in skills/retrieval_augmented_generation/evaluation/vectordb.py [0:0]
def load_data(self, data):
if self.embeddings and self.metadata:
print("Vector database is already loaded. Skipping data loading.")
return
if os.path.exists(self.db_path):
print("Loading vector database from disk.")
self.load_db()
return
texts = [f"Heading: {item['chunk_heading']}\n\n Chunk Text:{item['text']}" for item in data]
self._embed_and_store(texts, data)
self.save_db()
print("Vector database loaded and saved.")