Serving Openmed REST API

What it does

When your agent uses it

• The user wants to serve OpenMed over HTTP
• Deploy a de-id/NER REST API
• Run an inference endpoint for clinical text
• /pii/deidentify route

Example prompts

• “/serving-openmed-rest-api”

Requirements

• Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

1. 1Install + launch. pip install "openmed[service]", then run
2. 2Configure the runtime via env vars before start: set
3. 3Front it with auth/TLS. Place a reverse proxy or gateway (API keys/mTLS,
4. 4Health-check + warm. Poll GET /health; preloaded models warm during
5. 5Call the endpoints (/analyze, /pii/extract, /pii/deidentify) with
6. 6Manage memory with GET /models/loaded and POST /models/unload as

What it can do on your machine

Read from SKILL.md and the folder at commit 6b1bb2c. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • uvicorn
  • curl
  • pip

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • fastapi.tiangolo.com
  • uvicorn.org
  • openapis.org
  • hhs.gov

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Serving Openmed REST API loads about 2.1k tokens when it runs. Until then it costs about 171 tokens; SKILL.md has 672 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~171

When it runs · the whole SKILL.md, loaded when a task matches

~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from maziyarpanahi/openmed at commit 6b1bb2c, republished under its Apache-2.0 licence (© maziyarpanahi). 672 words, ~2,123 tokens.

name

serving-openmed-rest-api

description

Stand up OpenMed's FastAPI REST service for clinical NER, PII extraction, and de-identification, with health checks, model keep-alive/unload, optional dynamic batching, and no-PHI logging. Use when the user wants to serve OpenMed over HTTP, deploy a de-id/NER REST API, run an inference endpoint for clinical text, add a /analyze or /pii/deidentify route, or containerize OpenMed as a service. Covers the service extra, launching create_app with uvicorn, the real endpoints (/health, /analyze, /pii/extract, /pii/deidentify, /models/loaded, /models/unload), request/response shapes, ServiceRuntime env-var configuration, and self-hosted auth/CORS/TLS notes.

license

Apache-2.0

metadata.project

OpenMed

metadata.category

deployment-ops

metadata.pairs

adjacent

metadata.version

1.0

pip install "openmed[service]"          # FastAPI + uvicorn + pydantic

# Launch the ASGI app (factory create_app, or the module-level `app`)
uvicorn openmed.service.app:app --host 127.0.0.1 --port 8000

# Or build it in-process (e.g. to mount under a parent app / add middleware):
from openmed.service import create_app
app = create_app()

curl -s localhost:8000/health
# {"status":"ok","service":"openmed-rest","version":"...","profile":"prod"}

curl -s localhost:8000/analyze -H 'content-type: application/json' -d '{
  "text": "Patient received 75mg clopidogrel for NSTEMI.",
  "model_name": "disease_detection_superclinical"
}'

curl -s localhost:8000/pii/deidentify -H 'content-type: application/json' -d '{
  "text": "John Doe called 555-123-4567 on 01/15/2020.",
  "method": "mask"
}'

OPENMED_SERVICE_PRELOAD_MODELS="disease_detection_superclinical" \
OPENMED_SERVICE_BATCHING_ENABLED=true \
uvicorn openmed.service.app:app --host 0.0.0.0 --port 8000

FROM python:3.11-slim
RUN pip install --no-cache-dir "openmed[service]"
ENV OPENMED_SERVICE_PRELOAD_MODELS="disease_detection_superclinical"
EXPOSE 8000
CMD ["uvicorn", "openmed.service.app:app", "--host", "0.0.0.0", "--port", "8000"]

© maziyarpanahi, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/serving-openmed-rest-api of maziyarpanahi/openmed.

Open the folder on GitHubat commit 6b1bb2c