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/pipeline_conf.json'
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    environment:
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      WAIT_HOSTS: "sentseg:8011, ranking-based-response-selector:8002,
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          dff-intent-responder-skill:8012, intent-catcher-commands:8014, ner:8021,
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          combined-classification:8087, entity-detection:8103, dff-command-selector-skill:8148,
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          sentence-ranker:8128, prompt-selector:8135, openai-api-chatgpt:8145,
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          dff-dream-persona-chatgpt-prompted-skill:8137,
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          openai-api-chatgpt-16k:8167"
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      WAIT_HOSTS_TIMEOUT: ${WAIT_TIMEOUT:-1000}
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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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  ranking-based-response-selector:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_PORT: 8002
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        SERVICE_NAME: response_selector
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        LANGUAGE: EN
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        SENTENCE_RANKER_ANNOTATION_NAME: sentence_ranker
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        SENTENCE_RANKER_SERVICE_URL: http://sentence-ranker:8128/respond
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        SENTENCE_RANKER_TIMEOUT: 3
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        N_UTTERANCES_CONTEXT: 5
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        FILTER_TOXIC_OR_BADLISTED: 1
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        FALLBACK_FILE: fallbacks_dream_en.json
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      context: .
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      dockerfile: ./response_selectors/ranking_based_response_selector/Dockerfile
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    command: flask run -h 0.0.0.0 -p 8002
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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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  sentseg:
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    env_file: [ .env ]
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    build:
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      context: ./annotators/SentSeg/
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    command: flask run -h 0.0.0.0 -p 8011
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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: 1.5G
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        reservations:
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          memory: 1.5G
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  dff-intent-responder-skill:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_PORT: 8012
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        SERVICE_NAME: dff_intent_responder_skill
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        INTENT_RESPONSE_PHRASES_FNAME: intent_response_phrases.json
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      context: .
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      dockerfile: ./skills/dff_intent_responder_skill/Dockerfile
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    command: gunicorn --workers=1 server:app -b 0.0.0.0:8012 --reload
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    deploy:
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      resources:
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        limits:
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          memory: 128M
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        reservations:
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          memory: 128M
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  dff-command-selector-skill:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_PORT: 8148
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        SERVICE_NAME: dff_command_selector_skill
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        LANGUAGE: EN
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        ROS_FSM_SERVER: http://robot-fake-server:8038
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      context: .
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      dockerfile: ./skills/dff_command_selector_skill/Dockerfile
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    command: gunicorn --workers=1 server:app -b 0.0.0.0:8148 --reload
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    deploy:
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      resources:
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        limits:
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          memory: 128M
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        reservations:
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          memory: 128M
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  intent-catcher-commands:
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    env_file: [ .env ]
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    build:
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      context: .
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      dockerfile: ./annotators/IntentCatcherTransformers/Dockerfile
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      args:
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        SERVICE_PORT: 8014
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        CONFIG_NAME: intents_model_dp_config_commands.json
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        INTENT_PHRASES_PATH: intent_phrases_commands.json
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    command: python -m flask run -h 0.0.0.0 -p 8014
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    environment:
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      - FLASK_APP=server
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      - CUDA_VISIBLE_DEVICES=0
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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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  ner:
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    env_file: [ .env ]
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    build:
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      args:
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        CONFIG: ner_case_agnostic_multilingual_bert_base_extended.json
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        SERVICE_PORT: 8021
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        SRC_DIR: annotators/NER_deeppavlov
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        COMMIT: f5117cd9ad1e64f6c2d970ecaa42fc09ccb23144
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      context: ./
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      dockerfile: annotators/NER_deeppavlov/Dockerfile
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    command: flask run -h 0.0.0.0 -p 8021
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    environment:
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      - FLASK_APP=server
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      - CUDA_VISIBLE_DEVICES=0
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    tty: true
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    deploy:
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      resources:
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        limits:
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          memory: 2G
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        reservations:
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          memory: 2G
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  combined-classification:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_PORT: 8087
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        SERVICE_NAME: combined_classification
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        CONFIG: combined_classifier.json
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      context: .
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      dockerfile: ./annotators/combined_classification/Dockerfile
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    command: gunicorn --workers=1 server:app -b 0.0.0.0:8087 --timeout 600
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    environment:
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      - CUDA_VISIBLE_DEVICES=0
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    deploy:
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      resources:
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        limits:
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          memory: 2G
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        reservations:
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          memory: 2G
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  entity-detection:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_NAME: entity_detection
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        SEQ_TAG_CONFIG: wikipedia_entity_detection_distilbert.json
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        CONFIG: entity_detection_eng.json
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        LOWERCASE: 1
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        SERVICE_PORT: 8103
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        SRC_DIR: annotators/entity_detection/
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        FINEGRAINED: 0
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      context: ./
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      dockerfile: annotators/entity_detection/Dockerfile
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    command: flask run -h 0.0.0.0 -p 8103
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    environment:
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      - FLASK_APP=server
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      - CUDA_VISIBLE_DEVICES=0
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    deploy:
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      resources:
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        limits:
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          memory: 2.5G
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        reservations:
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          memory: 2.5G
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  prompt-selector:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_PORT: 8135
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        SERVICE_NAME: prompt_selector
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        SENTENCE_RANKER_SERVICE_URL: http://sentence-ranker:8128/respond
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        N_SENTENCES_TO_RETURN: 3
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        PROMPTS_TO_CONSIDER: dream_persona,dream_faq
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      context: .
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      dockerfile: ./annotators/prompt_selector/Dockerfile
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    command: flask run -h 0.0.0.0 -p 8135
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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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  sentence-ranker:
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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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        SERVICE_NAME: sentence_ranker
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        PRETRAINED_MODEL_NAME_OR_PATH: sentence-transformers/all-MiniLM-L6-v2
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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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  openai-api-chatgpt:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_PORT: 8145
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        SERVICE_NAME: openai_api_chatgpt
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        PRETRAINED_MODEL_NAME_OR_PATH: gpt-3.5-turbo
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      context: .
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      dockerfile: ./services/openai_api_lm/Dockerfile
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    command: flask run -h 0.0.0.0 -p 8145
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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: 500M
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        reservations:
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          memory: 100M
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  dff-dream-persona-chatgpt-prompted-skill:
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    env_file: [ .env,.env_secret ]
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    build:
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      args:
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        SERVICE_PORT: 8137
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        SERVICE_NAME: dff_dream_persona_prompted_skill
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        PROMPT_FILE: common/prompts/dream_persona.json
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        GENERATIVE_SERVICE_URL: http://openai-api-chatgpt:8145/respond
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        GENERATIVE_SERVICE_CONFIG: openai-chatgpt.json
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        GENERATIVE_TIMEOUT: 120
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        N_UTTERANCES_CONTEXT: 7
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        ENVVARS_TO_SEND: OPENAI_API_KEY,OPENAI_ORGANIZATION
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      context: .
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      dockerfile: ./skills/dff_template_prompted_skill/Dockerfile
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    deploy:
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      resources:
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        limits:
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          memory: 128M
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        reservations:
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          memory: 128M
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  dff-google-api-skill:
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    env_file: [ .env,.env_secret ]
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    build:
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      args:
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        SERVICE_PORT: 8162
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        SERVICE_NAME: dff_google_api_skill
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        ENVVARS_TO_SEND: OPENAI_API_KEY,GOOGLE_CSE_ID,GOOGLE_API_KEY
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      context: .
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      dockerfile: ./skills/dff_google_api_skill/Dockerfile
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    deploy:
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      resources:
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        limits:
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          memory: 128M
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        reservations:
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          memory: 128M
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  openai-api-chatgpt-16k:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_PORT: 8167
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        SERVICE_NAME: openai_api_chatgpt_16k
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        PRETRAINED_MODEL_NAME_OR_PATH: gpt-3.5-turbo-16k
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      context: .
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      dockerfile: ./services/openai_api_lm/Dockerfile
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    command: flask run -h 0.0.0.0 -p 8167
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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: 500M
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        reservations:
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          memory: 100M
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  robot-command-sender:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_PORT: 8035
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        ROS_FSM_SERVER: http://robot-fake-server:8038
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      context: .
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      dockerfile: ./services/robot_command_sender/Dockerfile
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    command: flask run -h 0.0.0.0 -p 8035
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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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  robot-notifications:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_PORT: 8036
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        ROS_FSM_SERVER: http://robot-fake-server:8038
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      context: .
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      dockerfile: ./services/robot_notifications/Dockerfile
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    command: flask run -h 0.0.0.0 -p 8036
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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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  robot-fake-server:
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    env_file: [ .env ]
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    build:
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      args:
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        SERVICE_PORT: 8038
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      context: .
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      dockerfile: ./services/robot_fake_server/Dockerfile
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    command: flask run -h 0.0.0.0 -p 8038
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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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version: '3.7'
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