=hosted. Credentials stay server-side:

TIMMY_VISION_BASE_URL=https://your-openai-compatible-provider/v1 \
TIMMY_VISION_API_KEY=... \
TIMMY_VISION_MODEL=your-vision-model \
npm start

Set TIMMY_VISION_ENABLED=0 to disable uploads and retain manual-only operation.

Verify

npm test
npm run test:ui       # server required on port 4173
npm run test:photo    # mocked positive suggestion through the real browser UX
npm audit --audit-level=high

What works

Photo-first camera/file capture
Client-side image compression before transfer
Explicit consent before one-time provider analysis
Structured AI suggestions for visible Bristol form and color only
Confidence display, low-confidence abstention, and user confirmation
Urgency, discomfort, notes, and symptoms remain strictly user-reported
Manual logging that never uploads
Red-flag symptom escalation
Local browser ledger, calendar, pattern summary, JSON portability, and delete-all
Installable/offline PWA shell for the manual and saved-ledger paths

What is deliberately not faked

The positive photo-prefill interface is covered by a deterministic provider fixture. A live self-hosted SmolVLM2-2.2B model was exercised against a CC-licensed real Type 4 stool photograph. It accepted the content and identified stool, but predicted the wrong type with low confidence; Timmy correctly abstained. The open model removes provider moderation from the path, but its Bristol accuracy is not clinically established.

Timmy does not diagnose disease, identify bleeding, infer pain/urgency, recommend treatment, or clear foods. The selected VLM is a bootstrap worker, not the final classifier. See research/SELF-HOSTED-STOOL-VISION.md for the measured receipts, hardware gate, consented-data pipeline, specialist-classifier plan, and sources.

Architecture

Browser PWA
├── app.js                    photo-first UX, local persistence, compression
├── src/domain.js             tested health/safety and summary rules
├── src/analysis.js           strict AI schema, validation, visual-only merge
├── server.mjs                static server + bounded /api/analyze route
├── src/vision-service.js     server-side OpenAI-compatible provider adapter
├── src/vision-config.js      hosted/self-hosted profiles and readiness probe
├── scripts/run_selfhost_smolvlm.sh
├── scripts/ingest_training_photo.py
├── localStorage              saved ledger and attached photos
└── llama.cpp / hosted API    selected per server-side profile

The server accepts JPEG/PNG/WebP data URLs up to 4 MB, uses a bounded 60-second hosted or 120-second self-hosted timeout, never accepts an API key from browser input, does not write inference images to disk, and returns only validated visual suggestions. The separate dataset ingester runs only for explicit, consented contributions.

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