Modify Image with DreamStudio (Stable Diffusion) API on New Scheduled Tasks from Pipedream API

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New Scheduled Tasks from the Pipedream API

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Modify Image with the DreamStudio (Stable Diffusion) API

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Getting Started#

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

Select this integration
Configure the New Scheduled Tasks trigger
1. Connect your Pipedream account
2. Optional- Configure Secret
Configure the Modify Image action
1. Connect your DreamStudio (Stable Diffusion) account
2. Select a Organization Id
3. Select a Engine Id
4. Configure Text Prompts
5. Configure Init Image
6. Optional- Configure Cfg Scale
7. Optional- Select a Clip Guidance Preset
8. Optional- Select a Sampler
9. Optional- Configure Samples
10. Optional- Configure Seed
11. Optional- Configure Steps
12. Optional- Select a Style Preset
13. Optional- Configure Extras
14. Optional- Select a Init Image Mode
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 Scheduled Tasks on Pipedream

Description:Exposes an HTTP API for scheduling messages to be emitted at a future time

Version:0.3.1

Key:pipedream-new-scheduled-tasks

View on GitHub

Pipedream Overview#

Pipedream is an API that allows you to build applications that can connect to
various data sources and processes them in real-time. You can use Pipedream to
create applications that can perform ETL (Extract, Transform, and Load) tasks,
as well as to create data-driven workflows.

Some examples of applications you can build using the Pipedream API include:

An application that can extract data from a database, transform it, and then
load it into another database.
An application that can monitor a data source for changes, and then trigger a
workflow in response to those changes.
An application that can poll an API for new data, and then process that data
in real-time.

Trigger Code#

import pipedream from "../../pipedream.app.mjs";
import sampleEmit from "./test-event.mjs";
import { uuid } from "uuidv4";

export default {
  key: "pipedream-new-scheduled-tasks",
  name: "New Scheduled Tasks",
  type: "source",
  description:
    "Exposes an HTTP API for scheduling messages to be emitted at a future time",
  version: "0.3.1",
  dedupe: "unique", // Dedupe on a UUID generated for every scheduled task
  props: {
    pipedream,
    secret: {
      type: "string",
      secret: true,
      label: "Secret",
      optional: true,
      description:
        "**Optional but recommended**: if you enter a secret here, you must pass this value in the `x-pd-secret` HTTP header when making requests",
    },
    http: {
      label: "Endpoint",
      description: "The endpoint where you'll send task scheduler requests",
      type: "$.interface.http",
      customResponse: true,
    },
    db: "$.service.db",
  },
  methods: {
    // To schedule future emits, we emit to the selfChannel of the component
    selfChannel() {
      return "self";
    },
    // Queue for future emits that haven't yet been delivered
    queuedEventsChannel() {
      return "$in";
    },
    httpRespond({
      status, body,
    }) {
      this.http.respond({
        headers: {
          "content-type": "application/json",
        },
        status,
        body,
      });
    },
    async selfSubscribe() {
      // Subscribe the component to itself. We do this here because even in
      // the activate hook, the component isn't available to take subscriptions.
      // Scheduled tasks are sent to the self channel, which emits the message at
      // the specified delivery_ts to this component.
      const isSubscribedToSelf = this.db.get("isSubscribedToSelf");
      if (!isSubscribedToSelf) {
        const componentId = process.env.PD_COMPONENT;
        const selfChannel = this.selfChannel();
        console.log(`Subscribing to ${selfChannel} channel for event source`);
        console.log(
          await this.pipedream.subscribe(componentId, componentId, selfChannel),
        );
        this.db.set("isSubscribedToSelf", true);
      }
    },
    validateEventBody(event, operation) {
      const errors = [];

      // Secrets are optional, so we first check if the user configured
      // a secret, then check its value against the prop (validation below)
      if (this.secret && event.headers["x-pd-secret"] !== this.secret) {
        errors.push(
          "Secret on incoming request doesn't match the configured secret",
        );
      }

      if (operation === "schedule") {
        const {
          timestamp,
          message,
        } = event.body;
        // timestamp should be an ISO 8601 string. Parse and check for validity below.
        const epoch = Date.parse(timestamp);

        if (!timestamp) {
          errors.push(
            "No timestamp included in payload. Please provide an ISO8601 timestamp in the 'timestamp' field",
          );
        }
        if (timestamp && !epoch) {
          errors.push("Timestamp isn't a valid ISO 8601 string");
        }
        if (!message) {
          errors.push("No message passed in payload");
        }
      }

      return errors;
    },
    scheduleTask(event) {
      const errors = this.validateEventBody(event, "schedule");
      let status, body;

      if (errors.length) {
        console.log(errors);
        status = 400;
        body = {
          errors,
        };
      } else {
        const id = this.emitScheduleEvent(event.body, event.body.timestamp);
        status = 200;
        body = {
          msg: "Successfully scheduled task",
          id,
        };
      }

      this.httpRespond({
        status,
        body,
      });
    },
    emitScheduleEvent(event, timestamp) {
      const selfChannel = this.selfChannel();
      const epoch = Date.parse(timestamp);
      const $id = uuid();

      console.log(`Scheduled event to emit on: ${new Date(epoch)}`);

      this.$emit(
        {
          ...event,
          $channel: selfChannel,
          $id,
        },
        {
          name: selfChannel,
          id: $id,
          delivery_ts: epoch,
        },
      );

      return $id;
    },
    async cancelTask(event) {
      const errors = this.validateEventBody(event, "cancel");
      let status, msg;

      if (errors.length) {
        console.log(errors);
        status = 400;
        msg = "Secret on incoming request doesn't match the configured secret";
      } else {
        try {
          const id = event.body.id;
          const isCanceled = await this.deleteEvent(event);
          if (isCanceled) {
            status = 200;
            msg = `Cancelled scheduled task for event ${id}`;
          } else {
            status = 404;
            msg = `No event with ${id} found`;
          }
        } catch (error) {
          console.log(error);
          status = 500;
          msg = "Failed to schedule task. Please see the logs";
        }
      }

      this.httpRespond({
        status,
        body: {
          msg,
        },
      });
    },
    async deleteEvent(event) {
      const componentId = process.env.PD_COMPONENT;
      const inChannel = this.queuedEventsChannel();

      // The user must pass a scheduled event UUID they'd like to cancel
      // We lookup the event by ID and delete it
      const { id } = event.body;

      // List events in the $in channel - the queue of scheduled events, to be emitted in the future
      const events = await this.pipedream.listEvents(
        componentId,
        inChannel,
      );
      console.log("Events: ", events);

      // Find the event in the list by id
      const eventToCancel = events.data.find((e) => {
        const { metadata } = e;
        return metadata.id === id;
      });

      console.log("Event to cancel: ", eventToCancel);

      if (!eventToCancel) {
        console.log(`No event with ${id} found`);
        return false;
      }

      // Delete the event
      await this.pipedream.deleteEvent(
        componentId,
        eventToCancel.id,
        inChannel,
      );
      return true;
    },
    emitEvent(event, summary) {
      // Delete the channel name and id from the incoming event, which were used only as metadata
      const id = event.$id;
      delete event.$channel;
      delete event.$id;

      this.$emit(event, {
        summary: summary ?? JSON.stringify(event),
        id,
        ts: +new Date(),
      });
    },
  },
  async run(event) {
    await this.selfSubscribe();

    const { path } = event;
    if (path === "/schedule") {
      this.scheduleTask(event);
    } else if (path === "/cancel") {
      await this.cancelTask(event);
    } else if (event.$channel === this.selfChannel()) {
      this.emitEvent(event);
    }
  },
  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
Pipedream	`pipedream`	`app`	This component uses the Pipedream app.
Secret	`secret`	`string`	Optional but recommended: if you enter a secret here, you must pass this value in the `x-pd-secret` HTTP header when making requests
N/A	`http`	`$.interface.http`	This component uses `$.interface.http` to generate a unique URL when the component is first instantiated. Each request to the URL will trigger the `run()` method of the component.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.

Trigger Authentication#

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

About Pipedream#

Integration platform for developers

Action#

Modify Image on DreamStudio (Stable Diffusion)

Description:Modify an image based on a text prompt. [See the documentation](https://platform.stability.ai/docs/api-reference#tag/v1generation/operation/imageToImage)

Version:0.0.2

Key:dreamstudio-modify-image

View on GitHub

DreamStudio (Stable Diffusion) Overview#

The DreamStudio (Stable Diffusion) API taps into the power of AI to generate creative visual content from textual descriptions. With Pipedream, you can automate the process of creating images, integrate with various apps, and build complex workflows without servers. You can trigger image generation on demand, process user inputs, or schedule image creation - All seamlessly within Pipedream's ecosystem.

Action Code#

import FormData from "form-data";
import fs from "node:fs";
import {
  getImagePath, parsePrompts, writeImg,
} from "../../common/utils.mjs";
import common from "../common/images.mjs";

export default {
  ...common,
  key: "dreamstudio-modify-image",
  name: "Modify Image",
  version: "0.0.2",
  description: "Modify an image based on a text prompt. [See the documentation](https://platform.stability.ai/docs/api-reference#tag/v1generation/operation/imageToImage)",
  type: "action",
  props: {
    ...common.props,
    textPrompts: {
      propDefinition: [
        common.props.dreamstudio,
        "textPrompts",
      ],
    },
    initImage: {
      type: "string",
      label: "Init Image",
      description: "Image used to initialize the diffusion process, in lieu of random noise. It can be an URL to the image or a path to the image file saved to the `/tmp` directory (e.g. `/tmp/image.png`). [see docs here](https://pipedream.com/docs/workflows/steps/code/nodejs/working-with-files/#the-tmp-directory).",
    },
    cfgScale: {
      propDefinition: [
        common.props.dreamstudio,
        "cfgScale",
      ],
      optional: true,
    },
    clipGuidancePreset: {
      propDefinition: [
        common.props.dreamstudio,
        "clipGuidancePreset",
      ],
      optional: true,
    },
    sampler: {
      propDefinition: [
        common.props.dreamstudio,
        "sampler",
      ],
      optional: true,
    },
    samples: {
      propDefinition: [
        common.props.dreamstudio,
        "samples",
      ],
      optional: true,
    },
    seed: {
      propDefinition: [
        common.props.dreamstudio,
        "seed",
      ],
      optional: true,
    },
    steps: {
      propDefinition: [
        common.props.dreamstudio,
        "steps",
      ],
      optional: true,
    },
    stylePreset: {
      propDefinition: [
        common.props.dreamstudio,
        "stylePreset",
      ],
      optional: true,
    },
    extras: {
      propDefinition: [
        common.props.dreamstudio,
        "extras",
      ],
      optional: true,
    },
    initImageMode: {
      type: "string",
      label: "Init Image Mode",
      description: "Used to control how much influence the `init image` has on the result.",
      options: [
        "IMAGE_STRENGTH",
        "STEP_SCHEDULE",
      ],
      reloadProps: true,
      optional: true,
    },
  },
  async additionalProps() {
    const props = {};
    if (this.initImageMode === "STEP_SCHEDULE") {
      props.stepScheduleStart = {
        type: "string",
        label: "Step Schedule Start",
        description: "Skips a proportion of the start of the diffusion steps, allowing the init_image to influence the final generated image. Lower values will result in more influence from the init_image, while higher values will result in more influence from the diffusion steps. (e.g. a value of `0` would simply return you the init_image, where a value of `1` would return you a completely different image).",
        optional: true,
      };
      props.stepScheduleEnd = {
        type: "string",
        label: "Step Schedule End",
        description: "Skips a proportion of the end of the diffusion steps, allowing the init_image to influence the final generated image. Lower values will result in more influence from the init_image, while higher values will result in more influence from the diffusion steps.",
        optional: true,
      };
    }
    return props;
  },
  async run({ $ }) {
    const {
      dreamstudio,
      organizationId,
      engineId,
      textPrompts,
      initImage,
      initImageMode,
      cfgScale,
      clipGuidancePreset,
      stylePreset,
      stepScheduleStart,
      stepScheduleEnd,
      ...appendData
    } = this;
    const formData = new FormData();

    const parsedPrompts = parsePrompts(textPrompts);
    let i = 0;
    for (const prompt of parsedPrompts) {
      formData.append(`text_prompts[${i}][text]`, prompt.text);
      formData.append(`text_prompts[${i}][weight]`, prompt.weight);
      i++;
    }

    const imagePath = await getImagePath(initImage);
    formData.append("init_image", fs.readFileSync(imagePath));
    initImageMode && formData.append("init_image_mode", initImageMode);
    cfgScale && formData.append("cfg_scale", cfgScale);
    clipGuidancePreset && formData.append("clip_guidance_preset", clipGuidancePreset);
    stylePreset && formData.append("style_preset", stylePreset);
    stepScheduleStart && formData.append("step_schedule_start", stepScheduleStart);
    stepScheduleEnd && formData.append("step_schedule_end", stepScheduleEnd);

    for (const [
      label,
      value,
    ] of Object.entries(appendData)) {
      formData.append(label, value.toString());
    }

    const response = await dreamstudio.modifyImage({
      $,
      engineId,
      headers: {
        organization: organizationId,
        ...formData.getHeaders(),
      },
      data: formData,
    });

    const paths = await writeImg(response.artifacts);

    $.export("$summary", `The image was successfully modified and sent to ${paths.toString()}!`);
    return {
      ...response,
      tmpPaths: paths,
    };
  },
};

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
DreamStudio (Stable Diffusion)	`dreamstudio`	`app`	This component uses the DreamStudio (Stable Diffusion) app.
Organization Id	`organizationId`	`string`	Select a value from the drop down menu.
Engine Id	`engineId`	`string`	Select a value from the drop down menu.
Text Prompts	`textPrompts`	`string[]`	An array of valid JSON objects to use for generation. The JSON object must have the text and the weight. e.g.`{"text": "A lighthouse on a cliff", "weight": 0.5}`
Init Image	`initImage`	`string`	Image used to initialize the diffusion process, in lieu of random noise. It can be an URL to the image or a path to the image file saved to the `/tmp` directory (e.g. `/tmp/image.png`). see docs here.
Cfg Scale	`cfgScale`	`integer`	How strictly the diffusion process adheres to the prompt text (higher values keep your image closer to your prompt).
Clip Guidance Preset	`clipGuidancePreset`	`string`	Select a value from the drop down menu:`FAST_BLUEFAST_GREENNONESIMPLESLOWSLOWERSLOWEST`
Sampler	`sampler`	`string`	Select a value from the drop down menu:`DDIMDDPMK_DPMPP_2MK_DPMPP_2S_ANCESTRALK_DPM_2K_DPM_2_ANCESTRALK_EULERK_EULER_ANCESTRALK_HEUNK_LMS`
Samples	`samples`	`integer`	Number of images to generate
Seed	`seed`	`integer`	Random noise seed (omit this option or use `0` for a random seed).
Steps	`steps`	`integer`	Number od diffusion steps to run.
Style Preset	`stylePreset`	`string`	Select a value from the drop down menu:`3d-modelanalog-filmanimecinematiccomic-bookdigital-artenhancefantasy-artisometricline-artlow-polymodeling-compoundneon-punkorigamiphotographicpixel-arttile-texture`
Extras	`extras`	`object`	Extra parameters passed to the engine. These parameters are used for in-development or experimental features and may charge without werning, so please use with caution.
Init Image Mode	`initImageMode`	`string`	Select a value from the drop down menu:`IMAGE_STRENGTHSTEP_SCHEDULE`

Action Authentication#

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

Visit https://beta.dreamstudio.ai/account to find your API key and enter it below.

About DreamStudio (Stable Diffusion)#

DreamStudio is an easy-to-use interface for creating images using the latest version of the Stable Diffusion image generation model

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