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with Contentful (API Key) and Pinecone?
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Popular Contentful (API Key) and Pinecone Actions#
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
Overview of Contentful (API Key)#
The Contentful GraphQL Content API opens up a world of possibilities for creating, managing, and delivering content across multiple platforms. With this API, you can query your Contentful content model using GraphQL, allowing for more efficient data retrieval with fewer requests. Integrate this with Pipedream's serverless capabilities, and you've got a powerful tool to automate content workflows, sync content across applications, trigger notifications based on content changes, and more.
Connect Contentful (API Key)#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
contentful_graphql: {
type: "app",
app: "contentful_graphql",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://graphql.contentful.com/content/v1/spaces/[SPACE]/environments/[ENVIRONMENT]`,
headers: {
Authorization: `Bearer ${this.contentful_graphql.$auth.access_token}`,
},
params: {
query: `query($preview: Boolean){
assetCollection(preview: $preview){
items{
title
}
}
}`,
},
})
},
})
Overview of Pinecone#
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.
Connect Pinecone#
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}`,
},
})
},
})
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