Chat with OpenAI (ChatGPT) API on New Submission (Instant) from Jotform API

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New Submission (Instant) from the Jotform API

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Chat with the OpenAI (ChatGPT) API

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Getting Started#

This integration creates a workflow with a Jotform 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 Submission (Instant) trigger
1. Connect your Jotform account
2. Optional- Select a Team
3. Select a Form
Configure the Chat action
1. Connect your OpenAI (ChatGPT) account
2. Configure alert
3. Select a Model
4. Configure User Message
5. Optional- Configure Max Tokens
6. Optional- Configure Temperature
7. Optional- Configure Top P
8. Optional- Configure N
9. Optional- Configure Stop
10. Optional- Configure Presence Penalty
11. Optional- Configure Frequency Penalty
12. Optional- Configure User
13. Optional- Configure System Instructions
14. Optional- Configure Prior Message History
15. Optional- Configure Images
16. Optional- Configure Audio
17. Optional- Select a Response Format
18. Optional- Select one or more Tool Types
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 Submission (Instant) on Jotform

Description:Emit new event when a form is submitted

Version:0.1.6

Key:jotform-new-submission

View on GitHub

Jotform Overview#

Jotform’s API is a powerhouse for automating form and survey data management. With Pipedream, harness this API to trigger workflows from new form submissions, manipulate and analyze your form data, and sync it across various platforms. Think streamlined data entry to CRMs, instant notifications for new leads or feedback, and timely data backups to cloud storage.

Trigger Code#

import jotform from "../../jotform.app.mjs";
import sampleEmit from "./test-event.mjs";

export default {
  key: "jotform-new-submission",
  name: "New Submission (Instant)",
  description: "Emit new event when a form is submitted",
  version: "0.1.6",
  type: "source",
  dedupe: "unique",
  props: {
    jotform,
    http: "$.interface.http",
    teamId: {
      propDefinition: [
        jotform,
        "teamId",
      ],
    },
    formId: {
      propDefinition: [
        jotform,
        "formId",
        (c) => ({
          teamId: c.teamId,
          excludeDeleted: true,
        }),
      ],
    },
  },
  hooks: {
    async deploy() {
      const { content: form } = await this.jotform.getForm(this.formId, this.teamId);
      const { content: submissions } = await this.jotform.getFormSubmissions({
        formId: this.formId,
        teamId: this.teamId,
        params: {
          limit: 25,
          orderby: "created_at",
        },
      });
      for (let submission of submissions.reverse()) {
        const meta = {
          id: submission.id,
          summary: form.title,
          ts: Date.now(),
        };
        this.$emit(submission, meta);
      }
    },
    async activate() {
      return (await this.jotform.createHook({
        endpoint: this.http.endpoint,
        formId: this.formId,
        teamId: this.teamId,
      }));
    },
    async deactivate() {
      return (await this.jotform.deleteHook({
        endpoint: this.http.endpoint,
        formId: this.formId,
        teamId: this.teamId,
      }));
    },
  },
  async run(event) {
    const { body } = event;
    let { content: submission } = await this.jotform.getFormSubmission({
      submissionId: body.submissionID,
      teamId: this.teamId,
    });

    // insert answers from the webhook event
    const rawRequest = JSON.parse(body.rawRequest);
    for (const key of Object.keys(rawRequest)) {
      const regex = /^q(\d+)_/;
      const match = key.match(regex);
      if (match && match[1]) {
        submission.answers[match[1]].answer = rawRequest[key];
      }
    }

    this.$emit(submission, {
      summary: body.formTitle || JSON.stringify(body),
      id: body.submissionID,
      ts: Date.now(),
    });
  },
  sampleEmit,
};

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
Jotform	`jotform`	`app`	This component uses the Jotform app.
N/A	`http`	`$.interface.http`	This component uses `$.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.
Team	`teamId`	`string`	Select a value from the drop down menu.
Form	`formId`	`string`	Select a value from the drop down menu.

Trigger Authentication#

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

About Jotform#

Jotform enables you to create online forms, collect responses directly in your email, and create fillable PDF forms.

Action#

Chat on OpenAI (ChatGPT)

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:0.2.8

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

export default {
  ...common,
  name: "Chat",
  version: "0.2.8",
  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,
    alert: {
      type: "alert",
      alertType: "info",
      content: "Looking to chat with your tools? Check out our individual actions: [Chat using Web Search](https://pipedream.com/apps/openai/actions/chat-using-web-search), [Chat using File Search](https://pipedream.com/apps/openai/actions/chat-using-file-search), and [Chat using Functions](https://pipedream.com/apps/openai/actions/chat-using-functions).",
    },
    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.",
    },
    ...common.props,
    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,
    },
    audio: {
      type: "string",
      label: "Audio",
      description: "Provide the file path to an audio file in the `/tmp` directory. For use with the `gpt-4o-audio-preview` model. Currently supports `wav` and `mp3` files.",
      optional: true,
    },
    responseFormat: {
      type: "string",
      label: "Response Format",
      description: "- **Text**: Returns unstructured text output.\n- **JSON Schema**: Enables you to define a [specific structure for the model's output using a JSON schema](https://platform.openai.com/docs/guides/structured-outputs?api-mode=responses).",
      options: Object.values(constants.CHAT_RESPONSE_FORMAT),
      default: constants.CHAT_RESPONSE_FORMAT.TEXT.value,
      optional: true,
      reloadProps: true,
    },
    toolTypes: {
      type: "string[]",
      label: "Tool Types",
      description: "The types of tools to enable on the assistant",
      options: constants.TOOL_TYPES.filter((toolType) => toolType === "function"),
      optional: true,
      reloadProps: true,
    },
  },
  additionalProps() {
    const {
      responseFormat,
      toolTypes,
      numberOfFunctions,
    } = this;
    const props = {};

    if (responseFormat === constants.CHAT_RESPONSE_FORMAT.JSON_SCHEMA.value) {
      props.jsonSchema = {
        type: "string",
        label: "JSON Schema",
        description: "Define the schema that the model's output must adhere to. [See the documentation here](https://platform.openai.com/docs/guides/structured-outputs/supported-schemas).",
      };
    }

    if (toolTypes?.includes("function")) {
      props.numberOfFunctions = {
        type: "integer",
        label: "Number of Functions",
        description: "The number of functions to define",
        optional: true,
        reloadProps: true,
        default: 1,
      };

      for (let i = 0; i < (numberOfFunctions || 1); i++) {
        props[`functionName_${i}`] = {
          type: "string",
          label: `Function Name ${i + 1}`,
          description: "The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.",
        };
        props[`functionDescription_${i}`] = {
          type: "string",
          label: `Function Description ${i + 1}`,
          description: "A description of what the function does, used by the model to choose when and how to call the function.",
          optional: true,
        };
        props[`functionParameters_${i}`] = {
          type: "object",
          label: `Function Parameters ${i + 1}`,
          description: "The parameters the functions accepts, described as a JSON Schema object. See the [guide](https://platform.openai.com/docs/guides/text-generation/function-calling) for examples, and the [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for documentation about the format.",
          optional: true,
        };
      }
    }

    return props;
  },
  methods: {
    ...common.methods,
    _buildTools() {
      const tools = this.toolTypes?.filter((toolType) => toolType !== "function")?.map((toolType) => ({
        type: toolType,
      })) || [];
      if (this.toolTypes?.includes("function")) {
        const numberOfFunctions = this.numberOfFunctions || 1;
        for (let i = 0; i < numberOfFunctions; i++) {
          tools.push({
            type: "function",
            function: {
              name: this[`functionName_${i}`],
              description: this[`functionDescription_${i}`],
              parameters: this[`functionParameters_${i}`],
            },
          });
        }
      }
      return tools.length
        ? tools
        : undefined;
    },
  },
  async run({ $ }) {
    if (this.audio && !this.modelId.includes("gpt-4o-audio-preview")) {
      throw new ConfigurationError("Use of audio files requires using the `gpt-4o-audio-preview` model.");
    }

    const args = this._getChatArgs();

    const response = await this.openai.createChatCompletion({
      $,
      data: {
        ...args,
        tools: this._buildTools(),
      },
    });

    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.
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
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
Audio	`audio`	`string`	Provide the file path to an audio file in the `/tmp` directory. For use with the `gpt-4o-audio-preview` model. Currently supports `wav` and `mp3` files.
Response Format	`responseFormat`	`string`	Select a value from the drop down menu:`{ "label": "Text", "value": "text" }{ "label": "JSON Object", "value": "json_object" }{ "label": "JSON Schema", "value": "json_schema" }`
Tool Types	`toolTypes`	`string[]`	Select a value from the drop down menu:`function`

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) + Jotform#

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Pipedream makes it easy to connect APIs for OpenAI (ChatGPT), Jotform and 2,500+ other apps remarkably fast.

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

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