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| from llmware.models import ModelCatalog | |
| from llmware.prompts import Prompt | |
| def classify_sentiment(text): | |
| sentiment_model = ModelCatalog().load_model("slim-sentiment-tool") | |
| response_sentiment = sentiment_model.function_call(text, get_logits=False) | |
| return response_sentiment | |
| def detect_emotions(text): | |
| emotions_model = ModelCatalog().load_model("slim-emotions-tool") | |
| response_emotions = emotions_model.function_call(text, get_logits=False) | |
| return response_emotions | |
| def generate_tags(text): | |
| tags_model = ModelCatalog().load_model("slim-tags-tool") | |
| response_tags = tags_model.function_call(text, get_logits=False) | |
| return response_tags | |
| def identify_topics(text): | |
| topics_model = ModelCatalog().load_model("slim-topics-tool") | |
| response_topics = topics_model.function_call(text, get_logits=False) | |
| return response_topics | |
| def perform_intent(text): | |
| intent_model = ModelCatalog().load_model("slim-intent-tool") | |
| response_intent = intent_model.function_call(text) | |
| return response_intent | |
| def get_ratings(text): | |
| ratings_model = ModelCatalog().load_model("slim-ratings-tool") | |
| response_ratings = ratings_model.function_call(text) | |
| return response_ratings | |
| def get_category(text): | |
| category_model = ModelCatalog().load_model("slim-category-tool") | |
| response_category = category_model.function_call(text) | |
| return response_category | |
| def perform_ner(text): | |
| ner_model = ModelCatalog().load_model("slim-ner-tool") | |
| response_ner = ner_model.function_call(text) | |
| return response_ner | |
| def perform_nli(text): | |
| nli_model = ModelCatalog().load_model("slim-nli-tool") | |
| response_nli = nli_model.function_call(text) | |
| return response_nli |