Chat with Azure OpenAI Service API on New Message In Channels (Instant) from Slack API

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New Message In Channels (Instant) from the Slack API

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Getting Started#

This integration creates a workflow with a Slack trigger and Azure OpenAI Service action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New Message In Channels (Instant) trigger
1. Connect your Slack account
2. Optional- Select one or more Channels
3. Configure slackApphook
4. Optional- Configure Resolve Names
5. Optional- Configure Ignore Bots
6. Optional- Configure Ignore replies in threads
Configure the Chat action
1. Connect your Azure OpenAI Service account
2. Configure User Message
3. Optional- Configure System Instructions
4. Optional- Configure Prior Message History
5. Optional- Configure Temperature
6. Optional- Configure N
7. Optional- Configure Stream
8. Optional- Configure Stop
9. Optional- Configure Max Tokens
10. Optional- Configure Presence Penalty
11. Optional- Configure Frequency Penalty
12. 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 Message In Channels (Instant) on Slack

Description:Emit new event when a new message is posted to one or more channels

Version:1.0.15

Key:slack-new-message-in-channels

View on GitHub

Slack Overview#

The Pipedream Slack app enables you to build event-driven workflows that interact with the Slack API. When you authorize the Pipedream app's access to your workspace, you can use Pipedream workflows to perform common Slack actions, or write your own code against the Slack API.

The Pipedream Slack app is not a typical app. You don't interact with it directly as a bot, and it doesn't add custom functionality to your workspace out of the box. It makes it easier to automate anything you'd typically use the Slack API for, using Pipedream workflows.

Automate posting updates to your team channels
Create a bot to answer common questions
Integrate with your existing tools and services
And much more!

Trigger Code#

import common from "../common/base.mjs";
import constants from "../common/constants.mjs";
import sampleEmit from "./test-event.mjs";

export default {
  ...common,
  key: "slack-new-message-in-channels",
  name: "New Message In Channels (Instant)",
  version: "1.0.15",
  description: "Emit new event when a new message is posted to one or more channels",
  type: "source",
  dedupe: "unique",
  props: {
    ...common.props,
    conversations: {
      propDefinition: [
        common.props.slack,
        "conversation",
      ],
      type: "string[]",
      label: "Channels",
      description: "Select one or more channels to monitor for new messages.",
      optional: true,
    },
    // eslint-disable-next-line pipedream/props-description,pipedream/props-label
    slackApphook: {
      type: "$.interface.apphook",
      appProp: "slack",
      async eventNames() {
        return this.conversations || [
          "message",
        ];
      },
    },
    resolveNames: {
      propDefinition: [
        common.props.slack,
        "resolveNames",
      ],
    },
    ignoreBot: {
      propDefinition: [
        common.props.slack,
        "ignoreBot",
      ],
    },
    ignoreThreads: {
      type: "boolean",
      label: "Ignore replies in threads",
      description: "Ignore replies to messages in threads",
      optional: true,
    },
  },
  methods: {
    ...common.methods,
    getSummary() {
      return "New message in channel";
    },
    async processEvent(event) {
      if (event.type !== "message") {
        console.log(`Ignoring event with unexpected type "${event.type}"`);
        return;
      }
      if (event.subtype && !constants.ALLOWED_MESSAGE_IN_CHANNEL_SUBTYPES.includes(event.subtype)) {
        // This source is designed to just emit an event for each new message received.
        // Due to inconsistencies with the shape of message_changed and message_deleted
        // events, we are ignoring them for now. If you want to handle these types of
        // events, feel free to change this code!!
        console.log("Ignoring message with subtype.");
        return;
      }
      if ((this.ignoreBot) && (event.subtype == "bot_message" || event.bot_id)) {
        return;
      }
      console.log(event.s);
      // There is no thread message type only the thread_ts field
      // indicates if the message is part of a thread in the event.
      if (this.ignoreThreads && event.thread_ts) {
        console.log("Ignoring reply in thread");
        return;
      }
      if (this.resolveNames) {
        if (event.user) {
          event.user_id = event.user;
          event.user = await this.getUserName(event.user);
        } else if (event.bot_id) {
          event.bot = await this.getBotName(event.bot_id);
        }
        event.channel_id = event.channel;
        event.channel = await this.getConversationName(event.channel);
        if (event.team) {
          event.team_id = event.team;
          event.team = await this.getTeamName(event.team);
        }
      }
      return event;
    },
  },
  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
Slack	`slack`	`app`	This component uses the Slack app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Channels	`conversations`	`string[]`	Select a value from the drop down menu.
	`slackApphook`	`$.interface.apphook`
Resolve Names	`resolveNames`	`boolean`	Instead of returning `channel`, `team`, and `user` as IDs, return their human-readable names.
Ignore Bots	`ignoreBot`	`boolean`	Ignore messages from bots
Ignore replies in threads	`ignoreThreads`	`boolean`	Ignore replies to messages in threads

Trigger Authentication#

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

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

bookmarks:writecalls:readcalls:writechannels:historychannels:readchannels:writednd:readdnd:writeemoji:readfiles:readgroups:historygroups:readgroups:writeim:historyim:readim:writelinks:readlinks:writempim:historympim:readmpim:writepins:readpins:writereactions:readreactions:writereminders:readreminders:writeremote_files:readremote_files:sharestars:readstars:writeteam:readusergroups:readusergroups:writeusers:readusers:read.emailusers:writechat:write:botchat:write:usercommandsfiles:write:userusers.profile:writeusers.profile:readsearch:read

About Slack#

Slack is a channel-based messaging platform. With Slack, people can work together more effectively, connect all their software tools and services, and find the information they need to do their best work — all within a secure, enterprise-grade environment.

Action#

Chat on Azure OpenAI Service

Description:Create completions for chat messages with the GPT-35-Turbo and GPT-4 models. [See the documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#chat-completions)

Version:0.0.1

Key:azure_openai_service-chat

View on GitHub

Azure OpenAI Service Overview#

The Azure OpenAI Service API provides access to powerful AI models that can understand and generate human-like text. With Pipedream, you can harness this capability to create a variety of serverless workflows, automating tasks like content creation, code generation, and language translation. By integrating the API with other apps on Pipedream, you can streamline processes, analyze sentiment, and even automate customer support.

Action Code#

import azureOpenAI from "../../azure_openai_service.app.mjs";
import common from "../common/common.mjs";

export default {
  ...common,
  key: "azure_openai_service-chat",
  name: "Chat",
  description: "Create completions for chat messages with the GPT-35-Turbo and GPT-4 models. [See the documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#chat-completions)",
  version: "0.0.1",
  type: "action",
  props: {
    azureOpenAI,
    userMessage: {
      type: "string",
      label: "User Message",
      description: "The user messages to provide instructions to the assistant.",
    },
    systemInstructions: {
      label: "System Instructions",
      type: "string",
      description: "The system message helps set the behavior of the assistant. For example: \"You are a helpful assistant.\"",
      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,
    },
    ...common.props,
  },
  async run({ $ }) {
    const data = this._getChatArgs();
    const response = await this.azureOpenAI.createChatCompletion({
      data,
      $,
    });

    if (response) {
      $.export("$summary", `Successfully sent chat with ID ${response.id}.`);
    }

    const { messages } = data;
    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
Azure OpenAI Service	`azureOpenAI`	`app`	This component uses the Azure OpenAI Service app.
User Message	`userMessage`	`string`	The user messages to provide instructions to the assistant.
System Instructions	`systemInstructions`	`string`	The system message helps set the behavior of the assistant. For example: "You are a helpful assistant."
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.
Temperature	`temperature`	`string`	What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.
N	`n`	`integer`	How many completions to generate
Stream	`stream`	`boolean`	If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message.
Stop	`stop`	`string`	Up to 4 sequences where the API will stop generating further tokens.
Max Tokens	`maxTokens`	`integer`	The maximum number of tokens allowed for the generated answer. By default, the number of tokens the model can return will be (4096 - prompt tokens).
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 Azure OpenAI to monitor and detect abuse.

Action Authentication#

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

Before you start, you'll need to deploy a model in the Azure OpenAI Service.

Once that's done, enter the name of your Azure OpenAI resource, the deployment name you chose when you deployed the model, and your Azure OpenAI key below.

About Azure OpenAI Service#

Apply large language models and generative AI to a variety of use cases

More Ways to Connect Azure OpenAI Service + Slack#

Other Popular Integrations#

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Chat with Azure OpenAI Service API on New Message In Channels (Instant) from Slack API

Pipedream makes it easy to connect APIs for Azure OpenAI Service, Slack and 2,000+ other apps remarkably fast.

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

Developers ♥ Pipedream

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