Generate Embeddings with Ollama API on New Email Open Instant from ReachMail API

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Trigger workflow on

New Email Open Instant from the ReachMail API

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Generate Embeddings with the Ollama API

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Getting Started#

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

Select this integration
Configure the New Email Open Instant trigger
1. Connect your ReachMail account
Configure the Generate Embeddings action
1. Connect your Ollama account
2. Select a Model Name
3. Configure Input
4. Optional- Configure Truncate
5. Optional- Configure Advanced Options
6. Optional- Configure Keep Alive
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 Email Open Instant on ReachMail

Description:Emit new event when a recipient opens an email.

Version:0.0.1

Key:reachmail-new-open-instant

View on GitHub

ReachMail Overview#

The ReachMail API lets you seamlessly integrate email marketing capabilities into your workflows on Pipedream. With it, you can automate email list management, campaign creation, and performance tracking. This flexibility opens up possibilities for custom email marketing automation, audience segmentation, and targeted outreach based on user actions or data from other apps. By harnessing the power of Pipedream's serverless platform, you can build workflows that trigger from various events and connect with numerous other services to create a sophisticated, automated email marketing machine.

Trigger Code#

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

export default {
  ...common,
  key: "reachmail-new-open-instant",
  name: "New Email Open Instant",
  description: "Emit new event when a recipient opens an email.",
  version: "0.0.1",
  type: "source",
  dedupe: "unique",
  methods: {
    ...common.methods,
    getAction() {
      return "Open";
    },
    getSummary(body) {
      return `Email opened by ${body.Email}`;
    },
  },
  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
ReachMail	`reachmail`	`app`	This component uses the ReachMail app.
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.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.

Trigger Authentication#

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

About ReachMail#

ReachMail is a simple, web-based tool to create, deliver and track beautiful HTML email campaigns and newsletters.

Action#

Generate Embeddings on Ollama

Description:Generate embeddings from a model. [See the documentation](https://github.com/ollama/ollama/blob/main/docs/api.md#generate-embeddings).

Version:0.0.1

Key:ollama-generate-embeddings

View on GitHub

Action Code#

import utils from "../../common/utils.mjs";
import app from "../../ollama.app.mjs";

export default {
  key: "ollama-generate-embeddings",
  name: "Generate Embeddings",
  description: "Generate embeddings from a model. [See the documentation](https://github.com/ollama/ollama/blob/main/docs/api.md#generate-embeddings).",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    model: {
      propDefinition: [
        app,
        "model",
      ],
    },
    input: {
      type: "string[]",
      label: "Input",
      description: "The list of texts to generate embeddings for.",
    },
    truncate: {
      type: "boolean",
      label: "Truncate",
      description: "Truncates the end of each input to fit within context length. Returns error if `false` and context length is exceeded. Defaults to `true`.",
      optional: true,
    },
    options: {
      propDefinition: [
        app,
        "options",
      ],
    },
    keepAlive: {
      propDefinition: [
        app,
        "keepAlive",
      ],
    },
  },
  methods: {
    generateEmbeddings(args = {}) {
      return this.app.post({
        path: "/embed",
        ...args,
      });
    },
  },
  async run({ $ }) {
    const {
      generateEmbeddings,
      model,
      input,
      truncate,
      options,
      keepAlive,
    } = this;

    const response = await generateEmbeddings({
      $,
      data: {
        model,
        input,
        truncate,
        options: utils.parseOptions(options),
        keep_alive: keepAlive,
      },
    });
    $.export("$summary", "Successfully generated embeddings.");
    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
Ollama	`app`	`app`	This component uses the Ollama app.
Model Name	`model`	`string`	Select a value from the drop down menu.
Input	`input`	`string[]`	The list of texts to generate embeddings for.
Truncate	`truncate`	`boolean`	Truncates the end of each input to fit within context length. Returns error if `false` and context length is exceeded. Defaults to `true`.
Advanced Options	`options`	`object`	Additional model parameters listed in the documentation for the Modelfile such as `temperature`
Keep Alive	`keepAlive`	`string`	Controls how long the model will stay loaded into memory following the request (default: 5m).