How to Extract topics from text with Python

With a few lines of Python code, you can extract topics from text. Leverage use-case-ready, vertically pre-trained models, packaged in an API that accepts any text input, and responds with processed text and extracted metadata as output.

Use Language Skill

Topics

Identify topics discussed in articles and conversations

With Text Input

Text

Analyze any text, including emails, chats, documents, reviews, transcripts, and tweets

import oneai oneai.api_key = "CLICK_TO_GET_YOUR_API_KEY" pipeline = oneai.Pipeline(steps=[ oneai.skills.Topics(), ]) output = pipeline.run("your_input_here") print(output)

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import OneAI from 'oneai'; const oneai = new OneAI({apiKey: 'CLICK_TO_GET_YOUR_API_KEY'}); const pipeline = new oneai.Pipeline( oneai.skills.(), ); const output = await pipeline.run('your_input_here'); console.log(output);

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curl -X POST \ 'https://api.oneai.com/api/v0/pipeline' \ -H 'accept: application/json' \ -H 'Content-Type: application/json' \ -H 'api-key: CLICK_TO_GET_YOUR_API_KEY' \ -d '{ "input": "your_input_here", "steps": [{ "skill": "Topics" }] }'

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