Chat with OpenAI (ChatGPT) API on New Custom Event from Strava API

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New Custom Event from the Strava API

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Chat with the OpenAI (ChatGPT) API

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Getting Started#

This integration creates a workflow with a Strava 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 Custom Event trigger
1. Connect your Strava account
2. Select one or more Strava Events
3. Configure stravaApphook
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 Custom Event on Strava

Description:Emit new event when an activity is created, updated, or deleted

Version:0.0.3

Key:strava-custom-events

View on GitHub

Strava Overview#

The Strava API lets you tap into the robust data from Strava's fitness app, which is a playground for athletes worldwide to track their workouts. With Pipedream, you can automate actions based on activities uploaded to Strava, such as running, biking, or swimming. Imagine syncing workout data to spreadsheets for analysis, auto-posting achievements to social media, or integrating with calendar apps for better scheduling. Pipedream's serverless platform makes it a breeze to create workflows that can listen for Strava webhooks, process data, and trigger actions in countless other apps.

Trigger Code#

import strava from "../../strava.app.mjs";

export default {
  key: "strava-custom-events",
  name: "New Custom Event",
  description: "Emit new event when an activity is created, updated, or deleted",
  version: "0.0.3",
  type: "source",
  props: {
    strava,
    eventNameOptions: {
      label: "Strava Events",
      description: "Select from events",
      type: "string[]",
      async options() {
        return [
          "activity.create",
          "activity.update",
          "activity.delete",
        ];
      },
    },
    stravaApphook: {
      type: "$.interface.apphook",
      appProp: "strava",
      async eventNames() {
        return this.eventNameOptions;
      },
    },
  },
  async run(event) {
    console.log(event);
    const ts = event.event_time * 1000;
    if (event.object_type === "activity") {
      let details;
      // Optimistically fetch activity details. When an event is deleted, this will fail
      try {
        details = await this.strava.getActivity({
          activityId: event.object_id,
        });
      } catch (err) {
        console.log(`Error fetching activity details: ${err}`);
      }
      this.$emit(
        {
          event,
          details,
        },
        {
          summary: `Activity ${event.aspect_type}d`,
          ts,
        },
      );
    }
  },
};

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
Strava	`strava`	`app`	This component uses the Strava app.
Strava Events	`eventNameOptions`	`string[]`	Select a value from the drop down menu.
	`stravaApphook`	`$.interface.apphook`

Trigger Authentication#

Strava uses OAuth authentication. When you connect your Strava account, Pipedream will open a popup window where you can sign into Strava and grant Pipedream permission to connect to your account. Pipedream securely stores and automatically refreshes the OAuth tokens so you can easily authenticate any Strava API.

Pipedream requests the following authorization scopes when you connect your account:

readactivity:writeactivity:readactivity:read_all

About Strava#

Designed by athletes, for athletes, Strava's mobile app and website connect millions of runners and cyclists through the sports they love.

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#

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: "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.

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.

More Ways to Connect OpenAI (ChatGPT) + Strava#

Other Popular Integrations#

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

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

Developers ♥ Pipedream

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