Add Request to Queue with fal.ai API on New Run State Changed from OpenAI (ChatGPT) API

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New Run State Changed from the OpenAI (ChatGPT) API

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Add Request to Queue with the fal.ai API

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Getting Started#

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

Select this integration
Configure the New Run State Changed trigger
1. Connect your OpenAI (ChatGPT) account
2. Configure timer
3. Configure Thread ID
Configure the Add Request to Queue action
1. Connect your fal.ai account
2. Configure App ID
3. Configure Data
4. Optional- Configure Rerun Enabled
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 Run State Changed on OpenAI (ChatGPT)

Description:Emit new event every time a run changes its status. [See the documentation](https://platform.openai.com/docs/api-reference/runs/listRuns)

Version:0.0.6

Key:openai-new-run-state-changed

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:

Trigger Code#

import common from "../common/common.mjs";
import sampleEmit from "./test-event.mjs";

export default {
  ...common,
  key: "openai-new-run-state-changed",
  name: "New Run State Changed",
  description: "Emit new event every time a run changes its status. [See the documentation](https://platform.openai.com/docs/api-reference/runs/listRuns)",
  version: "0.0.6",
  type: "source",
  dedupe: "unique",
  props: {
    ...common.props,
    threadId: {
      propDefinition: [
        common.props.openai,
        "threadId",
      ],
    },
  },
  methods: {
    ...common.methods,
    getStatusItems() {
      return this.db.get("statusItems");
    },
    setStatusItems(value) {
      this.db.set("statusItems", value);
    },
    async getData() {
      const {
        openai,
        threadId,
      } = this;

      const { data } = await openai.listRuns({
        threadId,
      });

      return data;
    },
    getMeta(item) {
      const ts = Date.now();
      return {
        id: `${item.id}-${ts}`,
        summary: `Run State Changed: ${item.id}`,
        ts,
      };
    },
    statusByItemId(itemId, statusItems) {
      const { [itemId]: status } = statusItems || {};
      return status;
    },
    buildStatusItems(data) {
      return data?.reduce((acc, item) => ({
        ...acc,
        [item.id]: item.status,
      }), {});
    },
    async getAndProcessItems(maxEvents) {
      const {
        getData,
        getStatusItems,
        setStatusItems,
        statusByItemId,
        buildStatusItems,
        getMeta,
        $emit: emit,
      } = this;

      const data = await getData();
      const statusItems = getStatusItems();

      Array.from(data)
        .reverse()
        .forEach((item, index) => {
          const statusChanged = statusByItemId(item.id, statusItems) !== item.status;
          if ((!maxEvents || index < maxEvents) && statusChanged) {
            emit(item, getMeta(item));
          }
        });

      setStatusItems(buildStatusItems(data));
    },
  },
  sampleEmit,
};

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
OpenAI (ChatGPT)	`openai`	`app`	This component uses the OpenAI (ChatGPT) app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`
Thread ID	`threadId`	`string`	The unique identifier for the thread. Example: `thread_abc123`. To locate the thread ID, make sure your OpenAI Threads setting (Settings -> Organization/Personal -> General -> Features and capabilities -> Threads) is set to "Visible to organization owners" or "Visible to everyone". You can then access the list of threads and click on individual threads to reveal their IDs

Trigger 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.

Action#

Add Request to Queue on fal.ai

Description:Adds a request to the queue for asynchronous processing, including specifying a webhook URL for receiving updates. [See the documentation](https://fal.ai/docs/model-endpoints/queue#queue-endpoints).

Version:0.0.1

Key:fal_ai-add-request-to-queue

View on GitHub

Action Code#

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

export default {
  key: "fal_ai-add-request-to-queue",
  name: "Add Request to Queue",
  description: "Adds a request to the queue for asynchronous processing, including specifying a webhook URL for receiving updates. [See the documentation](https://fal.ai/docs/model-endpoints/queue#queue-endpoints).",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    appId: {
      propDefinition: [
        app,
        "appId",
      ],
    },
    data: {
      type: "object",
      label: "Data",
      description: "Additional data to include with the request. [See the documentation](https://fal.ai/models/fal-ai/lora/api#schema-input) for more input fields.",
      default: {
        model_name: "stabilityai/stable-diffusion-xl-base-1.0",
        prompt: "Photo of a european medieval 40 year old queen, silver hair, highly detailed face, detailed eyes, head shot, intricate crown, age spots, wrinkles",
      },
    },
    reRunEnabled: {
      type: "boolean",
      label: "Rerun Enabled",
      description: "Enable the step to rerun to retrieve the request response. [See the documentation](https://pipedream.com/docs/code/nodejs/rerun/#flowrerun).",
      optional: true,
      reloadProps: true,
      default: false,
    },
  },
  additionalProps() {
    if (this.reRunEnabled) {
      return {
        reRunTimeoutInSecs: {
          type: "integer",
          label: "Rerun Timeout",
          description: "The time in seconds to wait before rerunning the step to retrieve the request response. Eg. `30`. [See the documentation](https://pipedream.com/docs/code/nodejs/rerun/#flowrerun).",
          optional: true,
          min: 10,
        },
      };
    }

    return {
      falWebhook: {
        type: "string",
        label: "Webhook URL",
        description: "The URL to receive updates via webhook.",
        optional: true,
      },
    };
  },
  methods: {
    addToQueue({
      appId, ...args
    } = {}) {
      return this.app.post({
        path: `/${appId}`,
        ...args,
      });
    },
  },
  async run({ $ }) {
    const {
      context: {
        run: {
          runs,
          callback_request: callbackRequest,
        },
      },
    } = $;

    const {
      app,
      addToQueue,
      appId,
      data,
      falWebhook,
      reRunEnabled,
      reRunTimeoutInSecs,
    } = this;

    if (!reRunEnabled) {
      const response = await addToQueue({
        $,
        appId,
        params: {
          fal_webhook: falWebhook,
        },
        data,
      });

      $.export("$summary", `Successfully added the request to the queue with ID \`${response.request_id}\`.`);
      return response;
    }

    if (runs === 1) {
      const timeout = 1000 * (reRunTimeoutInSecs || 10);
      const { resume_url: resumeUrl } = $.flow.rerun(timeout, null, 1);

      return addToQueue({
        $,
        appId,
        params: {
          fal_webhook: resumeUrl,
        },
        data,
      });
    }

    const response = await app.getRequestResponse({
      $,
      appId,
      requestId: callbackRequest.body?.request_id,
    });

    $.export("$summary", "Successfully retrieved the request response.");
    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
fal.ai	`app`	`app`	This component uses the fal.ai app.
App ID	`appId`	`string`	The unique identifier for the app. Eg. `lora`.
Data	`data`	`object`	Additional data to include with the request. See the documentation for more input fields.
Rerun Enabled	`reRunEnabled`	`boolean`	Enable the step to rerun to retrieve the request response. See the documentation.