Sentiment Analysis
POST
https://vulavula-services.lelapa.ai/api/v1/sentiment_analysis/process.
The Sentiment endpoint analyses the provided text and returns the emotional tone as positive, negative, or neutral. Each request can handle up to 2,000 tokens, with a recommended limit of 180 tokens for optimal performance.
BODY PARAMS
encoded_text string required.
This parameter represents the text input that will be analysed for named entities. It is required for the endpoint to function properly. The encoded_text
should be provided as a string and contains the text to be processed by the Sentiment model.
HEADERS
X-CLIENT-TOKEN string required.
Represents the authentication token required for accessing the API. This header ensures that only authorized clients can make requests to the endpoint.
EXAMPLES
pdm add vulavulabash
from vulavula import VulavulaClient client = VulavulaClient("<INSERT_TOKEN>") sentiment_result = client.get_sentiments({'encoded_text': 'am happy. i am sad. hello!'}) print(sentiment_result)python
RESPONSES
🟢 200 OK
{ "Id": "a9529bd6-35c9-406b-ae01-f7c9cd95cf54", "Sentiments": [ { "text": "am happy", "sentiment": [ { "label": "positive", "score": 0.9991829991340637 } ] }, { "text": " i am sad", "sentiment": [ { "label": "negative", "score": 0.960746169090271 } ] }, { "text": " hello", "sentiment": [ { "label": "neutral", "score": 0.8527688384056091 } ] } ] }json
RESPONSE BODY PARAMS
Object |
---|
Sentiments string required. Sentences seperated by (. and !) and returned as a list of sentiments |
sentiment obj required. Object with the response analysed for each of the sentences |
text string required. Contains text which makes up each of the sentences |
label string required. Indicates the sentiment returned by the Model for each sentence |
score number required. Model confidence that the answer is of that specific Sentiment |