Create Fine-Tune Job with Lamini API on Changes to Specific Files from Google Drive API

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Changes to Specific Files from the Google Drive API

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Create Fine-Tune Job with the Lamini API

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Getting Started#

This integration creates a workflow with a Google Drive trigger and Lamini action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the Changes to Specific Files trigger
1. Connect your Google Drive account
2. Optional- Configure Drive
3. Configure Push notification renewal schedule
4. Select one or more Files
5. Configure intervalAlert
6. Optional- Configure Minimum Interval Per File
7. Select one or more Types of updates
Configure the Create Fine-Tune Job action
1. Connect your Lamini account
2. Select a Model Name
3. Configure Dataset ID
4. Optional- Configure Finetune Arguments
5. Optional- Configure GPU Config
6. Optional- Configure Is Public
7. Optional- Configure Custom Model Name
8. Optional- Configure Wait for Completion
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#

Changes to Specific Files on Google Drive

Description:Watches for changes to specific files, emitting an event when a change is made to one of those files. To watch for changes to [shared drive](https://support.google.com/a/users/answer/9310351) files, use the **Changes to Specific Files (Shared Drive)** source instead.

Version:0.2.6

Key:google_drive-changes-to-specific-files

View on GitHub

Google Drive Overview#

The Google Drive API on Pipedream allows you to automate various file management tasks, such as creating, reading, updating, and deleting files within your Google Drive. You can also share files, manage permissions, and monitor changes to files and folders. This opens up possibilities for creating workflows that seamlessly integrate with other apps and services, streamlining document handling, backup processes, and collaborative workflows.

Trigger Code#

import cronParser from "cron-parser";
import sampleEmit from "./test-event.mjs";
import includes from "lodash/includes.js";
import { v4 as uuid } from "uuid";
import { MY_DRIVE_VALUE } from "../../common/constants.mjs";
import changesToSpecificFiles from "../changes-to-specific-files-shared-drive/changes-to-specific-files-shared-drive.mjs";

/**
 * This source uses the Google Drive API's
 * {@link https://developers.google.com/drive/api/v3/reference/files/watch files: watch}
 * endpoint to subscribe to changes to specific files in the user's drive.
 */
export default {
  ...changesToSpecificFiles,
  key: "google_drive-changes-to-specific-files",
  name: "Changes to Specific Files",
  description: "Watches for changes to specific files, emitting an event when a change is made to one of those files. To watch for changes to [shared drive](https://support.google.com/a/users/answer/9310351) files, use the **Changes to Specific Files (Shared Drive)** source instead.",
  version: "0.2.6",
  type: "source",
  // Dedupe events based on the "x-goog-message-number" header for the target channel:
  // https://developers.google.com/drive/api/v3/push#making-watch-requests
  dedupe: "unique",
  props: {
    ...changesToSpecificFiles.props,
    drive: {
      type: "string",
      label: "Drive",
      description: "Defaults to `My Drive`. To use a [Shared Drive](https://support.google.com/a/users/answer/9310351), use the **Changes to Specific Files (Shared Drive)** source instead.",
      optional: true,
      default: MY_DRIVE_VALUE,
    },
    updateTypes: {
      propDefinition: [
        changesToSpecificFiles.props.googleDrive,
        "updateTypes",
      ],
    },
  },
  hooks: {
    ...changesToSpecificFiles.hooks,
    async activate() {
      // Called when a component is created or updated. Handles all the logic
      // for starting and stopping watch notifications tied to the desired
      // files.

      // You can pass the same channel ID in watch requests for multiple files, so
      // our channel ID is fixed for this component to simplify the state we have to
      // keep track of.
      const channelID = uuid();

      // Subscriptions are keyed on Google's resourceID, "an opaque value that
      // identifies the watched resource". This value is included in request
      // headers, allowing us to look up the watched resource.
      let subscriptions = this._getSubscriptions() || {};

      const files = this.files;
      for (const fileID of files) {
        const {
          expiration,
          resourceId,
        } = await this.googleDrive.activateFileHook(
          channelID,
          this.http.endpoint,
          fileID,
        );
        // The fileID must be kept with the subscription metadata so we can
        // renew the watch request for this specific file when it expires.
        subscriptions[resourceId] = {
          expiration,
          fileID,
        };
      }

      // Save metadata on the subscription so we can stop / renew later
      this._setSubscriptions(subscriptions);
      this._setChannelID(channelID);
    },
    async deactivate() {
      const channelID = this._getChannelID();
      if (!channelID) {
        console.log(
          "Channel not found, cannot stop notifications for non-existent channel",
        );
        return;
      }

      const subscriptions = this._getSubscriptions() || {};
      for (const resourceId of Object.keys(subscriptions)) {
        await this.googleDrive.stopNotifications(channelID, resourceId);
      }

      // Reset DB state
      this._setSubscriptions({});
      this._setChannelID(null);
    },
  },
  methods: {
    ...changesToSpecificFiles.methods,
    _getSubscriptions() {
      return this.db.get("subscriptions") || {};
    },
    _setSubscriptions(subscriptions) {
      this.db.set("subscriptions", subscriptions);
    },
    _getNextTimerEventTimestamp(event) {
      if (event.cron) {
        return cronParser
          .parseExpression(event.cron)
          .next()
          .getTime();
      }
      if (event.interval_seconds) {
        return Date.now() + event.interval_seconds * 1000;
      }
    },
    async renewFileSubscriptions(event) {
      const subscriptions = this._getSubscriptions() || {};
      const channelID = this._getChannelID();
      const newChannelID = uuid();

      const nextRunTimestamp = this._getNextTimerEventTimestamp(event);

      for (const [
        currentResourceId,
        metadata,
      ] of Object.entries(subscriptions)) {
        const { fileID } = metadata;

        const subscription = {
          ...metadata,
          resourceId: currentResourceId,
        };
        const {
          expiration,
          resourceId,
        } = await this.googleDrive.renewFileSubscription(
          subscription,
          this.http.endpoint,
          channelID,
          newChannelID,
          fileID,
          nextRunTimestamp,
        );
        subscriptions[resourceId] = {
          expiration,
          fileID,
        };
      }
      this._setSubscriptions(subscriptions);
      this._setChannelID(newChannelID);
    },
  },
  async run(event) {
    // This function is polymorphic: it can be triggered as a cron job, to make sure we renew
    // watch requests for specific files, or via HTTP request (the change payloads from Google)

    // Component was invoked by timer
    if (event.timestamp) {
      return this.renewFileSubscriptions(event);
    }

    const channelID = this._getChannelID();
    let subscriptions = this._getSubscriptions() || {};

    const { headers } = event;

    if (
      !headers["x-goog-resource-state"] ||
      !headers["x-goog-resource-id"] ||
      !headers["x-goog-resource-uri"] ||
      !headers["x-goog-message-number"]
    ) {
      console.log("Request missing necessary headers: ", headers);
      return;
    }

    const incomingChannelID = headers["x-goog-channel-id"];
    if (incomingChannelID !== channelID) {
      console.log(
        `Channel ID of ${incomingChannelID} not equal to deployed component channel of ${channelID}`,
      );
      return;
    }

    if (subscriptions[headers["x-goog-resource-id"]] === undefined) {
      console.log(
        `Resource ID of ${headers["x-goog-resource-id"]} not currently being tracked. Exiting`,
      );
      return;
    }

    if (!includes(this.updateTypes, headers["x-goog-resource-state"])) {
      console.log(
        `Update type ${headers["x-goog-resource-state"]} not in list of updates to watch: `,
        this.updateTypes,
      );
      return;
    }

    // We observed false positives where a single change to a document would trigger two changes:
    // one to "properties" and another to "content,properties". But changes to properties
    // alone are legitimate, most users just won't want this source to emit in those cases.
    // If x-goog-changed is _only_ set to "properties", only move on if the user set the prop
    if (
      !this.watchForPropertiesChanges &&
      headers["x-goog-changed"] === "properties"
    ) {
      console.log(
        "Change to properties only, which this component is set to ignore. Exiting",
      );
      return;
    }

    const file = await this.googleDrive.getFileMetadata(
      headers["x-goog-resource-uri"],
    );

    if (!file || !Object.keys(file).length) {
      console.log("No file metadata returned, nothing to emit");
      return;
    }

    const [
      checkedFile,
    ] = this.checkMinimumInterval([
      file,
    ]);
    if (checkedFile) {
      this.processChange(file, headers);
    }
  },
  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
Google Drive	`googleDrive`	`app`	This component uses the Google Drive app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
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.
Drive	`drive`	`string`	Defaults to `My Drive`. To use a Shared Drive, use the Changes to Specific Files (Shared Drive) source instead.
Files	`files`	`string[]`	Select a value from the drop down menu.
Minimum Interval Per File	`perFileInterval`	`integer`	How many minutes to wait until the same file can emit another event. If set to `0`, this interval is disabled and all events will be emitted.
Types of updates	`updateTypes`	`string[]`	Select a value from the drop down menu:`{ "label": "'sync' - A channel was successfully created. You can expect to start receiving notifications for it.", "value": "sync" }{ "label": "'add' - A resource was created or shared.", "value": "add" }{ "label": "'remove' - An existing resource was deleted or unshared.", "value": "remove" }{ "label": "'update' - One or more properties (metadata) of a resource have been updated.", "value": "update" }{ "label": "'trash' - A resource has been moved to the trash.", "value": "trash" }{ "label": "'untrash' - A resource has been removed from the trash.", "value": "untrash" }{ "label": "'change' - One or more changelog items have been added.", "value": "change" }`

Trigger Authentication#

Google Drive uses OAuth authentication. When you connect your Google Drive account, Pipedream will open a popup window where you can sign into Google Drive and grant Pipedream permission to connect to your account. Pipedream securely stores and automatically refreshes the OAuth tokens so you can easily authenticate any Google Drive API.

Pipedream requests the following authorization scopes when you connect your account:

https://www.googleapis.com/auth/drive

About Google Drive#

Google Drive is a file storage and synchronization service which allows you to create and share your work online, and access your documents from anywhere.

Action#

Create Fine-Tune Job on Lamini

Description:Create a fine-tuning job with a dataset. [See the documentation](https://docs.lamini.ai/api/).

Version:0.0.2

Key:lamini-create-fine-tune-job

View on GitHub

Action Code#

import app from "../../lamini.app.mjs";
import constants from "../../common/constants.mjs";
import utils from "../../common/utils.mjs";

export default {
  key: "lamini-create-fine-tune-job",
  name: "Create Fine-Tune Job",
  description: "Create a fine-tuning job with a dataset. [See the documentation](https://docs.lamini.ai/api/).",
  version: "0.0.2",
  type: "action",
  props: {
    app,
    modelName: {
      description: "Base model to be fine-tuned.",
      propDefinition: [
        app,
        "modelName",
        () => ({
          includeFineTunedModels: false,
        }),
      ],
    },
    datasetId: {
      type: "string",
      label: "Dataset ID",
      description: "Previously uploaded dataset to use for training. Please use the **Upload Dataset** action to upload a dataset.",
    },
    fineTuneArgs: {
      type: "object",
      label: "Finetune Arguments",
      description: "Optional hyperparameters for fine-tuning. Each property is optional:\n- `index_pq_m`: Number of subquantizers for PQ (eg. 8)\n- `index_max_size`: Maximum index size (eg. 65536)\n- `max_steps`: Maximum number of training steps (eg. 60)\n- `batch_size`: Training batch size (eg. 1)\n- `learning_rate`: Learning rate (eg. 0.0003)\n- `index_pq_nbits`: Number of bits per subquantizer (eg. 8)\n- `max_length`: Maximum sequence length (eg. 2048)\n- `index_ivf_nlist`: Number of IVF lists (eg. 2048)\n- `save_steps`: Steps between checkpoints (eg. 60)\n- `args_name`: Name for the argument set (eg. \"demo\")\n- `r_value`: R value for LoRA (eg. 32)\n- `index_hnsw_m`: Number of neighbors in HNSW (eg. 32)\n- `index_method`: Indexing method (eg. \"IndexIVFPQ\")\n- `optim`: Optimizer to use (eg. \"adafactor\")\n- `index_hnsw_efConstruction`: HNSW construction parameter (eg. 16)\n- `index_hnsw_efSearch`: HNSW search parameter (eg. 8)\n- `index_k`: Number of nearest neighbors (eg. 2)\n- `index_ivf_nprobe`: Number of IVF probes (eg. 48)\n- `eval_steps`: Steps between evaluations (eg. 30)\n[See the documentation](https://docs.lamini.ai/tuning/hyperparameters/#finetune_args).",
      optional: true,
    },
    gpuConfig: {
      type: "object",
      label: "GPU Config",
      description: "Optional GPU configuration for fine-tuning. [See the documentation](https://docs.lamini.ai/tuning/hyperparameters/#gpu_config).",
      optional: true,
    },
    isPublic: {
      type: "boolean",
      label: "Is Public",
      description: "Whether this fine-tuning job and dataset should be publicly accessible.",
      optional: true,
    },
    customModelName: {
      type: "string",
      label: "Custom Model Name",
      description: "A human-readable name for the fine-tuned model.",
      optional: true,
    },
    waitForCompletion: {
      type: "boolean",
      label: "Wait for Completion",
      description: "If set to `true`, the action will wait and poll until the fine-tuning job is `COMPLETED`. If is set to `false`, it will return immediately after creating the job.",
      default: false,
      optional: true,
    },
  },
  methods: {
    createFineTuneJob(args = {}) {
      return this.app.post({
        versionPath: constants.VERSION_PATH.V1,
        path: "/train",
        ...args,
      });
    },
  },
  async run({ $ }) {
    const {
      app,
      createFineTuneJob,
      modelName,
      datasetId,
      fineTuneArgs,
      gpuConfig,
      isPublic,
      customModelName,
      waitForCompletion,
    } = this;

    const MAX_RETRIES = 15;
    const DELAY = 1000 * 30; // 30 seconds
    const { run } = $.context;

    // First run: Create the fine-tune job
    if (run.runs === 1) {
      const { upload_base_path: uploadBasePath } =
        await app.getUploadBasePath({
          $,
        });

      await app.getExistingDataset({
        $,
        data: {
          dataset_id: datasetId,
          upload_base_path: uploadBasePath,
        },
      });

      const response = await createFineTuneJob({
        $,
        data: {
          model_name: modelName,
          dataset_id: datasetId,
          upload_file_path: `${uploadBasePath}/${datasetId}.jsonlines`,
          finetune_args: utils.parseJson(fineTuneArgs),
          gpu_config: utils.parseJson(gpuConfig),
          is_public: isPublic,
          custom_model_name: customModelName,
        },
      });

      $.export("$summary", `Successfully created a fine-tune job with ID \`${response.job_id}\`.`);

      // If user doesn't want to wait, return immediately
      if (!waitForCompletion) {
        return response;
      }

      // Store job_id for polling and start rerun
      $.flow.rerun(DELAY, {
        jobId: response.job_id,
      }, MAX_RETRIES);
      return response;
    }

    // Subsequent runs: Poll for job status
    if (run.runs > MAX_RETRIES) {
      throw new Error("Max retries exceeded - fine-tuning job may still be running");
    }

    const { jobId } = run.context;

    // Poll for status
    const statusResponse = await app.getJobStatus({
      $,
      jobId,
    });

    // If job is completed, return the final status
    if (statusResponse.status === "COMPLETED") {
      $.export("$summary", `Fine-tuning job \`${jobId}\` completed successfully.`);
      return statusResponse;
    }

    // If job failed, throw error
    if (statusResponse.status === "FAILED") {
      throw new Error(`Fine-tuning job \`${jobId}\` failed.`);
    }

    // Otherwise, continue polling
    $.flow.rerun(DELAY, {
      jobId,
    }, MAX_RETRIES);
    return {
      status: statusResponse.status,
      jobId,
      message: `Job is still running. Current status: ${statusResponse.status}`,
    };
  },
};

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
Lamini	`app`	`app`	This component uses the Lamini app.
Model Name	`modelName`	`string`	Select a value from the drop down menu.
Dataset ID	`datasetId`	`string`	Previously uploaded dataset to use for training. Please use the Upload Dataset action to upload a dataset.
Finetune Arguments	`fineTuneArgs`	`object`	Optional hyperparameters for fine-tuning. Each property is optional: `index_pq_m`: Number of subquantizers for PQ (eg. 8) `index_max_size`: Maximum index size (eg. 65536) `max_steps`: Maximum number of training steps (eg. 60) `batch_size`: Training batch size (eg. 1) `learning_rate`: Learning rate (eg. 0.0003) `index_pq_nbits`: Number of bits per subquantizer (eg. 8) `max_length`: Maximum sequence length (eg. 2048) `index_ivf_nlist`: Number of IVF lists (eg. 2048) `save_steps`: Steps between checkpoints (eg. 60) `args_name`: Name for the argument set (eg. "demo") `r_value`: R value for LoRA (eg. 32) `index_hnsw_m`: Number of neighbors in HNSW (eg. 32) `index_method`: Indexing method (eg. "IndexIVFPQ") `optim`: Optimizer to use (eg. "adafactor") `index_hnsw_efConstruction`: HNSW construction parameter (eg. 16) `index_hnsw_efSearch`: HNSW search parameter (eg. 8) `index_k`: Number of nearest neighbors (eg. 2) `index_ivf_nprobe`: Number of IVF probes (eg. 48) `eval_steps`: Steps between evaluations (eg. 30) See the documentation
GPU Config	`gpuConfig`	`object`	Optional GPU configuration for fine-tuning. See the documentation
Is Public	`isPublic`	`boolean`	Whether this fine-tuning job and dataset should be publicly accessible.
Custom Model Name	`customModelName`	`string`	A human-readable name for the fine-tuned model.
Wait for Completion	`waitForCompletion`	`boolean`	If set to `true`, the action will wait and poll until the fine-tuning job is `COMPLETED`. If is set to `false`, it will return immediately after creating the job.

Action Authentication#

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

About Lamini#

Enterprise LLM Platform

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Pipedream makes it easy to connect APIs for Lamini, Google Drive and 2,700+ other apps remarkably fast.

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

Developers ♥ Pipedream

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