dream

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services:
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  agent:
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    command: sh -c 'bin/wait && python -m deeppavlov_agent.run agent.pipeline_config=assistant_dists/dream_multilingual/pipeline_conf.json'
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    environment:
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      WAIT_HOSTS: "convers-evaluation-selector:8009, 
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          gpt2-multilingual:8132, toxic-classification-multilingual:8013,
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          sentiment-classification-multilingual:8024, sentence-ranker-multilingual:8128"
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      WAIT_HOSTS_TIMEOUT: ${WAIT_TIMEOUT:-1200}
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      HIGH_PRIORITY_INTENTS: 1
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      RESTRICTION_FOR_SENSITIVE_CASE: 1
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      ALWAYS_TURN_ON_ALL_SKILLS: 0
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      LANGUAGE: EN
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      FALLBACK_FILE: fallbacks_dream_en.json
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  convers-evaluation-selector:
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    env_file: [ .env ]
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    build:
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      args:
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        TAG_BASED_SELECTION: 1
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        CALL_BY_NAME_PROBABILITY: 0.5
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        PROMPT_PROBA: 0.1
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        ACKNOWLEDGEMENT_PROBA: 0.3
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        PRIORITIZE_WITH_REQUIRED_ACT: 0
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        PRIORITIZE_NO_DIALOG_BREAKDOWN: 0
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        PRIORITIZE_WITH_SAME_TOPIC_ENTITY: 0
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        IGNORE_DISLIKED_SKILLS: 0
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        GREETING_FIRST: 1
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        RESTRICTION_FOR_SENSITIVE_CASE: 1
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        PRIORITIZE_PROMTS_WHEN_NO_SCRIPTS: 1
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        MAX_TURNS_WITHOUT_SCRIPTS: 7
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        ADD_ACKNOWLEDGMENTS_IF_POSSIBLE: 1
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        PRIORITIZE_SCRIPTED_SKILLS: 0
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        CONFIDENCE_STRENGTH: 0.8
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        CONV_EVAL_STRENGTH: 0.4
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        PRIORITIZE_HUMAN_INITIATIVE: 1
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        QUESTION_TO_QUESTION_DOWNSCORE_COEF: 0.8
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        LANGUAGE: EN
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        FALLBACK_FILE: fallbacks_dream_en.json
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      context: .
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      dockerfile: ./response_selectors/convers_evaluation_based_selector/Dockerfile
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    command: flask run -h 0.0.0.0 -p 8009
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    environment:
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      - FLASK_APP=server
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    deploy:
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      resources:
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        limits:
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          memory: 100M
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        reservations:
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          memory: 100M
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  gpt2-multilingual:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_PORT: 8132
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        SERVICE_NAME: gpt2_generator
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        CONFIG_NAME: mgpt.json
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        PRETRAINED_MODEL_NAME_OR_PATH: sberbank-ai/mGPT
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        N_HYPOTHESES_TO_GENERATE: 3
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        MAX_HISTORY_DEPTH: 3
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      context: ./services/gpt2_generator/
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    command: flask run -h 0.0.0.0 -p 8132
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    environment:
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      - CUDA_VISIBLE_DEVICES=0
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      - FLASK_APP=server
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    deploy:
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      resources:
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        limits:
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          memory: 6G
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        reservations:
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          memory: 6G
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  toxic-classification-multilingual:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_PORT: 8013
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        SERVICE_NAME: toxic_classification
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        PRETRAINED_MODEL_NAME_OR_PATH: https://github.com/unitaryai/detoxify/releases/download/v0.4-alpha/multilingual_debiased-0b549669.ckpt
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      context: ./annotators/MultilingualToxicClassification/
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    command: flask run -h 0.0.0.0 -p 8013
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    environment:
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      - CUDA_VISIBLE_DEVICES=0
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      - FLASK_APP=server
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    deploy:
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      resources:
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        limits:
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          memory: 3.5G
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        reservations:
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          memory: 3.5G
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  sentiment-classification-multilingual:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_PORT: 8024
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        SERVICE_NAME: sentiment_classification
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        PRETRAINED_MODEL_NAME_OR_PATH: cardiffnlp/twitter-xlm-roberta-base-sentiment
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      context: ./annotators/MultilingualSentimentClassification/
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    command: flask run -h 0.0.0.0 -p 8024
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    environment:
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      - CUDA_VISIBLE_DEVICES=0
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      - FLASK_APP=server
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    deploy:
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      resources:
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        limits:
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          memory: 3.5G
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        reservations:
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          memory: 3.5G
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  sentence-ranker-multilingual:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_PORT: 8128
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        PRETRAINED_MODEL_NAME_OR_PATH: DeepPavlov/bert-base-multilingual-cased-sentence
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      context: ./services/sentence_ranker/
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    command: flask run -h 0.0.0.0 -p 8128
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    environment:
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      - CUDA_VISIBLE_DEVICES=0
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      - FLASK_APP=server
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    deploy:
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      resources:
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        limits:
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          memory: 3G
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        reservations:
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          memory: 3G
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version: '3.7'
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