Hello everyone, I use an agent in my bot, but with the new version of rasa (rasa 1.0) I am getting a wired message. My basic implementation is like this: interpreter = RasaNLUInterpreter('./models/nlu/current') action_endpoint = EndpointConfig(url="http://localhost:5055/webhook") agent = Agent.load('./models/dialogue', interpreter=interpreter, action_endpoint=action_endpoint) and the agent handles the messages using the handle_text function as in: reply = agent.handle_text(userMsg) so, right now I when I use this method I am getting the following message: <coroutine object Agent.handle_text at 0x133236af0> This is not an error message, it is just the output of the function and this is not what it used to be in the older version of Rasa that I’ve used. I’d really appreciate any help from you guys.

Do you mean using a custom connector? I am trying to write a custom connector to implement my own custom channel. Can you please elaborate on [image] Leo_Sal: I am using webhook with a global agent.

Here is something that I think might help, this should probably answer some of your questions. app = Flask(__name__) app.secret_key = '' CORS(app) global agent action_endpoint = EndpointConfig(url="http://localhost:5055/webhook") agent = Agent.load(str(modelPath), action_endpoint=action_endpoint) @app.route('/yourRoute', methods=['POST']) def webhook(): global agent userMsg = request.form['Msg'] if agent.is_ready(): loop = asyncio.new_event_loop() asyncio.set_event_loop(loop) response = loop.run_until_complete(parse(userMsg)) if response is not None : if type(response) is list: return response[0].get('text') else: return response else: return 'The response was not valid' async def parse(text: Text): global agent response = await agent.handle_text(text) return response if __name__ == '__main__': port = int(os.getenv('PORT', xxxx)) print("Starting app on port %d" % port) app.run(debug=False, port=port, host='127.0.0.1')

[image] Leo_Sal: EndpointConfig Thanks for the sample code. For me when I run the code if agent.is_ready(): is not getting true because in below code I see empty self.policy_ensemble. Seems like I have to pass policy while creating agent instance. def is_ready(self): """Check if all necessary components are instantiated to use agent.""" return ( self.tracker_store is not None and self.policy_ensemble is not None and self.interpreter is not None ) But my question is why it worked for you? AND why do we need to pass policy while doing inference? I tried doing this way also but still, it failed because self.is_ready() is false. agent = Agent(policies=[KerasPolicy()]) agent = agent.load(str("./models/")) Can you help, please?

Hi @kothiyayogesh , I’m glad my sample code helped. As for the if agent.is_ready():, I thought that using it might help, but I’m not entirely sure. My logic behind it is that I don’t want the agent to parse the message if it is not ready but this has never actually happened before. I assume that you can safely remove it and it will still work normally.

[image] kothiyayogesh: But my question is why it worked for you? I use the policies when training rasa, so I’m assuming that my policies exist in the trained model that I am loading to the agent.

I also passed policy while training the model. This is what part of my core model metadata.json looks like. "python": "3.6.6", "max_histories": [ 7, null, 5 ], "ensemble_name": "rasa.core.policies.ensemble.SimplePolicyEnsemble", "policy_names": [ "rasa.core.policies.keras_policy.KerasPolicy", "rasa.core.policies.fallback.FallbackPolicy", "rasa.core.policies.memoization.MemoizationPolicy" ], "trained_at": "20190606-203530", "rasa": "1.0.3", "tensorflow": "1.13.1", "sklearn": "0.20.3" } It means an agent should load the policy from my model, right?

For me self.is_ready() is always false because self.policy_ensemble is none in is_ready defination.

It’s working. Problem was my model folder was zipped hence rasa was not able to extract policy detail. After unzipping manually it worked. Thanks

both methods not working either it gives None Response or Type Error Coroutine Object not Callable, and how about rasa core train , load_data ?

Agent.handle_text not working properly with Rasa 1.0

Rasa Open Source

ermarkar (Sunil Garg) August 2, 2021, 5:52am 28

i need the confidence as well, but this just returns the text, any help on this?

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Agent.handle_text not working properly with Rasa 1.0

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