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https://github.com/NousResearch/hermes-agent.git
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fix(api-server): persist response snapshot on client disconnect when store=True
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commit
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1 changed files with 74 additions and 22 deletions
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@ -1204,10 +1204,12 @@ class APIServerAdapter(BasePlatformAdapter):
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If the client disconnects mid-stream, ``agent.interrupt()`` is
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called so the agent stops issuing upstream LLM calls, then the
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asyncio task is cancelled. When ``store=True`` the full response
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is persisted to the ResponseStore in a ``finally`` block so GET
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/v1/responses/{id} and ``previous_response_id`` chaining work the
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same as the batch path.
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asyncio task is cancelled. When ``store=True`` an initial
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``in_progress`` snapshot is persisted immediately after
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``response.created`` and disconnects update it to an
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``incomplete`` snapshot so GET /v1/responses/{id} and
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``previous_response_id`` chaining still have something to
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recover from.
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"""
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import queue as _q
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@ -1269,6 +1271,26 @@ class APIServerAdapter(BasePlatformAdapter):
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final_response_text = ""
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agent_error: Optional[str] = None
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usage: Dict[str, int] = {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
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terminal_snapshot_persisted = False
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def _persist_response_snapshot(
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response_env: Dict[str, Any],
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*,
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conversation_history_snapshot: Optional[List[Dict[str, Any]]] = None,
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) -> None:
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if not store:
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return
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if conversation_history_snapshot is None:
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conversation_history_snapshot = list(conversation_history)
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conversation_history_snapshot.append({"role": "user", "content": user_message})
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self._response_store.put(response_id, {
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"response": response_env,
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"conversation_history": conversation_history_snapshot,
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"instructions": instructions,
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"session_id": session_id,
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})
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if conversation:
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self._response_store.set_conversation(conversation, response_id)
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try:
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# response.created — initial envelope, status=in_progress
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@ -1278,6 +1300,7 @@ class APIServerAdapter(BasePlatformAdapter):
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"type": "response.created",
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"response": created_env,
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})
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_persist_response_snapshot(created_env)
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last_activity = time.monotonic()
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async def _open_message_item() -> None:
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@ -1534,6 +1557,18 @@ class APIServerAdapter(BasePlatformAdapter):
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"output_tokens": usage.get("output_tokens", 0),
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"total_tokens": usage.get("total_tokens", 0),
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}
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_failed_history = list(conversation_history)
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_failed_history.append({"role": "user", "content": user_message})
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if final_response_text or agent_error:
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_failed_history.append({
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"role": "assistant",
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"content": final_response_text or agent_error,
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})
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_persist_response_snapshot(
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failed_env,
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conversation_history_snapshot=_failed_history,
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)
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terminal_snapshot_persisted = True
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await _write_event("response.failed", {
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"type": "response.failed",
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"response": failed_env,
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@ -1546,30 +1581,47 @@ class APIServerAdapter(BasePlatformAdapter):
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"output_tokens": usage.get("output_tokens", 0),
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"total_tokens": usage.get("total_tokens", 0),
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}
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full_history = list(conversation_history)
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full_history.append({"role": "user", "content": user_message})
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if isinstance(result, dict) and result.get("messages"):
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full_history.extend(result["messages"])
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else:
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full_history.append({"role": "assistant", "content": final_response_text})
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_persist_response_snapshot(
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completed_env,
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conversation_history_snapshot=full_history,
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)
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terminal_snapshot_persisted = True
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await _write_event("response.completed", {
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"type": "response.completed",
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"response": completed_env,
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})
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# Persist for future chaining / GET retrieval, mirroring
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# the batch path behavior.
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if store:
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full_history = list(conversation_history)
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full_history.append({"role": "user", "content": user_message})
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if isinstance(result, dict) and result.get("messages"):
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full_history.extend(result["messages"])
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else:
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full_history.append({"role": "assistant", "content": final_response_text})
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self._response_store.put(response_id, {
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"response": completed_env,
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"conversation_history": full_history,
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"instructions": instructions,
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"session_id": session_id,
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})
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if conversation:
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self._response_store.set_conversation(conversation, response_id)
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except (ConnectionResetError, ConnectionAbortedError, BrokenPipeError, OSError):
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if store and not terminal_snapshot_persisted:
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incomplete_text = "".join(final_text_parts) or final_response_text
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incomplete_items: List[Dict[str, Any]] = list(emitted_items)
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if incomplete_text:
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incomplete_items.append({
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"type": "message",
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"role": "assistant",
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"content": [{"type": "output_text", "text": incomplete_text}],
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})
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incomplete_env = _envelope("incomplete")
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incomplete_env["output"] = incomplete_items
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incomplete_env["usage"] = {
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"input_tokens": usage.get("input_tokens", 0),
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"output_tokens": usage.get("output_tokens", 0),
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"total_tokens": usage.get("total_tokens", 0),
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}
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incomplete_history = list(conversation_history)
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incomplete_history.append({"role": "user", "content": user_message})
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if incomplete_text:
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incomplete_history.append({"role": "assistant", "content": incomplete_text})
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_persist_response_snapshot(
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incomplete_env,
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conversation_history_snapshot=incomplete_history,
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)
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# Client disconnected — interrupt the agent so it stops
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# making upstream LLM calls, then cancel the task.
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agent = agent_ref[0] if agent_ref else None
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