116 lines
6.2 KiB
Python
116 lines
6.2 KiB
Python
import os, json, datetime, textwrap, requests, gradio as gr
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from pathlib import Path
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#───────────────────────────────────────────────────────────────────────────────
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# 1. 服务端 & 权重路径
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#───────────────────────────────────────────────────────────────────────────────
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API_URL = "http://localhost:30000/generate"
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API_KEY = "token-abc123"
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MODEL_PATH = Path("/root/.cradle/Alibaba/Qwen3-30B-A3B-Base") # ← 改成 supervisor 里传的路径
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# 自动读取权重里的名字，若失败就退回目录名
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def detect_model_name(model_path: Path) -> str:
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cfg = model_path / "config.json"
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if cfg.exists():
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with open(cfg, "r", encoding="utf-8") as f:
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data = json.load(f)
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# Qwen / LLaMA / GPT‑NeoX … 都有 "architectures" 或 "model_type"
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return data.get("architectures", [None])[0] or data.get("model_type") or model_path.name
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return model_path.name
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MODEL_NAME = detect_model_name(MODEL_PATH)
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def now():
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return datetime.datetime.now().strftime("%H:%M:%S")
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#───────────────────────────────────────────────────────────────────────────────
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# 2. 调用 SGLang /generate
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#───────────────────────────────────────────────────────────────────────────────
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def call_backend(text, sampling):
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payload = {"model": MODEL_NAME, "text": text, "sampling_params": sampling}
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print(f"\n🟡 [{now()} payload] {json.dumps(payload, ensure_ascii=False)[:400]}…")
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resp = requests.post(
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API_URL,
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headers={"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"},
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json=payload, timeout=180
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)
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if resp.status_code != 200:
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return f"[HTTP {resp.status_code}] {resp.text[:300]}"
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try:
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return json.loads(resp.text).get("text", "").strip() or "[⚠ 后端无 text]"
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except json.JSONDecodeError:
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snippet = textwrap.shorten(resp.text, 300, placeholder=" …")
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return f"[⚠ JSON 解析失败] {snippet}"
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#───────────────────────────────────────────────────────────────────────────────
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# 3. Gradio 主函数
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#───────────────────────────────────────────────────────────────────────────────
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def chat(
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user_msg, history,
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max_new, temperature, top_p, top_k,
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rep_pen, pres_pen, stop_raw
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):
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stop = [s.strip() for s in stop_raw.split(",") if s.strip()] or None
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sampling = {
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"max_new_tokens": int(max_new),
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"temperature": temperature,
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"top_p": top_p,
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"top_k": int(top_k),
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"repetition_penalty": rep_pen,
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"presence_penalty": pres_pen,
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}
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if stop: sampling["stop"] = stop
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return call_backend(user_msg, sampling)
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#───────────────────────────────────────────────────────────────────────────────
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# 4. Gradio UI
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#───────────────────────────────────────────────────────────────────────────────
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with gr.Blocks(title="Base 模型对话界面") as demo:
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gr.Markdown(f"## 💬 Base 模型对话界面 \n*正在使用权重* **{MODEL_PATH.name}**")
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# ── 采样参数控件 ───────────────────────────────────────────────────────────
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with gr.Row():
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max_new = gr.Slider(32, 32768, 2048, label="max_new_tokens")
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temperature = gr.Slider(0.0, 1.5, 0.8, step=0.05, label="temperature")
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with gr.Row():
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top_p = gr.Slider(0.0, 1.0, 0.95, step=0.01, label="top_p")
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top_k = gr.Slider(0, 200, 50, step=1, label="top_k")
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with gr.Row():
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rep_pen = gr.Slider(0.8, 2.0, 1.05, step=0.01, label="repetition_penalty")
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pres_pen = gr.Slider(0.0, 2.0, 0.0, step=0.05, label="presence_penalty")
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stop_text = gr.Textbox("", label="stop 序列（逗号分隔）", placeholder="如: ###,END")
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# ── Chatbot & 按钮 ────────────────────────────────────────────────────────
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ping_btn = gr.Button("🔁 测试 API")
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ping_out = gr.Textbox(label="API 测试结果", interactive=False)
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chat_ui = gr.ChatInterface(
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fn=chat,
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additional_inputs=[max_new, temperature, top_p, top_k, rep_pen, pres_pen, stop_text],
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type="messages"
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)
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def ping_api(max_new, temperature, top_p, top_k, rep_pen, pres_pen, stop_raw):
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stop = [s.strip() for s in stop_raw.split(",") if s.strip()] or None
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sampling = {
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"max_new_tokens": int(max_new),
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"temperature": temperature,
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"top_p": top_p,
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"top_k": int(top_k),
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"repetition_penalty": rep_pen,
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"presence_penalty": pres_pen,
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**({"stop": stop} if stop else {})
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}
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return call_backend("Ping?", sampling)[:200]
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ping_btn.click(
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fn=ping_api,
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inputs=[max_new, temperature, top_p, top_k, rep_pen, pres_pen, stop_text],
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outputs=ping_out
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)
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demo.launch(server_name="0.0.0.0", server_port=30001)
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