Create Message with gpt-trainer API on Random item from multiple RSS feeds from RSS API

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Trigger workflow on

Random item from multiple RSS feeds from the RSS API

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Create Message with the gpt-trainer API

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Getting Started#

This integration creates a workflow with a RSS trigger and gpt-trainer action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the Random item from multiple RSS feeds trigger
1. Connect your RSS account
2. Configure timer
3. Configure Feed URLs
Configure the Create Message action
1. Connect your gpt-trainer account
2. Select a Chatbot UUID
3. Select a Session UUID
4. Configure Message Query
Deploy the workflow
Send a test event to validate your setup
Turn on the trigger

Details#

This integration uses pre-built, source-available components from Pipedream's GitHub repo. These components are developed by Pipedream and the community, and verified and maintained by Pipedream.

To contribute an update to an existing component or create a new component, create a PR on GitHub. If you're new to Pipedream component development, you can start with quickstarts for trigger span and action development, and then review the component API reference.

Trigger#

Random item from multiple RSS feeds on RSS

Description:Emit a random item from multiple RSS feeds

Version:0.2.7

Key:rss-random-item-in-multiple-feeds

View on GitHub

RSS Overview#

The RSS app allows users to automatically fetch and parse updates from web feeds. This functionality is pivotal for staying abreast of content changes or updates from websites, blogs, and news outlets that offer RSS feeds. With Pipedream, you can harness the RSS API to trigger workflows that enable a broad range of automations, like content aggregation, monitoring for specific keywords, notifications, and data synchronization across platforms.

Trigger Code#

import rss from "../../app/rss.app.mjs";
import { defineSource } from "@pipedream/types";
import rssCommon from "../common/common.mjs";
export default defineSource({
    ...rssCommon,
    key: "rss-random-item-in-multiple-feeds",
    name: "Random item from multiple RSS feeds",
    type: "source",
    description: "Emit a random item from multiple RSS feeds",
    version: "0.2.7",
    props: {
        ...rssCommon.props,
        urls: {
            propDefinition: [
                rss,
                "urls",
            ],
        },
    },
    dedupe: "unique",
    hooks: {
        async activate() {
            // Try to parse the feed one time to confirm we can fetch and parse.
            // The code will throw any errors to the user.
            for (const url of this.urls) {
                await this.rss.fetchAndParseFeed(url);
            }
        },
    },
    async run() {
        const items = [];
        for (const url of this.urls) {
            const feedItems = await this.rss.fetchAndParseFeed(url);
            items.push(...feedItems);
        }
        const item = items[Math.floor(Math.random() * items.length)];
        const meta = this.generateMeta(item);
        this.$emit(item, meta);
    },
});

Trigger Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI and CLI.

Label	Prop	Type	Description
RSS	`rss`	`app`	This component uses the RSS app.
	`timer`	`$.interface.timer`	How often you want to poll the feed for new items
Feed URLs	`urls`	`string[]`	Enter either one or multiple URLs from any public RSS feed

Trigger Authentication#

The RSS API does not require authentication.

About RSS#

Real Simple Syndication

Action#

Create Message on gpt-trainer

Description:Create a session message for a chatbot session specified by session UUID. [See the documentation](https://guide.gpt-trainer.com/api-reference/messages/create)

Version:0.0.1

Key:gpt_trainer-create-message

View on GitHub

gpt-trainer Overview#

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.

Action Code#

import app from "../../gpt_trainer.app.mjs";

export default {
  key: "gpt_trainer-create-message",
  name: "Create Message",
  description: "Create a session message for a chatbot session specified by session UUID. [See the documentation](https://guide.gpt-trainer.com/api-reference/messages/create)",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    chatbotUuid: {
      propDefinition: [
        app,
        "chatbotUuid",
      ],
    },
    sessionUuid: {
      propDefinition: [
        app,
        "sessionUuid",
        ({ chatbotUuid }) => ({
          chatbotUuid,
        }),
      ],
    },
    query: {
      type: "string",
      label: "Message Query",
      description: "The query message to send to the chatbot session",
    },
  },
  methods: {
    createSessionMessage({
      sessionUuid, ...args
    } = {}) {
      return this.app.post({
        path: `/session/${sessionUuid}/message/stream`,
        ...args,
      });
    },
  },
  async run({ $ }) {
    const {
      createSessionMessage,
      sessionUuid,
      query,
    } = this;

    const response = await createSessionMessage({
      $,
      sessionUuid,
      data: {
        query,
      },
    });

    $.export("$summary", "Successfully created message.");
    return response;
  },
};

Action Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI.

Label	Prop	Type	Description
gpt-trainer	`app`	`app`	This component uses the gpt-trainer app.
Chatbot UUID	`chatbotUuid`	`string`	Select a value from the drop down menu.
Session UUID	`sessionUuid`	`string`	Select a value from the drop down menu.
Message Query	`query`	`string`	The query message to send to the chatbot session