Upload interface.py

interface.py

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+# inference.py
+import joblib
+from sentence_transformers import SentenceTransformer
+import numpy as np
+
+# -----------------------------
+# Load model + embedder at container startup
+# -----------------------------
+MODEL_FILENAME = "/Users/mazamessomeba/Desktop/Projects/Soulprint_snapshot/kinara-regression/Kinara_xgb_model.pkl"  # change per repo
+model = joblib.load(MODEL_FILENAME)
+embedder = SentenceTransformer("all-mpnet-base-v2")
+
+# -----------------------------
+# Hugging Face Inference API entrypoint
+# -----------------------------
+def predict(inputs: dict) -> dict:
+    """
+    Expected input:
+    {
+        "text": "During a heated family argument, I stayed calm and reminded everyone of our values."
+    }
+
+    Returns:
+    {
+        "score": 0.752
+    }
+    """
+    if "text" not in inputs:
+        return {"error": "Missing required field 'text'"}
+
+    text = inputs["text"]
+
+    # Convert text to embedding
+    embedding = embedder.encode([text])
+
+    # Predict with model
+    score = model.predict(embedding)[0]
+
+    # Ensure it's a float for JSON serialization
+    return {"score": float(score)}