.

gradio_ui.py

@@ -1,3 +1,14 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Gradio UI + EvalScope 调度脚本（量产版）
+
+关键改动
+1. 独立 Stop Evaluation 按钮，queue=False，立即触发 `stop_eval()`
+2. `stop_eval()` 使用 psutil 递归杀进程树并 wait()，杜绝僵尸
+3. 所有生成器统一返回 4 个输出：output_text ‖ is_running ‖ run_button 更新 ‖ stop_button 更新
+"""
+
 import time
 import os
 import glob
@@ -17,8 +28,10 @@ EVAL_DATASETS = [
     "hellaswag", "humaneval", "mmlu", "mmlu_pro", "race",
     "trivia_qa", "truthful_qa"
 ]
-
+PERF_DATASETS = [
-PERF_DATASETS = ["openqa", "flickr8k", "longalpaca", "random_dataset", "line_by_line", "custom", "speed_benchmark"]
+    "openqa", "flickr8k", "longalpaca", "random_dataset",
+    "line_by_line", "custom", "speed_benchmark"
+]
 
 # ---------------- perf 模式运行 ----------------
 def run_perf(
@@ -49,32 +62,37 @@ def run_perf(
     ]
 
     full_output = f"[Eval Started @ {timestamp}]\nCmd: {' '.join(command)}\n"
-    yield full_output, True, gr.update(value="Stop Evaluation")
+    yield full_output, True, gr.update(interactive=False), gr.update(visible=True)
 
     try:
         current_process = subprocess.Popen(
-            command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT,
+            command,
-            text=True, bufsize=1, start_new_session=True
+            stdout=subprocess.PIPE,
+            stderr=subprocess.STDOUT,
+            text=True,
+            bufsize=1,
+            start_new_session=True,   # 独立进程组，便于后续 killpg / psutil
         )
 
         for line in current_process.stdout:
             if should_stop:
                 break
             full_output += line
-            yield full_output, True, gr.update(value="Stop Evaluation")
+            yield full_output, True, gr.update(interactive=False), gr.update(visible=True)
 
         current_process.stdout.close()
         current_process.wait()
 
     except Exception as e:
         full_output += f"[Error] {e}\n"
-        yield full_output, False, gr.update(value="Run Evaluation")
+        yield full_output, False, gr.update(value="Run Evaluation", interactive=True), gr.update(visible=False)
 
     finally:
         current_process = None
 
     full_output += "[Eval Finished]\n"
 
+    # 自动启动可视化
     if "Evaluation Report" in output_choices:
         vis_port = 7901
         outputs_root = "./outputs"
@@ -101,7 +119,7 @@ def run_perf(
 
         full_output += f"[Visualization 👉] http://localhost:{vis_port}\n"
 
-    yield full_output, False, gr.update(value="Run Evaluation")
+    yield full_output, False, gr.update(value="Run Evaluation", interactive=True), gr.update(visible=False)
 
 # ---------------- eval 模式运行 ----------------
 def run_eval_tool(
@@ -132,26 +150,30 @@ def run_eval_tool(
         command += ["--limit", str(int(num_requests))]
 
     full_output = f"[Eval Started @ {timestamp}]\nCmd: {' '.join(command)}\n"
-    yield full_output, True, gr.update(value="Stop Evaluation")
+    yield full_output, True, gr.update(interactive=False), gr.update(visible=True)
 
     try:
         current_process = subprocess.Popen(
-            command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT,
+            command,
-            text=True, bufsize=1, start_new_session=True
+            stdout=subprocess.PIPE,
+            stderr=subprocess.STDOUT,
+            text=True,
+            bufsize=1,
+            start_new_session=True
         )
 
         for line in current_process.stdout:
             if should_stop:
                 break
             full_output += line
-            yield full_output, True, gr.update(value="Stop Evaluation")
+            yield full_output, True, gr.update(interactive=False), gr.update(visible=True)
 
         current_process.stdout.close()
         current_process.wait()
 
     except Exception as e:
         full_output += f"[Error] {e}\n"
-        yield full_output, False, gr.update(value="Run Evaluation")
+        yield full_output, False, gr.update(value="Run Evaluation", interactive=True), gr.update(visible=False)
 
     finally:
         current_process = None
@@ -184,15 +206,15 @@ def run_eval_tool(
 
         full_output += f"[Visualization 👉] http://localhost:{vis_port}\n"
 
-    yield full_output, False, gr.update(value="Run Evaluation")
+    yield full_output, False, gr.update(value="Run Evaluation", interactive=True), gr.update(visible=False)
 
 # ---------------- 停止函数 ----------------
-def stop_eval():
+def stop_eval() -> str:
     """
     彻底终止 current_process 及其全部子孙进程：
-    1. 先发 SIGINT（Ctrl‑C）尝试优雅退出
+    1. SIGINT（优雅退出，3 秒宽限）
-    2. 3 秒内仍存活的进程升级为 SIGKILL
+    2. 仍存活则 SIGKILL
-    3. 最后 wait() 主进程，防止僵尸
+    3. wait() 主进程，防止僵尸
     """
     global current_process, should_stop
     should_stop = True
@@ -202,34 +224,29 @@ def stop_eval():
 
     try:
         parent = psutil.Process(current_process.pid)
-        family = parent.children(recursive=True) + [parent]  # 整棵进程树
+        family = parent.children(recursive=True) + [parent]
 
-        # ── 1) 尝试优雅终止 ──────────────────────
+        # 1) SIGINT
         for p in family:
             p.send_signal(signal.SIGINT)
+        _, alive = psutil.wait_procs(family, timeout=3)
 
-        # 给 10 秒宽限期
+        # 2) SIGKILL
-        _, alive = psutil.wait_procs(family, timeout=10)
-
-        # ── 2) 强制 kill 仍存活的 ────────────────
         for p in alive:
             p.kill()
-        psutil.wait_procs(alive, timeout=10)
+        psutil.wait_procs(alive, timeout=3)
-
-        # ── 3) 回收僵尸，确保句柄关闭 ────────────
-        current_process.wait(timeout=10)
 
+        # 3) reap
+        current_process.wait(timeout=3)
         return "[✅ 已终止进程树 (SIGINT ➜ SIGKILL fallback)]\n"
 
-    except Exception as e:
+    except Exception as exc:
-        return f"[❌ 终止失败: {e}]\n"
+        return f"[❌ 终止失败: {exc}]\n"
 
     finally:
         current_process = None
 
-
+# ---------------- 控制器（仅负责启动） ----------------
-
-# ---------------- 控制器 ----------------
 def toggle_run(
     inputs, native, other, output_choices,
     api_url, api_token,
@@ -244,10 +261,9 @@ def toggle_run(
 
     if not inputs:
         msg = "[❌ 错误] 必须至少选择一个输入源（API、本地、基准或自定义）才能开始运行。\n"
-        yield msg, False, gr.update(value="Run Evaluation")
+        yield msg, False, gr.update(value="Run Evaluation", interactive=True), gr.update(visible=False)
         return
 
-    if not is_running:
     should_stop = False
     if run_mode == "perf":
         yield from run_perf(
@@ -268,11 +284,8 @@ def toggle_run(
             model_override
         )
     elif run_mode == "app":
-            yield "[⚠️ 当前为 app 模式，请手动打开 http://localhost:7901 查看报告]", False, gr.update(value="Run Evaluation")
+        info = "[⚠️ 当前为 app 模式，请手动打开 http://localhost:7901 查看报告]\n"
-    else:
+        yield info, False, gr.update(value="Run Evaluation", interactive=True), gr.update(visible=False)
-        msg = stop_eval()
-        yield msg, False, gr.update(value="Run Evaluation")
-
 
 # ---------------- 输入源互斥逻辑 ----------------
 def enforce_input_exclusive_and_toggle_fields(selected):
@@ -299,6 +312,7 @@ def enforce_input_exclusive_and_toggle_fields(selected):
 with gr.Blocks(title="EvalScope 全功能界面") as demo:
     is_running = gr.State(value=False)
 
+    # ── 顶栏：模式选择 ─────────────────────────────
     with gr.Group():
         with gr.Row():
             mode_dropdown = gr.Dropdown(
@@ -308,6 +322,7 @@ with gr.Blocks(title="EvalScope 全功能界面") as demo:
                 info="eval: 智力评测；perf: 性能评测；app: 可视化"
             )
 
+    # ── 输入源选择 ────────────────────────────────
     with gr.Group():
         with gr.Row():
             input_choices = gr.CheckboxGroup(
@@ -316,13 +331,22 @@ with gr.Blocks(title="EvalScope 全功能界面") as demo:
                 interactive=True
             )
 
+    # ── API 参数 ─────────────────────────────────
     with gr.Column(visible=False) as api_fields:
         api_url_input   = gr.Textbox(label="API 地址", placeholder="https://.../v1/chat/completions")
         api_token_input = gr.Textbox(label="Token 密钥", type="password", placeholder="sk-xxx")
         with gr.Accordion("运行参数（可选修改）", open=False):
             with gr.Row():
-                api_provider_dropdown = gr.Dropdown(label="API Provider", choices=["openai", "azure", "ollama", "gemini"], value="openai")
+                api_provider_dropdown = gr.Dropdown(
-                dataset_dropdown = gr.Dropdown(label="评测数据集 (--dataset)", choices=PERF_DATASETS, value=PERF_DATASETS[0])
+                    label="API Provider",
+                    choices=["openai", "azure", "ollama", "gemini"],
+                    value="openai"
+                )
+                dataset_dropdown = gr.Dropdown(
+                    label="评测数据集 (--dataset)",
+                    choices=PERF_DATASETS,
+                    value=PERF_DATASETS[0]
+                )
             model_override_input = gr.Textbox(label="自定义模型名 (--model)", placeholder="llm-name")
             with gr.Row():
                 max_tokens_slider = gr.Slider(label="Max Tokens", minimum=256, maximum=8192, step=256, value=1024)
@@ -330,18 +354,39 @@ with gr.Blocks(title="EvalScope 全功能界面") as demo:
             with gr.Row():
                 parallel_slider   = gr.Slider(label="并发请求数", minimum=1, maximum=100, step=1, value=1)
                 num_req_slider    = gr.Slider(label="请求条数", minimum=1, maximum=1000, step=1, value=100)
-            max_prompt_len_slider = gr.Slider(label="最大 Prompt 长度", minimum=2048, maximum=262144, step=512, value=15360)
+            max_prompt_len_slider = gr.Slider(
+                label="最大 Prompt 长度", minimum=2048, maximum=262144, step=512, value=15360
+            )
 
+    # ── 本地/外部模块勾选 ──────────────────────────
     with gr.Row():
         with gr.Column():
-            native_choices = gr.CheckboxGroup(label="启用本地模块", choices=["Model Adapter", "Data Adapter", "Evaluator", "Perf Monitor"])
+            native_choices = gr.CheckboxGroup(
+                label="启用本地模块",
+                choices=["Model Adapter", "Data Adapter", "Evaluator", "Perf Monitor"]
+            )
         with gr.Column():
-            other_choices = gr.CheckboxGroup(label="启用外部后端", choices=["OpenCompass", "VLMEvalKit", "RAGAS", "MTEB/CMTEB"])
+            other_choices = gr.CheckboxGroup(
+                label="启用外部后端",
+                choices=["OpenCompass", "VLMEvalKit", "RAGAS", "MTEB/CMTEB"]
+            )
 
-    output_choices = gr.CheckboxGroup(label="输出形式", choices=["Evaluation Report", "Gradio", "WandB", "Swanlab"])
+    # ── 输出开关 ─────────────────────────────────
-    run_button = gr.Button("Run Evaluation")
+    output_choices = gr.CheckboxGroup(
-    output_text = gr.TextArea(label="执行结果", lines=20, interactive=False, show_copy_button=True)
+        label="输出形式",
+        choices=["Evaluation Report", "Gradio", "WandB", "Swanlab"]
+    )
 
+    # ── Run & Stop 按钮 ─────────────────────────
+    run_button  = gr.Button("Run Evaluation",  variant="primary")
+    stop_button = gr.Button("Stop Evaluation", variant="stop", visible=False)
+
+    # ── 输出区域 ─────────────────────────────────
+    output_text = gr.TextArea(
+        label="执行结果", lines=20, interactive=False, show_copy_button=True
+    )
+
+    # ── 逻辑绑定 ─────────────────────────────────
     input_choices.change(
         fn=enforce_input_exclusive_and_toggle_fields,
         inputs=input_choices,
@@ -357,6 +402,7 @@ with gr.Blocks(title="EvalScope 全功能界面") as demo:
         outputs=dataset_dropdown
     )
 
+    # ---- Run 按钮（queue=True）----
     run_button.click(
         fn=toggle_run,
         inputs=[
@@ -370,9 +416,23 @@ with gr.Blocks(title="EvalScope 全功能界面") as demo:
             is_running,
             mode_dropdown
         ],
-        outputs=[output_text, is_running, run_button],
+        outputs=[output_text, is_running, run_button, stop_button],
-        show_progress=True
+        show_progress=True,
+        queue=True
     )
 
+    # ---- Stop 按钮（queue=False）----
+    def stop_action():
+        msg = stop_eval()
+        return msg, False, gr.update(value="Run Evaluation", interactive=True), gr.update(visible=False)
+
+    stop_button.click(
+        fn=stop_action,
+        inputs=None,
+        outputs=[output_text, is_running, run_button, stop_button],
+        queue=False
+    )
+
+# ---------------- 入口 ----------------
 if __name__ == "__main__":
     demo.launch(server_name="0.0.0.0", server_port=7900)

gradio_ui_2025_7_18.py

@@ -0,0 +1,378 @@
+import time
+import os
+import glob
+import threading
+import subprocess
+import gradio as gr
+import psutil
+import signal
+
+# ---------------- 全局进程句柄 ----------------
+current_process = None
+should_stop = False
+
+# ---------------- 可选数据集 ----------------
+EVAL_DATASETS = [
+    "arc", "bbh", "ceval", "cmmlu", "competition_math", "gsm8k",
+    "hellaswag", "humaneval", "mmlu", "mmlu_pro", "race",
+    "trivia_qa", "truthful_qa"
+]
+
+PERF_DATASETS = ["openqa", "flickr8k", "longalpaca", "random_dataset", "line_by_line", "custom", "speed_benchmark"]
+
+# ---------------- perf 模式运行 ----------------
+def run_perf(
+    inputs, native, other, output_choices,
+    api_url, api_token,
+    api_provider, dataset,
+    max_tokens, min_tokens, parallel_reqs,
+    max_prompt_len, num_requests,
+    model_override
+):
+    global current_process
+
+    timestamp = time.strftime("%Y%m%d-%H%M%S")
+    model_name = model_override.strip() or timestamp
+
+    command = [
+        "evalscope", "perf",
+        "--url", api_url.strip(),
+        "--api", api_provider,
+        "--model", model_name,
+        "--dataset", dataset,
+        "--max-tokens", str(int(max_tokens)),
+        "--min-tokens", str(int(min_tokens)),
+        "--parallel", str(int(parallel_reqs)),
+        "--max-prompt-length", str(int(max_prompt_len)),
+        "--number", str(int(num_requests)),
+        "--api-key", api_token.strip(),
+    ]
+
+    full_output = f"[Eval Started @ {timestamp}]\nCmd: {' '.join(command)}\n"
+    yield full_output, True, gr.update(value="Stop Evaluation")
+
+    try:
+        current_process = subprocess.Popen(
+            command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT,
+            text=True, bufsize=1, start_new_session=True
+        )
+
+        for line in current_process.stdout:
+            if should_stop:
+                break
+            full_output += line
+            yield full_output, True, gr.update(value="Stop Evaluation")
+
+        current_process.stdout.close()
+        current_process.wait()
+
+    except Exception as e:
+        full_output += f"[Error] {e}\n"
+        yield full_output, False, gr.update(value="Run Evaluation")
+
+    finally:
+        current_process = None
+
+    full_output += "[Eval Finished]\n"
+
+    if "Evaluation Report" in output_choices:
+        vis_port = 7901
+        outputs_root = "./outputs"
+        try:
+            latest_output = max(
+                glob.glob(os.path.join(outputs_root, "*")),
+                key=os.path.getmtime
+            )
+        except ValueError:
+            latest_output = outputs_root
+
+        vis_cmd = [
+            "evalscope", "app",
+            "--outputs", outputs_root,
+            "--server-name", "0.0.0.0",
+            "--server-port", str(vis_port),
+        ]
+        threading.Thread(
+            target=subprocess.Popen,
+            args=(vis_cmd,),
+            kwargs={"stdout": subprocess.DEVNULL, "stderr": subprocess.STDOUT},
+            daemon=True
+        ).start()
+
+        full_output += f"[Visualization 👉] http://localhost:{vis_port}\n"
+
+    yield full_output, False, gr.update(value="Run Evaluation")
+
+# ---------------- eval 模式运行 ----------------
+def run_eval_tool(
+    inputs, native, other, output_choices,
+    api_url, api_token,
+    api_provider, dataset,
+    max_tokens, min_tokens, parallel_reqs,
+    max_prompt_len, num_requests,
+    model_override
+):
+    global current_process
+
+    timestamp = time.strftime("%Y%m%d-%H%M%S")
+    model_name = model_override.strip() or timestamp
+
+    command = [
+        "evalscope", "eval",
+        "--model", model_name,
+        "--datasets", dataset
+    ]
+    if api_url.strip():
+        command += [
+            "--eval-type", "service",
+            "--api-url", api_url.strip(),
+            "--api-key", api_token.strip()
+        ]
+    if num_requests:
+        command += ["--limit", str(int(num_requests))]
+
+    full_output = f"[Eval Started @ {timestamp}]\nCmd: {' '.join(command)}\n"
+    yield full_output, True, gr.update(value="Stop Evaluation")
+
+    try:
+        current_process = subprocess.Popen(
+            command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT,
+            text=True, bufsize=1, start_new_session=True
+        )
+
+        for line in current_process.stdout:
+            if should_stop:
+                break
+            full_output += line
+            yield full_output, True, gr.update(value="Stop Evaluation")
+
+        current_process.stdout.close()
+        current_process.wait()
+
+    except Exception as e:
+        full_output += f"[Error] {e}\n"
+        yield full_output, False, gr.update(value="Run Evaluation")
+
+    finally:
+        current_process = None
+
+    full_output += "[Eval Finished]\n"
+
+    if "Evaluation Report" in output_choices:
+        vis_port = 7901
+        outputs_root = "./outputs"
+        try:
+            latest_output = max(
+                glob.glob(os.path.join(outputs_root, "*")),
+                key=os.path.getmtime
+            )
+        except ValueError:
+            latest_output = outputs_root
+
+        vis_cmd = [
+            "evalscope", "app",
+            "--outputs", outputs_root,
+            "--server-name", "0.0.0.0",
+            "--server-port", str(vis_port),
+        ]
+        threading.Thread(
+            target=subprocess.Popen,
+            args=(vis_cmd,),
+            kwargs={"stdout": subprocess.DEVNULL, "stderr": subprocess.STDOUT},
+            daemon=True
+        ).start()
+
+        full_output += f"[Visualization 👉] http://localhost:{vis_port}\n"
+
+    yield full_output, False, gr.update(value="Run Evaluation")
+
+# ---------------- 停止函数 ----------------
+def stop_eval():
+    """
+    彻底终止 current_process 及其全部子孙进程：
+    1. 先发 SIGINT（Ctrl‑C）尝试优雅退出
+    2. 3 秒内仍存活的进程升级为 SIGKILL
+    3. 最后 wait() 主进程，防止僵尸
+    """
+    global current_process, should_stop
+    should_stop = True
+
+    if not (current_process and current_process.poll() is None):
+        return "[⚠️ 无活动 evalscope 进程]\n"
+
+    try:
+        parent = psutil.Process(current_process.pid)
+        family = parent.children(recursive=True) + [parent]  # 整棵进程树
+
+        # ── 1) 尝试优雅终止 ──────────────────────
+        for p in family:
+            p.send_signal(signal.SIGINT)
+
+        # 给 3 秒宽限期
+        _, alive = psutil.wait_procs(family, timeout=3)
+
+        # ── 2) 强制 kill 仍存活的 ────────────────
+        for p in alive:
+            p.kill()
+        psutil.wait_procs(alive, timeout=3)
+
+        # ── 3) 回收僵尸，确保句柄关闭 ────────────
+        current_process.wait(timeout=3)
+
+        return "[✅ 已终止进程树 (SIGINT ➜ SIGKILL fallback)]\n"
+
+    except Exception as e:
+        return f"[❌ 终止失败: {e}]\n"
+
+    finally:
+        current_process = None
+
+
+
+# ---------------- 控制器 ----------------
+def toggle_run(
+    inputs, native, other, output_choices,
+    api_url, api_token,
+    api_provider, dataset,
+    max_tokens, min_tokens, parallel_reqs,
+    max_prompt_len, num_requests,
+    model_override,
+    is_running,
+    run_mode
+):
+    global should_stop
+
+    if not inputs:
+        msg = "[❌ 错误] 必须至少选择一个输入源（API、本地、基准或自定义）才能开始运行。\n"
+        yield msg, False, gr.update(value="Run Evaluation")
+        return
+
+    if not is_running:
+        should_stop = False
+        if run_mode == "perf":
+            yield from run_perf(
+                inputs, native, other, output_choices,
+                api_url, api_token,
+                api_provider, dataset,
+                max_tokens, min_tokens, parallel_reqs,
+                max_prompt_len, num_requests,
+                model_override
+            )
+        elif run_mode == "eval":
+            yield from run_eval_tool(
+                inputs, native, other, output_choices,
+                api_url, api_token,
+                api_provider, dataset,
+                max_tokens, min_tokens, parallel_reqs,
+                max_prompt_len, num_requests,
+                model_override
+            )
+        elif run_mode == "app":
+            yield "[⚠️ 当前为 app 模式，请手动打开 http://localhost:7901 查看报告]", False, gr.update(value="Run Evaluation")
+    else:
+        msg = stop_eval()
+        yield msg, False, gr.update(value="Run Evaluation")
+
+
+# ---------------- 输入源互斥逻辑 ----------------
+def enforce_input_exclusive_and_toggle_fields(selected):
+    order = ["API Models", "Local Models", "Benchmarks", "Custom Datasets"]
+    group1 = {"API Models", "Local Models"}
+    group2 = {"Benchmarks", "Custom Datasets"}
+
+    def keep_only_one(group):
+        filtered = [item for item in selected if item in group]
+        return filtered[-1:]
+
+    final_sel = set(selected)
+    final_sel -= group1
+    final_sel |= set(keep_only_one(group1))
+    final_sel -= group2
+    final_sel |= set(keep_only_one(group2))
+
+    final_list = [itm for itm in order if itm in final_sel]
+    input_update = gr.update() if list(selected) == final_list else gr.update(value=final_list)
+    api_field_update = gr.update(visible="API Models" in final_sel)
+    return input_update, api_field_update
+
+# ---------------- UI 构建 ----------------
+with gr.Blocks(title="EvalScope 全功能界面") as demo:
+    is_running = gr.State(value=False)
+
+    with gr.Group():
+        with gr.Row():
+            mode_dropdown = gr.Dropdown(
+                label="评测类型",
+                choices=["eval", "perf", "app"],
+                value="perf",
+                info="eval: 智力评测；perf: 性能评测；app: 可视化"
+            )
+
+    with gr.Group():
+        with gr.Row():
+            input_choices = gr.CheckboxGroup(
+                label="选择输入源",
+                choices=["API Models", "Local Models", "Benchmarks", "Custom Datasets"],
+                interactive=True
+            )
+
+    with gr.Column(visible=False) as api_fields:
+        api_url_input = gr.Textbox(label="API 地址", placeholder="https://.../v1/chat/completions")
+        api_token_input = gr.Textbox(label="Token 密钥", type="password", placeholder="sk-xxx")
+        with gr.Accordion("运行参数（可选修改）", open=False):
+            with gr.Row():
+                api_provider_dropdown = gr.Dropdown(label="API Provider", choices=["openai", "azure", "ollama", "gemini"], value="openai")
+                dataset_dropdown = gr.Dropdown(label="评测数据集 (--dataset)", choices=PERF_DATASETS, value=PERF_DATASETS[0])
+            model_override_input = gr.Textbox(label="自定义模型名 (--model)", placeholder="llm-name")
+            with gr.Row():
+                max_tokens_slider = gr.Slider(label="Max Tokens", minimum=256, maximum=8192, step=256, value=1024)
+                min_tokens_slider = gr.Slider(label="Min Tokens", minimum=0, maximum=4096, step=64, value=1024)
+            with gr.Row():
+                parallel_slider = gr.Slider(label="并发请求数", minimum=1, maximum=100, step=1, value=1)
+                num_req_slider = gr.Slider(label="请求条数", minimum=1, maximum=1000, step=1, value=100)
+            max_prompt_len_slider = gr.Slider(label="最大 Prompt 长度", minimum=2048, maximum=262144, step=512, value=15360)
+
+    with gr.Row():
+        with gr.Column():
+            native_choices = gr.CheckboxGroup(label="启用本地模块", choices=["Model Adapter", "Data Adapter", "Evaluator", "Perf Monitor"])
+        with gr.Column():
+            other_choices = gr.CheckboxGroup(label="启用外部后端", choices=["OpenCompass", "VLMEvalKit", "RAGAS", "MTEB/CMTEB"])
+
+    output_choices = gr.CheckboxGroup(label="输出形式", choices=["Evaluation Report", "Gradio", "WandB", "Swanlab"])
+    run_button = gr.Button("Run Evaluation")
+    output_text = gr.TextArea(label="执行结果", lines=20, interactive=False, show_copy_button=True)
+
+    input_choices.change(
+        fn=enforce_input_exclusive_and_toggle_fields,
+        inputs=input_choices,
+        outputs=[input_choices, api_fields]
+    )
+
+    mode_dropdown.change(
+        lambda mode: gr.update(
+            choices=EVAL_DATASETS if mode == "eval" else PERF_DATASETS,
+            value=EVAL_DATASETS[0] if mode == "eval" else PERF_DATASETS[0]
+        ),
+        inputs=mode_dropdown,
+        outputs=dataset_dropdown
+    )
+
+    run_button.click(
+        fn=toggle_run,
+        inputs=[
+            input_choices, native_choices, other_choices,
+            output_choices,
+            api_url_input, api_token_input,
+            api_provider_dropdown, dataset_dropdown,
+            max_tokens_slider, min_tokens_slider, parallel_slider,
+            max_prompt_len_slider, num_req_slider,
+            model_override_input,
+            is_running,
+            mode_dropdown
+        ],
+        outputs=[output_text, is_running, run_button],
+        show_progress=True
+    )
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7900)