← Dropbox + OpenAI (ChatGPT) integrations

Chat using File Search with OpenAI (ChatGPT) API on New Folder from Dropbox API

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New Folder from the Dropbox API
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Chat using File Search with the OpenAI (ChatGPT) API
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Getting Started

This integration creates a workflow with a Dropbox 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 Folder trigger
    1. Connect your Dropbox account
    2. Select a Path
    3. Configure Recursive
    4. Configure dropboxApphook
  3. Configure the Chat using File Search action
    1. Connect your OpenAI (ChatGPT) account
    2. Configure alert
    3. Select a Model
    4. Select a Vector Store ID
    5. Configure Chat Input
    6. Optional- Configure Instructions
    7. Optional- Configure Include Search Results
    8. Optional- Configure Max Number of Results
    9. Optional- Configure Metadata Filtering
    10. Optional- Configure Previous Response ID
    11. Optional- Select a Truncation
    12. Optional- Select a Response Format
    13. Optional- Configure Skip This Step
  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 when a new folder is created. Make sure the number of files/folders in the watched folder does not exceed 4000.
Version:0.0.18
Key:dropbox-new-folder

Dropbox Overview

The Dropbox API on Pipedream enables you to automate file and folder operations, streamlining workflows that involve storing, syncing, and sharing content. With this API, you can programmatically manage files, set up event-driven triggers based on changes within Dropbox, and leverage Pipedream's capabilities to connect with hundreds of other apps for extended automation scenarios. It's ideal for building custom file management solutions, archiving systems, or collaborative content workflows without writing extensive code.

Trigger Code

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

export default {
  ...common,
  dedupe: "unique",
  type: "source",
  key: "dropbox-new-folder",
  name: "New Folder",
  version: "0.0.18",
  description: "Emit new event when a new folder is created. Make sure the number of files/folders in the watched folder does not exceed 4000.",
  hooks: {
    async activate() {
      await this.getHistoricalEvents([
        "folder",
      ]);
      const state = await this.dropbox.initState(this);
      this._setDropboxState(state);
    },
  },
  async run() {
    const state = this._getDropboxState();
    const {
      ret: updates, state: newState,
    } = await this.dropbox.getUpdates(this, state);
    this._setDropboxState(newState);
    for (const update of updates) {
      if (update[".tag"] !== "folder") {
        continue;
      }
      this.$emit(update, this.getMeta(update.id, update.path_display || update.id));
    }
  },
  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.
LabelPropTypeDescription
DropboxdropboxappThis component uses the Dropbox app.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
PathpathstringSelect a value from the drop down menu.
Recursiverecursiveboolean

Also watch sub-directories and their contents.

dropboxApphook$.interface.apphook

Trigger Authentication

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

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

About Dropbox

Dropbox gives you secure access to all your files. Collaborate with friends, family, and coworkers from any device.

Action

Description:Chat with your files knowledge base (vector stores). [See the documentation](https://platform.openai.com/docs/guides/tools-file-search)
Version:0.0.6
Key:openai-chat-using-file-search

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 common from "../common/common.mjs";
import constants from "../../common/constants.mjs";

export default {
  ...common,
  name: "Chat using File Search",
  version: "0.0.6",
  key: "openai-chat-using-file-search",
  description: "Chat with your files knowledge base (vector stores). [See the documentation](https://platform.openai.com/docs/guides/tools-file-search)",
  type: "action",
  props: {
    openai,
    alert: {
      type: "alert",
      alertType: "info",
      content: "To use this action, you need to have set up a knowledge base in a vector store and uploaded files to it. [More infomation here](https://platform.openai.com/docs/guides/tools-file-search?lang=javascript#overview).",
    },
    modelId: {
      propDefinition: [
        openai,
        "chatCompletionModelId",
      ],
    },
    vectorStoreId: {
      propDefinition: [
        openai,
        "vectorStoreId",
      ],
      description: "The identifier of a vector store. Currently supports only one vector store at a time",
    },
    input: {
      type: "string",
      label: "Chat Input",
      description: "Text inputs to the model used to generate a response",
    },
    instructions: {
      type: "string",
      label: "Instructions",
      description: "Inserts a system (or developer) message as the first item in the model's context",
      optional: true,
    },
    includeSearchResults: {
      type: "boolean",
      label: "Include Search Results",
      description: "Include the search results in the response",
      default: false,
      optional: true,
    },
    maxNumResults: {
      type: "integer",
      label: "Max Number of Results",
      description: "Customize the number of results you want to retrieve from the vector store",
      optional: true,
    },
    metadataFiltering: {
      type: "boolean",
      label: "Metadata Filtering",
      description: "Configure how the search results are filtered based on file metadata",
      optional: true,
      reloadProps: true,
    },
    previousResponseId: {
      type: "string",
      label: "Previous Response ID",
      description: "The unique ID of the previous response to the model. Use this to create multi-turn conversations",
      optional: true,
    },
    truncation: {
      type: "string",
      label: "Truncation",
      description: "Specifies the truncation mode for the response if it's larger than the context window size",
      optional: true,
      default: "auto",
      options: [
        "auto",
        "disabled",
      ],
    },
    responseFormat: {
      type: "string",
      label: "Response Format",
      description: "- **Text**: Returns unstructured text output.\n- **JSON Schema**: Enables you to define a [specific structure for the model's output using a JSON schema](https://platform.openai.com/docs/guides/structured-outputs?api-mode=responses).",
      options: [
        "text",
        "json_schema",
      ],
      default: "text",
      optional: true,
      reloadProps: true,
    },
    skipThisStep: {
      type: "boolean",
      label: "Skip This Step",
      description: "Pass in a boolean custom expression to skip this step's execution at runtime",
      optional: true,
      default: false,
    },
  },
  additionalProps() {
    const {
      modelId,
      metadataFiltering,
      responseFormat,
    } = this;
    const props = {};

    if (this.openai.isReasoningModel(modelId)) {
      props.reasoningEffort = {
        type: "string",
        label: "Reasoning Effort",
        description: "Constrains effort on reasoning for reasoning models",
        optional: true,
        options: [
          "low",
          "medium",
          "high",
        ],
      };

      // aparrently not supported yet as of 12/march/2025
      // props.generateSummary = {
      //   type: "string",
      //   label: "Generate Reasoning Summary",
      //   description: "A summary of the reasoning performed by the model",
      //   optional: true,
      //   options: [
      //     "concise",
      //     "detailed",
      //   ],
      // };
    }

    // TODO: make this configuration user-friendly
    // https://platform.openai.com/docs/guides/retrieval?attributes-filter-example=region#attribute-filtering
    if (metadataFiltering) {
      props.filters = {
        type: "object",
        label: "Filters",
        description: "Filter the search results based on file metadata. [See the documentation here](https://platform.openai.com/docs/guides/retrieval#attribute-filtering)",
      };
    }

    if (responseFormat === constants.CHAT_RESPONSE_FORMAT.JSON_SCHEMA.value) {
      props.jsonSchema = {
        type: "string",
        label: "JSON Schema",
        description: "Define the schema that the model's output must adhere to. [Generate one here](https://platform.openai.com/docs/guides/structured-outputs/supported-schemas).",
      };
    }

    return props;
  },
  methods: {
    ...common.methods,
  },
  async run({ $ }) {
    if (this.skipThisStep) {
      $.export("$summary", "Step execution skipped");
      return;
    }

    const data = {
      model: this.modelId,
      input: this.input,
      instructions: this.instructions,
      previous_response_id: this.previousResponseId,
      truncation: this.truncation,
      tools: [
        {
          type: "file_search",
          vector_store_ids: [
            this.vectorStoreId,
          ],
          max_num_results: this.maxNumResults,
        },
      ],
    };

    if (this.includeSearchResults) {
      data.include = [
        "output[*].file_search_call.search_results",
      ];
    }

    if (this.filters) {
      data.tools[0].filters = this.filters;
    }

    if (this.openai.isReasoningModel(this.modelId) && this.reasoningEffort) {
      data.reasoning = {
        ...data.reasoning,
        effort: this.reasoningEffort,
      };
    }

    if (this.openai.isReasoningModel(this.modelId) && this.generateSummary) {
      data.reasoning = {
        ...data.reasoning,
        generate_summary: this.generateSummary,
      };
    }

    if (this.responseFormat === constants.CHAT_RESPONSE_FORMAT.JSON_SCHEMA.value) {
      try {
        data.text = {
          format: {
            type: this.responseFormat,
            ...JSON.parse(this.jsonSchema),
          },
        };
      } catch (error) {
        throw new Error("Invalid JSON format in the provided JSON Schema");
      }
    }

    const response = await this.openai.responses({
      $,
      data,
    });

    if (response) {
      $.export("$summary", `Successfully sent chat with id ${response.id}`);
      $.export("chat_responses", response.output);
    }

    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.
ModelmodelIdstringSelect a value from the drop down menu.
Vector Store IDvectorStoreIdstringSelect a value from the drop down menu.
Chat Inputinputstring

Text inputs to the model used to generate a response

Instructionsinstructionsstring

Inserts a system (or developer) message as the first item in the model's context

Include Search ResultsincludeSearchResultsboolean

Include the search results in the response

Max Number of ResultsmaxNumResultsinteger

Customize the number of results you want to retrieve from the vector store

Metadata FilteringmetadataFilteringboolean

Configure how the search results are filtered based on file metadata

Previous Response IDpreviousResponseIdstring

The unique ID of the previous response to the model. Use this to create multi-turn conversations

TruncationtruncationstringSelect a value from the drop down menu:autodisabled
Response FormatresponseFormatstringSelect a value from the drop down menu:textjson_schema
Skip This StepskipThisStepboolean

Pass in a boolean custom expression to skip this step's execution at runtime

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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