Chat with OpenAI (ChatGPT) API on New Customer Rating from Nicereply API

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New Customer Rating from the Nicereply API

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Getting Started#

This integration creates a workflow with a Nicereply 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 Customer Rating trigger
1. Connect your Nicereply account
2. Configure timer
3. Select a Customer ID
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 Customer Rating on Nicereply

Description:Emit new event on each new customer rating.

Version:0.0.2

Key:nicereply-new-customer-rating

View on GitHub

Nicereply Overview#

With Nicereply API, you can create powerful customer feedback solutions and
measure customer satisfaction scores in different ways.

Whether you're a developer, marketer, customer service agent, or product
manager, the Nicereply API makes it easy to set up and manage your customer
feedback solutions.

Here are some examples of what you can do with Nicereply API:

Automatically send surveys to customers and collect customer feedback.
Display customer satisfaction scores in various ways for different teams.
Track customer support metrics and trends over time.
Generate reports on customer satisfaction and support efficiency.
Integrate with third-party applications to extend your customer feedback
solutions.
Design custom interaction forms and data fields.
Automate customer follow-ups and notifications.
Monitor customer sentiment across multiple channels.

Trigger Code#

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

export default {
  ...common,
  name: "New Customer Rating",
  version: "0.0.2",
  key: "nicereply-new-customer-rating",
  description: "Emit new event on each new customer rating.",
  type: "source",
  dedupe: "unique",
  props: {
    ...common.props,
    customerId: {
      propDefinition: [
        common.props.nicereply,
        "customerId",
      ],
    },
  },
  methods: {
    ...common.methods,
    emitEvent(data) {
      this.$emit(data, {
        id: data.id,
        summary: `New customer rating with id ${data.id}`,
        ts: Date.parse(data.created_at),
      });
    },
    getRatings() {
      return this.nicereply.getCustomerRatings;
    },
    getRequestExtraArgs() {
      return {
        customerId: this.customerId,
      };
    },
  },
};

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
Nicereply	`nicereply`	`app`	This component uses the Nicereply app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`
Customer ID	`customerId`	`string`	Select a value from the drop down menu.

Trigger Authentication#

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

To get your private API key go to your Nicereply account > Settings > API > and copy the private key.

About Nicereply#

Nicereply helps our customers tell us whether they’re getting what they need. This creates opportunities to respond to specific feedback in the short-term while developing longer-term solutions in our approach.

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 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.

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 Customer Rating from Nicereply API

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

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

Developers ♥ Pipedream

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