← Phantombuster + OpenAI (ChatGPT) integrations

Chat with OpenAI (ChatGPT) API on New Output Created Event from Phantombuster API

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New Output Created Event from the Phantombuster API
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Chat with the OpenAI (ChatGPT) API
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Getting Started

This integration creates a workflow with a Phantombuster 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 Output Created Event trigger
    1. Connect your Phantombuster account
    2. Configure timer
    3. Select a Agent ID
  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:Emit new events when new outputs are created. [See the docs here](https://hub.phantombuster.com/reference/get_agents-fetch-output-1)
Version:0.0.1
Key:phantombuster-new-output

Phantombuster Overview

Phantombuster is a powerful API that enables users to build efficient web
automation solutions. It provides a pool of services and tools to help users
quickly, easily and securely interact with multiple websites at once.

With Phantombuster, users can create custom automated solutions to perform
various tasks such as data extraction, lead generation, marketing automation,
and web scraping. Here are a few of the things users can build using
Phantombuster:

  • Data extraction - Phantombuster's API allows users to quickly and securely
    extract data from multiple sites and APIs, allowing users to access large
    amounts of data at once and extract only what they need.
  • Lead generation - Phantombuster's API connects to multiple social networks
    and websites, allowing users to quickly and accurately gather leads or
    potential contacts and store them into a database.
  • Automated marketing campaigns - Phantombuster's API enables users to create
    and launch automated marketing campaigns, automating the entire process and
    saving time and money.
  • Web scraping - Phantombuster's API allows users to scrape entire webpages or
    just parts of it, enabling streamlined data years.
  • Robot monitoring - Phantombuster's API enables users to monitor robots,
    allowing them to keep an eye on their tasks and ensuring their bots are
    running as efficiently as possible.
  • Data analytics - Phantombuster's API allows users to easily analyze and
    visualize their gathered data, allowing them to quickly make decisions based
    on their collected data.

Trigger Code

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

export default {
  key: "phantombuster-new-output",
  name: "New Output Created Event",
  description: "Emit new events when new outputs are created. [See the docs here](https://hub.phantombuster.com/reference/get_agents-fetch-output-1)",
  version: "0.0.1",
  type: "source",
  props: {
    app,
    timer: {
      type: "$.interface.timer",
      default: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
    db: "$.service.db",
    agentId: {
      propDefinition: [
        app,
        "agentId",
      ],
    },
  },
  methods: {
    setLastUpdated(lastUpdated) {
      this.db.set("lastUpdated", lastUpdated);
    },
    getLastUpdated() {
      return this.db.get("lastUpdated") || 0;
    },
    setLastContainerId(lastContainerId) {
      this.db.set("lastContainerId", lastContainerId);
    },
    getLastContainerId() {
      return this.db.get("lastContainerId") || 0;
    },
  },
  async run() {
    const resp = await this.app.getOutput({ //always there is one last output for an agent
      params: {
        id: this.agentId,
      },
    });
    if (this.getLastContainerId() != resp.containerId ||
      (resp.mostRecentEndedAt && this.getLastUpdated() < resp.mostRecentEndedAt)) {
      this.$emit(
        resp,
        {
          id: resp.mostRecentEndedAt || Date.now(),
          summary: resp.output,
          ts: resp.mostRecentEndedAt || Date.now(),
        },
      );
      this.setLastUpdated(resp.mostRecentEndedAt);
      this.setLastContainerId(resp.containerId);
    }
  },
};

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
PhantombusterappappThis component uses the Phantombuster app.
timer$.interface.timer
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
Agent IDagentIdstringSelect a value from the drop down menu.

Trigger Authentication

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

Your API key resides in your Phantombuster Org settings page. This page is also accessible through your navbar's menu, under the label "Org settings". Please notice that for security reasons, you key will only be shown once, on creation. You better copy it in a safe place before refreshing or leaving the page.

For more info, refer to Phantombuster's API documentation.

About Phantombuster

Code-free automations and data extraction. Chain actions and data extraction on the web to generate business leads, marketing audiences and overall growth. Phantombuster gives you the tools and know-how to grow your business faster.

Action

Description:The Chat API, using the `gpt-3.5-turbo` or `gpt-4` model. [See docs here](https://platform.openai.com/docs/api-reference/chat)
Version:0.1.9
Key:openai-chat

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

export default {
  ...common,
  name: "Chat",
  version: "0.1.9",
  key: "openai-chat",
  description: "The Chat API, using the `gpt-3.5-turbo` or `gpt-4` model. [See docs here](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: [
        "text",
        "json_object",
      ],
      optional: true,
      default: "text",
    },
    ...common.props,
  },
  async run({ $ }) {
    const args = this._getChatArgs();

    const response = await this.openai.createChatCompletion({
      $,
      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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