Cradl AI

Automate internal document processes with AI.

Integrate the Cradl AI API with the Python API

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

Run Python Code with Python API on New Document Parsing Completed (Instant) from Cradl AI API
Cradl AI + Python
 
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New Document Parsing Completed (Instant) from the Cradl AI API

Emit new event when a document processing flow has completed.

 
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Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

 
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Parse Document with the Cradl AI API

Parses data from a document using a custom selected model. See the documentation

 
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Parse Document with Human in the Loop with the Cradl AI API

Sends a document to an existing flow for human-in-the-loop processing. See the documentation

 
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Overview of Cradl AI

Cradl AI is a powerful tool for creating customized machine learning models without extensive coding knowledge. It specializes in processing and understanding various forms of data, including text and images. Utilizing the Cradl AI API on Pipedream, developers can automate workflows involving data analysis, enhance data-driven decision-making, and integrate AI capabilities into applications seamlessly. This opens up opportunities for dynamic interactions with other services, streamlining operations and enhancing user experiences.

Connect Cradl AI

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    cradl_ai: {
      type: "app",
      app: "cradl_ai",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.lucidtech.ai/v1/users`,
      headers: {
        Authorization: `Bearer ${this.cradl_ai.$auth.oauth_access_token}`,
      },
    })
  },
})

Overview of Python

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python

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def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}