Apply large language models and generative AI to a variety of use cases
Create completions for chat messages with the GPT-35-Turbo and GPT-4 models. See the documentation
Create a new document in a collection of your choice. See the docs here
Classify items into specific categories. See the documentation
Creates an image given a prompt, and returns a URL to the image. See the documentation
The Azure OpenAI Service API provides access to powerful AI models that can understand and generate human-like text. With Pipedream, you can harness this capability to create a variety of serverless workflows, automating tasks like content creation, code generation, and language translation. By integrating the API with other apps on Pipedream, you can streamline processes, analyze sentiment, and even automate customer support.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
azure_openai_service: {
type: "app",
app: "azure_openai_service",
}
},
async run({steps, $}) {
const data = {
"messages": [{ role: 'user', content: "Hello, world!" }],
}
return await axios($, {
method: "post",
url: `https://${this.azure_openai_service.$auth.resource_name}.openai.azure.com/openai/deployments/${this.azure_openai_service.$auth.deployment_name}/chat/completions?api-version=2023-05-15`,
headers: {
"Content-Type": `application/json`,
"api-key": `${this.azure_openai_service.$auth.api_key}`,
},
data,
})
},
})
The MongoDB API provides powerful capabilities to interact with a MongoDB database, allowing you to perform CRUD (Create, Read, Update, Delete) operations, manage databases, and execute sophisticated queries. With Pipedream, you can harness these abilities to automate tasks, sync data across various apps, and react to events in real-time. It’s a combo that’s particularly potent for managing data workflows, syncing application states, or triggering actions based on changes to your data.
import mongodb from 'mongodb'
export default defineComponent({
props: {
mongodb: {
type: "app",
app: "mongodb",
},
collection: {
type: "string"
},
filter: {
type: "object"
}
},
async run({steps, $}) {
const MongoClient = mongodb.MongoClient
const {
database,
hostname,
username,
password,
} = this.mongodb.$auth
const url = `mongodb+srv://${username}:${password}@${hostname}/test?retryWrites=true&w=majority`
const client = await MongoClient.connect(url, {
useNewUrlParser: true,
useUnifiedTopology: true
})
const db = client.db(database)
const results = await db.collection(this.collection).find(this.filter).toArray();
$.export('results', results);
await client.close()
},
})