Create summarizer.py

summarizer.py

@@ -0,0 +1,27 @@
+from sentence_transformers import SentenceTransformer, util
+import json, os
+
+class MemorySummarizer:
+    def __init__(self, memory_path="semantic_memory.json"):
+        self.memory_path = memory_path
+        self.model = SentenceTransformer("all-MiniLM-L6-v2")
+
+    def summarize(self):
+        if not os.path.exists(self.memory_path):
+            return "No stored memories yet."
+
+        with open(self.memory_path, "r") as f:
+            data = json.load(f)
+
+        memories = [d["text"] for d in data]
+        if not memories:
+            return "Memory empty."
+
+        joined = " ".join(memories)
+        sentences = [s.strip() for s in joined.split(".") if s.strip()]
+        embeddings = self.model.encode(sentences)
+        clusters = util.paraphrase_mining_embeddings(embeddings)
+
+        key_lines = [sentences[i] for (score, i, j) in clusters if score > 0.6][:5]
+        summary = "Here’s what I know about you:\n- " + "\n- ".join(key_lines)
+        return summary