26-7-31-1

2026-07-31 12:27:41 +08:00
commit 9b8b8b57b3
142 changed files with 22408 additions and 0 deletions
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+"""OpenAI 兼容 LLM 客户端（DeepSeek / Qwen）。支持 .env + 管理端运行时覆盖。"""
+from __future__ import annotations
+
+import json
+import logging
+import re
+from typing import Any
+
+import httpx
+
+from app.config import Settings, get_settings
+from app.services.llm_runtime import get_runtime_llm
+
+logger = logging.getLogger(__name__)
+
+
+class LlmClient:
+    def __init__(self, settings: Settings | None = None):
+        self.settings = settings or get_settings()
+
+    def _effective_key(self) -> str:
+        rt = get_runtime_llm()
+        if rt.api_key is not None:
+            return rt.api_key.strip()
+        return (self.settings.llm_api_key or "").strip()
+
+    def _effective_base_url(self) -> str:
+        rt = get_runtime_llm()
+        if rt.api_base_url:
+            return rt.api_base_url.rstrip("/")
+        return (self.settings.llm_base_url or "https://api.deepseek.com").rstrip("/")
+
+    def _effective_model(self) -> str:
+        rt = get_runtime_llm()
+        if rt.model:
+            return rt.model
+        return self.settings.llm_model or "deepseek-chat"
+
+    def _effective_temperature(self, override: float | None = None) -> float:
+        if override is not None:
+            return override
+        rt = get_runtime_llm()
+        if rt.temperature is not None:
+            return float(rt.temperature)
+        return float(self.settings.llm_temperature)
+
+    @property
+    def enabled(self) -> bool:
+        """管理端 enabled=false 强制关闭；否则有可用 API Key 即启用。"""
+        key = self._effective_key()
+        if not key:
+            return False
+        rt = get_runtime_llm()
+        if rt.enabled is False:
+            return False
+        if rt.enabled is True:
+            return True
+        # 未下发 enabled 时：有 key（env 或 runtime）即视为可用
+        return True
+
+    def info(self) -> dict[str, Any]:
+        rt = get_runtime_llm()
+        return {
+            "enabled": self.enabled,
+            "api_key_configured": bool(self._effective_key()),
+            "api_base_url": self._effective_base_url(),
+            "model": self._effective_model(),
+            "temperature": self._effective_temperature(),
+            "source": rt.source if (rt.api_key or rt.enabled is not None) else "env",
+        }
+
+    def chat(self, messages: list[dict[str, str]], temperature: float | None = None) -> str:
+        if not self.enabled:
+            raise RuntimeError("未配置 LLM（请在管理端「AI 配置」启用并填写 API Key，或设置 ai-service/.env 的 LLM_API_KEY）")
+        base = self._effective_base_url()
+        if base.endswith("/v1"):
+            url = base + "/chat/completions"
+        else:
+            url = base + "/v1/chat/completions"
+        payload = {
+            "model": self._effective_model(),
+            "temperature": self._effective_temperature(temperature),
+            "messages": messages,
+        }
+        headers = {
+            "Authorization": f"Bearer {self._effective_key()}",
+            "Content-Type": "application/json",
+        }
+        with httpx.Client(timeout=90.0) as client:
+            resp = client.post(url, headers=headers, json=payload)
+            if resp.status_code >= 400:
+                raise RuntimeError(f"LLM HTTP {resp.status_code}: {resp.text[:300]}")
+            data = resp.json()
+            content = (
+                data.get("choices", [{}])[0]
+                .get("message", {})
+                .get("content", "")
+            )
+            if not content:
+                raise RuntimeError("LLM 返回空内容")
+            return content.strip()
+
+    def chat_json(self, messages: list[dict[str, str]]) -> dict[str, Any]:
+        text = self.chat(messages, temperature=0.2)
+        return extract_json(text)
+
+
+def extract_json(text: str) -> dict[str, Any]:
+    text = text.strip()
+    try:
+        return json.loads(text)
+    except json.JSONDecodeError:
+        pass
+    fence = re.search(r"```(?:json)?\s*([\s\S]*?)```", text)
+    if fence:
+        try:
+            return json.loads(fence.group(1).strip())
+        except json.JSONDecodeError:
+            pass
+    start, end = text.find("{"), text.rfind("}")
+    if start >= 0 and end > start:
+        try:
+            return json.loads(text[start : end + 1])
+        except json.JSONDecodeError:
+            pass
+    raise ValueError("无法从模型输出解析 JSON")
+
+
+_llm: LlmClient | None = None
+
+
+def get_llm() -> LlmClient:
+    global _llm
+    if _llm is None:
+        _llm = LlmClient()
+    return _llm
+
+
+def reset_llm_client() -> None:
+    """测试或热更新后可重置单例（配置本身已从 runtime 动态读取，一般无需调用）。"""
+    global _llm
+    _llm = None