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| title: Genome Firewall Inference | |
| emoji: 🧬 | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: docker | |
| app_port: 8000 | |
| pinned: false | |
| # Genome Firewall inference service | |
| FASTA → antibiotic-response prediction. This is the service the Convex action | |
| (`convex/analysis.ts`) calls. It runs the real trained E. coli models from | |
| [`Darkroom4364/genome-firewall-ecoli`](https://huggingface.co/Darkroom4364/genome-firewall-ecoli). | |
| ## Pipeline | |
| 1. `POST /predict` receives an assembled genome FASTA + a target antibiotic. | |
| 2. **AMRFinderPlus 4.2.7** (NCBI) detects resistance genes / point mutations. | |
| 3. Hits become a 600-dim binary feature vector (`features/build_feature_matrix.py`). | |
| 4. The per-drug calibrated elastic-net model gives `p_fail` (probability of resistance). | |
| 5. No-call bands (`models/<drug>/nocall_bands.json`) decide work / fail / abstain. | |
| 6. Evidence genes are mapped per drug (`features/map_evidence.py` + `drug_class_map.yaml`). | |
| Response `score = 1 − p_fail` (probability the drug is **effective**). Contract: see | |
| [`../convex/README.md`](../convex/README.md). | |
| Supported drugs: `ciprofloxacin`, `gentamicin`, `ampicillin`, `cefotaxime`, | |
| `trimethoprim_sulfamethoxazole` (UI labels are mapped in `gf_infer.py:LABEL_TO_KEY`). | |
| ## Contents | |
| | Path | What | | |
| |---|---| | |
| | `serve.py` | FastAPI service (`/health`, `/predict`) | | |
| | `gf_infer.py` | Inference core: TSV/features → model → app contract | | |
| | `features/` | `build_feature_matrix.py`, `map_evidence.py`, `drug_class_map.yaml`, `feature_columns.json`, `metadata.json` (reused from branch `sprint/baseline`) | | |
| | `models/<drug>/` | `model.skops` + `nocall_bands.json` (from Hugging Face) | | |
| | `requirements.txt`, `Dockerfile`, `.dockerignore` | packaging | | |
| ## Deploy (recommended — container has AMRFinderPlus + DB baked in) | |
| ```bash | |
| cd inference | |
| docker build --platform linux/amd64 -t genome-firewall-api . | |
| docker run --platform linux/amd64 -p 8000:8000 \ | |
| -e INFERENCE_API_TOKEN=<optional-shared-secret> \ | |
| genome-firewall-api | |
| ``` | |
| Then set `INFERENCE_API_URL` (the public URL of this host) in the Convex dashboard. | |
| Host needs an amd64 runtime with enough RAM/CPU for AMRFinderPlus (a genome takes ~1–3 min). | |
| ## Local dev (host Python; AMRFinderPlus via Docker) | |
| ```bash | |
| cd inference | |
| uv venv --python 3.13 .venv | |
| uv pip install --python .venv/bin/python -r requirements.txt | |
| ./.venv/bin/uvicorn serve:app --host 0.0.0.0 --port 8000 | |
| ``` | |
| When the `amrfinder` binary is not on `PATH`, `serve.py` runs AMRFinderPlus via | |
| `docker run staphb/ncbi-amrfinderplus:4.2.7-2026-03-24.1` automatically. `GET /health` | |
| reports `"amrfinder": "binary"` or `"docker"` accordingly. | |
| ```bash | |
| curl -s localhost:8000/health | jq | |
| curl -s localhost:8000/predict -H 'content-type: application/json' \ | |
| -d "{\"fasta\": \"$(sed ':a;N;$!ba;s/\n/\\n/g' genome.fna)\", \"antibiotic\": \"Ampicillin\"}" | jq | |
| ``` | |
| > Research prototype. All predictions must be confirmed with standard laboratory | |
| > susceptibility testing. Not a medical device. | |