with Weaviate and Pinterest?
Emit new events when new pins are created on a board or board section. See the docs here and here
Weaviate is a cloud-native, modular, real-time vector search engine that enables scalable, high-performance semantic search. It's built for a wide range of applications, from autocomplete and similar object suggestions to full-text search and automatic categorization. With the Weaviate API, you can index and search through large amounts of data using machine learning models to understand the content and context of the data. On Pipedream, you can leverage this API to create serverless workflows that automate data ingestion, enrichment, and search capabilities, enhancing your apps with intelligent search functions.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
weaviate: {
type: "app",
app: "weaviate",
}
},
async run({steps, $}) {
return await axios($, {
url: `${this.weaviate.$auth.cluster_url}//v1/schema`,
headers: {
Authorization: `Bearer ${this.weaviate.$auth.api_key}`,
},
})
},
})
The Pinterest API opens a portal to interact programmatically with Pinterest's rich data, including boards, pins, and user information. By leveraging this API on Pipedream, you can automate actions like posting new pins, extracting pin data for analysis, and synchronizing Pinterest content with other platforms. The potential extends to marketing optimization, content management, and audience engagement, all automated and integrated within the Pipedream ecosystem.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
pinterest: {
type: "app",
app: "pinterest",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.pinterest.com/v5/user_account`,
headers: {
Authorization: `Bearer ${this.pinterest.$auth.oauth_access_token}`,
},
})
},
})