with Fullstory and Pinecone?
Emit new events when native mobile crash events occur. See the docs here
Emit new events when new note created. See the docs here
Emit new events when segment treshold alerts occur. See the docs here
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
Updates vector in a namespace. If a value is included, it will overwrite the previous value. See the documentation
Writes vectors into a namespace. If a new value is upserted for an existing vector ID, it will overwrite the previous value. See the documentation
The Fullstory API unlocks a treasure trove of user session data, enabling developers to automate deep insights into customer experiences on their digital platforms. Leveraging this API on Pipedream allows you to craft custom workflows that respond to specific user interactions, seamlessly integrate session insights with other tools, and trigger actions based on user behavior metrics. It's a boon for teams aiming to enhance user experience, address pain points, and bolster conversion rates.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
fullstory: {
type: "app",
app: "fullstory",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.fullstory.com/operations/v1`,
headers: {
"Authorization": `Basic ${this.fullstory.$auth.api_key}`,
},
})
},
})
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}`,
},
})
},
})