ChatGPT Sentiment Analyzer

sentimentanalyzer.py

import openai

class SentimentAnalyzer(object):

    def __init__(self, language):
        self._language = language

    def _prompt(self):
        prompt = """
            The following sentence is in %s language. 
            Categorize the sentence in to good, bad, neutral or sarcastic sentiment. 
            Provide output in the form of JSONL without any wrapping text. Valid
            return values are "positive", "negative", "neutral", "sarcastic". Also include
            the sentence in the json. Do not provide any explanation so that the result can
            be parsed by json parser.
        """ % self._language
        return prompt

    def evaluate(self, messages):
        prompt = self._prompt() + "\n".join(messages)
        completion = openai.ChatCompletion.create(model='gpt-3.5-turbo', messages=[{'role': 'user', 'content': prompt}])
        return completion.choices[0].message.content

analyzer = SentimentAnalyzer('malay')

print(analyzer.evaluate(messages=['tak boleh blah']))
print(analyzer.evaluate(messages=['tak suka makan', 'ye la tu, suka la sangat', 'jom makan']))

seems to handle sarcasm ok

$ export OPENAI_API_KEY="sk-...."
$ ./bin/python sentiment.py
{"sentence": "tak boleh blah", "sentiment": "negative"}
{"sentence": "tak suka makan", "sentiment": "negative"}
{"sentence": "ye la tu, suka la sangat", "sentiment": "sarcastic"}
{"sentence": "jom makan", "sentiment": "positive"}

lol. xD