From dfa909019804011390dd74249bf3680a1803abe0 Mon Sep 17 00:00:00 2001
From: Dita Aji Pratama <ditaajipratama@protonmail.com>
Date: Tue, 7 Jul 2026 05:13:49 +0700
Subject: [PATCH] Updating

---
 config.py                   |  5 +++--
 memories_semantic_search.py | 28 ++++++++++------------------
 memories_test.py            |  6 +++---
 table_create.py             | 23 ++---------------------
 table_modify.py             |  8 ++++----
 5 files changed, 22 insertions(+), 48 deletions(-)

diff --git a/config.py b/config.py
index 654fe21..9bc0e8d 100644
--- a/config.py
+++ b/config.py
@@ -1,5 +1,6 @@
 model_url             = "http://localhost:11434/api/embed"
 model_name            = "nomic-embed-text"
-memories_db_path      = "./memories"
-memories_table        = "knowledge_stories"
+
+memories_db_path      = "./ragroleplay"
 memories_vector_size  = 768
+
diff --git a/memories_semantic_search.py b/memories_semantic_search.py
index 46b3740..aab946f 100644
--- a/memories_semantic_search.py
+++ b/memories_semantic_search.py
@@ -1,28 +1,22 @@
 import gc, sys, lancedb
-import config, embedding
+import config, lib.ragroleplay as ragroleplay
 
-def main():
+def memories_check(question, search_limit):
     db = lancedb.connect(config.memories_db_path)
-    table = db.open_table(config.memories_table)
-    question = sys.argv[1]
-    query_vector = embedding.embed_text(config.model_url, config.model_name, question)
+    table = db.open_table("knowledge_memories")
+    query_vector = ragroleplay.embed_text(config.model_url, config.model_name, question)
+    results = table.search(query_vector, vector_column_name="vector_context").limit(search_limit).to_list()
 
-    results = (
-        table.search(query_vector, vector_column_name="vector_context")
-        .limit(3)
-        .to_list()
-    )
-
-    print("\n" + "=" * 60)
+    print("")
     print(f"Pertanyaan: {question}")
-    print("=" * 60)
+    print("")
 
     if not results:
         print("Tidak ada memori yang ditemukan.")
     else:
         print(f"Ditemukan {len(results)} memori yang relevan berdasarkan KONTEKS:\n")
         for i, row in enumerate(results, 1):
-            print(f"--- Memori #{i} ---")
+            print(f"Memori #{i}")
             print(f"Kapan: {row['relative_time']}")
             print(f"Kejadian: {row['event']}")
             print(f"Detail: {row['detail']}")
@@ -30,13 +24,11 @@ def main():
             print(f"Emosi: {row['emotional']}")
             print(f"Kategori: {row['category']}")
             print(f"Skor Jarak: {row.get('_distance', 'N/A')}")
-            print("-" * 30)
-
-    print("=" * 60)
+            print("")
 
     del table
     del db
     gc.collect()
 
 if __name__ == "__main__":
-    main()
+    memories_check(sys.argv[1], 3)
diff --git a/memories_test.py b/memories_test.py
index 911d61a..ddf3a99 100644
--- a/memories_test.py
+++ b/memories_test.py
@@ -1,6 +1,6 @@
-import config, embedding
-text = "Saya lupa password di HRIS AFMS2"
-vector = embedding.embed_text(config.model_url, config.model_name, text)
+import config, lib.ragroleplay as ragroleplay
+text = "Saya lupa password"
+vector = ragroleplay.embed_text(config.model_url, config.model_name, text)
 print("Text:")
 print(text)
 print("Vector:")
diff --git a/table_create.py b/table_create.py
index 7310bcb..6a3b8cb 100644
--- a/table_create.py
+++ b/table_create.py
@@ -1,23 +1,4 @@
-import gc, lancedb, pyarrow
-import config
-
-def main():
-    db = lancedb.connect(config.memories_db_path)
-    schema = pyarrow.schema([
-        pyarrow.field('id',              pyarrow.uuid(),           metadata={'description': 'Unique identifier (UUID)'}),
-        pyarrow.field('timestamp',       pyarrow.timestamp('ms'),  metadata={'description': 'When record created'}),
-        pyarrow.field('relative_time',   pyarrow.string(),         metadata={'description': 'Explaining when it happen'}),
-        pyarrow.field('event',           pyarrow.string(),         metadata={'description': 'What event'}),
-        pyarrow.field('category',        pyarrow.string(),         metadata={'description': 'Event category'}),
-        pyarrow.field('detail',          pyarrow.string(),         metadata={'description': 'Event detail'}),
-        pyarrow.field('physical',        pyarrow.string(),         metadata={'description': 'Character physical state'}),
-        pyarrow.field('emotional',       pyarrow.string(),         metadata={'description': 'Character emotional state'}),
-        pyarrow.field('vector_context',  pyarrow.list_(pyarrow.float32(), config.memories_vector_size)),
-    ])
-    db.create_table(config.memories_table, schema=schema)
-    print(f'Table "{config.memories_table}" berhasil diproses.')
-    del db
-    gc.collect()
+import config, lib.ragroleplay as ragroleplay
 
 if __name__ == "__main__":
-    main()
+    ragroleplay.create_table(config.memories_db_path, config.memories_vector_size)
diff --git a/table_modify.py b/table_modify.py
index ed2fd17..fcb4f86 100644
--- a/table_modify.py
+++ b/table_modify.py
@@ -1,10 +1,10 @@
 import gc, lancedb, uuid
 from datetime import datetime, timedelta
-import config, embedding
+import config, lib.ragroleplay as ragroleplay
  
 def main():
     db = lancedb.connect(config.memories_db_path)
-    table = db.open_table(config.memories_table)
+    table = db.open_table("knowledge_memories")
     now = datetime.now()
 
     memories = [
@@ -121,13 +121,13 @@ def main():
             "detail": mem["detail"],
             "physical": mem["physical"],
             "emotional": mem["emotional"],
-            "vector_context": embedding.embed_text(config.model_url, config.model_name, context_text),
+            "vector_context": ragroleplay.embed_text(config.model_url, config.model_name, context_text),
         }
         table.add([row])
         print(f"Menambahkan memori: {mem['event']}")
 
     print("\nTable memori roleplaying dengan vector_context berhasil diproses.")
-    print("Nama table:", config.memories_table)
+    print("Nama table: knowledge_memories")
     print("Jumlah row:", table.count_rows())
 
     del table