Create Chat Completion with DeepSeek API on New Interaction Events (Instant) from Slack API

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New Interaction Events (Instant) from the Slack API

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Create Chat Completion with the DeepSeek API

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Getting Started#

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

Select this integration
Configure the New Interaction Events (Instant) trigger
1. Connect your Slack account
2. Configure alert
3. Optional- Configure Action IDs
4. Optional- Select one or more Channels
5. Configure slackApphook
Configure the Create Chat Completion action
1. Connect your DeepSeek account
2. Configure Messages
3. Optional- Configure Frequency Penalty
4. Optional- Configure Max Tokens
5. Optional- Configure Presence Penalty
6. Optional- Select a Response Format Type
7. Optional- Configure Stop Sequences
8. Optional- Configure Stream
9. Optional- Configure Stream Include Usage
10. Optional- Configure Temperature
11. Optional- Configure Top P
12. Optional- Configure Tools
13. Optional- Configure Tool Choice
14. Optional- Configure Log Probs
15. Optional- Configure Top Log Probabilities
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 Interaction Events (Instant) on Slack

Description:Emit new events on new Slack [interactivity events](https://api.slack.com/interactivity) sourced from [Block Kit interactive elements](https://api.slack.com/interactivity/components), [Slash commands](https://api.slack.com/interactivity/slash-commands), or [Shortcuts](https://api.slack.com/interactivity/shortcuts).

Version:0.0.21

Key:slack_v2-new-interaction-event-received

View on GitHub

New Interaction Events (Instant) Overview#

Slack messages can contain interactive elements like buttons, dropdowns, radio buttons, and more. This source subscribes to interactive events, like when a button is clicked in a message.

Example of a Slack button

Then this source will be triggered when you or another Slack user in your workspace clicks a button, selects an option or fills out a form.

Example feed of interaction events coming from Slack

With this trigger, you can build workflows that perform some work with other APIs or services, and then reply back to the original message.

Trigger Code#

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

export default {
  name: "New Interaction Events (Instant)",
  version: "0.0.21",
  key: "slack_v2-new-interaction-event-received",
  description: "Emit new events on new Slack [interactivity events](https://api.slack.com/interactivity) sourced from [Block Kit interactive elements](https://api.slack.com/interactivity/components), [Slash commands](https://api.slack.com/interactivity/slash-commands), or [Shortcuts](https://api.slack.com/interactivity/shortcuts).",
  type: "source",
  props: {
    ...common.props,
    alert: {
      type: "alert",
      alertType: "info",
      content: "Please note that only messages created via Pipedream's [Send Block Kit Message](https://pipedream.com/apps/slack/actions/send-block-kit-message) Action, or via API call from the Pipedream app will emit an interaction event with this trigger. \n\nBlock kit messages sent directly via the Slack's block kit builder will not trigger an interaction event. \n\nSee the [documentation](https://pipedream.com/apps/slack/triggers/new-interaction-event-received) for more details.",
    },
    action_ids: {
      type: "string[]",
      label: "Action IDs",
      description: "Filter interaction events by specific `action_id`'s to subscribe for new interaction events. If none are specified, all `action_ids` created via Pipedream will emit new events.",
      optional: true,
      default: [],
    },
    conversations: {
      propDefinition: [
        common.props.slack,
        "conversation",
      ],
      type: "string[]",
      label: "Channels",
      description: "Filter interaction events by one or more channels. If none selected, any interaction event in any channel will emit new events.",
      optional: true,
      default: [],
    },
    // eslint-disable-next-line pipedream/props-description,pipedream/props-label
    slackApphook: {
      type: "$.interface.apphook",
      appProp: "slack",
      /**
       * Subscribes to potentially 4 different events:
       * `interaction_events` - all interaction events on the authenticated account
       * `interaction_events:${action_id}` - all interaction events with a specific given action_id
       * `interaction_events:${channel_id}` - all interaction events within a specific channel
       * `interaction_events:${channel_id}:${action_id}` - action_id within a specific channel
       * @returns string[]
       */
      async eventNames() {
        // start with action_ids, since they can be the most specific
        const action_events = this.action_ids.reduce((carry, action_id) => {
          // if channels are provided, spread them
          if (this.conversations && this.conversations.length > 0) {
            return [
              ...carry,
              ...this.conversations.map(
                (channel) => `interaction_events:${channel}:${action_id}`,
              ),
            ];
          }

          return [
            ...carry,
            `interaction_events:${action_id}`,
          ];
        }, []);

        if (action_events.length > 0) return action_events;

        // if no action_ids are specified, move down to channels
        const channel_events = this.conversations.map(
          (channel) => `interaction_events:${channel}`,
        );

        if (channel_events.length > 0) return channel_events;

        // if not specific action_ids or channels are specified, subscribe to all events
        return [
          "interaction_events",
        ];
      },
    },
  },
  methods: {},
  async run(event) {
    this.$emit(
      {
        event,
      },
      {
        summary: `New interaction event${
          event?.channel?.id
            ? ` in channel ${event.channel.id}`
            : ""
        }${
          event.actions?.length > 0
            ? ` from action_ids ${event.actions
              .map((action) => action.action_id)
              .join(", ")}`
            : ""
        }`,
        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
Slack	`slack`	`app`	This component uses the Slack app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Action IDs	`action_ids`	`string[]`	Filter interaction events by specific `action_id`'s to subscribe for new interaction events. If none are specified, all `action_ids` created via Pipedream will emit new events.
Channels	`conversations`	`string[]`	Select a value from the drop down menu.
	`slackApphook`	`$.interface.apphook`

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:

chat:writechat:write.customizechat:write.publicfiles:read

About Slack#

Slack is the AI-powered platform for work bringing all of your conversations, apps, and customers together in one place. Around the world, Slack is helping businesses of all sizes grow and send productivity through the roof.

Action#

Create Chat Completion on DeepSeek

Description:Creates a chat completion using the DeepSeek API. [See the documentation](https://api-docs.deepseek.com/api/create-chat-completion)

Version:0.0.2

Key:deepseek-create-chat-completion

View on GitHub

Action Code#

import { RESPONSE_FORMAT_TYPE_OPTIONS } from "../../common/constants.mjs";
import { parseObject } from "../../common/util.mjs";
import deepseek from "../../deepseek.app.mjs";

export default {
  key: "deepseek-create-chat-completion",
  name: "Create Chat Completion",
  description: "Creates a chat completion using the DeepSeek API. [See the documentation](https://api-docs.deepseek.com/api/create-chat-completion)",
  version: "0.0.2",
  annotations: {
    destructiveHint: false,
    openWorldHint: true,
    readOnlyHint: false,
  },
  type: "action",
  props: {
    deepseek,
    messages: {
      type: "string[]",
      label: "Messages",
      description: "The messages for the chat conversation as JSON strings. Each message should be a JSON string like '{\"role\": \"user\", \"content\": \"Hello!\"}'. [See the documentation](https://api-docs.deepseek.com/api/create-chat-completion) for further details.",
    },
    frequencyPenalty: {
      type: "string",
      label: "Frequency Penalty",
      description: "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.",
      optional: true,
    },
    maxTokens: {
      type: "integer",
      label: "Max Tokens",
      description: "Integer between 1 and 8192. The maximum number of tokens that can be generated in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length. If `max_tokens` is not specified, the default value 4096 is used.",
      optional: true,
    },
    presencePenalty: {
      type: "string",
      label: "Presence Penalty",
      description: "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.",
      optional: true,
    },
    responseFormatType: {
      type: "string",
      label: "Response Format Type",
      description: "The format that the model must output. Setting to JSON Object enables JSON Output, which guarantees the message the model generates is valid JSON.",
      options: RESPONSE_FORMAT_TYPE_OPTIONS,
      optional: true,
    },
    stop: {
      type: "string[]",
      label: "Stop Sequences",
      description: "Up to 16 sequences where the API will stop generating further tokens.",
      optional: true,
    },
    stream: {
      type: "boolean",
      label: "Stream",
      description: "If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available, with the stream terminated by a `data: [DONE]` message.",
      optional: true,
      reloadProps: true,
    },
    streamIncludeUsage: {
      type: "string",
      label: "Stream Include Usage",
      description: "If set, an additional chunk will be streamed before the `data: [DONE]` message. The `usage` field on this chunk shows the token usage statistics for the entire request, and the `choices` field will always be an empty array. All other chunks will also include a `usage` field, but with a null value.",
      optional: true,
      hidden: true,
    },
    temperature: {
      type: "string",
      label: "Temperature",
      description: "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. We generally recommend altering this or Top P but not both.",
      optional: true,
    },
    topP: {
      type: "string",
      label: "Top P",
      description: "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.",
      optional: true,
    },
    tools: {
      type: "string[]",
      label: "Tools",
      description: "A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.",
      optional: true,
    },
    toolChoice: {
      type: "string",
      label: "Tool Choice",
      description: "Controls which (if any) tool is called by the model. [See the documentation](https://api-docs.deepseek.com/api/create-chat-completion) for further details.",
      optional: true,
    },
    logprobs: {
      type: "boolean",
      label: "Log Probs",
      description: "Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the `content` of `message`.",
      optional: true,
    },
    topLogprobs: {
      type: "string",
      label: "Top Log Probabilities",
      description: "An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. logprobs must be set to true if this parameter is used.",
      optional: true,
    },
  },
  async additionalProps(props) {
    props.streamIncludeUsage.hidden = !this.stream;
    return {};
  },
  async run({ $ }) {
    const response = await this.deepseek.createModelResponse({
      $,
      data: {
        messages: parseObject(this.messages),
        model: "deepseek-chat",
        frequency_penalty: this.frequencyPenalty && parseInt(this.frequencyPenalty),
        max_tokens: this.maxTokens,
        presence_penalty: this.presencePenalty && parseInt(this.presencePenalty),
        response_format: this.responseFormatType
          ? {
            type: this.responseFormatType,
          }
          : null,
        stop: parseObject(this.stop),
        stream: this.stream,
        stream_options: this.stream
          ? {
            include_usage: this.streamIncludeUsage,
          }
          : null,
        temperature: this.temperature && parseInt(this.temperature),
        top_p: this.topP && parseInt(this.topP),
        tools: parseObject(this.tools),
        tool_choice: parseObject(this.toolChoice),
        logprobs: this.logprobs,
        top_logprobs: this.topLogprobs && parseInt(this.topLogprobs),
      },
    });
    $.export("$summary", "Chat completion created");
    return 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
DeepSeek	`deepseek`	`app`	This component uses the DeepSeek app.
Messages	`messages`	`string[]`	The messages for the chat conversation as JSON strings. Each message should be a JSON string like '{"role": "user", "content": "Hello!"}'. See the documentation for further details.
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.
Max Tokens	`maxTokens`	`integer`	Integer between 1 and 8192. The maximum number of tokens that can be generated in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length. If `max_tokens` is not specified, the default value 4096 is used.
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.
Response Format Type	`responseFormatType`	`string`	Select a value from the drop down menu:`{ "label": "Text", "value": "text" }{ "label": "JSON Object", "value": "json_object" }`
Stop Sequences	`stop`	`string[]`	Up to 16 sequences where the API will stop generating further tokens.
Stream	`stream`	`boolean`	If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available, with the stream terminated by a `data: [DONE]` message.
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. We generally recommend altering this or Top P but not both.
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.
Tools	`tools`	`string[]`	A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.
Tool Choice	`toolChoice`	`string`	Controls which (if any) tool is called by the model. See the documentation for further details.
Log Probs	`logprobs`	`boolean`	Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the `content` of `message`.
Top Log Probabilities	`topLogprobs`	`string`	An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. logprobs must be set to true if this parameter is used.

Action Authentication#

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

About DeepSeek#

DeepSeek is an AI-powered tool that helps developers quickly find, understand, and optimize code using natural language search and contextual suggestions. It integrates seamlessly with your workflow, offering insights into your codebase to improve productivity and code quality. Perfect for teams and solo developers, DeepSeek simplifies code navigation and accelerates development.

More Ways to Connect DeepSeek + Slack#

Other Popular Integrations#

Create Chat Completion with DeepSeek API on New Channel Created (Instant) from Slack v2 API

Slack + DeepSeek

Create Chat Completion with DeepSeek API on New Interaction Events (Instant) from Slack API

Pipedream makes it easy to connect APIs for DeepSeek, Slack and 2,900+ other apps remarkably fast.

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

Developers ♥ Pipedream

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