with Intellexer API and Python?
Recognize language and encoding of an input text stream. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Extract named entities from a document using Intellexer API. See the documentation
Summarize a document using Intellexer API. See the documentation
Summarize text using Intellexer API. See the documentation
The Intellexer API offers a suite of linguistic and semantic analysis tools that can enhance text-based applications. With it, you can extract meaning, relations, and facts from the text, enabling smarter data management and decision-making processes. When paired with Pipedream's serverless execution model, the Intellexer API can be used to automate content analysis, enhance search functionalities, and preprocess data for more complex workflows.
import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    intellexer_api: {
      type: "app",
      app: "intellexer_api",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `http://api.intellexer.com/sentimentAnalyzerOntologies`,
      headers: {
        "Content-Type": `application/json`,
      },
      params: {
        apikey: `${this.intellexer_api.$auth.api_key}`,
      },
    })
  },
})
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:
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}}