Integrate the Relevance AI API with the MongoDB API

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

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Popular Ways to Connect Relevance AI with MongoDB#

Run Tool with Relevance AI API on New Collection from MongoDB API

MongoDB + Relevance AI

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Run Tool with Relevance AI API on New Database from MongoDB API

MongoDB + Relevance AI

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Run Tool with Relevance AI API on New Document from MongoDB API

MongoDB + Relevance AI

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Run Tool with Relevance AI API on New Field in Document from MongoDB API

MongoDB + Relevance AI

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Send Message to Agent with Relevance AI API on New Collection from MongoDB API

MongoDB + Relevance AI

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Popular Relevance AI and MongoDB Triggers#

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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Popular Relevance AI and MongoDB Actions#

Run Tool with the Relevance AI API

Executes a specific tool within Relevance AI and waits for a response for up to 60 seconds. See the documentation

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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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Send Message to Agent with the Relevance AI API

Sends a message directly to an agent in Relevance AI. This action doesn't wait for an agent response.

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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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Execute Aggregation with the MongoDB API

Execute an aggregation pipeline on a MongoDB collection. See the documentation

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Overview of Relevance AI#

Relevance AI is a powerful tool for handling complex data operations like clustering, vector search, and data visualization. On Pipedream, you can use the Relevance AI API to automate data enrichment, analysis, and integration tasks. This integration opens up possibilities for dynamic data workflows, enabling real-time data processing and insights generation across various platforms.

Connect Relevance AI#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    relevance_ai: {
      type: "app",
      app: "relevance_ai",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      method: "post",
      url: `https://api-${this.relevance_ai.$auth.region}.stack.tryrelevance.com/latest/agents/list `,
      headers: {
        "Authorization": `${this.relevance_ai.$auth.project}:${this.relevance_ai.$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#

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()
  },
})

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