update req

app.py

@@ -68,13 +68,18 @@ def main():
     if len(st.session_state['history']) == 0:
         if vector_store_is_outdated():
             docs = load_docs()
-            reordered_docs = reorder_embedding(docs)
-            vector_store = process_documents(reordered_docs)
-            save_vector_store(vector_store)
-        else:
-            vector_store = load_vector_store()
+            if len(docs) > 0:
+                reordered_docs = reorder_embedding(docs)
+                vector_store = process_documents(reordered_docs)
+                save_vector_store(vector_store)
+            else:
+                st.warning("Tidak ada dokumen ditemukan di folder 'data/'. Chatbot tetap bisa digunakan, tapi tanpa konteks dokumen.")
+                vector_store = None
+    else:
+        vector_store = load_vector_store()
+
+    st.session_state['vector_store'] = vector_store
 
-        st.session_state['vector_store'] = vector_store
 
     if st.session_state['vector_store'] is not None:
         chain = create_conversational_chain(st.session_state['vector_store'])

app/document_processor.py

@@ -27,6 +27,9 @@ def load_vector_store():
 
 
 def process_documents(docs):
+    if not docs:
+        raise ValueError("❌ Input 'docs' kosong. Tidak ada dokumen untuk diproses.")
+
     embeddings = HuggingFaceEmbeddings(
         model_name="LazarusNLP/all-indo-e5-small-v4",
         model_kwargs={"device": "cpu"}, 
@@ -38,7 +41,13 @@ def process_documents(docs):
         chunk_overlap=300
     )
     text_chunks = text_splitter.split_documents(docs)
+
+    if not text_chunks:
+        raise ValueError("❌ Split dokumen gagal. 'text_chunks' kosong setelah diproses.")
+
+    print(f"✅ {len(text_chunks)} text chunks berhasil diproses.")
+
     vector_store = FAISS.from_documents(text_chunks, embeddings)
-    
     return vector_store
 
+