Create core/vector.py

core/vector.py

@@ -0,0 +1,11 @@
+import numpy as np
+import re
+
+DIM = 512
+
+def embed(text: str) -> np.ndarray:
+    v = np.zeros(DIM, dtype=np.float32)
+    for w in re.findall(r"[a-zA-Z]{2,}", text.lower()):
+        v[hash(w) % DIM] += 1.0
+    n = np.linalg.norm(v)
+    return v / n if n > 0 else v