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00bd0c6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | import joblib
import numpy as np
import os
from sentence_transformers import SentenceTransformer
# Load trained model once at module import
CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
BACKEND_DIR = os.path.abspath(os.path.join(CURRENT_DIR, ".."))
MODEL_DIR = os.path.join(BACKEND_DIR, "models", "intent_classification")
classifier = joblib.load(os.path.join(MODEL_DIR, "intent_model2.pkl"))
id_to_label = joblib.load(os.path.join(MODEL_DIR, "id_to_label2.pkl"))
# Load model directly from HuggingFace
embedder = SentenceTransformer("all-MiniLM-L6-v2")
CONFIDENCE_THRESHOLD = 0.55
def classify_intent(text):
embedding = embedder.encode([text])
probs = classifier.predict_proba(embedding)[0]
pred_idx = np.argmax(probs)
confidence = float(probs[pred_idx])
label = id_to_label[pred_idx]
if confidence < CONFIDENCE_THRESHOLD:
return {
"status": "UNCERTAIN",
"label": label,
"confidence": confidence
}
return {
"status": "READY",
"label": label,
"confidence": confidence
}
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