fix(runs): expose active progress counters (#3148)

* fix(runs): expose active progress counters

* fix(runs): avoid delayed progress flush on completion

* fix(runs): tighten progress snapshot semantics

* fix(runs): preserve omitted progress fields

* chore(runs): remove duplicate journal initialization

backend/packages/harness/deerflow/runtime/runs/manager.py

@@ -38,6 +38,16 @@ class RunRecord:
     error: str | None = None
     model_name: str | None = None
     store_only: bool = False
+    total_input_tokens: int = 0
+    total_output_tokens: int = 0
+    total_tokens: int = 0
+    llm_call_count: int = 0
+    lead_agent_tokens: int = 0
+    subagent_tokens: int = 0
+    middleware_tokens: int = 0
+    message_count: int = 0
+    last_ai_message: str | None = None
+    first_human_message: str | None = None
 
 
 class RunManager:
@@ -102,16 +112,53 @@ class RunManager:
             error=row.get("error"),
             model_name=row.get("model_name"),
             store_only=True,
+            total_input_tokens=row.get("total_input_tokens") or 0,
+            total_output_tokens=row.get("total_output_tokens") or 0,
+            total_tokens=row.get("total_tokens") or 0,
+            llm_call_count=row.get("llm_call_count") or 0,
+            lead_agent_tokens=row.get("lead_agent_tokens") or 0,
+            subagent_tokens=row.get("subagent_tokens") or 0,
+            middleware_tokens=row.get("middleware_tokens") or 0,
+            message_count=row.get("message_count") or 0,
+            last_ai_message=row.get("last_ai_message"),
+            first_human_message=row.get("first_human_message"),
         )
 
     async def update_run_completion(self, run_id: str, **kwargs) -> None:
         """Persist token usage and completion data to the backing store."""
+        async with self._lock:
+            record = self._runs.get(run_id)
+            if record is not None:
+                for key, value in kwargs.items():
+                    if key == "status":
+                        continue
+                    if hasattr(record, key) and value is not None:
+                        setattr(record, key, value)
+                record.updated_at = _now_iso()
         if self._store is not None:
             try:
                 await self._store.update_run_completion(run_id, **kwargs)
             except Exception:
                 logger.warning("Failed to persist run completion for %s", run_id, exc_info=True)
 
+    async def update_run_progress(self, run_id: str, **kwargs) -> None:
+        """Persist a running token/message snapshot without changing status."""
+        should_persist = True
+        async with self._lock:
+            record = self._runs.get(run_id)
+            if record is not None:
+                should_persist = record.status == RunStatus.running
+            if record is not None and should_persist:
+                for key, value in kwargs.items():
+                    if hasattr(record, key) and value is not None:
+                        setattr(record, key, value)
+                record.updated_at = _now_iso()
+        if should_persist and self._store is not None:
+            try:
+                await self._store.update_run_progress(run_id, **kwargs)
+            except Exception:
+                logger.warning("Failed to persist run progress for %s", run_id, exc_info=True)
+
     async def create(
         self,
         thread_id: str,

backend/packages/harness/deerflow/runtime/runs/store/base.py

@@ -95,12 +95,30 @@ class RunStore(abc.ABC):
     ) -> None:
         pass
 
+    async def update_run_progress(
+        self,
+        run_id: str,
+        *,
+        total_input_tokens: int | None = None,
+        total_output_tokens: int | None = None,
+        total_tokens: int | None = None,
+        llm_call_count: int | None = None,
+        lead_agent_tokens: int | None = None,
+        subagent_tokens: int | None = None,
+        middleware_tokens: int | None = None,
+        message_count: int | None = None,
+        last_ai_message: str | None = None,
+        first_human_message: str | None = None,
+    ) -> None:
+        """Persist a best-effort running snapshot without changing run status."""
+        return None
+
     @abc.abstractmethod
     async def list_pending(self, *, before: str | None = None) -> list[dict[str, Any]]:
         pass
 
     @abc.abstractmethod
-    async def aggregate_tokens_by_thread(self, thread_id: str) -> dict[str, Any]:
+    async def aggregate_tokens_by_thread(self, thread_id: str, *, include_active: bool = False) -> dict[str, Any]:
         """Aggregate token usage for completed runs in a thread.
 
         Returns a dict with keys: total_tokens, total_input_tokens,

backend/packages/harness/deerflow/runtime/runs/store/memory.py

@@ -82,14 +82,22 @@ class MemoryRunStore(RunStore):
                     self._runs[run_id][key] = value
             self._runs[run_id]["updated_at"] = datetime.now(UTC).isoformat()
 
+    async def update_run_progress(self, run_id, **kwargs):
+        if run_id in self._runs and self._runs[run_id].get("status") == "running":
+            for key, value in kwargs.items():
+                if value is not None:
+                    self._runs[run_id][key] = value
+            self._runs[run_id]["updated_at"] = datetime.now(UTC).isoformat()
+
     async def list_pending(self, *, before=None):
         now = before or datetime.now(UTC).isoformat()
         results = [r for r in self._runs.values() if r["status"] == "pending" and r["created_at"] <= now]
         results.sort(key=lambda r: r["created_at"])
         return results
 
-    async def aggregate_tokens_by_thread(self, thread_id: str) -> dict[str, Any]:
-        completed = [r for r in self._runs.values() if r["thread_id"] == thread_id and r.get("status") in ("success", "error")]
+    async def aggregate_tokens_by_thread(self, thread_id: str, *, include_active: bool = False) -> dict[str, Any]:
+        statuses = ("success", "error", "running") if include_active else ("success", "error")
+        completed = [r for r in self._runs.values() if r["thread_id"] == thread_id and r.get("status") in statuses]
         by_model: dict[str, dict] = {}
         for r in completed:
             model = r.get("model_name") or "unknown"

backend/packages/harness/deerflow/runtime/runs/worker.py

@@ -153,8 +153,6 @@ async def run_agent(
 
     journal = None
 
-    journal = None
-
     # Track whether "events" was requested but skipped
     if "events" in requested_modes:
         logger.info(
@@ -177,6 +175,7 @@ async def run_agent(
                 thread_id=thread_id,
                 event_store=event_store,
                 track_token_usage=getattr(run_events_config, "track_token_usage", True),
+                progress_reporter=lambda snapshot: run_manager.update_run_progress(run_id, **snapshot),
             )
 
         # 1. Mark running