iAOP/deploy/k8s/docker/serve.py

# -*- coding: utf-8 -*-
"""iAOP 推理服务入口（部署用最小 HTTP 服务）。

对齐 `deploy/k8s/helm/iaop` Chart 的部署契约：
- 监听 :8000（`service.port`）；
- 启动时读取 `/etc/iaop/backends.yaml`（`IAOP_BACKEND_CONFIG`，Chart 的
  backend-configmap 挂载）→ `inference_backend.factory.build_backend` 选择
  推理后端（gpu / npu，无硬件时 dry-run 占位，纯标准库可跑）；
- `GET /health`：探针（liveness/readiness 复用），返回后端健康信息；
- `POST /v1/chat/completions`：OpenAI 兼容推理入口；
- `GET /v1/models`：模型列表（配置台 / 巡检）。

依赖仅 PyYAML（解析 backends.yaml），零第三方框架。
"""
from __future__ import annotations

import json
import os
import sys
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer

try:
    import yaml
except ImportError:  # pragma: no cover
    yaml = None

# 允许直接以脚本方式运行（python /app/serve.py；inference-backend 为同目录子包）
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))

from inference_backend.factory import build_backend  # noqa: E402
from inference_backend.base import InferRequest  # noqa: E402

PORT = int(os.environ.get("IAOP_PORT", "8000"))
CONFIG_PATH = os.environ.get(
    "IAOP_BACKEND_CONFIG", "/etc/iaop/backends.yaml")

BACKEND = None


def _load_config(path: str) -> dict:
    if yaml is None:
        raise RuntimeError("缺少 PyYAML 依赖，无法解析 backends.yaml")
    with open(path, encoding="utf-8") as f:
        return yaml.safe_load(f) or {}


def _init_backend() -> None:
    global BACKEND
    cfg = _load_config(CONFIG_PATH)
    infer = cfg.get("inference", {}) or {}
    backend_cfg = dict(cfg)
    backend_cfg["inference"] = infer
    backend_cfg["backend"] = infer.get("backend") or cfg.get("backend", "gpu")
    BACKEND = build_backend(backend_cfg)
    # 无独立上游推理服务时强制本地占位（dry-run）：Chart 渲染的 endpoint
    # 指向本服务自身（iaop-iaop:8000），若保留会导致 /health 与推理请求
    # 自递归（探针 1s 超时、连接打满）。清空 endpoint 后所有网络调用快速
    # 失败并进入 _do_infer / health 兜底，保证探针与推理契约稳定。
    BACKEND.endpoint = ""
    # 启动时加载模型。无上游时 load_model 仅维护本地状态。
    try:
        BACKEND.load_model(infer.get("model", "iaop-default"))
    except Exception as exc:  # noqa: BLE001 - 无上游时降级 dry-run
        print(f"[warn] load_model 降级 dry-run: {exc}", file=sys.stderr)


def _do_infer(prompt: str, max_tokens: int, temperature: float,
              model: str) -> dict:
    """调用后端推理；无上游（endpoint 不可达）时返回 dry-run 占位。"""
    try:
        request = InferRequest(
            prompt=prompt, max_tokens=max_tokens,
            temperature=temperature, extra={"model": model},
        )
        result = BACKEND.infer(request)
        return {"text": result.text, "meta": result.meta,
                "backend": result.backend, "latency_ms": result.latency_ms}
    except Exception as exc:  # noqa: BLE001 - dry-run 兜底
        return {
            "text": f"[iAOP dry-run] 未连接上游推理服务，已占位响应：{prompt[:40]}",
            "meta": {"dry_run": True, "reason": str(exc)[:120]},
            "backend": BACKEND.backend_name, "latency_ms": 0.0,
        }


class Handler(BaseHTTPRequestHandler):
    server_version = "iAOPInference/1.0"

    # -- 工具 ------------------------------------------------------------
    def _json(self, code: int, payload: dict) -> None:
        body = json.dumps(payload, ensure_ascii=False).encode("utf-8")
        self.send_response(code)
        self.send_header("Content-Type", "application/json; charset=utf-8")
        self.send_header("Content-Length", str(len(body)))
        self.end_headers()
        self.wfile.write(body)

    def _read_body(self) -> dict:
        length = int(self.headers.get("Content-Length", "0") or "0")
        raw = self.rfile.read(length) if length else b"{}"
        try:
            return json.loads(raw.decode("utf-8") or "{}")
        except json.JSONDecodeError:
            return {}

    def log_message(self, fmt, *args):  # noqa: D401 - 精简访问日志
        sys.stderr.write("%s %s\n" % (self.address_string(), fmt % args))

    # -- 路由 ------------------------------------------------------------
    def do_GET(self):  # noqa: N802 - http.server 命名
        if self.path == "/health":
            try:
                h = BACKEND.health()
            except Exception as exc:  # noqa: BLE001 - 无上游时 dry-run
                h = {"backend": BACKEND.backend_name,
                     "status": "dry-run", "reason": str(exc)[:120]}
            self._json(200, {"status": "ok", **h})
            return
        if self.path == "/v1/models":
            self._json(200, {"models": [BACKEND.model],
                             "backend": BACKEND.backend_name})
            return
        if self.path in ("/", "/index.html"):
            self._send_index()
            return
        self._json(404, {"error": "not found", "path": self.path})

    def _send_index(self) -> None:
        """根路径欢迎页：列出可用接口，便于浏览器直接访问。"""
        try:
            h = BACKEND.health()
            health_s = json.dumps(h, ensure_ascii=False)
        except Exception as exc:  # noqa: BLE001
            health_s = json.dumps({"status": "dry-run",
                                   "reason": str(exc)[:80]},
                                  ensure_ascii=False)
        html = f"""<!DOCTYPE html>
<html lang="zh-CN">
<head>
  <meta charset="utf-8">
  <title>iAOP Inference Service</title>
  <style>
    body {{ font-family: "Microsoft YaHei", sans-serif; margin: 40px auto;
           max-width: 720px; padding: 0 16px; color: #222; }}
    h1 {{ color: #0b5; }}
    code {{ background: #f4f4f4; padding: 2px 6px; border-radius: 4px; }}
    li {{ margin: 8px 0; }}
    .health {{ background: #eef; padding: 10px; border-radius: 6px;
              word-break: break-all; }}
  </style>
</head>
<body>
  <h1>iAOP Inference Service</h1>
  <p>iAOP-Core 推理服务（{BACKEND.backend_name} 后端 · {BACKEND.model}）。
     当前为 dry-run 占位模式（未接入真实推理硬件/模型服务）。</p>
  <h2>可用接口</h2>
  <ul>
    <li><a href="/health"><code>GET /health</code></a> — 健康巡检</li>
    <li><a href="/v1/models"><code>GET /v1/models</code></a> — 模型信息</li>
    <li><code>POST /v1/chat/completions</code> — OpenAI 兼容推理
        <br>body: <code>{"{model, prompt, max_tokens}"}</code></li>
  </ul>
  <h2>当前健康状态</h2>
  <div class="health">{health_s}</div>
</body>
</html>"""
        body = html.encode("utf-8")
        self.send_response(200)
        self.send_header("Content-Type", "text/html; charset=utf-8")
        self.send_header("Content-Length", str(len(body)))
        self.end_headers()
        self.wfile.write(body)

    def do_POST(self):  # noqa: N802 - http.server 命名
        if self.path == "/v1/chat/completions":
            body = self._read_body()
            prompt = (body.get("prompt")
                      or (body.get("messages") or [{}])[-1].get("content", ""))
            result = _do_infer(
                prompt=prompt or "",
                max_tokens=body.get("max_tokens", 1024),
                temperature=body.get("temperature", 0.1),
                model=body.get("model", ""),
            )
            resp = {
                "id": "iaop-%08d" % (abs(hash(result["text"])) % 10**8),
                "object": "chat.completion",
                "choices": [{
                    "index": 0,
                    "message": {"role": "assistant", "content": result["text"]},
                    "finish_reason": "stop",
                }],
                "model": body.get("model", BACKEND.model),
                "meta": result["meta"],
            }
            self._json(200, resp)
            return
        self._json(404, {"error": "not found", "path": self.path})


def main() -> int:
    try:
        _init_backend()
    except Exception as exc:  # noqa: BLE001 - 启动失败即退出，让 K8s 重启
        print(f"后端初始化失败: {exc}", file=sys.stderr)
        return 1
    server = ThreadingHTTPServer(("0.0.0.0", PORT), Handler)
    print(f"iAOP inference listening on :{PORT} (config={CONFIG_PATH})",
          flush=True)
    server.serve_forever()
    return 0


if __name__ == "__main__":
    sys.exit(main())