Post Chat Completion with xAI API on New Row from Snowflake API

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Trigger workflow on

New Row from the Snowflake API

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Post Chat Completion with the xAI API

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Getting Started#

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

Select this integration
Configure the New Row trigger
1. Connect your Snowflake account
2. Configure timer
3. Select a Database
4. Select a Schema
5. Select a Table Name
6. Select a Unique Key
7. Optional- Configure Emit individual events
Configure the Post Chat Completion action
1. Connect your xAI account
2. Select a Model
3. Configure Message
4. Optional- Configure Frequency Penalty
5. Optional- Configure Log Probabilities
6. Optional- Configure Max Tokens
7. Optional- Configure Completion Number
8. Optional- Configure Presence Penalty
9. Optional- Configure Seed
10. Optional- Configure Stream
11. Optional- Configure Temperature
12. Optional- Configure Nucleus Sampling
13. 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 Row on Snowflake

Description:Emit new event when a row is added to a table

Version:0.2.2

Key:snowflake-new-row

View on GitHub

Snowflake Overview#

Snowflake offers a cloud database and related tools to help developers create robust, secure, and scalable data warehouses. See Snowflake's Key Concepts & Architecture.

Getting Started

1. Create a user, role and warehouse in Snowflake

Snowflake recommends you create a new user, role, and warehouse when you integrate a third-party tool like Pipedream. This way, you can control permissions via the user / role, and separate Pipedream compute and costs with the warehouse. You can do this directly in the Snowflake UI.

We recommend you create a read-only account if you only need to query Snowflake. If you need to insert data into Snowflake, add permissions on the appropriate objects after you create your user.

2. Enter those details in Pipedream

Visit https://pipedream.com/accounts. Click the button to Connect an App. Enter the required Snowflake account data.

You'll only need to connect your account once in Pipedream. You can connect this account to multiple workflows to run queries against Snowflake, insert data, and more.

3. Build your first workflow

Visit https://pipedream.com/new to build your first workflow. Pipedream workflows let you connect Snowflake with 1,000+ other apps. You can trigger workflows on Snowflake queries, sending results to Slack, Google Sheets, or any app that exposes an API. Or you can accept data from another app, transform it with Python, Node.js, Go or Bash code, and insert it into Snowflake.

Learn more at Pipedream University.

Trigger Code#

import common from "../common-table-scan.mjs";

export default {
  ...common,
  type: "source",
  key: "snowflake-new-row",
  name: "New Row",
  description: "Emit new event when a row is added to a table",
  version: "0.2.2",
  methods: {
    ...common.methods,
    async getStatement(lastResultId) {
      const sqlText = `
        SELECT *
        FROM IDENTIFIER(:1)
        WHERE ${this.uniqueKey} > :2
        ORDER BY ${this.uniqueKey} ASC
      `;
      const binds = [
        this.tableName,
        lastResultId,
      ];
      return {
        sqlText,
        binds,
      };
    },
  },
};

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
Snowflake	`snowflake`	`app`	This component uses the Snowflake app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`	Watch for changes on this schedule
Database	`database`	`string`	Select a value from the drop down menu.
Schema	`schema`	`string`	Select a value from the drop down menu.
Table Name	`tableName`	`string`	Select a value from the drop down menu.
Unique Key	`uniqueKey`	`string`	Select a value from the drop down menu.
Emit individual events	`emitIndividualEvents`	`boolean`	Defaults to `true`, triggering workflows on each record in the result set. Set to `false` to emit records in batch (advanced)

Trigger Authentication#

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

We recommend you create a read-only account if you only need to query Snowflake. If you need to insert data into Snowflake, add permissions on the appropriate objects after you create your user.

About Snowflake#

A data warehouse built for the cloud

Action#

Post Chat Completion on xAI

Description:Create a language model response for a chat conversation. [See the documentation](https://docs.x.ai/api/endpoints#chat-completions)

Version:0.0.2

Key:x_ai-post-chat-completion

View on GitHub

Action Code#

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

export default {
  key: "x_ai-post-chat-completion",
  name: "Post Chat Completion",
  description: "Create a language model response for a chat conversation. [See the documentation](https://docs.x.ai/api/endpoints#chat-completions)",
  version: "0.0.2",
  type: "action",
  props: {
    app,
    model: {
      propDefinition: [
        app,
        "model",
      ],
    },
    message: {
      propDefinition: [
        app,
        "message",
      ],
    },
    frequencyPenalty: {
      propDefinition: [
        app,
        "frequencyPenalty",
      ],
    },
    logprobs: {
      propDefinition: [
        app,
        "logprobs",
      ],
    },
    maxTokens: {
      propDefinition: [
        app,
        "maxTokens",
      ],
    },
    n: {
      propDefinition: [
        app,
        "n",
      ],
    },
    presencePenalty: {
      propDefinition: [
        app,
        "presencePenalty",
      ],
    },
    seed: {
      propDefinition: [
        app,
        "seed",
      ],
    },
    stream: {
      propDefinition: [
        app,
        "stream",
      ],
    },
    temperature: {
      propDefinition: [
        app,
        "temperature",
      ],
    },
    topP: {
      propDefinition: [
        app,
        "topP",
      ],
    },
    user: {
      propDefinition: [
        app,
        "user",
      ],
    },
  },

  async run({ $ }) {
    const response = await this.app.postChatCompletion({
      $,
      data: {
        model: this.model,
        messages: [
          {
            role: "user",
            content: this.message,
          },
        ],
        frequency_penalty: Number(this.frequencyPenalty),
        logprobs: this.logprobs,
        max_tokens: this.maxTokens,
        n: this.n,
        presence_penalty: Number(this.presencePenalty),
        seed: this.seed,
        stream: this.stream,
        temperature: Number(this.temperature),
        top_p: Number(this.topP),
        user: this.user,
      },
    });
    $.export("$summary", `Successfully sent message to the model '${this.model}'`);
    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
xAI	`app`	`app`	This component uses the xAI app.
Model	`model`	`string`	Select a value from the drop down menu.
Message	`message`	`string`	Message for the chat completion
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
Log Probabilities	`logprobs`	`boolean`	Include the log probabilities on the `logprobs` most likely output tokens, as well the chosen tokens
Max Tokens	`maxTokens`	`integer`	Limits the number of tokens that can be produced in the output
Completion Number	`n`	`integer`	Determines how many completion sequences to produce for each prompt. Be cautious with its use due to high token consumption
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
Seed	`seed`	`integer`	If specified, our system will make a best effort to sample deterministically
Stream	`stream`	`boolean`	Whether to stream back partial progress. If set, tokens will be sent as data-only server-sent events as they become available
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
Nucleus Sampling	`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
User	`user`	`string`	A unique identifier representing your end-user, which can help xAI to monitor and detect abuse