143 lines
4.6 KiB
Python
143 lines
4.6 KiB
Python
import time
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import gradio as gr
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import subprocess
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# 全局变量：当前子进程
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current_process = None
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# 启动 evalscope 的逻辑（支持 yield 输出）
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def run_eval(inputs, native, other, outputs, api_url, api_token):
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global current_process
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timestamp = time.strftime("%Y%m%d-%H%M%S")
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command = [
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"evalscope", "perf",
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"--url", api_url.strip(),
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"--api", "openai",
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"--model", timestamp,
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"--dataset", "openqa",
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"--max-tokens", "1024",
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"--min-tokens", "1024",
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"--parallel", "1",
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"--max-prompt-length", "15360",
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"--number", "100",
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"--api-key", api_token.strip(),
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]
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full_output = f"[Eval Started @ {timestamp}]\n"
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yield full_output, True, gr.update(value="Stop Evaluation")
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try:
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current_process = subprocess.Popen(
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command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True, bufsize=1
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)
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for line in current_process.stdout:
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full_output += line
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yield full_output, True, gr.update(value="Stop Evaluation")
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current_process.stdout.close()
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current_process.wait()
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except Exception as e:
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full_output += f"[Error] {str(e)}\n"
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yield full_output, False, gr.update(value="Run Evaluation")
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finally:
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current_process = None
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full_output += "[Eval Finished]\n"
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yield full_output, False, gr.update(value="Run Evaluation")
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# 停止当前 evalscope 子进程
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def stop_eval():
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global current_process
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if current_process and current_process.poll() is None:
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current_process.terminate()
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current_process = None
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return "[Stopped by user]\n"
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return "[No active process]\n"
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# Run/Stop 按钮控制器（必须是 generator）
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def toggle_run(inputs, native, other, outputs, api_url, api_token, is_running):
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if not is_running:
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yield from run_eval(inputs, native, other, outputs, api_url, api_token)
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else:
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msg = stop_eval()
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yield msg, False, gr.update(value="Run Evaluation")
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# 控制输入互斥逻辑
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def enforce_input_exclusive_and_toggle_fields(selected):
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group1 = {"API Models", "Local Models"}
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group2 = {"Benchmarks", "Custom Datasets"}
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def keep_only_one(group):
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filtered = [item for item in selected if item in group]
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return filtered[-1:]
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final_selection = set(selected)
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final_selection -= group1
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final_selection |= set(keep_only_one(group1))
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final_selection -= group2
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final_selection |= set(keep_only_one(group2))
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show_api_fields = "API Models" in final_selection
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return (
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gr.update(value=list(final_selection)),
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gr.Row.update(visible=show_api_fields)
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)
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# 构建 Gradio UI
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with gr.Blocks(title="EvalScope 全功能界面") as demo:
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is_running = gr.State(value=False) # 当前运行状态
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with gr.Group():
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with gr.Row():
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input_choices = gr.CheckboxGroup(
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label="选择输入源",
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choices=["API Models", "Local Models", "Benchmarks", "Custom Datasets"],
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interactive=True
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)
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with gr.Row(visible=False) as api_fields:
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api_url_input = gr.Textbox(label="API 地址", placeholder="https://api.example.com/v1/chat")
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api_token_input = gr.Textbox(label="Token 密钥", type="password", placeholder="sk-xxx")
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with gr.Row():
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with gr.Column():
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native_choices = gr.CheckboxGroup(
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label="启用本地模块",
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choices=["Model Adapter", "Data Adapter", "Evaluator", "Perf Monitor"]
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)
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with gr.Column():
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other_choices = gr.CheckboxGroup(
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label="启用外部后端",
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choices=["OpenCompass", "VLMEvalKit", "RAGAS", "MTEB/CMTEB"]
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)
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with gr.Row():
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output_choices = gr.CheckboxGroup(
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label="输出形式",
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choices=["Evaluation Report", "Gradio", "WandB", "Swanlab"]
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)
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run_button = gr.Button("Run Evaluation")
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output_text = gr.TextArea(label="执行结果", lines=20, interactive=False, show_copy_button=True)
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input_choices.change(
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fn=enforce_input_exclusive_and_toggle_fields,
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inputs=input_choices,
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outputs=[input_choices, api_fields]
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)
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run_button.click(
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fn=toggle_run,
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inputs=[
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input_choices, native_choices, other_choices,
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output_choices, api_url_input, api_token_input, is_running
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],
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outputs=[output_text, is_running, run_button],
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show_progress=True
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)
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if __name__ == '__main__':
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demo.launch(server_name="0.0.0.0", server_port=7900)
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