# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# 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 json
from unittest.mock import AsyncMock, MagicMock, call

from fastapi.testclient import TestClient
from pytest import MonkeyPatch

from nemo_gym.config_types import ModelServerRef, ResourcesServerRef
from nemo_gym.openai_utils import (
    NeMoGymEasyInputMessage,
    NeMoGymResponseCreateParamsNonStreaming,
    NeMoGymResponseReasoningItem,
    NeMoGymSummary,
)
from nemo_gym.server_utils import ServerClient
from responses_api_agents.cvdp_agent.app import (
    SimpleAgent,
    SimpleAgentConfig,
)


class TestApp:
    def test_sanity(self) -> None:
        config = SimpleAgentConfig(
            host="0.0.0.0",
            port=8080,
            entrypoint="",
            name="",
            resources_server=ResourcesServerRef(
                type="resources_servers",
                name="",
            ),
            model_server=ModelServerRef(
                type="responses_api_models",
                name="",
            ),
        )
        SimpleAgent(config=config, server_client=MagicMock(spec=ServerClient))

    async def test_responses(self, monkeypatch: MonkeyPatch) -> None:
        config = SimpleAgentConfig(
            host="0.0.0.0",
            port=8080,
            entrypoint="",
            name="",
            model_server=ModelServerRef(
                type="responses_api_models",
                name="my server name",
            ),
            resources_server=ResourcesServerRef(
                type="resources_servers",
                name="",
            ),
        )
        server = SimpleAgent(config=config, server_client=MagicMock(spec=ServerClient))
        app = server.setup_webserver()
        client = TestClient(app)

        mock_response_data = {
            "id": "resp_688babb004988199b26c5250ba69c1e80abdf302bcd600d3",
            "created_at": 1753983920.0,
            "model": "dummy_model",
            "object": "response",
            "output": [
                {
                    "id": "msg_688babb17a7881998cc7a42d53c8e5790abdf302bcd600d3",
                    "content": [
                        {
                            "annotations": [],
                            "text": "Hello! How can I help you today?",
                            "type": "output_text",
                        }
                    ],
                    "role": "assistant",
                    "status": "completed",
                    "type": "message",
                }
            ],
            "parallel_tool_calls": True,
            "tool_choice": "auto",
            "tools": [],
        }

        dotjson_mock = AsyncMock()
        dotjson_mock.read.return_value = json.dumps(mock_response_data)
        dotjson_mock.cookies = MagicMock()
        server.server_client.post.return_value = dotjson_mock

        # No model provided should use the one from the config
        res_no_model = client.post("/v1/responses", json={"input": [{"role": "user", "content": "hello"}]})
        assert res_no_model.status_code == 200
        server.server_client.post.assert_called_with(
            server_name="my server name",
            url_path="/v1/responses",
            json=NeMoGymResponseCreateParamsNonStreaming(
                input=[NeMoGymEasyInputMessage(content="hello", role="user", type="message")]
            ),
            cookies=None,
        )

        actual_responses_dict = res_no_model.json()
        expected_responses_dict = {
            "id": "resp_688babb004988199b26c5250ba69c1e80abdf302bcd600d3",
            "created_at": 1753983920.0,
            "error": None,
            "incomplete_details": None,
            "instructions": None,
            "metadata": None,
            "model": "dummy_model",
            "object": "response",
            "output": [
                {
                    "id": "msg_688babb17a7881998cc7a42d53c8e5790abdf302bcd600d3",
                    "content": [
                        {
                            "annotations": [],
                            "text": "Hello! How can I help you today?",
                            "type": "output_text",
                            "logprobs": None,
                        }
                    ],
                    "role": "assistant",
                    "status": "completed",
                    "type": "message",
                }
            ],
            "parallel_tool_calls": True,
            "temperature": None,
            "tool_choice": "auto",
            "tools": [],
            "top_p": None,
            "background": None,
            "max_output_tokens": None,
            "max_tool_calls": None,
            "previous_response_id": None,
            "prompt": None,
            "reasoning": None,
            "service_tier": None,
            "status": None,
            "text": None,
            "top_logprobs": None,
            "truncation": None,
            "usage": None,
            "user": None,
            "conversation": None,
            "prompt_cache_key": None,
            "safety_identifier": None,
        }
        assert expected_responses_dict == actual_responses_dict

    async def test_responses_continues_on_reasoning_only(self, monkeypatch: MonkeyPatch) -> None:
        config = SimpleAgentConfig(
            host="0.0.0.0",
            port=8080,
            entrypoint="",
            name="",
            model_server=ModelServerRef(
                type="responses_api_models",
                name="my server name",
            ),
            resources_server=ResourcesServerRef(
                type="resources_servers",
                name="",
            ),
        )
        server = SimpleAgent(config=config, server_client=MagicMock(spec=ServerClient))
        app = server.setup_webserver()
        client = TestClient(app)

        mock_response_reasoning_data = {
            "id": "resp_688babb004988199b26c5250ba69c1e80abdf302bcd600d3",
            "created_at": 1753983920.0,
            "model": "dummy_model",
            "object": "response",
            "output": [
                {
                    "id": "msg_688babb17a7881998cc7a42d53c8e5790abdf302bcd600d3",
                    "summary": [
                        {
                            "text": "I'm thinking how to respond",
                            "type": "summary_text",
                        }
                    ],
                    "status": "completed",
                    "type": "reasoning",
                }
            ],
            "parallel_tool_calls": True,
            "tool_choice": "auto",
            "tools": [],
        }

        mock_response_chat_data = {
            "id": "resp_688babb004988199b26c5250ba69c1e80abdf302bcd600d3",
            "created_at": 1753983920.0,
            "model": "dummy_model",
            "object": "response",
            "output": [
                {
                    "id": "msg_688babb17a7881998cc7a42d53c8e5790abdf302bcd600d3",
                    "content": [
                        {
                            "annotations": [],
                            "text": "Hello! How can I help you today?",
                            "type": "output_text",
                        }
                    ],
                    "role": "assistant",
                    "status": "completed",
                    "type": "message",
                }
            ],
            "parallel_tool_calls": True,
            "tool_choice": "auto",
            "tools": [],
        }

        dotjson_mock = AsyncMock()
        dotjson_mock.read.side_effect = [json.dumps(mock_response_reasoning_data), json.dumps(mock_response_chat_data)]
        dotjson_mock.cookies = MagicMock()
        server.server_client.post.return_value = dotjson_mock

        # No model provided should use the one from the config
        res_no_model = client.post("/v1/responses", json={"input": [{"role": "user", "content": "hello"}]})
        assert res_no_model.status_code == 200

        expected_calls = [
            call(
                server_name="my server name",
                url_path="/v1/responses",
                json=NeMoGymResponseCreateParamsNonStreaming(
                    input=[NeMoGymEasyInputMessage(content="hello", role="user", type="message")]
                ),
                cookies=None,
            ),
            call().ok.__bool__(),
            call().read(),
            call(
                server_name="my server name",
                url_path="/v1/responses",
                json=NeMoGymResponseCreateParamsNonStreaming(
                    input=[
                        NeMoGymEasyInputMessage(content="hello", role="user", type="message"),
                        NeMoGymResponseReasoningItem(
                            id="msg_688babb17a7881998cc7a42d53c8e5790abdf302bcd600d3",
                            summary=[NeMoGymSummary(text="I'm thinking how to respond", type="summary_text")],
                            type="reasoning",
                            encrypted_content=None,
                            status="completed",
                        ),
                    ]
                ),
                cookies=dotjson_mock.cookies,
            ),
            call().ok.__bool__(),
            call().read(),
            call().cookies.items(),
            call().cookies.items().__iter__(),
            call().cookies.items().__len__(),
        ]
        server.server_client.post.assert_has_calls(expected_calls)

        actual_responses_dict = res_no_model.json()
        expected_responses_dict = {
            "id": "resp_688babb004988199b26c5250ba69c1e80abdf302bcd600d3",
            "created_at": 1753983920.0,
            "error": None,
            "incomplete_details": None,
            "instructions": None,
            "metadata": None,
            "model": "dummy_model",
            "object": "response",
            "output": [
                {
                    "id": "msg_688babb17a7881998cc7a42d53c8e5790abdf302bcd600d3",
                    "encrypted_content": None,
                    "summary": [
                        {
                            "text": "I'm thinking how to respond",
                            "type": "summary_text",
                        }
                    ],
                    "type": "reasoning",
                },
                {
                    "id": "msg_688babb17a7881998cc7a42d53c8e5790abdf302bcd600d3",
                    "content": [
                        {
                            "annotations": [],
                            "text": "Hello! How can I help you today?",
                            "type": "output_text",
                            "logprobs": None,
                        }
                    ],
                    "role": "assistant",
                    "status": "completed",
                    "type": "message",
                },
            ],
            "parallel_tool_calls": True,
            "temperature": None,
            "tool_choice": "auto",
            "tools": [],
            "top_p": None,
            "background": None,
            "max_output_tokens": None,
            "max_tool_calls": None,
            "previous_response_id": None,
            "prompt": None,
            "reasoning": None,
            "service_tier": None,
            "status": None,
            "text": None,
            "top_logprobs": None,
            "truncation": None,
            "usage": None,
            "user": None,
            "conversation": None,
            "prompt_cache_key": None,
            "safety_identifier": None,
        }
        assert expected_responses_dict == actual_responses_dict
