Chaindesk

Build ChatGPT Agents trained on custom data.

Integrate the Chaindesk API with the MongoDB API

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

Create New Document with MongoDB API on New Response Generated from Chaindesk API
Chaindesk + MongoDB
 
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Delete a Document with MongoDB API on New Response Generated from Chaindesk API
Chaindesk + MongoDB
 
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Execute Aggregation with MongoDB API on New Response Generated from Chaindesk API
Chaindesk + MongoDB
 
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Find Document by Id with MongoDB API on New Response Generated from Chaindesk API
Chaindesk + MongoDB
 
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Find Document with MongoDB API on New Response Generated from Chaindesk API
Chaindesk + MongoDB
 
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New Response Generated from the Chaindesk API

Emit new event when a new message from an agent is created.

 
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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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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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Submit Message with the Chaindesk API

Allows the API to send a message input from the user.

 
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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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Update Agent with the Chaindesk API

Updates the agent to improve the accuracy of generated responses.

 
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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 Chaindesk

Chaindesk API offers a platform to create, deploy, and manage AI chatbots. It includes features such as natural language processing, integration capabilities, and a conversational interface to engage with users. Using Pipedream, you can leverage the Chaindesk API to build serverless workflows that trigger on various events and interact with other services to automate tasks, analyze conversations, and enhance user experiences.

Connect Chaindesk

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    chaindesk: {
      type: "app",
      app: "chaindesk",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.chaindesk.ai/agents`,
      headers: {
        Authorization: `Bearer ${this.chaindesk.$auth.api_key}`,
        "Content-Type": `application/json`,
      },
    })
  },
})

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()
  },
})