rag_server/applications/utils/milvus/collection.py

# from pymilvus import connections, CollectionSchema, Collection
# from applications.utils.milvus.field import fields
# from applications.config import MILVUS_CONFIG
#
#
# connections.connect("default", **MILVUS_CONFIG)
#
# schema = CollectionSchema(
#     fields, description="Chunk multi-vector embeddings with metadata"
# )
# milvus_collection = Collection(name="chunk_multi_embeddings_v2", schema=schema)
#
# # create index
# vector_index_params = {
#     "index_type": "IVF_FLAT",
#     "metric_type": "COSINE",
#     "params": {"M": 16, "efConstruction": 200},
# }
#
# milvus_collection.create_index("vector_text", vector_index_params)
# milvus_collection.create_index("vector_summary", vector_index_params)
# milvus_collection.create_index("vector_questions", vector_index_params)
#
# milvus_collection.load()
#
# __all__ = ["milvus_collection"]