Post Chat Completion with xAI API on New Column from PostgreSQL API

Pipedream makes it easy to connect APIs for xAI, PostgreSQL and 2,400+ other apps remarkably fast.

Trigger workflow on

New Column from the PostgreSQL API

Next, do this

Post Chat Completion with the xAI API

No credit card required

▶

Watch us build a workflow

8 min

Watch now ➜

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

Developers ♥ Pipedream

Getting Started#

This integration creates a workflow with a PostgreSQL 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 Column trigger
1. Connect your PostgreSQL account
2. Configure Polling Interval
3. Select a Schema
4. Select a Table
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 Column on PostgreSQL

Description:Emit new event when a new column is added to a table. [See the documentation](https://node-postgres.com/features/queries)

Version:2.0.6

Key:postgresql-new-column

View on GitHub

PostgreSQL Overview#

On Pipedream, you can leverage the PostgreSQL app to create workflows that automate database operations, synchronize data across platforms, and react to database events in real-time. Think handling new row entries, updating records from webhooks, or even compiling reports on a set schedule. Pipedream's serverless platform provides a powerful way to connect PostgreSQL with a variety of apps, enabling you to create tailored automation that fits your specific needs.

Trigger Code#

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

export default {
  ...common,
  name: "New Column",
  key: "postgresql-new-column",
  description: "Emit new event when a new column is added to a table. [See the documentation](https://node-postgres.com/features/queries)",
  version: "2.0.6",
  type: "source",
  props: {
    ...common.props,
    schema: {
      propDefinition: [
        common.props.postgresql,
        "schema",
      ],
    },
    table: {
      propDefinition: [
        common.props.postgresql,
        "table",
        (c) => ({
          schema: c.schema,
        }),
      ],
    },
  },
  async run() {
    const previousColumns = this._getPreviousValues() || [];

    const columns = await this.postgresql.getColumns(this.table, this.schema);

    const newColumns = columns.filter((column) => !previousColumns.includes(column));
    for (const column of newColumns) {
      const meta = this.generateMeta(column);
      this.$emit(column, meta);
    }

    this._setPreviousValues(columns);
  },
};

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
PostgreSQL	`postgresql`	`app`	This component uses the PostgreSQL app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Polling Interval	`timer`	`$.interface.timer`	Pipedream will poll the API on this schedule
Schema	`schema`	`string`	Select a value from the drop down menu.
Table	`table`	`string`	Select a value from the drop down menu.

Trigger Authentication#

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

Connecting to Restricted Databases

Either enable the shared static IP for this account below, or configure a VPC to deploy any workflow in your workspace to a private network with a dedicated static IP. Learn more in our docs.

SSL Setup

Configure SSL on your PostgreSQL database by providing the CA (Certificate Authority), and choosing between Full Verification, Verify Certificate Authority (CA), or Skip Verification. Skipping verification is not recommended as this has serious security implications.

About PostgreSQL#

PostgreSQL is a free and open-source relational database management system emphasizing extensibility and SQL compliance.

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