Fix CI && python3.8 compatible (#920)

.github/workflows/e2e-test.yml

@@ -57,4 +57,4 @@ jobs:
         cd $HOME && python3 -m sglang.bench_serving --backend sglang --port 8413 --dataset-name random --num-prompts 3000 --random-input 256 --random-output 512
 
         echo "Stopping server..."
-        kill -9 $(ps aux | grep sglang | grep Meta-Llama-3.1-8B-Instruct | grep -v grep | awk '{print $2}')
+        kill -9 $(ps aux | grep sglang | grep Meta-Llama-3.1-8B-Instruct | grep -- "--port 8413" | grep -v grep | awk '{print $2}')

examples/usage/rag_using_parea/trace_and_evaluate_rag_using_parea.ipynb

@@ -71,6 +71,7 @@
    "source": [
     "import json\n",
     "import os\n",
+	"from typing import List\n",
     "\n",
     "import chromadb\n",
     "\n",
@@ -148,7 +149,7 @@
    "outputs": [],
    "source": [
     "@trace\n",
-    "def retrieval(question: str) -> list[str]:\n",
+    "def retrieval(question: str) -> List[str]:\n",
     "    return collection.query(\n",
     "        query_texts=[question],\n",
     "        n_results=1\n",
@@ -278,7 +279,7 @@
     "\n",
     "\n",
     "@trace(eval_funcs=[context_relevancy_eval, percent_target_supported_by_context])\n",
-    "def retrieval(question: str) -> list[str]:\n",
+    "def retrieval(question: str) -> List[str]:\n",
     "    return collection.query(\n",
     "        query_texts=[question],\n",
     "        n_results=1\n",

python/sglang/srt/hf_transformers_utils.py

@@ -19,7 +19,7 @@ import functools
 import json
 import os
 import warnings
-from typing import AbstractSet, Collection, Dict, Literal, Optional, Type, Union
+from typing import AbstractSet, Collection, Dict, List, Literal, Optional, Type, Union
 
 from huggingface_hub import snapshot_download
 from transformers import (
@@ -259,7 +259,7 @@ class TiktokenTokenizer:
                 Literal["all"], AbstractSet[str]
             ] = set(),  # noqa: B006
             disallowed_special: Union[Literal["all"], Collection[str]] = "all",
-        ) -> list[int]:
+        ) -> List[int]:
             if isinstance(allowed_special, set):
                 allowed_special |= self._default_allowed_special
             return tiktoken.Encoding.encode(

python/sglang/test/simple_eval_common.py

@@ -7,7 +7,7 @@ import time
 from collections import defaultdict
 from dataclasses import dataclass, field
 from multiprocessing.pool import ThreadPool
-from typing import Any
+from typing import Any, Dict, List, Tuple
 
 import httpx
 import jinja2
@@ -24,8 +24,8 @@ OPENAI_SYSTEM_MESSAGE_CHATGPT = (
 )
 
 
-Message = dict[str, Any]  # keys role, content
-MessageList = list[Message]
+Message = Dict[str, Any]  # keys role, content
+MessageList = List[Message]
 
 
 class SamplerBase:
@@ -45,9 +45,9 @@ class EvalResult:
     """
 
     score: float | None  # top-line metric
-    metrics: dict[str, float] | None  # other metrics
-    htmls: list[str]  # strings of valid HTML
-    convos: list[MessageList]  # sampled conversations
+    metrics: Dict[str, float] | None  # other metrics
+    htmls: List[str]  # strings of valid HTML
+    convos: List[MessageList]  # sampled conversations
 
 
 @dataclass
@@ -57,7 +57,7 @@ class SingleEvalResult:
     """
 
     score: float | None
-    metrics: dict[str, float] = field(default_factory=dict)
+    metrics: Dict[str, float] = field(default_factory=dict)
     html: str | None = None
     convo: MessageList | None = None  # sampled conversation
 
@@ -270,9 +270,9 @@ def _compute_stat(values: list, stat: str):
 
 
 def aggregate_results(
-    single_eval_results: list[SingleEvalResult],
-    default_stats: tuple[str] = ("mean", "std"),
-    name2stats: dict[str, tuple[str]] | None = None,
+    single_eval_results: List[SingleEvalResult],
+    default_stats: Tuple[str] = ("mean", "std"),
+    name2stats: Dict[str, Tuple[str]] | None = None,
 ) -> EvalResult:
     """
     Aggregate results from multiple evaluations into a single EvalResult.
@@ -302,7 +302,7 @@ def aggregate_results(
     )
 
 
-def map_with_progress(f: callable, xs: list[Any], num_threads: int):
+def map_with_progress(f: callable, xs: List[Any], num_threads: int):
     """
     Apply f to each element of xs, using a ThreadPool, and show progress.
     """
@@ -422,7 +422,7 @@ def make_report(eval_result: EvalResult) -> str:
     )
 
 
-def make_report_from_example_htmls(htmls: list[str]):
+def make_report_from_example_htmls(htmls: List[str]):
     """
     Create a standalone HTML report from a list of example htmls
     """

python/sglang/test/simple_eval_humaneval.py

@@ -14,7 +14,7 @@ import re
 from collections import Counter, defaultdict
 from concurrent.futures import ThreadPoolExecutor, as_completed
 from io import BytesIO
-from typing import Any, Tuple
+from typing import Any, Dict, List, Tuple
 
 import blobfile as bf
 import tqdm
@@ -38,8 +38,8 @@ from sglang.test.simple_eval_common import (
 
 
 def evaluate_functional_correctness(
-    sample: dict[str, str],
-    completions: list[str],
+    sample: Dict[str, str],
+    completions: List[str],
     n_workers: int = 4,
     timeout: float = 3.0,
 ):
@@ -70,7 +70,7 @@ class HumanEval(Eval):
         num_examples: int | None,
         num_threads: int,
         num_samples_per_task: int = 5,
-        ks_passes: list[int] = [1, 2, 5],
+        ks_passes: List[int] = [1, 2, 5],
         timeout: int = 120,
     ):
         self.seed = 0
@@ -97,7 +97,7 @@ class HumanEval(Eval):
             ]  # remove signature
             return extracted_answer
 
-        def fn(sample: dict[str, str]):
+        def fn(sample: Dict[str, str]):
             prompt_messages = [
                 sampler._pack_message(
                     role="user", content=instruction + sample["prompt"]

python/sglang/test/test_utils.py

@@ -8,7 +8,7 @@ import threading
 import time
 import unittest
 from functools import partial
-from typing import Callable, Optional
+from typing import Callable, List, Optional
 
 import numpy as np
 import requests
@@ -457,7 +457,7 @@ def run_with_timeout(
     return ret_value[0]
 
 
-def run_unittest_files(files: list[str], timeout_per_file: float):
+def run_unittest_files(files: List[str], timeout_per_file: float):
     tic = time.time()
     success = True
 

test/srt/test_chunked_prefill.py

@@ -11,7 +11,7 @@ class TestAccuracy(unittest.TestCase):
     @classmethod
     def setUpClass(cls):
         cls.model = MODEL_NAME_FOR_TEST
-        cls.base_url = f"http://localhost:30000"
+        cls.base_url = f"http://localhost:8157"
         cls.process = popen_launch_server(
             cls.model,
             cls.base_url,

test/srt/test_eval_accuracy.py

@@ -11,7 +11,7 @@ class TestAccuracy(unittest.TestCase):
     @classmethod
     def setUpClass(cls):
         cls.model = MODEL_NAME_FOR_TEST
-        cls.base_url = f"http://localhost:30000"
+        cls.base_url = f"http://localhost:8157"
         cls.process = popen_launch_server(cls.model, cls.base_url, timeout=300)
 
     @classmethod

test/srt/test_openai_server.py

@@ -12,7 +12,7 @@ class TestOpenAIServer(unittest.TestCase):
     @classmethod
     def setUpClass(cls):
         cls.model = MODEL_NAME_FOR_TEST
-        cls.base_url = f"http://localhost:30000"
+        cls.base_url = f"http://localhost:8157"
         cls.api_key = "sk-123456"
         cls.process = popen_launch_server(
             cls.model, cls.base_url, timeout=300, api_key=cls.api_key

test/srt/test_srt_endpoint.py

@@ -12,11 +12,9 @@ class TestSRTEndpoint(unittest.TestCase):
 
     @classmethod
     def setUpClass(cls):
-        port = 30000
-
         cls.model = MODEL_NAME_FOR_TEST
-        cls.base_url = f"http://localhost:{port}"
-        cls.process = popen_launch_server(cls.model, port, timeout=300)
+        cls.base_url = f"http://localhost:{8157}"
+        cls.process = popen_launch_server(cls.model, cls.base_url, timeout=300)
 
     @classmethod
     def tearDownClass(cls):

test/srt/test_torch_compile.py

@@ -11,7 +11,7 @@ class TestAccuracy(unittest.TestCase):
     @classmethod
     def setUpClass(cls):
         cls.model = MODEL_NAME_FOR_TEST
-        cls.base_url = f"http://localhost:30000"
+        cls.base_url = f"http://localhost:8157"
         cls.process = popen_launch_server(
             cls.model, cls.base_url, timeout=300, other_args=["--enable-torch-compile"]
         )