← Pipedream + OpenAI (ChatGPT) integrations

Chat with OpenAI (ChatGPT) API on New Scheduled Tasks from Pipedream API

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New Scheduled Tasks from the Pipedream API
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Chat with the OpenAI (ChatGPT) API
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Developers Pipedream

Getting Started

This integration creates a workflow with a Pipedream 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 Scheduled Tasks trigger
    1. Connect your Pipedream account
    2. Optional- Configure Secret
  3. Configure the Chat action
    1. Connect your OpenAI (ChatGPT) account
    2. Select a Model
    3. Configure User Message
    4. Optional- Configure System Instructions
    5. Optional- Configure Prior Message History
    6. Optional- Configure Images
    7. Optional- Select a Response Format
    8. Optional- Configure Max Tokens
    9. Optional- Configure Temperature
    10. Optional- Configure Top P
    11. Optional- Configure N
    12. Optional- Configure Stop
    13. Optional- Configure Presence Penalty
    14. Optional- Configure Frequency Penalty
    15. Optional- Configure User
  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:Exposes an HTTP API for scheduling messages to be emitted at a future time
Version:0.3.1
Key:pipedream-new-scheduled-tasks

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.
LabelPropTypeDescription
PipedreampipedreamappThis component uses the Pipedream app.
Secretsecretstring

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/Ahttp$.interface.httpThis component uses $.interface.http to generate a unique URL when the component is first instantiated. Each request to the URL will trigger the run() method of the component.
N/Adb$.service.dbThis 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

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:0.1.10
Key:openai-chat

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",
  version: "0.1.10",
  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.",
    },
    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,
    },
    responseFormat: {
      type: "string",
      label: "Response Format",
      description: "Specify the format that the model must output. [Setting to `json_object` guarantees the message the model generates is valid JSON](https://platform.openai.com/docs/api-reference/chat/create#chat-create-response_format). Defaults to `text`",
      options: constants.CHAT_RESPONSE_FORMATS,
      optional: true,
      default: "text",
    },
    ...common.props,
  },
  async run({ $ }) {
    const args = this._getChatArgs();

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

    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.

LabelPropTypeDescription
OpenAI (ChatGPT)openaiappThis component uses the OpenAI (ChatGPT) app.
ModelmodelIdstringSelect a value from the drop down menu.
User MessageuserMessagestring

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.

System InstructionssystemInstructionsstring

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 Historymessagesstring[]

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.

Imagesimagesstring[]

Provide one or more images to OpenAI's vision model. Accepts URLs or base64 encoded strings. Compatible with the gpt4-vision-preview model

Response FormatresponseFormatstringSelect a value from the drop down menu:textjson_object
Max TokensmaxTokensinteger

The maximum number of tokens to generate in the completion.

Temperaturetemperaturestring

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 PtopPstring

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.

Nninteger

How many completions to generate for each prompt

Stopstopstring[]

Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.

Presence PenaltypresencePenaltystring

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 PenaltyfrequencyPenaltystring

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.

Useruserstring

A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more here.

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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