Integrate the Google Dialogflow API with the Data Stores API

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

Popular Google Dialogflow and Data Stores Actions#

Create Context with the Google Dialogflow API

Creates a context, See REST docs and client API

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Add or update a single record with the Data Stores API

Add or update a single record in your Pipedream Data Store.

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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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Add or update multiple records with the Data Stores API

Add or update multiple records to your Pipedream Data Store.

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Create Entity Type with the Google Dialogflow API

Creates an Entity Type, See REST docs and client API docs

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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#

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.`)
    }
  },
})

Overview of Data Stores#

Data Stores are a key-value store that allow you to persist state and share data across workflows. You can perform CRUD operations, enabling dynamic data management within your serverless architecture. Use it to save results from API calls, user inputs, or interim data; then read, update, or enrich this data in subsequent steps or workflows. Data Stores simplify stateful logic and cross-workflow communication, making them ideal for tracking process statuses, aggregating metrics, or serving as a simple configuration store.

Connect Data Stores#

export default defineComponent({
  props: {
    myDataStore: {
      type: "data_store",
    },
  },
  async run({ steps, $ }) {
    await this.myDataStore.set("key_here","Any serializable JSON as the value")
    return await this.myDataStore.get("key_here")
  },
})