Create Embeddings with OpenAI (ChatGPT) API on New Updated Contact from GoDial API

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Trigger workflow on

New Updated Contact from the GoDial API

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Create Embeddings with the OpenAI (ChatGPT) API

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Getting Started#

This integration creates a workflow with a GoDial 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 Updated Contact trigger
1. Connect your GoDial account
2. Configure timer
3. Select a List ID
Configure the Create Embeddings action
1. Connect your OpenAI (ChatGPT) account
2. Select a Model
3. Configure Input
4. Optional- Configure User
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 Updated Contact on GoDial

Description:Emit new event on a contact is updated.

Version:0.0.3

Key:godial-new-updated-contact

View on GitHub

GoDial Overview#

The GoDial API can be used to build a variety of applications, including:

A dialer application to make phone calls
A VoIP application to make calls over the internet
A call center application to manage customer calls
An IVR system to manage phone calls for businesses

Trigger Code#

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

export default {
  name: "New Updated Contact",
  version: "0.0.3",
  key: "godial-new-updated-contact",
  description: "Emit new event on a contact is updated.",
  type: "source",
  dedupe: "unique",
  props: {
    godial,
    db: "$.service.db",
    timer: {
      type: "$.interface.timer",
      static: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
    listId: {
      propDefinition: [
        godial,
        "listId",
      ],
    },
  },
  methods: {
    emitEvent(data) {
      if (!data.modifiedOn) {
        return;
      }

      this.$emit(data, {
        id: `${data.id} - ${data.modifiedOn}`,
        summary: `New contact updated with ID ${data.id}`,
        ts: Date.parse(data.modifiedOn),
      });
    },
  },
  async run() {
    const contacts = await this.godial.getContacts({
      listId: this.listId,
    });

    contacts.reverse().forEach(this.emitEvent);
  },
};

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
GoDial	`godial`	`app`	This component uses the GoDial app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`
List ID	`listId`	`string`	Select a value from the drop down menu.

Trigger Authentication#

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

To retrieve your API Token,

Navigate to your GoDial account and sign in
Go to “Integration” > “External API” > “Connect”

About GoDial#

GoDial is a mobile app to help increase sales. Simple import your contact lists. Auto dial calls. Save call status. Schedule Callbacks. Add Notes.

Action#

Create Embeddings on OpenAI (ChatGPT)

Description:Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms. [See the docs here](https://platform.openai.com/docs/api-reference/embeddings)

Version:0.0.6

Key:openai-create-embeddings

View on GitHub

OpenAI (ChatGPT) Overview#

The OpenAI API is a powerful tool that provides access to a range of
high-powered machine learning models. With the OpenAI API, developers can
create products, services, and tools that enable humanizing AI experiences, and
build applications that extend the power of human language.

Using the OpenAI API, developers can create language-driven applications such
as:

Natural language understanding and sentiment analysis
Text-based search
Question answering
Dialogue systems and conversation agents
Intelligent text completion
Text summarization
Text classification
Machine translation
Language generation
Multi-factor authentication
Anomaly detection
Text analysis

Action Code#

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

export default {
  name: "Create Embeddings",
  version: "0.0.6",
  key: "openai-create-embeddings",
  description: "Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms. [See the docs here](https://platform.openai.com/docs/api-reference/embeddings)",
  type: "action",
  props: {
    openai,
    modelId: {
      propDefinition: [
        openai,
        "embeddingsModelId",
      ],
    },
    input: {
      label: "Input",
      description: "Input text to get embeddings for, encoded as a string or array of tokens. To get embeddings for multiple inputs in a single request, pass an array of strings or array of token arrays. Each input must not exceed 8192 tokens in length.",
      type: "string[]",
    },
    user: common.props.user,
  },
  async run({ $ }) {
    // Confirm no element is more than 8192 tokens in length
    for (const [
      i,
      element,
    ] of this.input.entries()) {
      if (element.length > 8192) {
        throw new ConfigurationError(`Element #${i} is more than 8192 tokens in length. Each input must not exceed 8192 tokens in length.`);
      }
    }

    const response = await this.openai.createEmbeddings({
      $,
      args: {
        model: this.modelId,
        input: this.input,
      },
    });

    if (response) {
      $.export("$summary", "Successfully created embeddings");
    }

    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.
Input	`input`	`string[]`	Input text to get embeddings for, encoded as a string or array of tokens. To get embeddings for multiple inputs in a single request, pass an array of strings or array of token arrays. Each input must not exceed 8192 tokens in length.
User	`user`	`string`	A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more here.