| from pymongo import MongoClient | |
| import certifi | |
| MONGO_URI = "mongodb+srv://bolorjinbat04_db_user:B221960018@cluster0.zkqt5pp.mongodb.net/?appName=Cluster0" | |
| mongo_client = MongoClient( | |
| MONGO_URI, | |
| tls=True, | |
| tlsCAFile=certifi.where(), # Atlas SSL сертификатыг шалгах | |
| ) | |
| mongo_db = mongo_client["database"] # өөрийн DB нэр | |
| mongo_col = mongo_db["data_rag"] # өөрийн collection нэр | |
| batch = [] | |
| BATCH_SIZE = 1000 | |
| for doc in mongo_col.find({}): | |
| emb = doc["embedding"] # [128] хэмжээтэй list | |
| # MaxSim multivector тул нэг вектороо list дотор хийж байна: [[128]] | |
| multi_emb = [emb] | |
| point = models.PointStruct( | |
| id=str(doc["_id"]), # ObjectId → string | |
| vector=multi_emb, # multivector | |
| payload={ | |
| "law_name": doc.get("law_name"), | |
| "num": doc.get("num"), | |
| "header": doc.get("header"), | |
| "content": doc.get("content"), | |
| }, | |
| ) | |
| batch.append(point) | |
| if len(batch) >= BATCH_SIZE: | |
| client.upsert(collection_name="data_rag", points=batch) | |
| batch = [] | |
| # сүүлчийн batch | |
| if batch: | |
| client.upsert(collection_name="data_rag", points=batch) | |