with Apify and Pinecone?
Deletes one or more vectors by ID, from a single namespace. See the documentation
Looks up and returns vectors by ID, from a single namespace.. See the documentation
Searches a namespace, using a query vector. It retrieves the ids of the most similar items in a namespace, along with their similarity scores. See the documentation
Performs an execution of a selected actor in Apify. See the documentation
The Apify API unleashes the power to automate web scraping, process data, and orchestrate web automation workflows. By utilizing Apify on Pipedream, you can create dynamic serverless workflows to manage tasks like extracting data from websites, running browser automation, and scheduling these jobs to run autonomously. It integrates smoothly with Pipedream's capabilities to trigger actions on various other apps, store the results, and manage complex data flow with minimal setup.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
apify: {
type: "app",
app: "apify",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.apify.com/v2/users/me`,
headers: {
Authorization: `Bearer ${this.apify.$auth.api_token}`,
},
})
},
})
The Pinecone API enables you to work with vector databases, which are essential for building and scaling applications with AI features like recommendation systems, image recognition, and natural language processing. On Pipedream, you can create serverless workflows integrating Pinecone with other apps, automate data ingestion, query vector databases in response to events, and orchestrate complex data processing pipelines that leverage Pinecone's similarity search.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
pinecone: {
type: "app",
app: "pinecone",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.pinecone.io/collections`,
headers: {
"Api-Key": `${this.pinecone.$auth.api_key}`,
},
})
},
})