Create Completion (Send Prompt) with OpenAI (ChatGPT) API on New Email from IMAP API

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New Email from the IMAP API

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Create Completion (Send Prompt) with the OpenAI (ChatGPT) API

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Getting Started#

This integration creates a workflow with a IMAP 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 New Email trigger
1. Connect your IMAP account
2. Configure Polling interval
3. Select a Mailbox
Configure the Create Completion (Send Prompt) action
1. Connect your OpenAI (ChatGPT) account
2. Select a Model
3. Configure Prompt
4. Optional- Configure Suffix
5. Optional- Configure Max Tokens
6. Optional- Configure Temperature
7. Optional- Configure Top P
8. Optional- Configure N
9. Optional- Configure Stop
10. Optional- Configure Presence Penalty
11. Optional- Configure Frequency Penalty
12. Optional- Configure User
13. Optional- Configure Best Of
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 Email on IMAP

Description:Emit new event for each new email in a mailbox

Version:0.0.4

Key:imap-new-email

View on GitHub

IMAP Overview#

Using Pipedream's IMAP API, developers can automate interactions with their email inbox, enabling serverless workflows that perform actions based on incoming emails. This could include parsing email contents, triggering events upon receiving emails from specific senders, attaching labels, and much more. By leveraging IMAP, Pipedream can act as a bridge between your email and other services, streamlining processes that would otherwise require manual intervention.

Trigger Code#

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

/**
 * Creates an IMAP server connection and emits emails added to a mailbox after the last emitted
 * email.
 */
export default {
  key: "imap-new-email",
  name: "New Email",
  description: "Emit new event for each new email in a mailbox",
  version: "0.0.4",
  type: "source",
  dedupe: "unique",
  props: {
    imap,
    db: "$.service.db",
    timer: {
      label: "Polling interval",
      description:
        "Pipedream will poll the IMAP server for new emails at this interval",
      type: "$.interface.timer",
      default: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
    mailbox: {
      propDefinition: [
        imap,
        "mailbox",
      ],
    },
  },
  methods: {
    _getLastUid(mailbox) {
      return this.db.get(`lastUid-${mailbox}`);
    },
    _setLastUid(mailbox, lastUid) {
      this.db.set(`lastUid-${mailbox}`, lastUid);
    },
    _getUidValidity(mailbox) {
      return this.db.get(`uidValidity-${mailbox}`);
    },
    _setUidValidity(mailbox, uidValidity) {
      this.db.set(`uidValidity-${mailbox}`, uidValidity);
    },
    _handleUidValidityChange(mailbox, uidValidity) {
      this._setUidValidity(mailbox, uidValidity);
      this._setLastUid(mailbox, null);
    },
    hasNewMessages(box) {
      const lastUid = this._getLastUid(box.name);
      return !lastUid || box.uidnext > lastUid + 1;
    },
    generateMeta(message) {
      const date = message.attributes?.date ?? new Date();
      const ts = Date.parse(date);
      return {
        id: `${message.attributes?.uid}-${ts}`,
        ts,
        summary: message.mail?.subject,
      };
    },
    processMessage(message) {
      const lastUid = message.attributes?.uid ?? lastUid;
      this._setLastUid(this.mailbox, lastUid);
      this.$emit(message.mail, this.generateMeta(message));
    },
    async processMessageStream(stream) {
      for await (const message of stream) {
        this.processMessage(message);
      }
    },
    async getHistoricalEvents() {
      const { mailbox } = this;
      const connection = await this.imap.getConnection();
      try {
        const box = await this.imap.openMailbox(connection, mailbox);
        const startSeqno = box.messages.total > 25
          ? box.messages.total - 24
          : 1;
        const messageStream = this.imap.fetchMessages(connection, {
          startSeqno,
        });
        await this.processMessageStream(messageStream);
      } finally {
        await this.imap.closeConnection(connection);
      }
    },
  },
  hooks: {
    async deploy() {
      await this.getHistoricalEvents();
    },
  },
  async run() {
    const { mailbox } = this;
    const connection = await this.imap.getConnection();

    try {
      const box = await this.imap.openMailbox(connection, mailbox);

      const uidValidity = this._getUidValidity(box.name);
      if (uidValidity !== box.uidvalidity) {
        this._handleUidValidityChange(box.name, box.uidvalidity);
      }

      if (!this.hasNewMessages(box)) {
        console.log("No new messages since last run");
        return;
      }

      const lastUid = this._getLastUid(box.name);

      // Fetch messages after lastUid if it exists, or most recent message otherwise
      const messageStream = this.imap.fetchMessages(connection, {
        startUid: lastUid && lastUid + 1,
        startSeqno: box.messages.total,
      });
      await this.processMessageStream(messageStream);
    } finally {
      await this.imap.closeConnection(connection);
    }
  },
};

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
IMAP	`imap`	`app`	This component uses the IMAP app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Polling interval	`timer`	`$.interface.timer`	Pipedream will poll the IMAP server for new emails at this interval
Mailbox	`mailbox`	`string`	Select a value from the drop down menu.

Trigger Authentication#

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

Below are the required fields to connect your IMAP account to Pipedream:

host: Enter the host Pipedream should connect to. Refer to your email provider's IMAP instructions if you aren't sure what to enter.
email: Enter the email address you use to sign in to the account you'd like to connect.
password: This is the password you use to sign in to your email account. Note: in order to connect a Gmail account, you must use an App Password.
port: Specify the port number, either 143 (default) or 993. Refer to your email provider's IMAP instructions if you aren't sure which to use.

For Gmail accounts, refer to these instructions.

About IMAP#

Connect Pipedream to any IMAP email provider to trigger custom workflows.

Action#

Create Completion (Send Prompt) on OpenAI (ChatGPT)

Description:OpenAI recommends using the **Chat** action for the latest `gpt-3.5-turbo` API, since it's faster and 10x cheaper. This action creates a completion for the provided prompt and parameters using the older `/completions` API. [See docs here](https://beta.openai.com/docs/api-reference/completions/create)

Version:0.1.7

Key:openai-send-prompt

View on GitHub

OpenAI (ChatGPT) Overview#

The OpenAI (ChatGPT) API offers a powerful gateway to natural language processing capabilities, enabling you to automate conversation-based tasks or generate text-based content programmatically. When paired with Pipedream's no-code platform, you can craft potent serverless workflows that trigger AI-generated text in response to various events, parse and analyze incoming data, or even add conversational AI to your apps and services.

Action Code#

import openai from "../../openai.app.mjs";
import common from "../common/common.mjs";

export default {
  ...common,
  name: "Create Completion (Send Prompt)",
  version: "0.1.7",
  key: "openai-send-prompt",
  description: "OpenAI recommends using the **Chat** action for the latest `gpt-3.5-turbo` API, since it's faster and 10x cheaper. This action creates a completion for the provided prompt and parameters using the older `/completions` API. [See docs here](https://beta.openai.com/docs/api-reference/completions/create)",
  type: "action",
  props: {
    openai,
    modelId: {
      propDefinition: [
        openai,
        "completionModelId",
      ],
    },
    prompt: {
      label: "Prompt",
      description: "The prompt to generate completions for",
      type: "string",
    },
    suffix: {
      label: "Suffix",
      description: "The suffix that comes after a completion of inserted text",
      type: "string",
      optional: true,
    },
    ...common.props,
    bestOf: {
      label: "Best Of",
      description: "Generates best_of completions server-side and returns the \"best\" (the one with the highest log probability per token). If set, results cannot be streamed.",
      type: "integer",
      optional: true,
    },
  },
  async run({ $ }) {
    const response = await this.openai.createCompletion({
      $,
      args: this._getCommonArgs(),
    });

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

    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.

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.
Prompt	`prompt`	`string`	The prompt to generate completions for
Suffix	`suffix`	`string`	The suffix that comes after a completion of inserted text
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.
Best Of	`bestOf`	`integer`	Generates best_of completions server-side and returns the "best" (the one with the highest log probability per token). If set, results cannot be streamed.