chore: opencode冗余清理 + LLM任务级模型选择 + systemd服务化

- 删除 opencode_search.py / mcp_search_server.py 及所有 MCP 引用
- 移除搜索缓存定时任务（scheduled_refresh_search_cache）
- 清理前后端所有 opencode/MCP 代码和注释
- LLM 提供商量换：opencode-go→nvidia(默认)+sensenova(合规审查)
- llm_configs 新增 is_default 字段，API 层互斥逻辑
- 所有定时任务支持独立 LLM 模型选择（LLM_TASK_PROVIDER env）
- compliance_optimizer.py 修复：import os / 解硬编码 / 关键词过滤
- Scheduler 日志修复：始终 INSERT，避免僵尸 running 行
- Systemd 服务化：Restart=always / 单 worker / Type=exec
- 搜索提供商：替换 opencode→360/搜狗/微信（免 Key）
- 更新 AGENTS.md / PROGRESS.md

platform/backend/app/core/scheduler.py

@@ -19,8 +19,25 @@ from .collector import run_collector_blocking
 
 logger = logging.getLogger(__name__)
 
+def _set_task_llm_provider(module_id: str):
+    """从 TaskConfig 读取 llm_provider 并设为环境变量，供子进程和 call_llm 读取"""
+    try:
+        from ..database import SessionLocal
+        from ..models import TaskConfig
+        db = SessionLocal()
+        cfg = db.query(TaskConfig).filter(TaskConfig.module_id == module_id).first()
+        db.close()
+        if cfg and cfg.params:
+            provider = cfg.params.get("llm_provider")
+            if provider:
+                os.environ["LLM_TASK_PROVIDER"] = provider
+                logger.debug("[%s] LLM provider set to %s", module_id, provider)
+                return
+    except Exception:
+        pass
+    os.environ.pop("LLM_TASK_PROVIDER", None)
+
 MODULES = {
-    "scheduled_refresh_search_cache": {"name": "🔍 搜索缓存", "cron": "01:00"},
     "scheduled_fetch_trends": {"name": "🔥 热点趋势", "cron": "01:10"},
     "scheduled_collect": {"name": "📡 内容采集", "cron": "01:30"},
     "scheduled_generate": {"name": "🤖 内容创作", "cron": "02:00"},
@@ -32,7 +49,6 @@ MODULES = {
 }
 
 LOG_FILE_MAP = {
-    "scheduled_refresh_search_cache": "opencode_search",
     "scheduled_fetch_trends": "trends",
     "scheduled_collect": "collector",
     "scheduled_generate": "creator",
@@ -149,7 +165,6 @@ class TaskScheduler:
             db.close()
 
         MODULE_JOBS = [
-            ("scheduled_refresh_search_cache", self._run_refresh_search_cache, "搜索缓存"),
             ("scheduled_fetch_trends", self._run_fetch_trends, "热点趋势"),
             ("scheduled_collect", self._run_collect, "内容采集"),
             ("scheduled_generate", self._run_generate, "内容创作"),
@@ -200,6 +215,7 @@ class TaskScheduler:
 
     def _run_fetch_trends(self):
         """定时刷新热点趋势（百度/微博/知乎实时热搜 + LLM补充）"""
+        _set_task_llm_provider("scheduled_fetch_trends")
         started = datetime.now(timezone.utc)
         log_id = _log_task("scheduled_fetch_trends", "running", started_at=started)
         try:
@@ -229,48 +245,8 @@ class TaskScheduler:
                       started_at=started, finished_at=datetime.now(timezone.utc))
             logger.exception("[Scheduled] Trends refresh error: %s", e)
 
-    def _run_refresh_search_cache(self):
-        """定时刷新搜索缓存（通过 opencode webfetch）"""
-        started = datetime.now(timezone.utc)
-        log_id = _log_task("scheduled_refresh_search_cache", "running", started_at=started)
-        try:
-            logger.info("[Scheduled] Refreshing search cache via opencode...")
-            import subprocess
-            result = subprocess.run(
-                [sys.executable, str(PROJECT_ROOT / "scripts" / "opencode_search.py"), "--refresh-cache"],
-                capture_output=True, text=True, timeout=600
-            )
-            for line in result.stdout.strip().split("\n"):
-                if line.strip():
-                    logger.info("[SearchCache] %s", line.strip())
-            for line in result.stderr.strip().split("\n"):
-                if line.strip():
-                    logger.warning("[SearchCache] %s", line.strip())
-            if result.returncode == 0:
-                _log_task("scheduled_refresh_search_cache", "success", log_id=log_id,
-                          message="搜索缓存刷新成功",
-                          result_data={"output_lines": len(result.stdout.splitlines())},
-                          started_at=started, finished_at=datetime.now(timezone.utc))
-                logger.info("[Scheduled] Search cache refreshed")
-            else:
-                _log_task("scheduled_refresh_search_cache", "failed", log_id=log_id,
-                          message="部分失败",
-                          error_trace=result.stderr[-500:],
-                          started_at=started, finished_at=datetime.now(timezone.utc))
-                logger.warning("[Scheduled] Search cache refresh may have partial failures")
-        except subprocess.TimeoutExpired:
-            _log_task("scheduled_refresh_search_cache", "failed", log_id=log_id,
-                      message="超时",
-                      started_at=started, finished_at=datetime.now(timezone.utc))
-            logger.warning("[Scheduled] Search cache refresh timed out")
-        except Exception as e:
-            _log_task("scheduled_refresh_search_cache", "failed", log_id=log_id,
-                      message=str(e),
-                      error_trace=traceback.format_exc(),
-                      started_at=started, finished_at=datetime.now(timezone.utc))
-            logger.exception("[Scheduled] Search cache refresh error: %s", e)
-
     def _run_generate(self):
+        _set_task_llm_provider("scheduled_generate")
         started = datetime.now(timezone.utc)
         log_id = _log_task("scheduled_generate", "running", started_at=started)
         try:
@@ -296,6 +272,7 @@ class TaskScheduler:
             logger.exception("[Scheduled] Generation pipeline failed: %s", e)
 
     def _run_optimize(self):
+        _set_task_llm_provider("scheduled_optimize")
         started = datetime.now(timezone.utc)
         log_id = _log_task("scheduled_optimize", "running", started_at=started)
         try:
@@ -314,6 +291,7 @@ class TaskScheduler:
             logger.exception("[Scheduled] Review failed: %s", e)
 
     def _run_collect(self):
+        _set_task_llm_provider("scheduled_collect")
         started = datetime.now(timezone.utc)
         log_id = _log_task("scheduled_collect", "running", started_at=started)
         try:
@@ -334,6 +312,7 @@ class TaskScheduler:
 
     def _run_optimize_sources(self, triggered_by="scheduler"):
         """AI自动优化采集类别与信息源：对比市场热点和当前配置，给出调整建议"""
+        _set_task_llm_provider("scheduled_optimize_sources")
         started = datetime.now(timezone.utc)
         log_id = _log_task("scheduled_optimize_sources", "running", started_at=started, triggered_by=triggered_by)
         try:
@@ -397,6 +376,7 @@ class TaskScheduler:
 
     def _run_metrics_sync(self, triggered_by="scheduler"):
         """定时从各平台公开API获取发布文章的效果数据（当前仅支持知乎）"""
+        _set_task_llm_provider("scheduled_metrics_sync")
         started = datetime.now(timezone.utc)
         log_id = _log_task("scheduled_metrics_sync", "running", started_at=started, triggered_by=triggered_by)
         try: