Lettria

Turn your text data into smarter decisions. End-to-end NLP solution.

Integrate the Lettria API with the Python API

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

Classify Text with the Lettria API

Classify one text. See the documentation.

 
Try it
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.

 
Try it

Overview of Lettria

The Lettria API offers advanced natural language processing (NLP) capabilities, enabling developers to analyze and extract meaningful information from text data. With Lettria's API, you can perform tasks like sentiment analysis, entity recognition, and semantic analysis. When integrated into Pipedream, these features unlock the potential for automating text-intensive workflows, making it simple to process feedback, categorize customer inquiries, or extract insights from unstructured data.

Connect Lettria

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    lettria: {
      type: "app",
      app: "lettria",
    }
  },
  async run({steps, $}) {
    const data = {
    "documents": [
       "First document to analyse"
    ]
  }
    return await axios($, {
      method: "post",
      url: `https://api.lettria.com`,
      headers: {
        "Content-Type": `application/json`,
        "Authorization": `LettriaProKey ${this.lettria.$auth.api_key}`,
      },
      data,
    })
  },
})

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

1
2
3
4
5
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}}