Integrate the LLMWhisperer API with the Python API

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

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Popular LLMWhisperer and Python Actions#

Extract Text with the LLMWhisperer API

Convert your PDF/scanned documents to text format which can be used by LLMs. See the documentation

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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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Get Status with the LLMWhisperer API

Get the status of the whisper process. This can be used to check the status of the conversion process when the conversion is done in async mode. See the documentation

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Highlight Locations with the LLMWhisperer API

Generate highlight locations for a search term in the document. See the documentation

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Retrieve Extracted Text with the LLMWhisperer API

Retrieve the extracted text executed through the whisper API. This can be used to retrieve the text of the conversion process when the conversion is done in async mode. See the documentation

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Connect LLMWhisperer#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    llmwhisperer: {
      type: "app",
      app: "llmwhisperer",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://llmwhisperer-api.unstract.com/v1/get-usage-info`,
      headers: {
        "unstract-key": `${this.llmwhisperer.$auth.api_key}`,
      },
    })
  },
})

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#

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}}

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