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unused_skills.yml
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unused_skills.yml
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services:
aiml:
build:
args:
skill_endpoint: aiml
skillconfig: skills/aiml/aiml_skill.json
skillhost: 0.0.0.0
skillport: 2080
context: ./
dockerfile: dp/dockerfile_skill_cpu
environment:
- CUDA_VISIBLE_DEVICES=""
ports:
- 2080:2080
transfertransfo:
build:
context: ./skills/transfertransfo/
environment:
DEVICE: cuda
command: gunicorn --workers=1 server:app -b 0.0.0.0:8007 -t 60
volumes: []
deploy:
mode: replicated
replicas: 1
placement:
constraints:
- node.labels.with_gpu == true
retrieval_chitchat:
build:
context: ./skills/retrieval_chitchat/
command: uvicorn server:app --host 0.0.0.0 --port 8015
volumes: []
deploy:
mode: replicated
replicas: 1
placement:
constraints:
- node.labels.with_gpu != true
convert_reddit_with_personality:
build:
context: ./skills/convert_reddit_with_personality/
command: gunicorn --workers=1 server:app -b 0.0.0.0:8048 -t 60
volumes: []
deploy:
mode: replicated
replicas: 2
placement:
constraints:
- node.labels.with_gpu != true
news_skill:
build:
context: .
dockerfile: ./skills/alexa-prize-news/Dockerfile
command: bash -c "python updater.py | gunicorn --workers=1 server:app -b 0.0.0.0:8027 -t 300"
volumes: []
deploy:
mode: replicated
replicas: 1
placement:
constraints:
- node.labels.with_gpu != true
topicalchat_convert_retrieval:
build:
context: ./skills/topicalchat_convert_retrieval/
command: gunicorn --workers=1 server:app -b 0.0.0.0:8060 -t 60
volumes: []
deploy:
mode: replicated
replicas: 2
placement:
constraints:
- node.labels.with_gpu != true
- node.labels.group == 0
reddit_ner_skill:
build:
context: .
dockerfile: ./skills/reddit_ner_skill/Dockerfile
command: gunicorn --workers=2 server:app -b 0.0.0.0:8035
deploy:
mode: replicated
replicas: 2
placement:
constraints:
- node.labels.with_gpu != true
question-generator:
build:
context: ./services/question_generator/
args:
MODEL_URL: http://lnsigo.mipt.ru/export/alexaprize_data/question_generator/model_24_0.94_37.23.pth
command: gunicorn --workers=1 --timeout 300 server:app -b 0.0.0.0:8079
environment:
- CUDA_VISIBLE_DEVICES=0
- DECODING=greedy
deploy:
mode: replicated
replicas: 1
resources:
limits:
memory: 3G
reservations:
memory: 3G
speech-function-classifier:
build:
args:
SERVICE_PORT: 8108
SERVICE_NAME: speech_function_classifier # has to be the same with skill dir name
context: ./annotators/speech_function_classifier/
command: uvicorn server:app --reload --host 0.0.0.0 --port 8108
deploy:
mode: replicated
replicas: 2
resources:
limits:
memory: 768M
reservations:
memory: 768M
speech-function-predictor:
build:
args:
SERVICE_PORT: 8107
SERVICE_NAME: speech_function_predictor # has to be the same with skill dir name
context: ./annotators/speech_function_predictor/
command: uvicorn server:app --reload --host 0.0.0.0 --port 8107
deploy:
mode: replicated
replicas: 2
resources:
limits:
memory: 768M
reservations:
memory: 768M
wikidata-dial-skill:
build:
args:
PORT: 8091
context: skills/wikidata_dial_skill
command: flask run -h 0.0.0.0 -p 8091
environment:
- FLASK_APP=server
deploy:
mode: replicated
replicas: 1
resources:
limits:
memory: 256M
reservations:
memory: 256M
wikidata-dial-service:
build:
args:
CONFIG: kg_dial_generator.json
PORT: 8092
COMMIT: 5dac85a06fde0e2983c7569ae058e3bf2d45ce2c
context: services/wikidata_dial_service
command: flask run -h 0.0.0.0 -p 8092
environment:
- CUDA_VISIBLE_DEVICES=0
- FLASK_APP=server
deploy:
mode: replicated
replicas: 1
resources:
limits:
memory: 10G
reservations:
memory: 10G
version: '3.7'