Integrate the Google Dialogflow API with the Python API

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

Popular Google Dialogflow and Python Actions#

Create Context with the Google Dialogflow API

Creates a context, See REST docs and client API

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Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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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 Entity Type with the Google Dialogflow API

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

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Create Intent with the Google Dialogflow API

Creates an intent, See REST docs and client API

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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 Python#

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python#

def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}