I have a portal using which I can update my fulfillment. I want to be able to do the same with training phrases, is it possible to store training phrases locally in webhook like fulfillment JSON.
No, you need to store training phrases on Dialogflow only, the reason is Dialogflow uses these phrases to train its model which will match your input request to an intent.
These phrases are not part of webhook, and cannot be stored locally on some other server.
Related
Dialogflow agent is matching intents accurately, but I want to use the same agent to recognize other languages and match the proper intents.
I'm using actions on google and dialogflow, I'm using webhook for most of the intents which i developed in nodejs using actions-on-google npm library.
I tried dialogflow middleware to detect the language of the user query and then convert into English language, but middleware is triggered after intent matching.
So what I want to achieve is convert the user query into English first then match one of the intent.
I have written and submitted an app via DialogFlow for Google Home which is now live. If I make use of the training facility in DialogFlow (https://dialogflow.com/docs/training-analytics/training) and match un-matched user questions to existing intents, do I need to resubmit my app to google for the training to take effect? Unfortunately the documentation is not clear on this point.
I contacted DialogFlow re the question and they confirmed that that app does need to be resubmitted to google if you use their training function as this alters the language model.
im a noob at making chatbots, and Im having some difficulties understanding how to make the bot reply back to queries and intents dynamically. My chatbot depends on replying back meaningful messages, more than fulfilling a request. Im was working with dialogflow but I thought Wit.ai would be more suitable, so I switched recently. But I still cant find how to train the bot to reply using RNN so it can first parse the intents, then reply back based on them. Any suggestions ?
Kuddos.
The request flow with wit.ai as follows,
First request is made by the user using the message provider(i.e, facebook messanger, slack, ect...), this request is received by the wit.ai. Then the all the required information is extracted by the wit.ai, then all the request parameters is sent to the webhook you specified in the wit.ai.
In the webhook you process the input parameters and respond to it according to it(e.g: user querying for restaurant search, wit provides the the name of the restaurant, you query data base using the name and prepares the response).
Then the prepared response is sent back to the wit.ai from webhook, then wit delivers your message to the respective user and message provider..
So you no need to train any rnn for responding the user.but if your business logic requires the rnn training you have to do it in the webhook (it's your web server).
You can refer to this link for more info: https://dialogflow.com/docs/fulfillment
I am using Dialogflow’s API to feed intents and their respective entities. We’re doing this as a team so modifications are made on a pretty regular basis.
In the meantime, we select some utterances for which we know the desired classification, and we check via Dialogflow’s API (the /query endpoint) that the actual result meets the expectations.
For intents, the results are great. We always get an intent back from the API, and all is well.
As far as entities are concerned however, we have a peculiar behavior :
when we update the training (we add utterances, intents and entities) via the API without any manual action on the DialogFlow console, we don’t get any entities in the JSON response to /query
when we do the same thing, but we manually click on the « Save » button of all the intents,** we get entities in the JSON response** after the « Agent Started Training » flash message disappears.
Does this mean that there is always at least one manual action required for the training to actually be fully done and for entities to be returned in JSON response to the /query endpoint ? Is there a way for us to launch that training via API and prevent the manual save of the 100+ intents we have for our Agent ?
Thanks for any help you can provide !
Best regards
I am trying to generate some "quick reply templates" i.e possible reply according to previous messages in a chat thread using Api.ai/Dialogflow.
I have trained api.ai agent to some extent to generate replies only for some selected queries. Now, I want to enhance it to generate replies for more queries but training an agent manually for a large number of queries is not practically possible. Is there any way to train the api.ai chatbot dynamically by analysing the previous chat thread, i already have stored in db or using the data of ongoing chats.
Users are some sellers so i assume they will talk regarding there product only, so questions will be somewhat similar in every chat thread.
Looks like there is now the ability to train via the API: https://dialogflow.com/docs/training, along with uploading text files with training lists.
You can add more Training Phrases using the POST and PUT API methods for the /intents endpoint.
Any changes made via the API to alter the agent's behavior, initiate the training in the same way when you save an intent. This trains the agent with the changes delievered through the API.
There currently isn't a API for training.
If you have a log of the queries for your agent (via the API or your webhook), you could "train" your agent by using those log to determine the most common unanswered queries by looking at how many queries match the default fallback intent and create new intents and responses for those queries using Dialogflow's API: https://dialogflow.com/docs/reference/agent/intents#post_intents