Create conversational experiences across devices and platforms.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Batch create entities, See REST docs and client API docs
Creates an Entity Type, See REST docs and client API docs
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.
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.`)
}
},
})
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:
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}}