Chat with OpenAI (ChatGPT) API on Watch Folder from pCloud API

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Watch Folder from the pCloud API

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Getting Started#

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

Select this integration
Configure the Watch Folder trigger
1. Connect your pCloud account
2. Configure Polling schedule
3. Select a Folder ID
4. Select a Folder Event
5. Optional- Configure Show Deleted?
Configure the Chat action
1. Connect your OpenAI (ChatGPT) account
2. Select a Model
3. Configure User Message
4. Optional- Configure Max Tokens
5. Optional- Configure Temperature
6. Optional- Configure Top P
7. Optional- Configure N
8. Optional- Configure Stop
9. Optional- Configure Presence Penalty
10. Optional- Configure Frequency Penalty
11. Optional- Configure User
12. Optional- Configure System Instructions
13. Optional- Configure Prior Message History
14. Optional- Configure Images
15. Optional- Configure Audio
16. Optional- Select a Response Format
17. Optional- Select one or more Tool Types
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#

Watch Folder on pCloud

Description:Emit new event when a file is created or modified in the specified folder.

Version:0.0.4

Key:pcloud-watch-folder

View on GitHub

pCloud Overview#

The pCloud API allows for direct interaction with your pCloud account, providing access to files and folders within your cloud storage. With Pipedream, you can automate file management tasks such as uploading, downloading, and synchronizing files. Additionally, you can create workflows to organize your cloud storage, share files with team members, or back up important data from various sources.

Trigger Code#

import pcloud from "../../pcloud.app.mjs";
import { DEFAULT_POLLING_SOURCE_TIMER_INTERVAL } from "@pipedream/platform";

export default {
  key: "pcloud-watch-folder",
  name: "Watch Folder",
  description: "Emit new event when a file is created or modified in the specified folder.",
  version: "0.0.4",
  type: "source",
  dedupe: "unique",
  props: {
    pcloud,
    db: "$.service.db",
    timer: {
      label: "Polling schedule",
      description: "Pipedream polls pCloud for events on this schedule.",
      type: "$.interface.timer",
      default: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
    folderId: {
      propDefinition: [
        pcloud,
        "folderId",
      ],
      description: "Select a **Folder** to watch for changes. Alternatively, you can provide a custom *Folder ID*.",
    },
    event: {
      type: "string",
      label: "Folder Event",
      options: [
        "Created",
        "Modified",
      ],
      description: "Specify when to emit an event related to a given folder.",
      default: "Created",
    },
    showDeleted: {
      propDefinition: [
        pcloud,
        "showDeleted",
      ],
    },
  },
  hooks: {
    async deploy() {
      const files = [];
      const { contents } = await this.getContents();
      if (!contents) {
        return;
      }
      for (const folderItem of contents) {
        if (this.isRelevant(folderItem)) {
          files.push(folderItem);
          if (files.length == 10) {
            break;
          }
        }
      }
      files.forEach(this.emitpCloudEvent);
      this._setPreviousFiles(contents);
    },
  },
  methods: {
    _getPreviousFiles() {
      return this.db.get("previousFiles");
    },
    _setPreviousFiles(files) {
      const key = this.getFileKey();
      const previousFiles = files.filter((file) => file[key]).map((file) => ({
        [file[key]]: true,
      }));
      this.db.set("previousFiles", previousFiles);
    },
    getFileKey() {
      return this.event === "Created"
        ? "fileid"
        : "hash";
    },
    async getContents() {
      return this.pcloud._withRetries(() =>
        this.pcloud.listContents(
          this.folderId,
          false,
          this.showDeleted,
          false,
          false,
        ));
    },
    emitpCloudEvent(pCloudEvent) {
      const metadata = this.getEventData(pCloudEvent);
      this.$emit(pCloudEvent, metadata);
    },
    getEventData(pcloudEvent) {
      const key = this.getFileKey();
      return {
        id: pcloudEvent[key],
        summary: `${this.event} file "${pcloudEvent.name}"`,
        ts: Date.now(),
      };
    },
    isRelevant(folderItem, previousFiles = []) {
      const key = this.getFileKey();
      return !folderItem.isFolder && !previousFiles[folderItem[key]];
    },
  },
  async run() {
    const previousFiles = this._getPreviousFiles();
    const files = [];
    const { contents } = await this.getContents();
    if (!contents) {
      console.log("No data available, skipping iteration");
      return;
    }
    for (const folderItem of contents) {
      if (this.isRelevant(folderItem, previousFiles)) {
        files.push(folderItem);
      }
    }
    files.forEach(this.emitpCloudEvent);
    this._setPreviousFiles(contents);
  },
};

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
pCloud	`pcloud`	`app`	This component uses the pCloud app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Polling schedule	`timer`	`$.interface.timer`	Pipedream polls pCloud for events on this schedule.
Folder ID	`folderId`	`integer`	Select a value from the drop down menu.
Folder Event	`event`	`string`	Select a value from the drop down menu:`CreatedModified`
Show Deleted?	`showDeleted`	`boolean`	If true, deleted files and folders that can be undeleted will be displayed.

Trigger Authentication#

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

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

About pCloud#

Secure encrypted cloud storage

Action#

Chat on OpenAI (ChatGPT)

Description:The Chat API, using the `gpt-3.5-turbo` or `gpt-4` model. [See the documentation](https://platform.openai.com/docs/api-reference/chat)

Version:0.2.3

Key:openai-chat

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:

Action Code#

import openai from "../../openai.app.mjs";
import common from "../common/common.mjs";
import constants from "../../common/constants.mjs";
import { ConfigurationError } from "@pipedream/platform";

export default {
  ...common,
  name: "Chat",
  version: "0.2.3",
  key: "openai-chat",
  description: "The Chat API, using the `gpt-3.5-turbo` or `gpt-4` model. [See the documentation](https://platform.openai.com/docs/api-reference/chat)",
  type: "action",
  props: {
    openai,
    modelId: {
      propDefinition: [
        openai,
        "chatCompletionModelId",
      ],
    },
    userMessage: {
      label: "User Message",
      type: "string",
      description: "The user messages provide instructions to the assistant. They can be generated by the end users of an application, or set by a developer as an instruction.",
    },
    ...common.props,
    systemInstructions: {
      label: "System Instructions",
      type: "string",
      description: "The system message helps set the behavior of the assistant. For example: \"You are a helpful assistant.\" [See these docs](https://platform.openai.com/docs/guides/chat/instructing-chat-models) for tips on writing good instructions.",
      optional: true,
    },
    messages: {
      label: "Prior Message History",
      type: "string[]",
      description: "_Advanced_. Because [the models have no memory of past chat requests](https://platform.openai.com/docs/guides/chat/introduction), all relevant information must be supplied via the conversation. You can provide [an array of messages](https://platform.openai.com/docs/guides/chat/introduction) from prior conversations here. If this param is set, the action ignores the values passed to **System Instructions** and **Assistant Response**, appends the new **User Message** to the end of this array, and sends it to the API.",
      optional: true,
    },
    images: {
      label: "Images",
      type: "string[]",
      description: "Provide one or more images to [OpenAI's vision model](https://platform.openai.com/docs/guides/vision). Accepts URLs or base64 encoded strings. Compatible with the `gpt4-vision-preview` model",
      optional: true,
    },
    audio: {
      type: "string",
      label: "Audio",
      description: "Provide the file path to an audio file in the `/tmp` directory. For use with the `gpt-4o-audio-preview` model. Currently supports `wav` and `mp3` files.",
      optional: true,
    },
    responseFormat: {
      type: "string",
      label: "Response Format",
      description: "Specify the format that the model must output. \n- **Text** (default): Returns unstructured text output.\n- **JSON Object**: Ensures the model's output is a valid JSON object.\n- **JSON Schema** (GPT-4o and later): Enables you to define a specific structure for the model's output using a JSON schema. Supported with models `gpt-4o-2024-08-06` and later, and `gpt-4o-mini-2024-07-18` and later.",
      options: Object.values(constants.CHAT_RESPONSE_FORMAT),
      default: constants.CHAT_RESPONSE_FORMAT.TEXT.value,
      optional: true,
      reloadProps: true,
    },
    toolTypes: {
      type: "string[]",
      label: "Tool Types",
      description: "The types of tools to enable on the assistant",
      options: constants.TOOL_TYPES.filter((toolType) => toolType === "function"),
      optional: true,
      reloadProps: true,
    },
  },
  additionalProps() {
    const {
      responseFormat,
      toolTypes,
      numberOfFunctions,
    } = this;
    const props = {};

    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. [See the documentation here](https://platform.openai.com/docs/guides/structured-outputs/supported-schemas).",
      };
    }

    if (toolTypes?.includes("function")) {
      props.numberOfFunctions = {
        type: "integer",
        label: "Number of Functions",
        description: "The number of functions to define",
        optional: true,
        reloadProps: true,
        default: 1,
      };

      for (let i = 0; i < (numberOfFunctions || 1); i++) {
        props[`functionName_${i}`] = {
          type: "string",
          label: `Function Name ${i + 1}`,
          description: "The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.",
        };
        props[`functionDescription_${i}`] = {
          type: "string",
          label: `Function Description ${i + 1}`,
          description: "A description of what the function does, used by the model to choose when and how to call the function.",
          optional: true,
        };
        props[`functionParameters_${i}`] = {
          type: "object",
          label: `Function Parameters ${i + 1}`,
          description: "The parameters the functions accepts, described as a JSON Schema object. See the [guide](https://platform.openai.com/docs/guides/text-generation/function-calling) for examples, and the [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for documentation about the format.",
          optional: true,
        };
      }
    }

    return props;
  },
  methods: {
    ...common.methods,
    _buildTools() {
      const tools = this.toolTypes?.filter((toolType) => toolType !== "function")?.map((toolType) => ({
        type: toolType,
      })) || [];
      if (this.toolTypes?.includes("function")) {
        const numberOfFunctions = this.numberOfFunctions || 1;
        for (let i = 0; i < numberOfFunctions; i++) {
          tools.push({
            type: "function",
            function: {
              name: this[`functionName_${i}`],
              description: this[`functionDescription_${i}`],
              parameters: this[`functionParameters_${i}`],
            },
          });
        }
      }
      return tools.length
        ? tools
        : undefined;
    },
  },
  async run({ $ }) {
    if (this.audio && !this.modelId.includes("gpt-4o-audio-preview")) {
      throw new ConfigurationError("Use of audio files requires using the `gpt-4o-audio-preview` model.");
    }

    const args = this._getChatArgs();

    const response = await this.openai.createChatCompletion({
      $,
      data: {
        ...args,
        tools: this._buildTools(),
      },
    });

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

    const { messages } = args;
    return {
      original_messages: messages,
      original_messages_with_assistant_response: messages.concat(response.choices[0]?.message),
      ...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
OpenAI (ChatGPT)	`openai`	`app`	This component uses the OpenAI (ChatGPT) app.
Model	`modelId`	`string`	Select a value from the drop down menu.
User Message	`userMessage`	`string`	The user messages provide instructions to the assistant. They can be generated by the end users of an application, or set by a developer as an instruction.
Max Tokens	`maxTokens`	`integer`	The maximum number of tokens to generate in the completion.
Temperature	`temperature`	`string`	Optional. What sampling temperature to use. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer.
Top P	`topP`	`string`	An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or `temperature` but not both.
N	`n`	`integer`	How many completions to generate for each prompt
Stop	`stop`	`string[]`	Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.
Presence Penalty	`presencePenalty`	`string`	Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
Frequency Penalty	`frequencyPenalty`	`string`	Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
User	`user`	`string`	A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more here.
System Instructions	`systemInstructions`	`string`	The system message helps set the behavior of the assistant. For example: "You are a helpful assistant." See these docs for tips on writing good instructions.
Prior Message History	`messages`	`string[]`	Advanced. Because the models have no memory of past chat requests, all relevant information must be supplied via the conversation. You can provide an array of messages from prior conversations here. If this param is set, the action ignores the values passed to System Instructions and Assistant Response, appends the new User Message to the end of this array, and sends it to the API.
Images	`images`	`string[]`	Provide one or more images to OpenAI's vision model. Accepts URLs or base64 encoded strings. Compatible with the `gpt4-vision-preview` model
Audio	`audio`	`string`	Provide the file path to an audio file in the `/tmp` directory. For use with the `gpt-4o-audio-preview` model. Currently supports `wav` and `mp3` files.
Response Format	`responseFormat`	`string`	Select a value from the drop down menu:`{ "label": "Text", "value": "text" }{ "label": "JSON Object", "value": "json_object" }{ "label": "JSON Schema", "value": "json_schema" }`
Tool Types	`toolTypes`	`string[]`	Select a value from the drop down menu:`function`

Chat with OpenAI (ChatGPT) API on Watch Folder from pCloud API

Pipedream makes it easy to connect APIs for OpenAI (ChatGPT), pCloud and 2,400+ other apps remarkably fast.

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

Developers ♥ Pipedream

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