Typless

Typless is an easy-to-use invoice OCR REST API powered by AI

Integrate the Typless API with the Go API

Setup the Typless API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate Typless and Go remarkably fast. Free for developers.

Run Go Code with the Go API

Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.

 
Try it

Overview of Typless

The Typless API offers a streamlined solution for extracting data from documents using machine learning. With its capability, you can automate the process of pulling out specific information from various document types, such as invoices, receipts, or identity documents, turning unstructured data into structured and actionable data points.

Connect Typless

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    typless: {
      type: "app",
      app: "typless",
    }
  },
  async run({steps, $}) {
    const data = {
      "document_type_name": `simple-invoice`,
    }
    return await axios($, {
      method: "post",
      url: `https://developers.typless.com/api/start-training`,
      headers: {
        "Accept": `application/json`,
        "Authorization": `Token ${this.typless.$auth.api_key}`,
        "Content-Type": `application/json`,
      },
      data,
    })
  },
})

Overview of Go

You can execute custom Go scripts on-demand or in response to various triggers and integrate with thousands of apps supported by Pipedream. Writing with Go on Pipedream enables backend operations like data processing, automation, or invoking other APIs, all within the Pipedream ecosystem. By leveraging Go's performance and efficiency, you can design powerful and fast workflows to streamline complex tasks.

Connect Go

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package main

import (
	"fmt"

	pd "github.com/PipedreamHQ/pipedream-go"
)

func main() {
	// Access previous step data using pd.Steps
	fmt.Println(pd.Steps)

	// Export data using pd.Export
	data := make(map[string]interface{})
	data["name"] = "Luke"
	pd.Export("data", data)
}