Chat with OpenAI (ChatGPT) API on New Repository Created from Beanstalk API

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New Repository Created from the Beanstalk API

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Getting Started#

This integration creates a workflow with a Beanstalk 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 Repository Created trigger
1. Connect your Beanstalk account
2. Configure Polling schedule
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
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 Repository Created on Beanstalk

Description:Emit new event when a new repository is created. [See the docs](https://api.beanstalkapp.com/repository.html).

Version:0.0.1

Key:beanstalkapp-new-repository-created

View on GitHub

Beanstalk Overview#

The Beanstalk API allows for streamlined version control and release management within your development workflow. By leveraging the API with Pipedream, you can automate interactions with your repositories, changesets, and deployment environments. You can create workflows that react to code commits, manage deploy environments, and integrate with other services for a more cohesive development lifecycle.

Trigger Code#

import common from "../common/polling.mjs";
import constants from "../../common/constants.mjs";

export default {
  ...common,
  key: "beanstalkapp-new-repository-created",
  name: "New Repository Created",
  description: "Emit new event when a new repository is created. [See the docs](https://api.beanstalkapp.com/repository.html).",
  type: "source",
  version: "0.0.1",
  dedupe: "unique",
  methods: {
    ...common.methods,
    getResourceName() {
      return "repository";
    },
    getResourceFn() {
      return this.app.listRepositories;
    },
    getResourceFnArgs() {
      return {
        params: {
          per_page: constants.DEFAULT_LIMIT,
        },
      };
    },
    generateMeta(resource) {
      return {
        id: resource.id,
        summary: `New Repository ${resource.name}`,
        ts: Date.parse(resource.created_at),
      };
    },
  },
};

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
Beanstalk	`app`	`app`	This component uses the Beanstalk app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Polling schedule	`timer`	`$.interface.timer`	How often to poll the API

Trigger Authentication#

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

To connect your Beanstalk account with Pipedream,

Retrieve your Access Token by going to Account > Developer API
Retrieve your username by going to your profile with your full name on the top right
Your domain is 12345678 if your Beanstalk URL is https://12345678.beanstalkapp.com/

About Beanstalk#

Beanstalk helps families work together to build a pot of money to give the children they love a better future. Designed to help every family, Beanstalk makes saving and investing easy no matter your family's shape or budget.

Action#

Chat on OpenAI (ChatGPT)

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

View on GitHub

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";

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.

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.
User Message	`userMessage`	`string`	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 Instructions	`systemInstructions`	`string`	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 History	`messages`	`string[]`	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.
Images	`images`	`string[]`	Provide one or more images to OpenAI's vision model. Accepts URLs or base64 encoded strings. Compatible with the `gpt4-vision-preview model`
Response Format	`responseFormat`	`string`	Select a value from the drop down menu:`textjson_object`
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.

Chat with OpenAI (ChatGPT) API on New Repository Created from Beanstalk API

Pipedream makes it easy to connect APIs for OpenAI (ChatGPT), Beanstalk and 2,000+ other apps remarkably fast.

Trusted by 800,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

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