Create Transcription with OpenAI (ChatGPT) API on New Item in Feed from RSS API

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New Item in Feed from the RSS API

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Create Transcription with the OpenAI (ChatGPT) API

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Getting Started#

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

Select this integration
Configure the New Item in Feed trigger
1. Connect your RSS account
2. Configure timer
3. Configure Feed URL
4. Configure Published After
Configure the Create Transcription action
1. Connect your OpenAI (ChatGPT) account
2. Configure File
3. Select a Model
4. Optional- Configure Include
5. Optional- Configure Language
6. Optional- Configure Prompt
7. Optional- Select a Response Format
8. Optional- Configure Temperature
9. Optional- Configure Timestamp Granularities
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#

New Item in Feed on RSS

Description:Emit new items from an RSS feed

Version:1.2.7

Key:rss-new-item-in-feed

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 { defineSource } from "@pipedream/types";
import rss from "../../app/rss.app.mjs";
import rssCommon from "../common/common.mjs";
export default defineSource({
    ...rssCommon,
    key: "rss-new-item-in-feed",
    name: "New Item in Feed",
    description: "Emit new items from an RSS feed",
    version: "1.2.7",
    type: "source",
    dedupe: "unique",
    props: {
        ...rssCommon.props,
        url: {
            propDefinition: [
                rss,
                "url",
            ],
        },
        publishedAfter: {
            type: "string",
            label: "Published After",
            description: "Emit items published after the specified date in ISO 8601 format .e.g `2022-12-07T12:57:10+07:00`",
            default: new Date(Date.now() - 24 * 60 * 60 * 1000).toISOString(), // default to one day ago
        },
    },
    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.
            await this.rss.fetchAndParseFeed(this.url);
        },
    },
    methods: {
        ...rssCommon.methods,
        generateMeta: function (item) {
            return {
                id: this.rss.itemKey(item),
                summary: item.title,
                ts: Date.now(),
            };
        },
    },
    async run() {
        const items = await this.rss.fetchAndParseFeed(this.url);
        for (const item of items.reverse()) {
            const publishedAfter = +new Date(this.publishedAfter);
            const ts = this.rss.itemTs(item);
            if (Number.isNaN(publishedAfter) || publishedAfter > ts) {
                continue;
            }
            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 URL	`url`	`string`	Enter the URL for any public RSS feed
Published After	`publishedAfter`	`string`	Emit items published after the specified date in ISO 8601 format .e.g `2022-12-07T12:57:10+07:00`

Trigger Authentication#

The RSS API does not require authentication.

About RSS#

Real Simple Syndication

Action#

Create Transcription on OpenAI (ChatGPT)

Description:Transcribes audio into the input language. [See the documentation](https://platform.openai.com/docs/api-reference/audio/createTranscription)

Version:0.2.0

Key:openai-create-transcription

View on GitHub

OpenAI (ChatGPT) Overview#

OpenAI provides a suite of powerful AI models through its API, enabling developers to integrate advanced natural language processing and generative capabilities into their applications. Here’s an overview of the services offered by OpenAI's API:

Use Python or Node.js code to make fully authenticated API requests with your OpenAI account:

Action Code#

import openai from "../../openai.app.mjs";
import FormData from "form-data";
import fs from "fs";

export default {
  key: "openai-create-transcription",
  name: "Create Transcription",
  description: "Transcribes audio into the input language. [See the documentation](https://platform.openai.com/docs/api-reference/audio/createTranscription)",
  version: "0.2.0",
  type: "action",
  props: {
    openai,
    file: {
      propDefinition: [
        openai,
        "file",
      ],
    },
    model: {
      type: "string",
      label: "Model",
      description: "ID of the model to use",
      options: [
        "gpt-4o-transcribe",
        "gpt-4o-mini-transcribe",
        "whisper-1",
      ],
    },
    include: {
      type: "string[]",
      label: "Include",
      description: "Additional information to include in the transcription response. `logprobs` will return the log probabilities of the tokens in the response to understand the model's confidence in the transcription. `logprobs` only works with response_format set to `json` and only with the models `gpt-4o-transcribe` and `gpt-4o-mini-transcribe`.",
      optional: true,
    },
    language: {
      type: "string",
      label: "Language",
      description: "The language of the input audio. Supplying the input language in [ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. en) format will improve accuracy and latency.",
      default: "en",
      optional: true,
    },
    prompt: {
      type: "string",
      label: "Prompt",
      description: "An optional text to guide the model's style or continue a previous audio segment. The [prompt](https://platform.openai.com/docs/guides/speech-to-text#prompting) should match the audio language.",
      optional: true,
    },
    response_format: {
      type: "string",
      label: "Response Format",
      description: "The format of the output. For `gpt-4o-transcribe` and `gpt-4o-mini-transcribe`, the only supported format is `json`.",
      options: [
        "json",
        "text",
        "srt",
        "verbose_json",
        "vtt",
      ],
      optional: true,
    },
    temperature: {
      type: "string",
      label: "Temperature",
      description: "The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use log probability to automatically increase the temperature until certain thresholds are hit.",
      optional: true,
    },
    timestamp_granularities: {
      type: "string[]",
      label: "Timestamp Granularities",
      description: "The timestamp granularities to populate for this transcription. `response_format` must be set `verbose_json` to use timestamp granularities. Either or both of these options are supported: `word`, or `segment`. Note: There is no additional latency for segment timestamps, but generating word timestamps incurs additional latency.",
      optional: true,
    },
  },
  methods: {
    createTranscription(opts = {}) {
      return this.openai._makeRequest({
        method: "POST",
        path: "/audio/transcriptions",
        ...opts,
      });
    },
  },
  async run({ $ }) {
    const {
      /* eslint-disable no-unused-vars */
      openai,
      file,
      createTranscription,
      ...fields
    } = this;

    const data = new FormData();
    const content = fs.createReadStream(file.includes("tmp/")
      ? file
      : `/tmp/${file}`);

    data.append("file", content);

    for (const [
      key,
      value,
    ] of Object.entries(fields)) {
      const v = Array.isArray(value)
        ? value.join(",")
        : value;
      data.append(key, v);
    }

    const response = await createTranscription({
      $,
      data,
      headers: data.getHeaders(),
    });

    $.export("$summary", "Successfully converted speech to text");
    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
OpenAI (ChatGPT)	`openai`	`app`	This component uses the OpenAI (ChatGPT) app.
File	`file`	`string`	The path to a file in the `/tmp` directory. See the documentation on working with files. See the Assistants Tools guide to learn more about the types of files supported. The Fine-tuning API only supports `.jsonl` files.
Model	`model`	`string`	Select a value from the drop down menu:`gpt-4o-transcribegpt-4o-mini-transcribewhisper-1`
Include	`include`	`string[]`	Additional information to include in the transcription response. `logprobs` will return the log probabilities of the tokens in the response to understand the model's confidence in the transcription. `logprobs` only works with response_format set to `json` and only with the models `gpt-4o-transcribe` and `gpt-4o-mini-transcribe`.
Language	`language`	`string`	The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.
Prompt	`prompt`	`string`	An optional text to guide the model's style or continue a previous audio segment. The prompt should match the audio language.
Response Format	`response_format`	`string`	Select a value from the drop down menu:`jsontextsrtverbose_jsonvtt`
Temperature	`temperature`	`string`	The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use log probability to automatically increase the temperature until certain thresholds are hit.
Timestamp Granularities	`timestamp_granularities`	`string[]`	The timestamp granularities to populate for this transcription. `response_format` must be set `verbose_json` to use timestamp granularities. Either or both of these options are supported: `word`, or `segment`. Note: There is no additional latency for segment timestamps, but generating word timestamps incurs additional latency.

Create Transcription with OpenAI (ChatGPT) API on New Item in Feed from RSS API

Pipedream makes it easy to connect APIs for OpenAI (ChatGPT), RSS and 2,500+ other apps remarkably fast.

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

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