.

Dockerfile.ok

@@ -1,59 +0,0 @@
-########################
-# 1️⃣  Build stage
-########################
-FROM python:3.10-slim AS builder
-ENV DEBIAN_FRONTEND=noninteractive
-
-# 系统依赖：编译 C/C++ 扩展 & git 拉源码
-RUN apt-get update && \
-    apt-get install -y --no-install-recommends \
-        build-essential  \
-        git              \
-        curl             && \
-    rm -rf /var/lib/apt/lists/*
-
-WORKDIR /build
-
-# 先复制 requirements 目录，利用 Docker layer cache
-COPY evalscope.0.17.0/requirements ./evalscope/requirements
-
-# 更新 pip & 预装常用 build tools
-RUN pip install --upgrade pip setuptools wheel
-
-# 把所有依赖装进 /install 目录（✳️ 关键）
-RUN pip install --no-cache-dir --prefix=/install \
-        -r ./evalscope/requirements/framework.txt \
-        -r ./evalscope/requirements/opencompass.txt \
-        -r ./evalscope/requirements/vlmeval.txt \
-        -r ./evalscope/requirements/aigc.txt \
-        -r ./evalscope/requirements/app.txt \
-        -r ./evalscope/requirements/dev.txt \
-        -r ./evalscope/requirements/docs.txt \
-        -r ./evalscope/requirements/perf.txt \
-        -r ./evalscope/requirements/rag.txt
-
-# 安装 evalscope 本体（非 editable，减少后续 COPY）
-COPY evalscope.0.17.0/ ./evalscope
-RUN pip install --no-cache-dir --prefix=/install ./evalscope
-
-# 仅带上入口脚本
-COPY gradio_ui.py .
-
-########################
-# 2️⃣  Runtime stage
-########################
-FROM python:3.10-slim AS runtime
-ENV DEBIAN_FRONTEND=noninteractive
-
-# 把 builder 阶段产物注入到 /usr/local 下
-# /install/bin 里可能有可执行文件；site-packages 在 /install/lib/…
-COPY --from=builder /install /usr/local
-COPY --from=builder /build/gradio_ui.py /app/gradio_ui.py
-
-WORKDIR /app
-EXPOSE 7900 7901
-
-# 可选：彻底关闭 pip 缓存，避免 runtime 再次安装时产生垃圾
-ENV PIP_NO_CACHE_DIR=1
-
-CMD ["python3", "gradio_ui.py"]

gradio_ui.py

@@ -17,6 +17,7 @@ import subprocess
 import gradio as gr
 import psutil
 import signal
+import shlex
 
 # ---------------- 全局进程句柄 ----------------
 current_process = None
@@ -40,7 +41,8 @@ def run_perf(
     api_provider, dataset,
     max_tokens, min_tokens, parallel_reqs,
     max_prompt_len, num_requests,
-    model_override
+    model_override,
+    extra_args
 ):
     global current_process
 
@@ -61,6 +63,10 @@ def run_perf(
         "--api-key", api_token.strip(),
     ]
 
+    
+    if extra_args.strip():
+        command += shlex.split(extra_args.strip())
+
     full_output = f"[Eval Started @ {timestamp}]\nCmd: {' '.join(command)}\n"
     yield full_output, True, gr.update(interactive=False), gr.update(visible=True)
 
@@ -128,7 +134,8 @@ def run_eval_tool(
     api_provider, dataset,
     max_tokens, min_tokens, parallel_reqs,
     max_prompt_len, num_requests,
-    model_override
+    model_override, extra_args
+    
 ):
     global current_process
 
@@ -149,6 +156,10 @@ def run_eval_tool(
     if num_requests:
         command += ["--limit", str(int(num_requests))]
 
+
+    if extra_args.strip():
+        command += shlex.split(extra_args.strip())
+
     full_output = f"[Eval Started @ {timestamp}]\nCmd: {' '.join(command)}\n"
     yield full_output, True, gr.update(interactive=False), gr.update(visible=True)
 
@@ -254,6 +265,7 @@ def toggle_run(
     max_tokens, min_tokens, parallel_reqs,
     max_prompt_len, num_requests,
     model_override,
+    extra_args,
     is_running,
     run_mode
 ):
@@ -272,7 +284,8 @@ def toggle_run(
             api_provider, dataset,
             max_tokens, min_tokens, parallel_reqs,
             max_prompt_len, num_requests,
-            model_override
+            model_override,
+            extra_args
         )
     elif run_mode == "eval":
         yield from run_eval_tool(
@@ -281,7 +294,8 @@ def toggle_run(
             api_provider, dataset,
             max_tokens, min_tokens, parallel_reqs,
             max_prompt_len, num_requests,
-            model_override
+            model_override,
+            extra_args
         )
     elif run_mode == "app":
         info = "[⚠️ 当前为 app 模式，请手动打开 http://localhost:7901 查看报告]\n"
@@ -348,6 +362,7 @@ with gr.Blocks(title="EvalScope 全功能界面") as demo:
                     value=PERF_DATASETS[0]
                 )
             model_override_input = gr.Textbox(label="自定义模型名 (--model)", placeholder="llm-name")
+            extra_args_input = gr.Textbox(label="额外 EvalScope 参数", placeholder="例如: --disable-cache --temperature 0.7")
             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)
@@ -413,6 +428,7 @@ with gr.Blocks(title="EvalScope 全功能界面") as demo:
             max_tokens_slider, min_tokens_slider, parallel_slider,
             max_prompt_len_slider, num_req_slider,
             model_override_input,
+            extra_args_input,
             is_running,
             mode_dropdown
         ],

gradio_ui_2025_7_18.py

@@ -1,378 +0,0 @@
-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)

gradio_ui_old.py

@@ -1,402 +0,0 @@
-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
-
-# ---------------- 核心运行函数 ----------------
-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")
-
-
-# ---------------- 停止函数 ----------------
-def stop_eval():
-    global current_process, should_stop
-    should_stop = True
-
-    if current_process and current_process.poll() is None:
-        try:
-            pgid = os.getpgid(current_process.pid)
-            os.killpg(pgid, signal.SIGINT)  # ✅ 优雅终止
-            time.sleep(2)
-            if current_process.poll() is None:
-                os.killpg(pgid, signal.SIGKILL)  # ❗ 强制终止
-            return "[✅ 已发送终止信号 (SIGINT → SIGKILL fallback)]\n"
-        except Exception as e:
-            return f"[❌ 终止失败: {e}]\n"
-        finally:
-            current_process = None
-    else:
-        return "[⚠️ 无活动 evalscope 进程]\n"
-
-
-
-# ---------------- Run/Stop 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  # 👈 增加这个参数
-):
-    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
-            )
-    else:
-        msg = stop_eval()
-        yield msg, False, gr.update(value="Run Evaluation")
-
-
-# ---------------- 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)
-
-    show_api_fields = "API Models" in final_sel
-    api_field_update = gr.update(visible=show_api_fields)  # ✅ 正确
-
-    return input_update, api_field_update
-
-
-
-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")
-
-
-
-
-# ---------------- 构建 Gradio UI ----------------
-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",
-                info="eval: 智力评测；perf: 推理性能；app: Web 可视化",
-                choices=["eval", "perf", "app"],
-                value="perf"
-            )
-
-    # ===== 输入源 =====
-    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
-            )
-
-    # ===== API 地址 & 运行参数（统一控制显示） =====
-    with gr.Column(visible=False) as api_fields:
-        api_url_input = gr.Textbox(
-            label="API 地址",
-            placeholder="https://ai.aiszaiai.com/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 (--api)",
-                    choices=["openai", "azure", "ollama", "gemini"],
-                    value="openai"
-                )
-                dataset_dropdown = gr.Dropdown(
-                    label="评测数据集 (--dataset)",
-                    choices=["openqa", "flickr8k", "longalpaca", "random_dataset", "line_by_line", "custom", "speed_benchmark"],
-                    value="openqa"
-                )
-            model_override_input = gr.Textbox(
-                label="自定义模型名 (--model)，留空则使用时间戳",
-                placeholder="e.g. my-llm-7b"
-            )
-            with gr.Row():
-                max_tokens_slider = gr.Slider(
-                    label="Max Tokens (--max-tokens)",
-                    minimum=256, maximum=8192, step=256, value=1024
-                )
-                min_tokens_slider = gr.Slider(
-                    label="Min Tokens (--min-tokens)",
-                    minimum=0, maximum=4096, step=64, value=1024
-                )
-            with gr.Row():
-                parallel_slider = gr.Slider(
-                    label="并发请求数 (--parallel)",
-                    minimum=1, maximum=16, step=1, value=1
-                )
-                num_req_slider = gr.Slider(
-                    label="请求条数 (--number)",
-                    minimum=1, maximum=1000, step=1, value=100
-                )
-            max_prompt_len_slider = gr.Slider(
-                label="最大 Prompt 长度 (--max-prompt-length)",
-                minimum=2048, maximum=32768, step=512, value=15360
-            )
-
-    # ===== 本地/外部组件 =====
-    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"]
-            )
-
-    # ===== 输出形式 =====
-    output_choices = gr.CheckboxGroup(
-        label="输出形式",
-        choices=["Evaluation Report", "Gradio", "WandB", "Swanlab"]
-    )
-
-    # ===== 控制按钮 & 日志 =====
-    run_button = gr.Button("Run Evaluation")
-    output_text = gr.TextArea(
-        label="执行结果",
-        lines=20,
-        interactive=False,
-        show_copy_button=True
-    )
-
-    # ===== 绑定事件 =====
-    input_choices.change(
-        fn=enforce_input_exclusive_and_toggle_fields,
-        inputs=input_choices,
-        outputs=[input_choices, api_fields]  # ✅ 只输出这两个
-    )
-
-    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  # ✅ 改为新的变量
-        ],
-        outputs=[output_text, is_running, run_button],
-        show_progress=True
-    )
-
-if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7900)