Update app.py

app.py

@@ -1,11 +1,65 @@
 import gradio as gr
+from sentence_transformers import SentenceTransformer, util
+import faiss
+import os
+import pickle
 
-def placeholder(query):
-    return "LifeSync Lite is initializing..."
+MODEL_NAME = "sentence-transformers/all-MiniLM-L6-v2"
+model = SentenceTransformer(MODEL_NAME)
 
-iface = gr.Interface(fn=placeholder,
-                     inputs="text",
-                     outputs="text",
-                     title="LifeSync Lite (Promptless Search)",
-                     description="Upload snippets, notes, or files—search coming soon.")
-iface.launch()
+INDEX_FILE = "vector_store.index"
+TEXT_FILE = "texts.pkl"
+
+# --- helper: load / save index ----
+def load_index():
+    if os.path.exists(INDEX_FILE) and os.path.exists(TEXT_FILE):
+        index = faiss.read_index(INDEX_FILE)
+        with open(TEXT_FILE, "rb") as f:
+            texts = pickle.load(f)
+    else:
+        index = faiss.IndexFlatIP(model.get_sentence_embedding_dimension())
+        texts = []
+    return index, texts
+
+def save_index(index, texts):
+    faiss.write_index(index, INDEX_FILE)
+    with open(TEXT_FILE, "wb") as f:
+        pickle.dump(texts, f)
+
+# --- core logic ----
+def add_text(docs):
+    index, texts = load_index()
+    embeddings = model.encode(docs, normalize_embeddings=True)
+    index.add(embeddings)
+    texts.extend(docs)
+    save_index(index, texts)
+    return f"✅ Added {len(docs)} snippet(s) to memory."
+
+def search(query):
+    index, texts = load_index()
+    if len(texts) == 0:
+        return "🪣 Memory empty — add some snippets first."
+    q_emb = model.encode([query], normalize_embeddings=True)
+    scores, ids = index.search(q_emb, 5)
+    results = []
+    for i, s in zip(ids[0], scores[0]):
+        if i < len(texts):
+            results.append(f"• {texts[i]}  (score {round(float(s),3)})")
+    return "\n\n".join(results)
+
+with gr.Blocks(title="LifeSync Lite") as demo:
+    gr.Markdown("## 🧠 LifeSync Lite — Promptless Search\nUpload or paste your notes, then ask natural-language questions.")
+
+    with gr.Tab("Add"):
+        docs_box = gr.Textbox(lines=6, label="Paste notes or text")
+        add_btn = gr.Button("Add to Memory")
+        add_out = gr.Textbox(label="Status")
+        add_btn.click(add_text, inputs=[docs_box], outputs=[add_out])
+
+    with gr.Tab("Search"):
+        query_box = gr.Textbox(lines=2, label="Ask something")
+        search_btn = gr.Button("Search Memory")
+        search_out = gr.Textbox(label="Results")
+        search_btn.click(search, inputs=[query_box], outputs=[search_out])
+
+demo.launch()