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| import gradio as gr | |
| import pickle | |
| import numpy as np | |
| from scipy.sparse import hstack | |
| from sklearn.feature_extraction.text import TfidfVectorizer | |
| from sklearn.linear_model import LogisticRegression | |
| # Load model and vectorizer | |
| try: | |
| # --- Load and inference code --- | |
| with open('password_model.pkl', 'rb') as f: | |
| model = pickle.load(f) | |
| with open('password_vectorizer.pkl', 'rb') as f: | |
| vectorizer = pickle.load(f) | |
| def extract_features(password): | |
| features = {} | |
| features['length'] = len(password) | |
| features['uppercase'] = sum(1 for c in password if c.isupper()) | |
| features['lowercase'] = sum(1 for c in password if c.islower()) | |
| features['digits'] = sum(1 for c in password if c.isdigit()) | |
| features['special'] = sum(1 for c in password if not c.isalnum()) | |
| return features | |
| def predict_password_strength(password, vectorizer, model): # Add vectorizer and model as arguments | |
| # Extract features from the input password | |
| features = extract_features(password) | |
| # Transform the input password using the trained vectorizer | |
| password_vectorized = vectorizer.transform([password]) | |
| password_vectorized = hstack((password_vectorized, np.array(list(features.values())).reshape(1, -1))) | |
| text="No password analyzed." | |
| # Make a prediction using the trained model | |
| prediction = model.predict(password_vectorized)[0] | |
| if prediction === 0: | |
| text = "Password is very weak." | |
| elif prediction === 1: | |
| text = "Password is weak." | |
| elif prediction === 2: | |
| text = "Password is average." | |
| elif prediction === 3: | |
| text = "Password is strong." | |
| elif prediction === 4: | |
| text = "Password is very strong." | |
| return password, prediction, text | |
| except Exception as e: | |
| return [[f"Error during prediction: {e}", "", ""]] | |
| demo = gr.Interface( | |
| fn=predict_password_strength, | |
| inputs=[gr.Textbox('Hello123', label='Password', info='The password to check the strength of', max_lines=1)], | |
| outputs=[ | |
| gr.Dataframe( | |
| row_count=(1, "fixed"), | |
| col_count=(3, "fixed"), | |
| headers=["Password", "Prediction", "Strength_Text"], | |
| label="Password Strength Analysis" | |
| ) | |
| ], | |
| title='Helix - Password Strength Analyzer', | |
| description='A password strength analyzer, trained on over 5 million different passwords.' | |
| ) | |
| demo.launch() |