diff --git a/gradio_ui copy.py b/gradio_ui copy.py new file mode 100644 index 0000000..79244c2 --- /dev/null +++ b/gradio_ui copy.py @@ -0,0 +1,286 @@ +import time +import os +import glob +import threading +import subprocess +import gradio as gr + +# ---------------- 全局进程句柄 ---------------- +current_process = None + + +# ---------------- 核心运行函数 ---------------- +def run_eval( + 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 +): + """ + 1. 动态拼装 evalscope perf 命令 + 2. 流式打印日志 + 3. （可选）启动可视化报告 + """ + 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 + ) + + for line in current_process.stdout: + 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" + + # ---------- 可视化报告 ---------- + if "Evaluation Report" in output_choices: + vis_port = 7861 + 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 + if current_process and current_process.poll() is None: + current_process.terminate() + current_process = None + return "[Stopped by user]\n" + return "[No active process]\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 +): + if not is_running: + yield from run_eval( + 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_row_update = gr.Row.update(visible=show_api_fields) + + show_run_params = bool(final_sel & {"API Models", "Local Models"}) + # 👇 修复：用通用 gr.update 而非 Column.update + run_params_update = gr.update(visible=show_run_params) + + return input_update, api_row_update, run_params_update + + +# ---------------- 构建 Gradio UI ---------------- +with gr.Blocks(title="EvalScope 全功能界面") as demo: + is_running = gr.State(value=False) + + # ===== 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 & Token ===== + with gr.Row(visible=False) as api_fields: + api_url_input = gr.Textbox( + label="API 地址", + placeholder="https://api.example.com/v1/chat" + ) + api_token_input = gr.Textbox( + label="Token 密钥", + type="password", + placeholder="sk-xxx" + ) + + # ===== 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"] + ) + + # ===== 运行参数（可隐藏） ===== + with gr.Column(visible=False) as run_params_section: + 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", "gsm8k", "mmlu", "truthfulqa"], + 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 + ) + + # ===== 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, run_params_section] + ) + + 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 + ], + outputs=[output_text, is_running, run_button], + show_progress=True + ) + +if __name__ == "__main__": + demo.launch(server_name="0.0.0.0", server_port=7900)