embedding = OpenAIEmbeddings()
        # Connect to a Zilliz instance
        milvus_store = Milvus(
            embedding_function = embedding,
            collection_name = "LangChainCollection",
            connection_args = {
                "uri": "https://in03-ba4234asae.api.gcp-us-west1.zillizcloud.com",
                "user": "temp",
                "password": "temp",
                "token": "temp", # API key as replacements for user and password
                "secure": True
            }
            drop_old: True,
        )
    Raises:
        ValueError: If the pymilvus python package is not installed.
    """
    def _create_index(self) -> None:
        """Create a index on the collection"""
        from pymilvus import Collection, MilvusException
        if isinstance(self.col, Collection) and self._get_index() is None:
            try:
                # If no index params, use a default AutoIndex based one
                if self.index_params is None:
                    self.index_params = {
                        "metric_type": "L2",
                        "index_type": "AUTOINDEX",
                        "params": {},
                    }
                try:
                    self.col.create_index(
                        self._vector_field,
                        index_params=self.index_params,
                        using=self.alias,
                    )
                # If default did not work, most likely Milvus self-hosted
                except MilvusException:
                    # Use HNSW based index
                    self.index_params = {
                        "metric_type": "L2",
                        "index_type": "HNSW",
                        "params": {"M": 8, "efConstruction": 64},
                    }
                    self.col.create_index(