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| from sklearn.mixture import GaussianMixture | |
| import pickle | |
| def build_gmm_clusters(embeddings, n_clusters=12): | |
| gmm = GaussianMixture( | |
| n_components=n_clusters, | |
| covariance_type="full", | |
| random_state=42 | |
| ) | |
| gmm.fit(embeddings) | |
| cluster_probs = gmm.predict_proba(embeddings) | |
| return gmm, cluster_probs | |
| def save_gmm_model(gmm, path="models/gmm_model.pkl"): | |
| with open(path, "wb") as f: | |
| pickle.dump(gmm, f) | |
| def load_gmm_model(path="models/gmm_model.pkl"): | |
| with open(path, "rb") as f: | |
| return pickle.load(f) |