← Google Cloud + OpenAI (ChatGPT) integrations

Chat with OpenAI (ChatGPT) API on New Pub/Sub Messages from Google Cloud API

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New Pub/Sub Messages from the Google Cloud API
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Getting Started

This integration creates a workflow with a Google Cloud 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 Pub/Sub Messages trigger
    1. Connect your Google Cloud account
    2. Select a Type
  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 Pub/Sub topic in your GCP account. Messages published to this topic are emitted from the Pipedream source.
Version:0.1.6
Key:google_cloud-new-pubsub-messages

Google Cloud Overview

The Google Cloud API opens a world of possibilities for enhancing cloud operations and automating tasks. It empowers you to manage, scale, and fine-tune various services within the Google Cloud Platform (GCP) programmatically. With Pipedream, you can harness this power to create intricate workflows, trigger cloud functions based on events from other apps, manage resources, and analyze data, all in a serverless environment. The ability to interconnect GCP services with numerous other apps enriches automation, making it easier to synchronize data, streamline development workflows, and deploy applications efficiently.

Trigger Code

import { PubSub } from "@google-cloud/pubsub";
import googleCloud from "../../google_cloud.app.mjs";

export default {
  key: "google_cloud-new-pubsub-messages",
  name: "New Pub/Sub Messages",
  description: "Emit new Pub/Sub topic in your GCP account. Messages published to this topic are emitted from the Pipedream source.",
  version: "0.1.6",
  type: "source",
  dedupe: "unique", // Dedupe on Pub/Sub message ID
  props: {
    googleCloud,
    http: "$.interface.http",
    db: "$.service.db",
    topicType: {
      type: "string",
      label: "Type",
      description: "Do you have an existing Pub/Sub topic, or would you like to create a new one?",
      options: [
        "existing",
        "new",
      ],
      reloadProps: true,
    },
  },
  async additionalProps() {
    const topic = {
      type: "string",
      label: "Pub/Sub Topic Name",
      description: "Select a Pub/Sub topic from your GCP account to watch",
      options: async () => {
        return this.getTopics();
      },
    };
    if (this.topicType === "new") {
      topic.description = "**Pipedream will create a Pub/Sub topic with this name in your account**, converting it to a [valid Pub/Sub topic name](https://cloud.google.com/pubsub/docs/admin#resource_names).";
      delete topic.options;
    }
    return {
      topic,
    };
  },
  methods: {
    _getTopicName() {
      return this.db.get("topicName");
    },
    _setTopicName(topicName) {
      this.db.set("topicName", topicName);
    },
    _getSubscriptionName() {
      return this.db.get("subscriptionName");
    },
    _setSubscriptionName(subscriptionName) {
      this.db.set("subscriptionName", subscriptionName);
    },
    async getTopics() {
      const sdkParams = this.googleCloud.sdkParams();
      const pubSubClient = new PubSub(sdkParams);
      const topics = (await pubSubClient.getTopics())[0];
      if (topics.length > 0) {
        return topics.map((topic) => topic.name);
      }
      return [];
    },
    convertNameToValidPubSubTopicName(name) {
      // For valid names, see https://cloud.google.com/pubsub/docs/admin#resource_names
      return name
        // Must not start with `goog`. We add a `pd-` at the beginning if that's the case.
        .replace(/(^goog.*)/g, "pd-$1")
        // Must start with a letter, otherwise we add `pd-` at the beginning.
        .replace(/^(?![a-zA-Z]+)/, "pd-")
        // Only certain characters are allowed, the rest will be replaced with a `-`.
        .replace(/[^a-zA-Z0-9_\-.~+%]+/g, "-");
    },
  },
  hooks: {
    async activate() {
      const sdkParams = this.googleCloud.sdkParams();
      const pubSubClient = new PubSub(sdkParams);

      const currentTopic = {
        name: this.topic,
      };
      if (this.topicType === "new") {
        const topicName = this.convertNameToValidPubSubTopicName(this.topic);
        console.log(`Creating Pub/Sub topic ${topicName}`);
        const [
          topic,
        ] = await pubSubClient.createTopic(topicName);
        currentTopic.name = topic.name;
      }
      this._setTopicName(currentTopic.name);

      const pushEndpoint = this.http.endpoint;
      const subscriptionName = this.convertNameToValidPubSubTopicName(pushEndpoint);
      const subscriptionOptions = {
        pushConfig: {
          pushEndpoint,
        },
      };
      console.log(
        `Subscribing this source's URL to the Pub/Sub topic: ${pushEndpoint}
        (under name ${subscriptionName}).`,
      );
      const [
        subscriptionResult,
      ] = await pubSubClient
        .topic(currentTopic.name)
        .createSubscription(subscriptionName, subscriptionOptions);
      this._setSubscriptionName(subscriptionResult.name);
    },
    async deactivate() {
      const sdkParams = this.googleCloud.sdkParams();
      const pubSubClient = new PubSub(sdkParams);

      const subscriptionName = this._getSubscriptionName();
      if (subscriptionName) {
        await pubSubClient.subscription(subscriptionName).delete();
      }

      if (this.topicType === "new") {
        const topicName = this._getTopicName();
        if (topicName) {
          await pubSubClient.topic(topicName).delete();
        }
      }
    },
  },
  async run(event) {
    const {
      data,
      messageId,
      publishTime,
    } = event.body.message;

    if (!data) {
      console.warn("No message present, exiting");
      return;
    }
    const dataString = Buffer.from(data, "base64").toString("utf-8");
    const metadata = {
      id: messageId,
      summary: dataString,
      ts: +new Date(publishTime),
    };

    let dataObj;
    try {
      dataObj = JSON.parse(dataString);
    } catch (err) {
      console.error(
        `Couldn't parse message as JSON. Emitting raw message. Error: ${err}`,
      );
      dataObj = {
        rawMessage: dataString,
      };
    }
    this.$emit(dataObj, metadata);
  },
};

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
Google CloudgoogleCloudappThis component uses the Google Cloud app.
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.
TypetopicTypestringSelect a value from the drop down menu:existingnew

Trigger Authentication

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

  1. Create a service account in GCP and set the permissions you need for Pipedream workflows.

  2. Generate a service account key

  3. Download the key details in JSON format

  4. Open the JSON in a text editor, and copy and paste its contents here.

About Google Cloud

The Google Cloud Platform, including BigQuery

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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