with Google Dialogflow and Llama AI?
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.`)
}
},
})
The Llama AI API provides powerful machine learning capabilities, enabling users to harness advanced AI for image recognition, natural language processing, and predictive modeling. By leveraging this API on Pipedream, you can automate complex workflows that require AI-driven insights, enhancing data analysis and decision-making processes across various business applications.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
llama_ai: {
type: "app",
app: "llama_ai",
}
},
async run({steps, $}) {
const data = {
"messages": [
{"role": "user", "content": "What is the weather like in Boston?"},
],
"functions": [
{
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA",
},
"days": {
"type": "number",
"description": "for how many days ahead you wants the forecast",
},
"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
},
},
"required": ["location", "days"],
}
],
"stream": "false",
"function_call": "get_current_weather",
}
return await axios($, {
method: "post",
url: `https://api.llama-api.com/chat/completions`,
headers: {
Authorization: `Bearer ${this.llama_ai.$auth.api_token}`,
},
data,
})
},
})