← SwaggerHub + OpenAI (ChatGPT) integrations

Create Fine Tuning Job with OpenAI (ChatGPT) API on New API Version Created from SwaggerHub API

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New API Version Created from the SwaggerHub API
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Create Fine Tuning Job with the OpenAI (ChatGPT) API
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Getting Started

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

  1. Select this integration
  2. Configure the New API Version Created trigger
    1. Connect your SwaggerHub account
    2. Configure timer
    3. Configure Owner
    4. Select a API
  3. Configure the Create Fine Tuning Job action
    1. Connect your OpenAI (ChatGPT) account
    2. Select a Fine Tuning Model
    3. Select a Training File
    4. Optional- Configure Hyperparameters
    5. Optional- Configure Suffix
    6. Optional- Select a Validation File
  4. Deploy the workflow
  5. Send a test event to validate your setup
  6. 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

Description:Emit new event for every created version of a specific API. [See the docs here](https://app.swaggerhub.com/apis/swagger-hub/registry-api/1.0.66#/APIs/getApiVersions)
Version:0.0.1
Key:swaggerhub-api-version-created

SwaggerHub Overview

The SwaggerHub API offers capabilities to streamline working with your Swagger (OpenAPI) definitions within SwaggerHub. On Pipedream, you can automate interactions with the SwaggerHub API to keep APIs in sync, manage your API versions, and integrate your API design workflow with other tools and services. Leverage Pipedream's serverless platform to create, update, and share your SwaggerHub API definitions across different environments or teams efficiently.

Trigger Code

import base from "../common/polling.mjs";

export default {
  ...base,
  key: "swaggerhub-api-version-created",
  name: "New API Version Created",
  description: "Emit new event for every created version of a specific API. [See the docs here](https://app.swaggerhub.com/apis/swagger-hub/registry-api/1.0.66#/APIs/getApiVersions)",
  type: "source",
  dedupe: "unique",
  version: "0.0.1",
};

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.
LabelPropTypeDescription
SwaggerHubswaggerhubappThis component uses the SwaggerHub app.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
timer$.interface.timer
Ownerownerstring

The owner of the API .e.g HUNGV. Please tap Refresh field on the other props after you change the value in this prop to get the up-to-date data.

APIapistringSelect a value from the drop down menu.

Trigger Authentication

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

To retrieve your API Key,

  • Navigate to your SwaggerHub account and sign in
  • Click the dropdown on the top right
  • Go to “API Key”

About SwaggerHub

Accelerating API delivery and quality through standards and collaboration, built on OpenAPI.

Action

Description:Creates a job that fine-tunes a specified model from a given dataset. [See the documentation](https://platform.openai.com/docs/api-reference/fine-tuning/create)
Version:0.0.6
Key:openai-create-fine-tuning-job

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";

export default {
  key: "openai-create-fine-tuning-job",
  name: "Create Fine Tuning Job",
  description: "Creates a job that fine-tunes a specified model from a given dataset. [See the documentation](https://platform.openai.com/docs/api-reference/fine-tuning/create)",
  version: "0.0.6",
  type: "action",
  props: {
    openai,
    model: {
      propDefinition: [
        openai,
        "fineTuningModel",
      ],
    },
    trainingFile: {
      propDefinition: [
        openai,
        "fileId",
        () => ({
          purpose: "fine-tune",
        }),
      ],
      label: "Training File",
      description: "The ID of an uploaded file that contains training data. You can use the **Upload File** action and reference the returned ID here.",
    },
    hyperParameters: {
      type: "object",
      label: "Hyperparameters",
      description: "The hyperparameters used for the fine-tuning job. [See details in the documentation](https://platform.openai.com/docs/api-reference/fine-tuning/create#fine-tuning-create-hyperparameters).",
      optional: true,
    },
    suffix: {
      type: "string",
      label: "Suffix",
      description: "A string of up to 18 characters that will be added to your fine-tuned model name.",
      optional: true,
    },
    validationFile: {
      propDefinition: [
        openai,
        "fileId",
        () => ({
          purpose: "fine-tune",
        }),
      ],
      label: "Validation File",
      description: "The ID of an uploaded file that contains validation data. [See details in the documentation](https://platform.openai.com/docs/api-reference/fine-tuning/create#fine-tuning-create-validation_file).",
      optional: true,
    },
  },
  async run({ $ }) {
    const response = await this.openai.createFineTuningJob({
      $,
      data: {
        model: this.model,
        training_file: this.trainingFile,
        hyperparameters: this.hyperParameters,
        suffix: this.suffix,
        validation_file: this.validationFile,
      },
    });

    $.export("$summary", `Successfully created fine-tuning job with model ${this.model}`);
    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.

LabelPropTypeDescription
OpenAI (ChatGPT)openaiappThis component uses the OpenAI (ChatGPT) app.
Fine Tuning ModelmodelstringSelect a value from the drop down menu:{ "label": "gpt-3.5-turbo-1106 (recommended)", "value": "gpt-3.5-turbo-1106" }{ "label": "gpt-3.5-turbo-0613", "value": "gpt-3.5-turbo-0613" }{ "label": "babbage-002", "value": "babbage-002" }{ "label": "davinci-002", "value": "davinci-002" }{ "label": "gpt-4-0613 (experimental — eligible users will be presented with an option to request access in the fine-tuning UI)", "value": "gpt-4-0613" }
Training FiletrainingFilestringSelect a value from the drop down menu.
HyperparametershyperParametersobject

The hyperparameters used for the fine-tuning job. See details in the documentation.

Suffixsuffixstring

A string of up to 18 characters that will be added to your fine-tuned model name.

Validation FilevalidationFilestringSelect a value from the drop down menu.

Action Authentication

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

About OpenAI (ChatGPT)

OpenAI is an AI research and deployment company with the mission to ensure that artificial general intelligence benefits all of humanity. They are the makers of popular models like ChatGPT, DALL-E, and Whisper.

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