from pymilvus import connections, FieldSchema, CollectionSchema, DataType, Collection,MilvusClient
from config import MILVUS_CLIENT
import time
from datetime import datetime, timedelta

def create_partition_by_hour(current_hour):
    # 连接到 Milvus 服务器
    connections.connect("default",uri=MILVUS_CLIENT)
    # 获取集合
    collection_name = "pdf_measure_v4"
    collection = Collection(collection_name)

    # 创建当前小时的分区
    partition_name = f"partition_{current_hour}"
    if not collection.has_partition(partition_name):
        collection.create_partition(partition_name)
        print(f"Created partition: {partition_name}")
        partition = collection.partition(partition_name)
        partition.load()

    # 获取所有分区
    partitions = collection.partitions
    # 删除所有分区（除了默认分区和当前分区）
    for partition in partitions:
        name = partition.name
        if name not in ["_default", partition_name]:  # 保留默认分区
            pre_partition = collection.partition(name)
            pre_partition.release()
            collection.drop_partition(name)
            print(f"Partition '{name}' deleted.")






from pymilvus import connections, CollectionSchema, Collection,utility,FieldSchema,DataType
# 连接到 B 服务器上的 Milvus
# connections.connect(host='124.70.129.232', port='19530')# 测试服务器
connections.connect(host='127.0.0.1', port='19530')# 测试服务器
# # 获取集合列表
utility.drop_collection("pdf_measure_v4")

# 定义字段
fields = [
    FieldSchema(name="id", dtype=DataType.INT64, is_primary=True, auto_id=True),
    FieldSchema(name="vector", dtype=DataType.FLOAT_VECTOR, dim=1536),
    FieldSchema(name="table_num", dtype=DataType.INT16),
    FieldSchema(name="table_index", dtype=DataType.INT16),
    FieldSchema(name="measure_name", dtype=DataType.VARCHAR, max_length=200),
    FieldSchema(name="measure_value", dtype=DataType.VARCHAR, max_length=200),
    FieldSchema(name="file_id", dtype=DataType.VARCHAR, max_length=200),
    FieldSchema(name="measure_unit", dtype=DataType.VARCHAR, max_length=200)
]

# 定义集合的 schema
schema = CollectionSchema(fields=fields, description="My Milvus collection")

# 创建集合
collection = Collection(name="pdf_measure_v4", schema=schema)

collection = Collection("pdf_measure_v4")
index_params = {
    "index_type": "IVF_FLAT",
    "metric_type": "COSINE",
    "params": {"nlist": 128}
}
collection.create_index(field_name="vector", index_params=index_params)
collection.load()