import json
import os
import subprocess
import time
import unittest
from types import SimpleNamespace
from urllib.parse import urlparse

import requests

from sglang.srt.utils import kill_process_tree
from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
from sglang.test.test_utils import (
    DEFAULT_EAGLE_DRAFT_MODEL_FOR_TEST,
    DEFAULT_EAGLE_TARGET_MODEL_FOR_TEST,
    DEFAULT_MODEL_NAME_FOR_TEST,
    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
    DEFAULT_URL_FOR_TEST,
    CustomTestCase,
    popen_launch_pd_server,
)


class TestDisaggregationAccuracy(CustomTestCase):
    @classmethod
    def setUpClass(cls):
        cls.model = DEFAULT_MODEL_NAME_FOR_TEST
        parsed_url = urlparse(DEFAULT_URL_FOR_TEST)
        cls.base_host = parsed_url.hostname
        base_port = str(parsed_url.port)
        cls.lb_port = base_port
        cls.prefill_port = f"{int(base_port) + 100}"
        cls.decode_port = f"{int(base_port) + 200}"
        cls.prefill_url = f"http://{cls.base_host}:{cls.prefill_port}"
        cls.decode_url = f"http://{cls.base_host}:{cls.decode_port}"
        cls.lb_url = f"http://{cls.base_host}:{cls.lb_port}"
        print(f"{cls.base_host=} {cls.lb_port=} {cls.prefill_port=} {cls.decode_port=}")

        # Non blocking start servers
        cls.start_prefill()
        cls.start_decode()

        # Block until both
        cls.wait_server_ready(cls.prefill_url + "/health")
        cls.wait_server_ready(cls.decode_url + "/health")

        lb_command = [
            "python3",
            "-m",
            "sglang.srt.disaggregation.mini_lb",
            "--prefill",
            cls.prefill_url,
            "--decode",
            cls.decode_url,
            "--host",
            cls.base_host,
            "--port",
            cls.lb_port,
        ]

        print("Starting load balancer:", " ".join(lb_command))
        cls.process_lb = subprocess.Popen(
            lb_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE
        )
        cls.wait_server_ready(cls.lb_url + "/health")

    @classmethod
    def start_prefill(cls):
        prefill_args = [
            "--trust-remote-code",
            "--disaggregation-mode",
            "prefill",
            "--tp",
            "1",
            "--disaggregation-ib-device",
            "mlx5_roce0",
        ]
        cls.process_prefill = popen_launch_pd_server(
            cls.model,
            cls.prefill_url,
            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
            other_args=prefill_args,
        )

    @classmethod
    def start_decode(cls):
        decode_args = [
            "--trust-remote-code",
            "--disaggregation-mode",
            "decode",
            "--tp",
            "1",
            "--base-gpu-id",
            "1",
            "--disaggregation-ib-device",
            "mlx5_roce1",
        ]
        cls.process_decode = popen_launch_pd_server(
            cls.model,
            cls.decode_url,
            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
            other_args=decode_args,
        )

    @classmethod
    def wait_server_ready(cls, url, timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH):
        start_time = time.perf_counter()
        while True:
            try:
                response = requests.get(url)
                if response.status_code == 200:
                    print(f"Server {url} is ready")
                    return
            except Exception:
                pass

            if time.perf_counter() - start_time > timeout:
                raise RuntimeError(f"Server {url} failed to start in {timeout}s")
            time.sleep(1)

    @classmethod
    def tearDownClass(cls):
        for process in [cls.process_lb, cls.process_decode, cls.process_prefill]:
            if process:
                try:
                    kill_process_tree(process.pid)
                except Exception as e:
                    print(f"Error killing process {process.pid}: {e}")

        # wait for 5 seconds
        time.sleep(5)

    def test_gsm8k(self):
        args = SimpleNamespace(
            num_shots=5,
            data_path=None,
            num_questions=200,
            max_new_tokens=512,
            parallel=128,
            host=f"http://{self.base_host}",
            port=int(self.lb_port),
        )
        metrics = run_eval_few_shot_gsm8k(args)
        print(f"Evaluation metrics: {metrics}")

        self.assertGreater(metrics["accuracy"], 0.62)

    def test_logprob(self):
        prompt = "The capital of france is "
        response = requests.post(
            self.lb_url + "/generate",
            json={
                "text": prompt,
                "sampling_params": {"temperature": 0},
                "return_logprob": True,
                "return_input_logprob": True,
                "logprob_start_len": 0,
            },
        )

        j = response.json()
        completion_tokens = j["meta_info"]["completion_tokens"]
        input_logprobs = j["meta_info"]["input_token_logprobs"]
        output_logprobs = j["meta_info"]["output_token_logprobs"]

        assert (
            len(output_logprobs) == completion_tokens
        ), f"output_logprobs and completion_tokens should have the same length, but got {len(output_logprobs)} and {completion_tokens}"
        assert (
            len(input_logprobs) > 0
        ), f"input_logprobs should have at least one token, but got {len(input_logprobs)}"

    def test_structured_output(self):
        json_schema = json.dumps(
            {
                "type": "object",
                "properties": {
                    "name": {"type": "string", "pattern": "^[\\w]+$"},
                    "population": {"type": "integer"},
                },
                "required": ["name", "population"],
            }
        )

        # JSON
        response = requests.post(
            f"{self.lb_url}/generate",
            json={
                "text": "Here is the information of the capital of France in the JSON format.\n",
                "sampling_params": {
                    "temperature": 0,
                    "max_new_tokens": 64,
                    "json_schema": json_schema,
                },
            },
        )
        output = response.json()["text"]
        # ensure the output is a valid JSON
        json.loads(output)


class TestDisaggregationMooncakeFailure(CustomTestCase):
    @classmethod
    def setUpClass(cls):
        # set DISAGGREGATION_TEST_FAILURE_PROB to simulate failure
        os.environ["DISAGGREGATION_TEST_FAILURE_PROB"] = "0.05"

        cls.model = DEFAULT_MODEL_NAME_FOR_TEST
        parsed_url = urlparse(DEFAULT_URL_FOR_TEST)
        cls.base_host = parsed_url.hostname
        base_port = str(parsed_url.port)
        cls.lb_port = base_port
        cls.prefill_port = f"{int(base_port) + 100}"
        cls.decode_port = f"{int(base_port) + 200}"
        cls.prefill_url = f"http://{cls.base_host}:{cls.prefill_port}"
        cls.decode_url = f"http://{cls.base_host}:{cls.decode_port}"
        cls.lb_url = f"http://{cls.base_host}:{cls.lb_port}"
        print(f"{cls.base_host=} {cls.lb_port=} {cls.prefill_port=} {cls.decode_port=}")

        # Non blocking start servers
        cls.start_prefill()
        cls.start_decode()

        # Block until both
        cls.wait_server_ready(cls.prefill_url + "/health")
        cls.wait_server_ready(cls.decode_url + "/health")

        lb_command = [
            "python3",
            "-m",
            "sglang.srt.disaggregation.mini_lb",
            "--prefill",
            cls.prefill_url,
            "--decode",
            cls.decode_url,
            "--host",
            cls.base_host,
            "--port",
            cls.lb_port,
        ]

        print("Starting load balancer:", " ".join(lb_command))
        cls.process_lb = subprocess.Popen(
            lb_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE
        )
        cls.wait_server_ready(cls.lb_url + "/health")

    @classmethod
    def start_prefill(cls):
        prefill_args = [
            "--trust-remote-code",
            "--disaggregation-mode",
            "prefill",
            "--tp",
            "1",
            "--disaggregation-ib-device",
            "mlx5_roce0",
        ]
        cls.process_prefill = popen_launch_pd_server(
            cls.model,
            cls.prefill_url,
            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
            other_args=prefill_args,
        )

    @classmethod
    def start_decode(cls):
        decode_args = [
            "--trust-remote-code",
            "--disaggregation-mode",
            "decode",
            "--tp",
            "1",
            "--base-gpu-id",
            "1",
            "--disaggregation-ib-device",
            "mlx5_roce1",
        ]
        cls.process_decode = popen_launch_pd_server(
            cls.model,
            cls.decode_url,
            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
            other_args=decode_args,
        )

    @classmethod
    def wait_server_ready(cls, url, timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH):
        start_time = time.perf_counter()
        while True:
            try:
                response = requests.get(url)
                if response.status_code == 200:
                    print(f"Server {url} is ready")
                    return
            except Exception:
                pass

            if time.perf_counter() - start_time > timeout:
                raise RuntimeError(f"Server {url} failed to start in {timeout}s")
            time.sleep(1)

    @classmethod
    def tearDownClass(cls):
        # unset DISAGGREGATION_TEST_FAILURE_PROB
        os.environ.pop("DISAGGREGATION_TEST_FAILURE_PROB")
        for process in [cls.process_lb, cls.process_decode, cls.process_prefill]:
            if process:
                try:
                    kill_process_tree(process.pid)
                except Exception as e:
                    print(f"Error killing process {process.pid}: {e}")

        # wait for 5 seconds
        time.sleep(5)

    def test_gsm8k(self):
        args = SimpleNamespace(
            num_shots=5,
            data_path=None,
            num_questions=200,
            max_new_tokens=512,
            parallel=128,
            host=f"http://{self.base_host}",
            port=int(self.lb_port),
        )

        # Expect lots of failure but the server cannot crash
        try:
            metrics = run_eval_few_shot_gsm8k(args)
            print(f"Evaluation metrics: {metrics}")
        except Exception as e:
            print(f"Test encountered expected errors: {e}")
            # Check if servers are still healthy
            try:
                response = requests.get(self.prefill_url + "/health_generate")
                assert response.status_code == 200
                response = requests.get(self.decode_url + "/health_generate")
                assert response.status_code == 200
            except Exception as health_check_error:
                # If health check fails, re-raise the original exception
                raise e from health_check_error


class TestDisaggregationMooncakeSpec(CustomTestCase):

    @classmethod
    def setUpClass(cls):
        cls.model = DEFAULT_EAGLE_TARGET_MODEL_FOR_TEST
        cls.draft_model = DEFAULT_EAGLE_DRAFT_MODEL_FOR_TEST
        parsed_url = urlparse(DEFAULT_URL_FOR_TEST)
        cls.base_host = parsed_url.hostname
        base_port = str(parsed_url.port)
        cls.lb_port = base_port
        cls.prefill_port = f"{int(base_port) + 100}"
        cls.decode_port = f"{int(base_port) + 200}"
        cls.prefill_url = f"http://{cls.base_host}:{cls.prefill_port}"
        cls.decode_url = f"http://{cls.base_host}:{cls.decode_port}"
        cls.lb_url = f"http://{cls.base_host}:{cls.lb_port}"
        cls.spec_args = [
            "--speculative-algorithm",
            "EAGLE",
            "--speculative-draft-model-path",
            cls.draft_model,
            "--speculative-num-steps",
            "3",
            "--speculative-eagle-topk",
            "4",
            "--speculative-num-draft-tokens",
            "16",
            "--cuda-graph-max-bs",
            "8",
        ]
        print(f"{cls.base_host=} {cls.lb_port=} {cls.prefill_port=} {cls.decode_port=}")

        # Non blocking start servers
        cls.start_prefill()
        cls.start_decode()

        # Block until both
        cls.wait_server_ready(cls.prefill_url + "/health")
        cls.wait_server_ready(cls.decode_url + "/health")

        lb_command = [
            "python3",
            "-m",
            "sglang.srt.disaggregation.mini_lb",
            "--prefill",
            cls.prefill_url,
            "--decode",
            cls.decode_url,
            "--host",
            cls.base_host,
            "--port",
            cls.lb_port,
        ]

        print("Starting load balancer:", " ".join(lb_command))
        cls.process_lb = subprocess.Popen(
            lb_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE
        )
        cls.wait_server_ready(cls.lb_url + "/health")

    @classmethod
    def wait_server_ready(cls, url, timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH):
        start_time = time.perf_counter()
        while True:
            try:
                response = requests.get(url)
                if response.status_code == 200:
                    print(f"Server {url} is ready")
                    return
            except Exception:
                pass

            if time.perf_counter() - start_time > timeout:
                raise RuntimeError(f"Server {url} failed to start in {timeout}s")
            time.sleep(1)

    @classmethod
    def start_prefill(cls):
        prefill_args = [
            "--trust-remote-code",
            "--disaggregation-mode",
            "prefill",
            "--tp",
            "2",
            "--disaggregation-ib-device",
            "mlx5_roce0,mlx5_roce1",
        ] + cls.spec_args
        cls.process_prefill = popen_launch_pd_server(
            cls.model,
            cls.prefill_url,
            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
            other_args=prefill_args,
        )

    @classmethod
    def start_decode(cls):
        decode_args = [
            "--trust-remote-code",
            "--disaggregation-mode",
            "decode",
            "--tp",
            "2",
            "--base-gpu-id",
            "2",
            "--disaggregation-ib-device",
            "mlx5_roce2,mlx5_roce3",
        ] + cls.spec_args
        cls.process_decode = popen_launch_pd_server(
            cls.model,
            cls.decode_url,
            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
            other_args=decode_args,
        )

    @classmethod
    def tearDownClass(cls):
        for process in [cls.process_lb, cls.process_decode, cls.process_prefill]:
            if process:
                try:
                    kill_process_tree(process.pid)
                except Exception as e:
                    print(f"Error killing process {process.pid}: {e}")

        # wait for 5 seconds
        time.sleep(5)

    def test_gsm8k(self):
        args = SimpleNamespace(
            num_shots=5,
            data_path=None,
            num_questions=200,
            max_new_tokens=512,
            parallel=2,
            host=f"http://{self.base_host}",
            port=int(self.lb_port),
        )
        metrics = run_eval_few_shot_gsm8k(args)
        print(f"Evaluation metrics: {metrics}")

        self.assertGreater(metrics["accuracy"], 0.20)


class TestDisaggregationSimulatedRetract(CustomTestCase):
    @classmethod
    def setUpClass(cls):
        os.environ["SGLANG_TEST_RETRACT"] = "true"
        cls.model = DEFAULT_MODEL_NAME_FOR_TEST
        parsed_url = urlparse(DEFAULT_URL_FOR_TEST)
        cls.base_host = parsed_url.hostname
        base_port = str(parsed_url.port)
        cls.lb_port = base_port
        cls.prefill_port = f"{int(base_port) + 100}"
        cls.decode_port = f"{int(base_port) + 200}"
        cls.prefill_url = f"http://{cls.base_host}:{cls.prefill_port}"
        cls.decode_url = f"http://{cls.base_host}:{cls.decode_port}"
        cls.lb_url = f"http://{cls.base_host}:{cls.lb_port}"
        print(f"{cls.base_host=} {cls.lb_port=} {cls.prefill_port=} {cls.decode_port=}")

        # Non blocking start servers
        cls.start_prefill()
        cls.start_decode()

        # Block until both
        cls.wait_server_ready(cls.prefill_url + "/health")
        cls.wait_server_ready(cls.decode_url + "/health")

        lb_command = [
            "python3",
            "-m",
            "sglang.srt.disaggregation.mini_lb",
            "--prefill",
            cls.prefill_url,
            "--decode",
            cls.decode_url,
            "--host",
            cls.base_host,
            "--port",
            cls.lb_port,
        ]

        print("Starting load balancer:", " ".join(lb_command))
        cls.process_lb = subprocess.Popen(
            lb_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE
        )
        cls.wait_server_ready(cls.lb_url + "/health")

    @classmethod
    def start_prefill(cls):
        prefill_args = [
            "--trust-remote-code",
            "--disaggregation-mode",
            "prefill",
            "--tp",
            "1",
            "--disaggregation-ib-device",
            "mlx5_roce0",
        ]
        cls.process_prefill = popen_launch_pd_server(
            cls.model,
            cls.prefill_url,
            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
            other_args=prefill_args,
        )

    @classmethod
    def start_decode(cls):
        decode_args = [
            "--trust-remote-code",
            "--disaggregation-mode",
            "decode",
            "--tp",
            "1",
            "--base-gpu-id",
            "1",
            "--disaggregation-ib-device",
            "mlx5_roce1",
        ]
        cls.process_decode = popen_launch_pd_server(
            cls.model,
            cls.decode_url,
            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
            other_args=decode_args,
        )

    @classmethod
    def wait_server_ready(cls, url, timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH):
        start_time = time.perf_counter()
        while True:
            try:
                response = requests.get(url)
                if response.status_code == 200:
                    print(f"Server {url} is ready")
                    return
            except Exception:
                pass

            if time.perf_counter() - start_time > timeout:
                raise RuntimeError(f"Server {url} failed to start in {timeout}s")
            time.sleep(1)

    @classmethod
    def tearDownClass(cls):
        os.environ.pop("SGLANG_TEST_RETRACT")
        for process in [cls.process_lb, cls.process_decode, cls.process_prefill]:
            if process:
                try:
                    kill_process_tree(process.pid)
                except Exception as e:
                    print(f"Error killing process {process.pid}: {e}")

        # wait for 5 seconds
        time.sleep(5)

    def test_gsm8k(self):
        args = SimpleNamespace(
            num_shots=5,
            data_path=None,
            num_questions=200,
            max_new_tokens=512,
            parallel=128,
            host=f"http://{self.base_host}",
            port=int(self.lb_port),
        )
        metrics = run_eval_few_shot_gsm8k(args)
        print(f"Evaluation metrics: {metrics}")

        self.assertGreater(metrics["accuracy"], 0.62)


if __name__ == "__main__":
    unittest.main()
