feat: add configurable log level and token usage tracking (#1301)

* feat: add configurable log level and token usage tracking

- Add `log_level` config to control deerflow module log level, synced
  to LangGraph Server via serve.sh `--server-log-level`
- Add `token_usage.enabled` config with TokenUsageMiddleware that logs
  input/output/total tokens per LLM call from usage_metadata
- Add .omc/ to .gitignore

* fix: use info level for token usage logs since feature has its own toggle

* fix: sort imports to pass lint check

---------

Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>

backend/packages/harness/deerflow/agents/middlewares/token_usage_middleware.py

@@ -0,0 +1,37 @@
+"""Middleware for logging LLM token usage."""
+
+import logging
+from typing import override
+
+from langchain.agents import AgentState
+from langchain.agents.middleware import AgentMiddleware
+from langgraph.runtime import Runtime
+
+logger = logging.getLogger(__name__)
+
+
+class TokenUsageMiddleware(AgentMiddleware):
+    """Logs token usage from model response usage_metadata."""
+
+    @override
+    def after_model(self, state: AgentState, runtime: Runtime) -> dict | None:
+        return self._log_usage(state)
+
+    @override
+    async def aafter_model(self, state: AgentState, runtime: Runtime) -> dict | None:
+        return self._log_usage(state)
+
+    def _log_usage(self, state: AgentState) -> None:
+        messages = state.get("messages", [])
+        if not messages:
+            return None
+        last = messages[-1]
+        usage = getattr(last, "usage_metadata", None)
+        if usage:
+            logger.info(
+                "LLM token usage: input=%s output=%s total=%s",
+                usage.get("input_tokens", "?"),
+                usage.get("output_tokens", "?"),
+                usage.get("total_tokens", "?"),
+            )
+        return None