My bot is running slow very quickly

My code looks like the following:

async def parse(text: Text, agent: Agent):
    response = await agent.handle_text(text)

    return response

Initialize multiple agents:

    # create skill agents based on NLU and dialog models
    def create_agents(skills, endpoints):
        agents = {}
        for skill in skills:
                nlu_model_path = "./models/nlu/" + skill + "/nlu"
                interpreter = RasaNLUInterpreter(nlu_model_path)
                core_model_path = 'models/dialogue/' + skill
                agent = Agent.load(core_model_path, interpreter=interpreter, action_endpoint=endpoints.action)
                agents[skill] = agent
        return agents

    def generate_dialog(message)
    current_skill, current_agent = get_agent(message, all_agents, classification_interpreter)
        if current_agent:
            json_result =, current_agent, current_skill))
        return json_result

The problem with this code is that, when I call “generate_dialog” multiple times to process text from a file, after about processing 200 sentences, the bot quickly slows down.

No memory increases but cpu runs at about 100% at the time. What might cause this? Is that because the new “” or the similar ‘run_until_complete’?

Add a little more message: If i comment out the following function “await self._predict_and_execute_next_action(message, tracker)”, the speed becomes normal and stable:

    async def handle_message(self, message: UserMessage, current_skill,) -> \
        """Handle a single message with this processor."""

        # preprocess message if necessary
        tracker = await self.log_message(message, skill_list, current_skill, turn)

        if not tracker:
            return None

        await self._predict_and_execute_next_action(message, tracker)

        if isinstance(message.output_channel, CollectingOutputChannel):
            nlu_result = (tracker.latest_message_copy.intent, copy.deepcopy(tracker.slots).items(),
            return [message.output_channel.messages, nlu_result]
            return None

It is not because of run_until_complete. I reverted it to the previous release without using these async functions, and they are running into the same problem. In batch mode to process a few hundreds sentences, and the speed slows down significantly.

Any body had similar issues? And does the rasa team have any suggestions on this?

Hi @twittmin,

I’ve also encountered similar problems when the tracker size gets large. When it gets large, the performance deteriorates very quickly, often leading to unresponsiveness.

Here is a simple benchmark that I’ve run:

Did found this issue recently and clients started complaining.

I did dig deep into the code and able to solve by writing custom TrackerStore,

class MyCustomRedisTrackerStore(RedisTrackerStore):

read the existing events and delete the old events and save them back to the store. Hope this helps you too.

you could do the same with your existing tracker store.

Did you solve this?