Analyze Text Sentiment with Google Vertex AI API on New Record (Instant, of Selectable Type) from Salesforce API

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New Record (Instant, of Selectable Type) from the Salesforce API

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Analyze Text Sentiment with the Google Vertex AI API

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Getting Started#

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

Select this integration
Configure the New Record (Instant, of Selectable Type) trigger
1. Connect your Salesforce account
2. Configure timer
3. Select a Object Type
4. Optional- Select one or more Fields to Obtain
Configure the Analyze Text Sentiment action
1. Connect your Google Vertex AI account
2. Select a Project ID
3. Configure Text
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 Record (Instant, of Selectable Type) on Salesforce

Description:Emit new event when a record of the selected object type is created. [See the documentation](https://sforce.co/3yPSJZy)

Version:0.2.0

Key:salesforce_rest_api-new-record-instant

View on GitHub

Salesforce Overview#

The Salesforce (REST API) provides a powerful platform for creating and managing customer relationships with a wide array of features like data manipulation, querying, and complex automation. With Pipedream's serverless execution, you can create workflows that automate your sales processes, sync data with other platforms, enhance customer engagement, and trigger actions based on specific events. Dive into Salesforce data, streamline lead management, track customer interactions, and push or pull data to or from Salesforce seamlessly.

Trigger Code#

import startCase from "lodash/startCase.js";
import common from "../common.mjs";

export default {
  ...common,
  type: "source",
  name: "New Record (Instant, of Selectable Type)",
  key: "salesforce_rest_api-new-record-instant",
  description: "Emit new event when a record of the selected object type is created. [See the documentation](https://sforce.co/3yPSJZy)",
  version: "0.2.0",
  props: {
    ...common.props,
    fieldsToObtain: {
      propDefinition: [
        common.props.salesforce,
        "fieldsToObtain",
        (c) => ({
          objType: c.objectType,
        }),
      ],
      optional: true,
      description: "Select the field(s) to be retrieved for the records. Only applicable if the source is running on a timer. If running on a webhook, or if not specified, all fields will be retrieved.",
    },
  },
  hooks: {
    ...common.hooks,
    async deploy() {
      const objectType = this.objectType;
      const nameField = await this.salesforce.getNameFieldForObjectType(objectType);
      this.setNameField(nameField);

      // emit historical events
      const { recentItems } = await this.salesforce.listSObjectTypeIds(objectType);
      const ids = recentItems.map((item) => item.Id);
      for (const id of ids.slice(-25)) {
        const object = await this.salesforce.getSObject(objectType, id);
        const event = {
          body: {
            "New": object,
            "UserId": id,
          },
        };
        this.processWebhookEvent(event);
      }
    },
  },
  methods: {
    ...common.methods,
    generateTimerMeta(item, fieldName) {
      const { objectType } = this;
      const {
        CreatedDate: createdDate,
        [fieldName]: name,
        Id: id,
      } = item;
      const entityType = startCase(objectType);
      const summary = `New ${entityType} created: ${name ?? id}`;
      const ts = Date.parse(createdDate);
      return {
        id,
        summary,
        ts,
      };
    },
    generateWebhookMeta(data) {
      const nameField = this.getNameField();
      const { New: newObject } = data.body;
      const {
        CreatedDate: createdDate,
        Id: id,
        [nameField]: name,
      } = newObject;
      const entityType = startCase(this.objectType).toLowerCase();
      const summary = `New ${entityType} created: ${name ?? id}`;
      const ts = Date.parse(createdDate);
      return {
        id,
        summary,
        ts,
      };
    },
    getEventType() {
      return "new";
    },
    async processTimerEvent(eventData) {
      const {
        paginate,
        objectType,
        setLatestDateCovered,
        getObjectTypeColumns,
        getNameField,
        generateTimerMeta,
        $emit: emit,
      } = this;

      const {
        startTimestamp,
        endTimestamp,
      } = eventData;

      const fieldName = getNameField();
      const columns = getObjectTypeColumns();

      const events = await paginate({
        objectType,
        startTimestamp,
        endTimestamp,
        columns,
      });

      const [
        latestEvent,
      ] = events;

      if (latestEvent?.CreatedDate) {
        const latestDateCovered = new Date(latestEvent.CreatedDate);
        latestDateCovered.setSeconds(0);
        setLatestDateCovered(latestDateCovered.toISOString());
      }

      Array.from(events)
        .reverse()
        .forEach((item) => {
          const meta = generateTimerMeta(item, fieldName);
          emit(item, meta);
        });
    },
    async timerActivateHook() {
      const {
        objectType,
        getObjectTypeDescription,
        setObjectTypeColumns,
      } = this;

      let columns = this.fieldsToObtain;
      if (!columns?.length) {
        const { fields } = await getObjectTypeDescription(objectType);
        columns = fields.map(({ name }) => name);
      }

      setObjectTypeColumns(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
Salesforce	`salesforce`	`app`	This component uses the Salesforce app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
N/A	`http`	`$.interface.http`	This component uses `$.interface.http` to generate a unique URL when the component is first instantiated. Each request to the URL will trigger the `run()` method of the component.
	`timer`	`$.interface.timer`	The timer is only used as a fallback if instant event delivery (webhook) is not available.
Object Type	`objectType`	`string`	Select a value from the drop down menu.
Fields to Obtain	`fieldsToObtain`	`string[]`	Select a value from the drop down menu.

Trigger Authentication#

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

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

About Salesforce#

Web services API for interacting with Salesforce

Action#

Analyze Text Sentiment on Google Vertex AI

Description:Analyzes a specified text for its underlying sentiment. [See the documentation](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.publishers.models/generateContent)

Version:0.0.1

Key:google_vertex_ai-analyze-text-sentiment

View on GitHub

Google Vertex AI Overview#

With the Google Vertex AI API, you can tap into a robust suite of AI tools offered by Google Cloud to build, deploy, and scale machine learning models. Whether you're processing data, training custom models, or using pre-trained ones, Vertex AI provides a unified platform for AI development. In Pipedream, you can create serverless workflows that interact with Vertex AI, allowing you to automate tasks like model training, prediction, and resource management without provisioning your own infrastructure.

Action Code#

import vertexAi from "../../google_vertex_ai.app.mjs";

export default {
  key: "google_vertex_ai-analyze-text-sentiment",
  name: "Analyze Text Sentiment",
  description: "Analyzes a specified text for its underlying sentiment. [See the documentation](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.publishers.models/generateContent)",
  version: "0.0.1",
  type: "action",
  props: {
    vertexAi,
    projectId: {
      propDefinition: [
        vertexAi,
        "projectId",
      ],
    },
    text: {
      type: "string",
      label: "Text",
      description: "The content to analyze for sentiment",
    },
  },
  async run({ $ }) {
    const response = await this.vertexAi.generateContent({
      $,
      projectId: this.projectId,
      model: "gemini-1.0-pro",
      data: {
        contents: [
          {
            role: "user",
            parts: [
              {
                text: `${this.text}\nClassify the sentiment of the message:\n`,
              },
            ],
          },
        ],
      },
    });
    $.export("$summary", "Successfully analyzed text sentiment");
    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
Google Vertex AI	`vertexAi`	`app`	This component uses the Google Vertex AI app.
Project ID	`projectId`	`string`	Select a value from the drop down menu.
Text	`text`	`string`	The content to analyze for sentiment

Action Authentication#

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

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

emailprofilehttps://www.googleapis.com/auth/cloud-platform

About Google Vertex AI#

Vertex AI offers everything you need to build and use generative AI—from AI solutions, to Search and Conversation, to 130+ foundation models, to a unified AI platform.