Sentiment and emotion analysis cli that uses machine learning and natural language processing to identify and classify emotions in text data
Sentiment and emotion analysis cli that uses machine learning and natural language processing to identify and classify emotions in text data
Get your MONKEY_LEARN_API_KEY and MONKEY_LEARN_MODEL_ID from MonkeyLearn
You'll have to create a account and use the trial mode just to test it
Set your API_KEY and MODEL_ID:
emotive-ai config ui # to use ui prompt directly
emotive-ai config set MONKEY_LEARN_API_KEY=<your key> # for api key
emotive-ai config set MONKEY_LEARN_MODEL_ID=<your model id> # for model
Recommended
npx emotive-ai <text>
Using global installation
npm install -g emotive-ai # npm
yarn add global emotive-ai # yarn
emotive-ai <text>
emotive-ai hello guys
😄 : Positive with 65.81% of confidence A positive sentiment tag indicates that the sentiment of a piece of text is generally positive.This could mean that the text expresses a favorable opinion, conveys happiness or excitement, or generally has a positive tone.
emotive-ai its really a bad day
😢 : Negative with 93.82% of confidence A negative sentiment tag indicates that the sentiment of a piece of text is generally negative. This could mean that the text expresses a critical opinion, conveys sadness or disappointment, or generally has a negative tone.
EmotiveAI is an MIT-licensed open source project. It can grow thanks to the sponsors and support by the amazing backers.
EmotiveAI is MIT licensed.
FAQs
Sentiment and emotion analysis cli that uses machine learning and natural language processing to identify and classify emotions in text data
The npm package emotive-ai receives a total of 8 weekly downloads. As such, emotive-ai popularity was classified as not popular.
We found that emotive-ai demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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