| import gradio as gr | |
| from transformers import AutoTokenizer | |
| from transformers.utils import logging as hf_logging | |
| from configuration import Config | |
| from onnx_model import ONNXModel | |
| from postprocess import get_sentiment | |
| from theme import theme | |
| from utils import download_model | |
| hf_logging.disable_progress_bar() | |
| config = Config() | |
| model_path = download_model("ml-sentiment-adapter", "production") | |
| model = ONNXModel.from_dir(model_path) | |
| tokenizer = AutoTokenizer.from_pretrained(model.model_info.base_model) | |
| def predict(sentence: str): | |
| encoding = tokenizer([sentence], truncation=True, return_tensors="np") | |
| logits = model(**encoding) | |
| score, sentiment = get_sentiment(logits, config.negative_threshold, config.positive_threshold, config.zero) | |
| result = { | |
| sentiment: score | |
| } | |
| return result | |
| demo = gr.Interface( | |
| fn=predict, | |
| inputs=gr.Textbox(label="Customer Review", value="Lettria truelly handled all the overhead of a NLP project !"), | |
| outputs=gr.Label(label="Sentiment Level"), | |
| title="Lettria's Customer Sentiment Analysis", | |
| description="Introducing our Sentiment Analysis API powered by Deep Learning! It provides an easy-to-use solution for analyzing and understanding the sentiment expressed in text. With this API, you can gain valuable insights from customer feedback, social media posts, and reviews by accurately classifying text into positive, negative, or neutral sentiment categories. Seamlessly integrate it into your applications to make data-driven decisions, monitor brand reputation, and enhance customer satisfaction in real-time. Uncover the true sentiment behind text and unlock the power of sentiment analysis today!", | |
| examples=[ | |
| "I absolutely loved the movie! The storyline was captivating, and the acting was superb.", | |
| "I'm extremely disappointed with the quality of the product. It broke within a week of use.", | |
| "Today has been an average day. Nothing particularly good or bad happened.", | |
| "This book is a masterpiece. The author's writing style is brilliant, and the characters are well-developed.", | |
| "I'm feeling neutral about the new restaurant. The ambiance was nice, but the food was mediocre.", | |
| ], | |
| theme=theme, | |
| allow_flagging="never", | |
| ) | |
| demo.launch() |