code: def hello_milvus(host="127.0.0.1"):
      import time
  
      # create connection
      connections.connect(host=host, port="19530")
  
      print(f"\nList collections...")
      print(list_collections())
  
      # create collection
      dim = 128
      default_fields = [
          FieldSchema(
              name="int64", dtype=DataType.INT64, is_primary=True
          ),
          FieldSchema(name="float", dtype=DataType.FLOAT),
          FieldSchema(
              name="varchar", dtype=DataType.VARCHAR, max_length=65535
          ),
          FieldSchema(
              name="float_vector", dtype=DataType.FLOAT_VECTOR, dim=dim
          ),
      ]
      default_schema = CollectionSchema(
          fields=default_fields, description="test collection"
      )
  
      print(f"\nCreate collection...")
      collection = Collection(
          name="hello_milvus", schema=default_schema
      )
  
      print(f"\nList collections...")
      print(list_collections())
  
      #  insert data
      nb = 3000
      vectors = [
          [random.random() for _ in range(dim)] for _ in range(nb)
      ]
      t0 = time.time()
      collection.insert(
          [
              [i for i in range(nb)],
              [np.float32(i) for i in range(nb)],
              [str(i) for i in range(nb)],
              vectors,
          ]
      )
      t1 = time.time()
      print(f"\nInsert {nb} vectors cost {t1 - t0:.4f} seconds")
  
      t0 = time.time()
      print(f"\nGet collection entities...")
      collection.flush()
      print(collection.num_entities)
      t1 = time.time()
      print(f"\nGet collection entities cost {t1 - t0:.4f} seconds")
  
      print("\nGet replicas number")
      try:
          replicas_info = collection.get_replicas()
          replica_number = len(replicas_info.groups)
          print(f"\nReplicas number is {replica_number}")
      except Exception as e:
          print(str(e))
          replica_number = 1
  
      # create index and load table
      default_index = {
          "index_type": "IVF_SQ8",
          "metric_type": "L2",
          "params": {"nlist": 64},
      }
      print(f"\nCreate index...")
      t0 = time.time()
  
      collection.release()
  
      collection.create_index(
          field_name="float_vector", index_params=default_index
      )
      t1 = time.time()
      print(f"\nCreate index cost {t1 - t0:.4f} seconds")
      print(f"\nload collection...")
      t0 = time.time()
      collection.load(replica_number=replica_number)
      t1 = time.time()
      print(f"\nload collection cost {t1 - t0:.4f} seconds")
  
      # load and search
      topK = 5
      search_params = {"metric_type": "L2", "params": {"nprobe": 10}}
      t0 = time.time()
      print(f"\nSearch...")
      # define output_fields of search result
      res = collection.search(
          vectors[-2:],
          "float_vector",
          search_params,
          topK,
          "int64 > 100",
          output_fields=["int64", "float"],
          timeout=TIMEOUT,
      )
      t1 = time.time()
      print(f"search cost  {t1 - t0:.4f} seconds")
      # show result
      for hits in res:
          for hit in hits:
              # Get value of the random value field for search result
              print(hit, hit.entity.get("float"))
  
      # query
      expr = "int64 in [2,4,6,8]"
      output_fields = ["int64", "float"]
      res = collection.query(expr, output_fields, timeout=TIMEOUT)
      sorted_res = sorted(res, key=lambda k: k["int64"])
      for r in sorted_res:
          print(r)
  
imports: import random
  import numpy
  import time
  import argparse
  from pymilvus import connections, list_collections, FieldSchema, CollectionSchema, DataType, Collection
label_desc: Use image node_id 1 for calling a global function with example usage: hello_milvus(host) without return types