Create search/semantic.py

search/semantic.py

@@ -0,0 +1,23 @@
+from typing import List, Dict
+import faiss
+import numpy as np
+from sentence_transformers import SentenceTransformer
+
+MODEL_NAME = "sentence-transformers/all-MiniLM-L6-v2"
+
+class SemanticIndex:
+    def __init__(self, documents: List[Dict]):
+        self.model = SentenceTransformer(MODEL_NAME)
+        self.texts = [d["text"] for d in documents]
+        self.meta = documents
+
+        embeddings = self.model.encode(self.texts, show_progress_bar=False)
+        self.embeddings = np.array(embeddings).astype("float32")
+
+        self.index = faiss.IndexFlatL2(self.embeddings.shape[1])
+        self.index.add(self.embeddings)
+
+    def search(self, query: str, k: int = 5) -> List[Dict]:
+        q = self.model.encode([query]).astype("float32")
+        _, indices = self.index.search(q, k)
+        return [self.meta[i] for i in indices[0]]