NLP-Sentiment-Analysis / docker-compose.yml
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feat: Serve the irony head as a quantised ONNX graph
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services:
api:
build: .
container_name: nlp_api
command: uvicorn api.main:app --host 0.0.0.0 --port 8000
ports:
- "8000:8000"
environment:
- MODEL_NAME=distilbert/distilbert-base-uncased-finetuned-sst-2-english
- IRONY_MODEL_REPO=jorgeasmz/distilbert-irony-tweeteval
volumes:
# Must match HF_HOME in the Dockerfile, or the cache silently lands
# somewhere the library never reads and the model re-downloads on every
# start.
- ./model_cache:/app/.cache
healthcheck:
test: ["CMD-SHELL", "python -c \"import urllib.request,json; assert json.load(urllib.request.urlopen('http://localhost:8000/'))['model_ready']\""]
interval: 10s
timeout: 5s
retries: 10
start_period: 60s
web:
build: .
container_name: nlp_web
command: streamlit run web/app.py --server.port 8501 --server.address 0.0.0.0
ports:
- "8501:8501"
environment:
- API_URL=http://api:8000
depends_on:
api:
condition: service_healthy