Chat with OpenAI (ChatGPT) API on New Or Updated Row from Microsoft SQL Server API

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New Or Updated Row from the Microsoft SQL Server API

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Getting Started#

This integration creates a workflow with a Microsoft SQL Server 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 Or Updated Row trigger
1. Connect your Microsoft SQL Server account
2. Configure Polling schedule
3. Select a Table
4. Select a Column
5. Select a Timestamp Column
Configure the Chat action
1. Connect your OpenAI (ChatGPT) account
2. Select a Model
3. Configure User Message
4. Optional- Configure Max Tokens
5. Optional- Configure Temperature
6. Optional- Configure Top P
7. Optional- Configure N
8. Optional- Configure Stop
9. Optional- Configure Presence Penalty
10. Optional- Configure Frequency Penalty
11. Optional- Configure User
12. Optional- Configure System Instructions
13. Optional- Configure Prior Message History
14. Optional- Configure Images
15. Optional- Configure Audio
16. Optional- Select a Response Format
17. Optional- Select one or more Tool Types
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 Or Updated Row on Microsoft SQL Server

Description:Triggers when a new row is added or an existing row is updated. [See the documentation](https://learn.microsoft.com/en-us/sql/t-sql/queries/select-transact-sql?view=sql-server-ver16)

Version:0.0.5

Key:microsoft_sql_server-new-or-updated-row

View on GitHub

Microsoft SQL Server Overview#

With the Microsoft SQL Server API on Pipedream, you can automate your database operations and create powerful integrations. This API allows you to execute queries, manage databases, and trigger actions based on data changes. Implementing workflows that react to database events, manipulate data, or synchronize SQL Server data with other services, becomes effortless with Pipedream's serverless platform.

Trigger Code#

import { v4 as uuidv4 } from "uuid";
import common from "../common/polling.mjs";

export default {
  ...common,
  key: "microsoft_sql_server-new-or-updated-row",
  name: "New Or Updated Row",
  description: "Triggers when a new row is added or an existing row is updated. [See the documentation](https://learn.microsoft.com/en-us/sql/t-sql/queries/select-transact-sql?view=sql-server-ver16)",
  type: "source",
  version: "0.0.5",
  dedupe: "unique",
  props: {
    ...common.props,
    table: {
      propDefinition: [
        common.props.app,
        "table",
      ],
    },
    column: {
      description: "The column is used to create a raw number for pagination.",
      propDefinition: [
        common.props.app,
        "column",
        ({ table }) => ({
          table,
        }),
      ],
    },
    timestampColumn: {
      propDefinition: [
        common.props.app,
        "column",
        ({ table }) => ({
          table,
        }),
      ],
      label: "Timestamp Column",
      description: "A datetime column, such as 'date_updated' or 'last_modified' that is set to the current datetime when a row is updated.",
    },
  },
  methods: {
    ...common.methods,
    getResourceName() {
      return "recordset";
    },
    getResourceFn() {
      return this.app.listResources;
    },
    getResourceFnArgs() {
      const {
        table,
        column,
      } = this;
      return {
        table,
        column,
      };
    },
    generateMeta() {
      return {
        id: uuidv4(),
        summary: "New Row Added/Updated",
        ts: Date.now(),
      };
    },
    processResources(resources) {
      const lastTs = this.getLastTs();
      let maxTs = lastTs;

      for (const resource of resources) {
        delete resource.pdId;
        const ts = Date.parse(resource[this.timestampColumn]);
        if (ts > lastTs) {
          this.$emit(resource, this.generateMeta(resource));
          if (ts > maxTs) {
            maxTs = ts;
          }
        }
      }

      this.setLastTs(maxTs);
    },
  },
};

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
Microsoft SQL Server	`app`	`app`	This component uses the Microsoft SQL Server app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Polling schedule	`timer`	`$.interface.timer`	How often to poll the API
Table	`table`	`string`	Select a value from the drop down menu.
Column	`column`	`string`	Select a value from the drop down menu.
Timestamp Column	`timestampColumn`	`string`	Select a value from the drop down menu.

Trigger Authentication#

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

Before you connect to your Microsoft SQL Server database from Pipedream, please make sure your database is either:

Accessible from the public internet (You may need to add a firewall rule on 0.0.0.0/0 on port 1433), or
Accessible from a static IP that you've configured from a VPC in Pipedream, and enabled the workflow to connect through that VPC

About Microsoft SQL Server#

Unleash the power of your data—on-premises, in the cloud, or at the edge—and reveal insights to transform your business.

Action#

Chat on OpenAI (ChatGPT)

Description:The Chat API, using the `gpt-3.5-turbo` or `gpt-4` model. [See the documentation](https://platform.openai.com/docs/api-reference/chat)

Version:0.2.3

Key:openai-chat

View on GitHub

OpenAI (ChatGPT) Overview#

OpenAI provides a suite of powerful AI models through its API, enabling developers to integrate advanced natural language processing and generative capabilities into their applications. Here’s an overview of the services offered by OpenAI's API:

Use Python or Node.js code to make fully authenticated API requests with your OpenAI account:

Action Code#

import openai from "../../openai.app.mjs";
import common from "../common/common.mjs";
import constants from "../../common/constants.mjs";
import { ConfigurationError } from "@pipedream/platform";

export default {
  ...common,
  name: "Chat",
  version: "0.2.3",
  key: "openai-chat",
  description: "The Chat API, using the `gpt-3.5-turbo` or `gpt-4` model. [See the documentation](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.",
    },
    ...common.props,
    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,
    },
    audio: {
      type: "string",
      label: "Audio",
      description: "Provide the file path to an audio file in the `/tmp` directory. For use with the `gpt-4o-audio-preview` model. Currently supports `wav` and `mp3` files.",
      optional: true,
    },
    responseFormat: {
      type: "string",
      label: "Response Format",
      description: "Specify the format that the model must output. \n- **Text** (default): Returns unstructured text output.\n- **JSON Object**: Ensures the model's output is a valid JSON object.\n- **JSON Schema** (GPT-4o and later): Enables you to define a specific structure for the model's output using a JSON schema. Supported with models `gpt-4o-2024-08-06` and later, and `gpt-4o-mini-2024-07-18` and later.",
      options: Object.values(constants.CHAT_RESPONSE_FORMAT),
      default: constants.CHAT_RESPONSE_FORMAT.TEXT.value,
      optional: true,
      reloadProps: true,
    },
    toolTypes: {
      type: "string[]",
      label: "Tool Types",
      description: "The types of tools to enable on the assistant",
      options: constants.TOOL_TYPES.filter((toolType) => toolType === "function"),
      optional: true,
      reloadProps: true,
    },
  },
  additionalProps() {
    const {
      responseFormat,
      toolTypes,
      numberOfFunctions,
    } = this;
    const props = {};

    if (responseFormat === constants.CHAT_RESPONSE_FORMAT.JSON_SCHEMA.value) {
      props.jsonSchema = {
        type: "string",
        label: "JSON Schema",
        description: "Define the schema that the model's output must adhere to. [See the documentation here](https://platform.openai.com/docs/guides/structured-outputs/supported-schemas).",
      };
    }

    if (toolTypes?.includes("function")) {
      props.numberOfFunctions = {
        type: "integer",
        label: "Number of Functions",
        description: "The number of functions to define",
        optional: true,
        reloadProps: true,
        default: 1,
      };

      for (let i = 0; i < (numberOfFunctions || 1); i++) {
        props[`functionName_${i}`] = {
          type: "string",
          label: `Function Name ${i + 1}`,
          description: "The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.",
        };
        props[`functionDescription_${i}`] = {
          type: "string",
          label: `Function Description ${i + 1}`,
          description: "A description of what the function does, used by the model to choose when and how to call the function.",
          optional: true,
        };
        props[`functionParameters_${i}`] = {
          type: "object",
          label: `Function Parameters ${i + 1}`,
          description: "The parameters the functions accepts, described as a JSON Schema object. See the [guide](https://platform.openai.com/docs/guides/text-generation/function-calling) for examples, and the [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for documentation about the format.",
          optional: true,
        };
      }
    }

    return props;
  },
  methods: {
    ...common.methods,
    _buildTools() {
      const tools = this.toolTypes?.filter((toolType) => toolType !== "function")?.map((toolType) => ({
        type: toolType,
      })) || [];
      if (this.toolTypes?.includes("function")) {
        const numberOfFunctions = this.numberOfFunctions || 1;
        for (let i = 0; i < numberOfFunctions; i++) {
          tools.push({
            type: "function",
            function: {
              name: this[`functionName_${i}`],
              description: this[`functionDescription_${i}`],
              parameters: this[`functionParameters_${i}`],
            },
          });
        }
      }
      return tools.length
        ? tools
        : undefined;
    },
  },
  async run({ $ }) {
    if (this.audio && !this.modelId.includes("gpt-4o-audio-preview")) {
      throw new ConfigurationError("Use of audio files requires using the `gpt-4o-audio-preview` model.");
    }

    const args = this._getChatArgs();

    const response = await this.openai.createChatCompletion({
      $,
      data: {
        ...args,
        tools: this._buildTools(),
      },
    });

    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.
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.
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
Audio	`audio`	`string`	Provide the file path to an audio file in the `/tmp` directory. For use with the `gpt-4o-audio-preview` model. Currently supports `wav` and `mp3` files.
Response Format	`responseFormat`	`string`	Select a value from the drop down menu:`{ "label": "Text", "value": "text" }{ "label": "JSON Object", "value": "json_object" }{ "label": "JSON Schema", "value": "json_schema" }`
Tool Types	`toolTypes`	`string[]`	Select a value from the drop down menu:`function`

Chat with OpenAI (ChatGPT) API on New Or Updated Row from Microsoft SQL Server API

Pipedream makes it easy to connect APIs for OpenAI (ChatGPT), Microsoft SQL Server and 2,400+ other apps remarkably fast.

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

Developers ♥ Pipedream

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