gpt-trainer

Create a personalized AI chatbot using your own data

Integrate the gpt-trainer API with the MongoDB API

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

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Create Chat Session with gpt-trainer API on New Collection from MongoDB API
MongoDB + gpt-trainer
 
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Create Chat Session with gpt-trainer API on New Database from MongoDB API
MongoDB + gpt-trainer
 
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Create Chat Session with gpt-trainer API on New Document from MongoDB API
MongoDB + gpt-trainer
 
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Create Chat Session with gpt-trainer API on New Field in Document from MongoDB API
MongoDB + gpt-trainer
 
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Create Chatbot with gpt-trainer API on New Collection from MongoDB API
MongoDB + gpt-trainer
 
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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 Chat Session with the gpt-trainer API

Create a chat session for a chatbot specified by chatbot UUID. 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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Create Chatbot with the gpt-trainer API

Creates a new chatbot that belongs to the authenticated user. See the documentation

 
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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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Create Message with the gpt-trainer API

Create a session message for a chatbot session specified by session UUID. See the documentation

 
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Overview of gpt-trainer

The gpt-trainer API is a tool designed to train, run, and manage custom GPT-2 and GPT-3 models. It provides endpoints for submitting training data, starting the training process, and generating text from the trained model. With Pipedream's serverless integration platform, you can automate workflows that interact with the gpt-trainer API. You can trigger workflows using webhooks, schedule them, or even run them in response to events from other apps. Integrate the gpt-trainer API with other services on Pipedream to create powerful applications such as automated content creation, personalized messaging, or AI-driven data analysis.

Connect gpt-trainer

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    gpt_trainer: {
      type: "app",
      app: "gpt_trainer",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://app.gpt-trainer.com/api/v1/chatbots`,
      headers: {
        Authorization: `Bearer ${this.gpt_trainer.$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()
  },
})

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