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with Microsoft Power BI and Google Dialogflow?

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Create Context with Google Dialogflow API on Dataset Refresh Completed from Microsoft Power BI API
Microsoft Power BI + Google Dialogflow
 
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Create Context with Google Dialogflow API on Dataset Refresh Failed from Microsoft Power BI API
Microsoft Power BI + Google Dialogflow
 
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Create Context with Google Dialogflow API on New Dataset Refresh Created from Microsoft Power BI API
Microsoft Power BI + Google Dialogflow
 
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Create Entities with Google Dialogflow API on Dataset Refresh Completed from Microsoft Power BI API
Microsoft Power BI + Google Dialogflow
 
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Create Entities with Google Dialogflow API on Dataset Refresh Failed from Microsoft Power BI API
Microsoft Power BI + Google Dialogflow
 
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Dataset Refresh Completed from the Microsoft Power BI API

Emits a new event when a dataset refresh operation has completed. See the documentation

 
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Dataset Refresh Failed from the Microsoft Power BI API

Emits an event when a dataset refresh operation has failed in Power BI. See the documentation

 
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New Dataset Refresh Created from the Microsoft Power BI API

Emit new event when a new dataset refresh operation is created. See the documentation

 
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Add Rows to Dataset Table with the Microsoft Power BI API

Adds new data rows to the specified table within the specified dataset from My workspace. See the documentation

 
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Create Context with the Google Dialogflow API

Creates a context, See REST docs and client API

 
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Cancel Dataset Refresh with the Microsoft Power BI API

Cancels a refresh operation for a specified dataset in Power BI. See the documentation

 
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Create Entities with the Google Dialogflow API

Batch create entities, See REST docs and client API docs

 
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Create Dataset with the Microsoft Power BI API

Creates a new Push Dataset in Power BI. See the documentation

 
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Integrate the Microsoft Power BI API with the Google Dialogflow API
Setup the Microsoft Power BI API trigger to run a workflow which integrates with the Google Dialogflow API. Pipedream's integration platform allows you to integrate Microsoft Power BI and Google Dialogflow remarkably fast. Free for developers.

Overview of Microsoft Power BI

The Microsoft Power BI API allows you to interact with your Power BI assets programmatically. With this API, you can embed your reports and dashboards into applications, manage Power BI datasets, push data into datasets for real-time dashboard updates, and automate your reporting workflows. On Pipedream, you can use this API to create intricate workflows that react to various triggers, like webhooks or schedules, and perform actions like refreshing datasets, posting to datasets, and managing Power BI assets.

Connect Microsoft Power BI

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    microsoft_power_bi: {
      type: "app",
      app: "microsoft_power_bi",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.powerbi.com/v1.0/myorg/availableFeatures`,
      headers: {
        Authorization: `Bearer ${this.microsoft_power_bi.$auth.oauth_access_token}`,
      },
    })
  },
})

Overview of Google Dialogflow

Google Dialogflow API empowers you to create conversational interfaces for websites, apps, and messaging platforms. Think chatbots that can engage in human-like dialogue, provide customer support, guide through sales processes, or control smart home devices with voice commands. With Pipedream's integration capabilities, you can create automated workflows that trigger actions in other apps based on Dialogflow's processed input, enabling seamless interaction across a plethora of services.

Connect Google Dialogflow

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module.exports = defineComponent({
  props: {
    google_dialogflow: {
      type: "app",
      app: "google_dialogflow",
    }
  },
  async run({steps, $}) {
    // Example code from the Dialogflow Node.js library:
    // https://github.com/googleapis/nodejs-dialogflow
    const dialogflow = require('dialogflow')
    const uuid = require('uuid')
    
    // A unique identifier for the given session
    const sessionId = uuid.v4()
    
    const key = JSON.parse(this.google_dialogflow.$auth.key_json)
     
    // Creates a session client from a Google service account key.
    const sessionClient = new dialogflow.SessionsClient({
      projectId: key.project_id,
      credentials: {
        client_email: key.client_email,
        private_key: key.private_key,
      }
    })
    const sessionPath = sessionClient.sessionPath(key.project_id, sessionId)
    
    // The text query request.
    const request = {
      session: sessionPath,
      queryInput: {
        text: {
          // The query to send to the dialogflow agent
          text: 'hello',
          // The language used by the client (en-US)
          languageCode: 'en-US',
        },
      },
    }
    
    // Send request and log result
    const responses = await sessionClient.detectIntent(request)
    console.log('Detected intent')
    const result = responses[0].queryResult
    console.log(`Query: ${result.queryText}`)
    console.log(`Response: ${result.fulfillmentText}`)
    if (result.intent) {
      console.log(`Intent: ${result.intent.displayName}`)
    } else {
      console.log(`No intent matched.`)
    }
  },
})

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Adyen logo
Appcues logo
Bandwidth logo
Checkr logo
ChartMogul logo
Dataminr logo
Gopuff logo
Gorgias logo
LinkedIn logo
Logitech logo
Replicated logo
Rudderstack logo
SAS logo
Scale AI logo
Webflow logo
Warner Bros. logo
Adyen logo
Appcues logo
Bandwidth logo
Checkr logo
ChartMogul logo
Dataminr logo
Gopuff logo
Gorgias logo
LinkedIn logo
Logitech logo
Replicated logo
Rudderstack logo
SAS logo
Scale AI logo
Webflow logo
Warner Bros. logo