v2.17.11

neurons/validator.py

@@ -50,10 +50,10 @@ async def spawn_loops(task_queue, scoring_queue, reward_events, miners_dict):
         logger.info("Starting loops...")
         profile = asyncio.create_task(profiler.print_stats(), name="Profiler")
         # TODO: Revisit why do we need simultaneous loops?
-        tasks = asyncio.create_task(task_loop.start(task_queue, scoring_queue, miners_dict, simultaneous_loops=4))
+        tasks = asyncio.create_task(task_loop.start(task_queue, scoring_queue, miners_dict, simultaneous_loops=2))
         models = asyncio.create_task(model_scheduler.start(scoring_queue, event_restart), name="ModelScheduler")
         scorer = asyncio.create_task(
-            task_scorer.start(model_scheduler, scoring_queue, reward_events, simultaneous_loops=4), name="TaskScorer"
+            task_scorer.start(model_scheduler, scoring_queue, reward_events, simultaneous_loops=2), name="TaskScorer"
         )
         all_tasks = [profile, tasks, models, scorer]
 
@@ -113,7 +113,7 @@ async def start():
     asyncio.run(start())
 
 
-async def start_task_sending_loop(
+def start_task_sending_loop(
     task_queue: list,
     scoring_queue: list,
     miners_dict: dict,
@@ -122,14 +122,15 @@ async def spawn_loops(task_queue, scoring_queue, miners_dict: dict):
         from prompting.tasks.task_sending import task_sender
 
         logger.info("Starting task sending loop in validator...")
-        asyncio.create_task(task_sender.start(task_queue, scoring_queue, miners_dict, simultaneous_loops=4))
+        asyncio.create_task(task_sender.start(task_queue, scoring_queue, miners_dict, simultaneous_loops=1))
+        logger.error("Task sending loop started")
         while True:
             await asyncio.sleep(5)
             logger.debug("Task sending loop is running")
 
     try:
         logger.info("Starting task sending loop in validator...")
-        await spawn_loops(task_queue, scoring_queue, miners_dict)
+        asyncio.run(spawn_loops(task_queue, scoring_queue, miners_dict))
 
     except Exception as e:
         logger.exception(f"Task sending loop error: {e}")
@@ -222,8 +223,13 @@ async def main(
             )
             tasks.append(loop_task)
 
-            sending_task = asyncio.create_task(start_task_sending_loop(task_queue, scoring_queue, miners_dict))
-            tasks.append(sending_task)
+            sending_task = mp.Process(
+                target=start_task_sending_loop,
+                args=(task_queue, scoring_queue, miners_dict),
+                name="SendingTaskProcess",
+            )
+            sending_task.start()
+            processes.append(sending_task)
 
             weight_setter_process = mp.Process(
                 target=start_weight_setter_loop,

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "prompting"
-version = "2.17.10"
+version = "2.17.11"
 description = "Subnetwork 1 runs on Bittensor and is maintained by Macrocosmos. It's an effort to create decentralised AI"
 authors = ["Kalei Brady, Dmytro Bobrenko, Felix Quinque, Steffen Cruz, Richard Wardle"]
 readme = "README.md"

shared/epistula.py

@@ -240,6 +240,8 @@ async def make_openai_query(
         choices = []
         chunks = []
         chunk_timings = []
+        last_finish_reason = None  # Only track the finish reason of the last chunk
+
         async for chunk in chat:
             if not chunk.choices:
                 continue
@@ -248,11 +250,19 @@ async def make_openai_query(
                     choices.append("")
                 if choice.delta.content:
                     choices[i] += choice.delta.content
+                # Save finish reason from the last chunk, safely handling the attribute
+                if hasattr(choice, "finish_reason") and choice.finish_reason is not None:
+                    last_finish_reason = choice.finish_reason
             if chunk.choices[0].delta.content:
                 chunks.append(chunk.choices[0].delta.content)
                 chunk_timings.append(time.perf_counter() - start_time)
+
         choices = [
-            Choice(index=i, message=ChatCompletionMessage(content=choice, role="assistant"), finish_reason="stop")
+            Choice(
+                index=i,
+                message=ChatCompletionMessage(content=choice, role="assistant"),
+                finish_reason=last_finish_reason or "stop",  # Use the captured finish_reason or fallback to "stop"
+            )
             for i, choice in enumerate(choices)
         ]
         # TODO: We need to find a better way to do this instead of sometimes returning a tuple and sometimes not, but for now this has to do