# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import os

import pytest
import pytest_asyncio

from llama_stack.apis.common.type_system import *  # noqa: F403
from llama_stack.apis.datasetio import *  # noqa: F403
from llama_stack.distribution.datatypes import *  # noqa: F403
import base64
import mimetypes
from pathlib import Path

from llama_stack.providers.tests.resolver import resolve_impls_for_test

# How to run this test:
#
# 1. Ensure you have a conda with the right dependencies installed. This is a bit tricky
#    since it depends on the provider you are testing. On top of that you need
#    `pytest` and `pytest-asyncio` installed.
#
# 2. Copy and modify the provider_config_example.yaml depending on the provider you are testing.
#
# 3. Run:
#
# ```bash
# PROVIDER_ID=<your_provider> \
#   PROVIDER_CONFIG=provider_config.yaml \
#   pytest -s llama_stack/providers/tests/datasetio/test_datasetio.py \
#   --tb=short --disable-warnings
# ```


@pytest_asyncio.fixture(scope="session")
async def datasetio_settings():
    impls = await resolve_impls_for_test(
        Api.datasetio,
    )
    return {
        "datasetio_impl": impls[Api.datasetio],
        "datasets_impl": impls[Api.datasets],
    }


def data_url_from_file(file_path: str) -> str:
    if not os.path.exists(file_path):
        raise FileNotFoundError(f"File not found: {file_path}")

    with open(file_path, "rb") as file:
        file_content = file.read()

    base64_content = base64.b64encode(file_content).decode("utf-8")
    mime_type, _ = mimetypes.guess_type(file_path)
    print(mime_type)

    data_url = f"data:{mime_type};base64,{base64_content}"

    return data_url


async def register_dataset(datasets_impl: Datasets):
    dataset = DatasetDefWithProvider(
        identifier="test_dataset",
        provider_id=os.environ["PROVIDER_ID"],
        url=URL(
            uri="https://openaipublic.blob.core.windows.net/simple-evals/mmlu.csv",
        ),
        dataset_schema={},
    )
    await datasets_impl.register_dataset(dataset)


async def register_local_dataset(datasets_impl: Datasets):
    test_file = Path(os.path.abspath(__file__)).parent / "test_dataset.jsonl"
    test_jsonl_url = data_url_from_file(str(test_file))
    dataset = DatasetDefWithProvider(
        identifier="test_dataset",
        provider_id=os.environ["PROVIDER_ID"],
        url=URL(
            uri=test_jsonl_url,
        ),
        dataset_schema={
            "generated_answer": StringType(),
            "expected_answer": StringType(),
            "input_query": StringType(),
        },
    )
    await datasets_impl.register_dataset(dataset)


# @pytest.mark.asyncio
# async def test_datasets_list(datasetio_settings):
#     # NOTE: this needs you to ensure that you are starting from a clean state
#     # but so far we don't have an unregister API unfortunately, so be careful
#     datasets_impl = datasetio_settings["datasets_impl"]
#     response = await datasets_impl.list_datasets()
#     assert isinstance(response, list)
#     assert len(response) == 0


# @pytest.mark.asyncio
# async def test_datasets_register(datasetio_settings):
#     # NOTE: this needs you to ensure that you are starting from a clean state
#     # but so far we don't have an unregister API unfortunately, so be careful
#     datasets_impl = datasetio_settings["datasets_impl"]
#     await register_dataset(datasets_impl)

#     response = await datasets_impl.list_datasets()
#     assert isinstance(response, list)
#     assert len(response) == 1

#     # register same dataset with same id again will fail
#     await register_dataset(datasets_impl)
#     response = await datasets_impl.list_datasets()
#     assert isinstance(response, list)
#     assert len(response) == 1
#     assert response[0].identifier == "test_dataset"


# @pytest.mark.asyncio
# async def test_get_rows_paginated(datasetio_settings):
#     datasetio_impl = datasetio_settings["datasetio_impl"]
#     datasets_impl = datasetio_settings["datasets_impl"]
#     await register_dataset(datasets_impl)

#     response = await datasetio_impl.get_rows_paginated(
#         dataset_id="test_dataset",
#         rows_in_page=3,
#     )

#     assert isinstance(response.rows, list)
#     assert len(response.rows) == 3
#     assert response.next_page_token == "3"

#     # iterate over all rows
#     response = await datasetio_impl.get_rows_paginated(
#         dataset_id="test_dataset",
#         rows_in_page=10,
#         page_token=response.next_page_token,
#     )

#     assert isinstance(response.rows, list)
#     assert len(response.rows) == 10
#     assert response.next_page_token == "13"


@pytest.mark.asyncio
async def test_datasets_validation(datasetio_settings):
    # NOTE: this needs you to ensure that you are starting from a clean state
    # but so far we don't have an unregister API unfortunately, so be careful
    datasets_impl = datasetio_settings["datasets_impl"]
    await register_local_dataset(datasets_impl)