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Components Multilingual Version

Dream Architecture is presented in the following image: DREAM

Name Requirements Description
Rule Based Selector Algorithm that selects list of skills to generate candidate responses to the current context based on topics, entities, emotions, toxicity, dialogue acts and dialogue history
Response Selector 50 MB RAM Algorithm that selects a final responses among the given list of candidate responses

Annotators

Name Requirements Description
Sentiment Classification 2 GB RAM, 2 GB GPU classifies sentiment to positive, negative and neutral classes
Toxic Classification 3 GB RAM, 2 GB GPU classifies toxicity: identity_attack, insult, obscene, severe_toxicity, sexual_explicit, threat, toxicity
Sentence Ranker 2.5 GB RAM, 1.8 GB GPU for a pair of sentences predicts a floating point value. For multilingual version, return cosine similarity between embeddings from multilingual sentence BERT

Skills & Services

Name Requirements Description
GPT-2 Multilingual 5 GB RAM, 6.5 GB GPU GPT2-based generative model. For Multilingual distribution we propose mgpt by Sberbank from HugginFace

Papers

Alexa Prize 3

Kuratov Y. et al. DREAM technical report for the Alexa Prize 2019 //Alexa Prize Proceedings. – 2020.

Alexa Prize 4

Baymurzina D. et al. DREAM Technical Report for the Alexa Prize 4 //Alexa Prize Proceedings. – 2021.

License

DeepPavlov Dream is licensed under Apache 2.0.

Program-y (see dream/skills/dff_program_y_skill, dream/skills/dff_program_y_wide_skill, dream/skills/dff_program_y_dangerous_skill) is licensed under Apache 2.0. Eliza (see dream/skills/eliza) is licensed under MIT License.

Report creating

For making certification xlsx - file with bot responses, you can use xlsx_responder.py script by executing

docker-compose -f docker-compose.yml -f dev.yml exec -T -u $(id -u) agent python3 \
        utils/xlsx_responder.py --url http://0.0.0.0:4242 \
        --input 'tests/dream/test_questions.xlsx' \
        --output 'tests/dream/output/test_questions_output.xlsx'\
      --cache tests/dream/output/test_questions_output_$(date --iso-8601=seconds).json

Make sure all services are deployed. --input - xlsx file with certification questions, --output - xlsx file with bot responses, --cache - json, that contains a detailed markup and is used for a cache.