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https://github.com/bytedance/deer-flow.git
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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
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@@ -95,12 +95,30 @@ class RunStore(abc.ABC):
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) -> None:
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pass
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async def update_run_progress(
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self,
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run_id: str,
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*,
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total_input_tokens: int | None = None,
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total_output_tokens: int | None = None,
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total_tokens: int | None = None,
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llm_call_count: int | None = None,
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lead_agent_tokens: int | None = None,
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subagent_tokens: int | None = None,
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middleware_tokens: int | None = None,
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message_count: int | None = None,
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last_ai_message: str | None = None,
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first_human_message: str | None = None,
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) -> None:
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"""Persist a best-effort running snapshot without changing run status."""
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return None
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@abc.abstractmethod
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async def list_pending(self, *, before: str | None = None) -> list[dict[str, Any]]:
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pass
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@abc.abstractmethod
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async def aggregate_tokens_by_thread(self, thread_id: str) -> dict[str, Any]:
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async def aggregate_tokens_by_thread(self, thread_id: str, *, include_active: bool = False) -> dict[str, Any]:
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"""Aggregate token usage for completed runs in a thread.
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Returns a dict with keys: total_tokens, total_input_tokens,
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@@ -82,14 +82,22 @@ class MemoryRunStore(RunStore):
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self._runs[run_id][key] = value
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self._runs[run_id]["updated_at"] = datetime.now(UTC).isoformat()
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async def update_run_progress(self, run_id, **kwargs):
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if run_id in self._runs and self._runs[run_id].get("status") == "running":
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for key, value in kwargs.items():
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if value is not None:
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self._runs[run_id][key] = value
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self._runs[run_id]["updated_at"] = datetime.now(UTC).isoformat()
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async def list_pending(self, *, before=None):
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now = before or datetime.now(UTC).isoformat()
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results = [r for r in self._runs.values() if r["status"] == "pending" and r["created_at"] <= now]
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results.sort(key=lambda r: r["created_at"])
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return results
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async def aggregate_tokens_by_thread(self, thread_id: str) -> dict[str, Any]:
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completed = [r for r in self._runs.values() if r["thread_id"] == thread_id and r.get("status") in ("success", "error")]
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async def aggregate_tokens_by_thread(self, thread_id: str, *, include_active: bool = False) -> dict[str, Any]:
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statuses = ("success", "error", "running") if include_active else ("success", "error")
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completed = [r for r in self._runs.values() if r["thread_id"] == thread_id and r.get("status") in statuses]
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by_model: dict[str, dict] = {}
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for r in completed:
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model = r.get("model_name") or "unknown"
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