I got a dialogflow agent located in europe-west1. Actually I'm trying to use the dialogflow's builtin environment system but I got a problem:
const contextsClient = new dialogflow.v2beta1.ContextsClient({ apiEndpoint: `${REGION_ID}-dialogflow.googleapis.com` })
const sessionClient = new dialogflow.v2beta1.SessionsClient({ apiEndpoint: `${REGION_ID}-dialogflow.googleapis.com` })
const sessionPath = sessionClient.projectLocationAgentSessionPath(PROJECT_ID, REGION_ID, sessionId)
await contextsClient.createContext({
parent: sessionPath,
context: {
name: `projects/${PROJECT_ID}/locations/${REGION_ID}/agent/environments/${ENVIRONMENT}/users/-/sessions/${sessionId}/contexts/${namespace}`,
lifespanCount: 1
}
})
For now google returns me the following error:
INVALID_ARGUMENT: com.google.apps.framework.request.BadRequestException: Context 'projects/project-name/locations/europe-west1/agent/environments/dev/users/-/sessions/3e3bc716-b164-4fe0-aa51-aeb42cf4930a/contexts/search' does not belong to session 'projects/project-name/locations/europe-west1/agent/sessions/3e3bc716-b164-4fe0-aa51-aeb42cf4930a'
Is there any sessionClient.projectLocationEnvironmentAgentSessionPath method? Can't find it in API's doc.
Finally found it, only available on 4.X dialogflow.v2beta1 release. The method is .projectLocationAgentEnvironmentUserSessionPath(PROJECT_ID, REGION_ID, ENVIRONMENT, '-', sessionId)
Just as additional information to #Pierre Clocher answer.
Dialogflow Essential is not fully supporting projectLocationAgentSessionPath yet, however you can find it is supported by Dialogflow CX.
In Dialogflow CX documentation - Interactions with the API you can find that sessionPath has what you need.
const sessionPath = client.projectLocationAgentSessionPath(
projectId,
location,
agentId,
sessionId
);
However in Dialogflow ES, in Quickstart: Interactions with the API is mention that you can use
const sessionPath = sessionClient.projectAgentSessionPath(
projectId,
sessionId
);
There is already a Feature Request reported to Google via Issue Tracker, that Dialogflow ES could support ProjectLocationAgentEnvironmentSessionPath. This Issue Tracker can be found here: Support ProjectLocationAgentEnvironmentSessionPath.
Reporter of this Feature Request also provided a workaround so it might work for you as well.
const projectLocationAgentEnvironmentPath = sessionClient.projectLocationAgentEnvironmentPath(
projectId,
location,
environment
);
const sessionPath = `${projectLocationAgentEnvironmentPath}/users/-/sessions/${sessionId}`;
Summary:
Use #Pierre Clocher solution
You could use Dialogflow CX instead of Dialogflow ES.
Try to use a workaround from Issue Tracker and click on +1 button in the Issue Tracker which will indicate that this FR is needed.
Related
I am trying to make my VUI repeat its last sentence when prompted for this (e.g. when user says 'I'm sorry, I did not hear you). I have tried to do this using the libraries multivocal and VoiceRepeater but this is not working for me so I want to implement it according to this guide: https://developers.google.com/assistant/conversational/tips
I have already taken the following steps:
Created an intent called 'Repeat'.
Added training phrases for the intent
Enabled webhook call for this intent
In Node.js added the following code:
// See https://github.com/dialogflow/dialogflow-fulfillment-nodejs
// for Dialogflow fulfillment library docs, samples, and to report issues
'use strict';
const functions = require('firebase-functions');
const {WebhookClient} = require('dialogflow-fulfillment');
const {Card, Suggestion} = require('dialogflow-fulfillment');
process.env.DEBUG = 'dialogflow:debug'; // enables lib debugging statements
exports.dialogflowFirebaseFulfillment = functions.https.onRequest((request, response) => {
const agent = new WebhookClient({ request, response });
function repeat(agent) {
const REPEAT_PREFIX = [
'Sorry, Ik zei ',
'Laat me het herhalen: ',
'Wat ik zei is'
];
const reply = (agent, inputPrompt, noInputPrompts) => {
agent.data.lastPrompt = inputPrompt;
agent.data.lastNoInputPrompts = noInputPrompts;
agent.ask(inputPrompt, noInputPrompts);
};
// Intent handlers
const normalIntent = (agent) => {
reply(agent, 'Hey this is a question', 'Ik zie niks');
};
let repeatPrefix = promptFetch.getRepeatPrefix(); // randomly chooses from REPEAT_PREFIX
// Move SSML start tags over
if (agent.data.lastPrompt.startsWith(promptFetch.getSSMLPrefix())) {
agent.data.lastPrompt =
agent.data.lastPrompt.slice(promptFetch.getSSMLPrefix().length);
repeatPrefix = promptFetch.getSSMLPrefix() + repeatPrefix;
}
agent.add(repeatPrefix + agent.data.lastPrompt,
agent.data.lastNoInputPrompts);
}
// Run the proper function handler based on the matched Dialogflow intent name
let intentMap = new Map();
intentMap.set('Repeat', repeat);
agent.handleRequest(intentMap);
});
Unfortunately, this does not work for me, one error I get it that it says 'FetchPrompt is not defined', which I don't understand. I know the setup is okay because this code does return: 'this is a response from the webhook' if I prompt the VUI for repeating its sentence:
// See https://github.com/dialogflow/dialogflow-fulfillment-nodejs
// for Dialogflow fulfillment library docs, samples, and to report issues
'use strict';
const functions = require('firebase-functions');
const {WebhookClient} = require('dialogflow-fulfillment');
const {Card, Suggestion} = require('dialogflow-fulfillment');
process.env.DEBUG = 'dialogflow:debug'; // enables lib debugging statements
exports.dialogflowFirebaseFulfillment = functions.https.onRequest((request, response) => {
const agent = new WebhookClient({ request, response });
function repeat(agent) {
agent.add('this is a response from the webhook');
}
// Run the proper function handler based on the matched Dialogflow intent name
let intentMap = new Map();
intentMap.set('Repeat', repeat);
agent.handleRequest(intentMap);
});
As #Prisoner points out, your code is intended to work only with dialogflow-fulfillment but you based it on an actions-on-google example. That's the cause of the code errors.
Some things you want to do are only available for Actions on Google, for example, the object conv contains functionality that only works when executed within Google Assistant, and this is the core of the problem.
Even if you fix the code, the example you're following uses conv.data as a temporary storage for the last reply of the agent during the conversation; however conv.data functionality is not availabe outside Google Assistant platforms, and, at the moment, Dialogflow doesn't have a straightforward approach to get the agent last response.
If you don't want to integrate with Google Assistant, then you'd need to find a suitable workaround to store your agent last reply. Here's a question where this issue with the temporary storage was discussed, maybe you can use it as a reference.
For your use case, I think you could get away with it by using contexts to store the last replies.
This flow is confusing me a bit and I would appreciate any help/diagram/flow-chart that could help me understand this better:
As an example, I would like to access Google's API. The thing is what I want to access sits on an enterprise account and to even get to use any of Google Suite Applications, I have to log in to my work account (SSO.) On top of that, all this needs to be done via VPN.
I've used Puppeteer for this in Node.js, and though it works on my machine, It stops working if I try to host it anywhere else because (I assume) due to the VPN issue. It's clunky and just plain hack-ish because I'm just automating what I normally do on the browser.
What are the best practices in being able to use Google's API? What does the algorithm look like?
you can use the 'googleapis' package on npm
https://www.npmjs.com/package/googleapis
here is an example...
const {google} = require('googleapis');
const bigquery = google.bigquery('v2');
async function main() {
// This method looks for the GCLOUD_PROJECT and GOOGLE_APPLICATION_CREDENTIALS
// environment variables.
const auth = new google.auth.GoogleAuth({
scopes: ['https://www.googleapis.com/auth/cloud-platform']
});
const authClient = await auth.getClient();
const projectId = await auth.getProjectId();
const request = {
projectId,
datasetId: '<YOUR_DATASET_ID>',
// This is a "request-level" option
auth: authClient
};
const res = await bigquery.datasets.delete(request);
console.log(res.data);
}
main().catch(console.error);
you can use a proxy by setting the process.env.http or process.env.httpsenvironment variables to solve your vpn issue
I'm developing a chat bot for Telegram using DialogFlow, but I can't go through two topics, and I can't find the documentation for them.
The flow of the conversation, is the user answer some closed questions and send an image.
How do I get this image?
And to save her along with the other answers?
The answers need to be saved as a form/survey and not as a conversation history.
I have a similar setup in my chatbot. I store the answers in a Firebase database.
In order to interact with the Firestore Database you should implement a Fulfillment
You can see a guide on how to implement Firebase for DialogFlow here
Here you can see a sample of my code. In general lines after setting up the connection to the Firebase database you just want to map your intents to your functions using intentMap.set.
As you said you are using closed answers you can set intets to handle the responses and each "final" intent will trigger a different function that will write a different message to the db.
To write the response to the Firesbase database you just only need to implement admin.database().ref().push().set({}) with the information and the desired structure.
In my example I also store the conversation Id from the chat payload and the date.
'use strict';
const functions = require('firebase-functions');
const admin = require('firebase-admin');
const {WebhookClient} = require('dialogflow-fulfillment');
const {Card, Suggestion} = require('dialogflow-fulfillment');
//const DialogflowApp = require('actions-on-google').DialogflowApp;
process.env.DEBUG = 'dialogflow:debug'; // enables lib debugging statements
admin.initializeApp({
credential : admin.credential.applicationDefault(),
databaseURL: 'ws://YOURDATABASE.firebaseio.com/'
});
exports.dialogflowFirebaseFulfillment = functions.https.onRequest((request, response) => {
const agent = new WebhookClient({ request, response });
console.log('Dialogflow Request headers: ' + JSON.stringify(request.headers));
console.log('Dialogflow Request body: ' + JSON.stringify(request.body));
var userId;
let conv = agent.conv();
const ROOTREF = admin.database().ref();
const actions = new Map();
let intentMap = new Map();
intentMap.set('Default Fallback Intent', fallback);
intentMap.set('NoTunel', handleWriteToDbNoTunnel(agent));
agent.handleRequest(intentMap);
function assignConv(agent){
userId = agent.parameters.UserId;
return admin.database().ref('Users/'+ userId).set({
Apellido:"XXXX",
Nombre:"XXXX",
chatId:333,
});}
function fallback(agent) {
agent.add(`I didn't understand`);
agent.add(`I'm sorry, can you try again?`);
}
var token = "YOUR TOKEN HERE";
var url = "https://api.telegram.org/bot"+ token;
function handleWriteToDbNoTunnel(agent){
const Dia = new Date();
if(matricula !== "")
return admin.database().ref('Limpieza/').push().set({
chatId: request.body.queryResult.outputContexts[3].parameters.telegram_chat_id+'"',
Field1: answer1,
Field2: answer2,
day: day.getTime()
});
}
});
Also if you want to store images with the user responses you can implement the getfile method from the telegram api and store the image code or the image itself
I am adding this answer to slightly improve on Chris32's answer.
There is a better way to get the value of the Telegram Chat ID as I am using it in a personal project.
I will go end to end to explain my approach.
I have mapped some files to some specific intents. In my intent-mapper.js file, I have mapped Default Welcome Intent to welcome.js file as prescribed in the documentation for the Dialogflow Fufillment library for NodeJS (Please note that the library is deprecated and not being updated, personally I am using a fork of the repo that I have worked on personally).
const intentMap = new Map();
intentMap.set('Default Welcome Intent', welcome);
.
.
Then, in welcome.js,
const globalParameters = {
'name': 'global-parameters',
'lifespan': 9999,
'parameters': {}
};
globalParameters.parameters.telegramChatId = agent.originalRequest?.payload?.data?.chat?.id || -1;
.
.
agent.setContext(globalParameters);
The telegramChatId variable in the global parameters context will save the value for the chat ID which can be passed to a helper function to send a message. In order to to retrieve the value from the global parameters, the code snippet is this.
const globalParameters = agent.getContext('global-parameters');
const telegramChatId = globalParameters.parameters.telegramChatId;
Then the Telegram message helper function is largely the same as in Chris32's answer. The message can be any string and chatId can be passed as an argument to the following helper function.
const TelegramBot = require('node-telegram-bot-api');
const { telegramBotToken } = process.env.TELEGRAM_BOT_TOKEN;
const bot = new TelegramBot(telegramBotToken, { polling: false });
const sendTelegramTextMessage = (message, chatId) => {
try {
bot.sendMessage(chatId, message, {parse_mode: 'html'});
} catch (err) {
console.log('Something went wrong when trying to send a Telegram notification', err);//remove console.log()
}
};
The reason I have put this all in a context since in my use case I am sending push notifications via Telegram once the user asks for it (this happens later in the conversation flow), so I have implemented it this way. The main point to note is that the agent object already has the detectIntentRequest variable saved inside it which in turn has the value we need as a part of its payload. Here's a snippet of the same.
Please note I have removed many lines from my code for brevity, but in a nutshell, the chat ID can be accessed from
agent.originalRequest?.payload?.data?.chat?.id
And the value for the telegram bot token is a secret value which can be saved in an environment variable or Secrets Manager. Please note my answer explains a better way to retrieve the chat ID without needing to refer directly to the request object since Dialogflow Fulfillment library already caches the value in the body for us. The other stuff for receiving and sending images is explained in the main answer.
I know this is in Beta, but I've set up a Knowledge base for my agent and the intent doesn't seem to get recognized.
When setting up the Knowledge base, the "try it" test works and retrieves successfully, but when trying the same request from the simple chat bot, the intent is not recognized. What else is necessary to hook the Knowledge feature to the agent?
What is the medium of that simple chat bot you are using?Is it android/web?
Assuming are using dialogflow v2 node.js library,We have to pass the full path of the knowledgeBase in the queryParams inside the detectIntent function request object.Then only dialogflow will look into knowledgeBase for matching the user input to the Knowledge base Intents.
Sample of request object-
// const projectId = 'ID of GCP project associated with your Dialogflow agent';
// const sessionId = `user specific ID of session, e.g. 12345`;
const sessionPath = sessionClient.sessionPath(projectId, sessionId);
let request = {
session: sessionPath,
queryInput: {
text: {
text: 'hi,how are you?',
languageCode: 'en-US',
},
},
queryParams: {
knowledgeBaseNames:['projects/stockmarket-XXXX/knowledgeBases/XXXXXXXXXXXXXXx'] //Paste your knowledge base path,Check this out from the diagnostic info
}
};
checkout https://github.com/googleapis/nodejs-dialogflow/blob/master/samples/detect.v2beta1.js#L438
Let me know if you have any questions :)
I have a Node JS app that make requests to a Dialogflow agent. I actually use a temporally token based request, but how can i change this to do it through google service credentials? (https://cloud.google.com/docs/authentication/getting-started). I have a credencial created (with billing added), and the service_account json file.
I would like to use the Dialogflow package in node (https://www.npmjs.com/package/dialogflow) but i don't underestand how to use it with the json file.
const projectId = 'ENTER_PROJECT_ID_HERE';
const sessionId = 'quickstart-session-id';
const query = 'hello';
const languageCode = 'en-US';
// Instantiate a DialogFlow client.
const dialogflow = require('dialogflow');
const sessionClient = new dialogflow.SessionsClient();
// Define session path
const sessionPath = sessionClient.sessionPath(projectId, sessionId);
The example of the package use Project ID and Session ID, but not with a json file like the example of the google services (or using big query like How to authenticate with gcloud big query using a json credentials file?). Anyway, where can i get this project and session id?
Please, if someone can help me or guide how to do this in a better way?. Thanks
First you have to create a service account and download a .JSON format file of credentials on your local system.
Now, there are three ways to use that credentials for authentication/authorisation in dialogflow library.
Method 1
Create a environment variable GOOGLE_APPLICATION_CREDENTIALS and it's value should be the absolute path of that JSON credentials file.By this method, google library will implicitly loads the file and use that credentials for authentication. We don't need to do anything inside our code relating to this credentials file.
export GOOGLE_APPLICATION_CREDENTIALS="<absolute-path-of-json-file>" # for UNIX,LINUX
# then run your code, google library will pick credentials file and loads it automatically
Method 2
Assume, you know the absolute path of your JSON file and put that as value in below snippet of credentials_file_path variable.
// You can find your project ID in your Dialogflow agent settings
const projectId = '<project-id-here>';
const sessionId = '<put-chat-session-id-here>';
// const sessionid = 'fa2d5904-a751-40e0-a878-d622fa8d65d9'
const query = 'hi';
const languageCode = 'en-US';
const credentials_file_path = '<absolute-file-path-of-JSON-file>';
// Instantiate a DialogFlow client.
const dialogflow = require('dialogflow');
const sessionClient = new dialogflow.SessionsClient({
projectId,
keyFilename: credentials_file_path,
});
Method 3
You can note down the project_id, client_email and private_key from the JSON, use them in your code for authentication explicitly.
// You can find your project ID in your Dialogflow agent settings
const projectId = '<project-id-here>';
const sessionId = '<put-chat-session-id-here>';
// const sessionid = 'fa2d5904-a751-40e0-a878-d622fa8d65d9'
const query = 'hi';
const languageCode = 'en-US';
const credentials = {
client_email: '<client-email-here>',
private_key:
'<private-key-here>',
};
// Instantiate a DialogFlow client.
const dialogflow = require('dialogflow');
const sessionClient = new dialogflow.SessionsClient({
projectId,
credentials,
});
Here is how you can do it with a service account code sample is in kotlin and definitely can be translated into the node.js sdk
val credentialsProvider = FixedCredentialsProvider.create(ServiceAccountCredentials
.fromStream(Classes.getResourceAsStream([YOUR JSON CONFIG FILE GOES HERE])))
val sessionsSettings = SessionsSettings.newBuilder().setCredentialsProvider(credentialsProvider).build()
sessionsClient = SessionsClient.create(sessionsSettings)
You can get the service account from Dialogflow settings click on the service account links and then create a json config file there in ur cloud console.