# -*- coding: utf-8 -*-

# Copyright 2022 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

import uuid
import pytest

from google.cloud import aiplatform

from tests.system.aiplatform import e2e_base

# project
_TEST_INDEX_DISPLAY_NAME = "index_display_name"
_TEST_INDEX_DESCRIPTION = "index_description"
_TEST_INDEX_DISTANCE_MEASURE_TYPE = "SQUARED_L2_DISTANCE"

_TEST_INDEX_CONFIG_DIMENSIONS = 100
_TEST_INDEX_APPROXIMATE_NEIGHBORS_COUNT = 150
_TEST_LEAF_NODE_EMBEDDING_COUNT = 123
_TEST_LEAF_NODES_TO_SEARCH_PERCENT = 50


_TEST_CONTENTS_DELTA_URI = (
    "gs://cloud-samples-data-us-central1/vertex-ai/matching_engine/glove100/initial"
)
_TEST_CONTENTS_DELTA_URI_UPDATE = (
    "gs://cloud-samples-data-us-central1/vertex-ai/matching_engine/glove100/incremental"
)
_TEST_IS_COMPLETE_OVERWRITE = True
_TEST_INDEX_DISTANCE_MEASURE_TYPE = "SQUARED_L2_DISTANCE"


_TEST_LABELS = {"my_key": "my_value"}
_TEST_DISPLAY_NAME_UPDATE = "my new display name"
_TEST_DESCRIPTION_UPDATE = "my description update"
_TEST_LABELS_UPDATE = {"my_key_update": "my_value_update"}

# ENDPOINT
_TEST_INDEX_ENDPOINT_DISPLAY_NAME = "endpoint_name"
_TEST_INDEX_ENDPOINT_DESCRIPTION = "my endpoint"

_TEST_INDEX_ENDPOINT_VPC_NETWORK = "projects/{}/global/networks/{}".format(
    e2e_base._PROJECT_NUMBER, e2e_base._VPC_NETWORK_NAME
)

# DEPLOYED INDEX
_TEST_DEPLOYED_INDEX_ID = f"deployed_index_id_{uuid.uuid4()}"
_TEST_DEPLOYED_INDEX_DISPLAY_NAME = f"deployed_index_display_name_{uuid.uuid4()}"
_TEST_MIN_REPLICA_COUNT_UPDATED = 4
_TEST_MAX_REPLICA_COUNT_UPDATED = 4

# QUERY
_TEST_MATCH_QUERY = query = [
    -0.11333,
    0.48402,
    0.090771,
    -0.22439,
    0.034206,
    -0.55831,
    0.041849,
    -0.53573,
    0.18809,
    -0.58722,
    0.015313,
    -0.014555,
    0.80842,
    -0.038519,
    0.75348,
    0.70502,
    -0.17863,
    0.3222,
    0.67575,
    0.67198,
    0.26044,
    0.4187,
    -0.34122,
    0.2286,
    -0.53529,
    1.2582,
    -0.091543,
    0.19716,
    -0.037454,
    -0.3336,
    0.31399,
    0.36488,
    0.71263,
    0.1307,
    -0.24654,
    -0.52445,
    -0.036091,
    0.55068,
    0.10017,
    0.48095,
    0.71104,
    -0.053462,
    0.22325,
    0.30917,
    -0.39926,
    0.036634,
    -0.35431,
    -0.42795,
    0.46444,
    0.25586,
    0.68257,
    -0.20821,
    0.38433,
    0.055773,
    -0.2539,
    -0.20804,
    0.52522,
    -0.11399,
    -0.3253,
    -0.44104,
    0.17528,
    0.62255,
    0.50237,
    -0.7607,
    -0.071786,
    0.0080131,
    -0.13286,
    0.50097,
    0.18824,
    -0.54722,
    -0.42664,
    0.4292,
    0.14877,
    -0.0072514,
    -0.16484,
    -0.059798,
    0.9895,
    -0.61738,
    0.054169,
    0.48424,
    -0.35084,
    -0.27053,
    0.37829,
    0.11503,
    -0.39613,
    0.24266,
    0.39147,
    -0.075256,
    0.65093,
    -0.20822,
    -0.17456,
    0.53571,
    -0.16537,
    0.13582,
    -0.56016,
    0.016964,
    0.1277,
    0.94071,
    -0.22608,
    -0.021106,
]


@pytest.mark.skip(reason="TestMatchingEngine not available")
class TestMatchingEngine(e2e_base.TestEndToEnd):

    _temp_prefix = "temp_vertex_sdk_e2e_matching_engine_test"

    def test_create_get_list_matching_engine_index(self, shared_state):
        aiplatform.init(
            project=e2e_base._PROJECT,
            location=e2e_base._LOCATION,
        )

        # Create an index
        index = aiplatform.MatchingEngineIndex.create_tree_ah_index(
            display_name=_TEST_INDEX_DISPLAY_NAME,
            contents_delta_uri=_TEST_CONTENTS_DELTA_URI,
            dimensions=_TEST_INDEX_CONFIG_DIMENSIONS,
            approximate_neighbors_count=_TEST_INDEX_APPROXIMATE_NEIGHBORS_COUNT,
            distance_measure_type=_TEST_INDEX_DISTANCE_MEASURE_TYPE,
            leaf_node_embedding_count=_TEST_LEAF_NODE_EMBEDDING_COUNT,
            leaf_nodes_to_search_percent=_TEST_LEAF_NODES_TO_SEARCH_PERCENT,
            description=_TEST_INDEX_DESCRIPTION,
            labels=_TEST_LABELS,
        )

        shared_state["resources"] = [index]
        shared_state["index"] = index
        shared_state["index_name"] = index.resource_name

        # Verify that the retrieved index is the same
        get_index = aiplatform.MatchingEngineIndex(index_name=index.resource_name)
        assert index.resource_name == get_index.resource_name

        # Create index and check that it is listed
        list_indexes = aiplatform.MatchingEngineIndex.list()
        assert get_index.resource_name in [
            index.resource_name for index in list_indexes
        ]

        # Update the index metadata
        updated_index = get_index.update_metadata(
            display_name=_TEST_DISPLAY_NAME_UPDATE,
            description=_TEST_DESCRIPTION_UPDATE,
            labels=_TEST_LABELS_UPDATE,
        )

        assert updated_index.name == get_index.name
        # TODO: Reinstate assertions once b/220005272 is fixed.
        # assert updated_index.display_name == _TEST_DISPLAY_NAME_UPDATE
        # assert updated_index.description == _TEST_DESCRIPTION_UPDATE
        # assert updated_index.labels == _TEST_LABELS_UPDATE

        # Update the index embeddings
        updated_index = get_index.update_embeddings(
            contents_delta_uri=_TEST_CONTENTS_DELTA_URI_UPDATE,
            is_complete_overwrite=_TEST_IS_COMPLETE_OVERWRITE,
        )

        assert updated_index.name == get_index.name

        # Delete index and check that it is no longer listed
        index.delete()
        list_indexes = aiplatform.MatchingEngineIndex.list()
        assert get_index.resource_name not in [
            index.resource_name for index in list_indexes
        ]
