Create Transcription with OpenAI (ChatGPT) API on Weather for ZIP Code from HERE API

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Weather for ZIP Code from the HERE 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 HERE 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 Weather for ZIP Code trigger
1. Connect your HERE account
2. Configure ZIP code
3. Configure timer
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#

Weather for ZIP Code on HERE

Description:Emits the weather report for a specific ZIP code on a schedule

Version:0.0.3

Key:here-weather-for-zip

View on GitHub

HERE Overview#

The HERE API provides a suite of location-based services including maps, geocoding, places, routing, and traffic. With Pipedream, you can automate workflows that require real-time location intelligence. For instance, enhance logistics with dynamic routing, personalize customer interactions with geolocation data, or monitor assets by integrating location updates into your systems.

Trigger Code#

const here = require("../../here.app.js");
const { DEFAULT_POLLING_SOURCE_TIMER_INTERVAL } = require("@pipedream/platform");

module.exports = {
  name: "Weather for ZIP Code",
  version: "0.0.3",
  key: "here-weather-for-zip",
  description: "Emits the weather report for a specific ZIP code on a schedule",
  type: "source",
  props: {
    here,
    zipCode: {
      propDefinition: [
        here,
        "zipCode",
      ],
    },
    timer: {
      type: "$.interface.timer",
      default: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
  },
  async run() {
    const report = await this.here.returnReportForZIP(this.zipCode);
    this.$emit(report, {
      summary: `Weather report for ${this.zipCode} at ${report.feedCreation}`,
      ts: Date.now(),
    });
  },
};

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
HERE	`here`	`app`	This component uses the HERE app.
ZIP code	`zipCode`	`integer`	The ZIP code you'd like to pull weather stats for (only supported for locations in the United States)
	`timer`	`$.interface.timer`

Trigger Authentication#

HERE uses API keys for authentication. When you connect your HERE account, Pipedream securely stores the keys so you can easily authenticate to HERE APIs in both code and no-code steps.

Sign up for a HERE account, then create a new application and associated API key — see the HERE Authentication Docs for step-by-step instructions.

Enter your API key below.

About HERE#

Build location-aware apps and services using the world’s #1 location platform

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 Weather for ZIP Code from HERE API

Pipedream makes it easy to connect APIs for OpenAI (ChatGPT), HERE 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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