Pinecone

Long-term Memory for AI. The Pinecone vector database makes it easy to build high-performance vector search applications. Developer-friendly, fully managed, and easily scalable without infrastructure hassles.

Integrate the Pinecone API with the MongoDB API

Setup the Pinecone API trigger to run a workflow which integrates with the MongoDB API. Pipedream's integration platform allows you to integrate Pinecone and MongoDB remarkably fast. Free for developers.

Delete Vectors with Pinecone API on New Collection from MongoDB API
MongoDB + Pinecone
 
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Delete Vectors with Pinecone API on New Database from MongoDB API
MongoDB + Pinecone
 
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Delete Vectors with Pinecone API on New Document from MongoDB API
MongoDB + Pinecone
 
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Delete Vectors with Pinecone API on New Field in Document from MongoDB API
MongoDB + Pinecone
 
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Fetch Vectors with Pinecone API on New Collection from MongoDB API
MongoDB + Pinecone
 
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New Collection from the MongoDB API

Emit new an event when a new collection is added to a database

 
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New Database from the MongoDB API

Emit new an event when a new database is added

 
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New Document from the MongoDB API

Emit new an event when a new document is added to a collection

 
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New Field in Document from the MongoDB API

Emit new an event when a new field is added to a document

 
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Delete Vectors with the Pinecone API

Deletes one or more vectors by ID, from a single namespace. See the docs.

 
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Create New Document with the MongoDB API

Create a new document in a collection of your choice. See the docs here

 
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Fetch Vectors with the Pinecone API

Looks up and returns vectors by ID, from a single namespace.. See the docs.

 
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Delete a Document with the MongoDB API

Delete a single document by ID. See the docs here

 
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Query IDs with the Pinecone API

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 docs.

 
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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

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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}`,
      },
    })
  },
})

Overview of MongoDB

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.

Connect MongoDB

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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()
  },
})