Update app.py

app.py

@@ -1,5 +1,5 @@
 # Import libraries
-import ollama
+from sentence_transformers import SentenceTransformer
 from PyPDF2 import PdfReader
 import tiktoken
 import groq
@@ -46,7 +46,8 @@ def chunk_text(text: str, max_tokens: int = 512) -> list:
 # == Embedding dengan Ollama ==
 def get_embedding(text: str):
     """Mendapatkan embedding dari teks menggunakan Ollama."""
-    embedding = ollama.embed(model="nomic-embed-text", input=text)
+    model = SentenceTransformer('all-MiniLM-L6-v2')
+    embedding = model.encode("This is a test sentence.")
     return np.array(embedding["embeddings"][0], dtype=np.float32)  # Pastikan mengambil list pertama
 
 # == Simpan Embedding ke FAISS ==