builds properly

build/lib/services/huggingface_ai_service.py

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+from services.ai_service import AIService
+from transformers import pipeline
+
+# These functions are just intended for testing, not production use. If you'd like to use HuggingFace, you should use your own models, or do some research into the specific models that will work best for your use case.
+class HuggingFaceAIService(AIService):
+    def __init__(self):
+        super().__init__()
+
+    def run_text_sentiment(self, sentence):
+        classifier = pipeline("sentiment-analysis")
+        return classifier(sentence)
+
+    # available models at https://huggingface.co/Helsinki-NLP (**not all models use 2-character language codes**)
+    def run_text_translation(self, sentence, source_language, target_language):
+        translator = pipeline(f"translation", model=f"Helsinki-NLP/opus-mt-{source_language}-{target_language}")
+        print(translator(sentence))
+
+        return translator(sentence)[0]["translation_text"]
+
+    def run_text_summarization(self, sentence):
+        summarizer = pipeline("summarization")
+        return summarizer(sentence)
+
+    def run_image_classification(self, image_path):
+        classifier = pipeline("image-classification")
+        return classifier(image_path)