| import gradio as gr | |
| import json | |
| import torch | |
| from typing import Optional | |
| from src.app.config import AppConfig | |
| from src.data_utils.config import TextProcessorConfig | |
| from src.data_utils.text_processor import TextProcessor | |
| class App: | |
| def __init__(self, config: AppConfig): | |
| self.config = config | |
| self.model: Optional[torch.nn.Module] = None | |
| self.text_processor: Optional[TextProcessor] = None | |
| self._load_model() | |
| self._load_text_processor() | |
| def _load_model(self): | |
| """ | |
| Load model with params from config | |
| """ | |
| with open(self.config.config_path, 'r') as f: | |
| config = json.load(f) | |
| model_type = config['model_type'] | |
| model_classes = { | |
| 'Transformer': 'TransformerClassifier', | |
| 'LSTM': 'LSTMClassifier', | |
| 'Mamba': 'MambaClassifier' | |
| } | |
| if model_type not in model_classes: | |
| raise ValueError(f"Unknown model type: {model_type}") | |
| module = __import__(f'src.models.models', fromlist=[model_classes[model_type]]) | |
| model_class = getattr(module, model_classes[model_type]) | |
| self.model = model_class(**config['model_params']) | |
| self.model.load_state_dict(torch.load(self.config.model_path)) | |
| self.model.eval() | |
| def _load_text_processor(self): | |
| with open(self.config.vocab_path, 'r') as f: | |
| vocab = json.load(f) | |
| processor_config = TextProcessorConfig( | |
| max_seq_len=self.config.max_seq_len, | |
| lowercase=True, | |
| remove_punct=False | |
| ) | |
| self.text_processor = TextProcessor( | |
| vocab=vocab, | |
| config=processor_config | |
| ) | |
| def predict(self, text: str) -> dict: | |
| """ | |
| Evaluating the tone of the text | |
| """ | |
| if not text.strip(): | |
| return {"Negative": 0.5, "Positive": 0.5} | |
| input_tensor = self.text_processor.text_to_tensor(text).unsqueeze(0) | |
| with torch.no_grad(): | |
| output = self.model(input_tensor) | |
| proba = torch.softmax(output, dim=1)[0].tolist() | |
| return {"Negative": proba[0], "Positive": proba[1]} | |
| def launch(self): | |
| """ | |
| Launch interface | |
| """ | |
| interface = gr.Interface( | |
| fn=self.predict, | |
| inputs=gr.Textbox(label="Enter your text"), | |
| outputs=gr.Label(label="Result"), | |
| title="Evaluating the tone of the text", | |
| examples=["Very good! Increadble! So fantastic", | |
| "Thw worst thing in the world!"] | |
| ) | |
| interface.launch( | |
| share=self.config.share, | |
| server_name=self.config.host, | |
| server_port=self.config.port | |
| ) | |