import os
import json
from llamaapi import LlamaAPI
from openai import OpenAI

# Initialize
llama = LlamaAPI("LL-AirERHEk0jLIE1yEPvMXeobNfLsqLWJWcxLRS53obrZ3XyqMTfZc4EAuOs7r3wso")

api_key = "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"
os.environ["OPENAI_API_KEY"] = api_key
client = OpenAI()


def classify_learning_content(user_input):
    messages = [
        {"role": "system", "content": "Classify the need as either "
                                      "'Vocabulary Building', 'Writing instruction', "
                                      "'Speaking Practice', 'Writing Assessment'."},
        {"role": "user", "content": user_input}
    ]

    completion = client.chat.completions.create(
        model="gpt-4",
        messages=messages
    )

    classification_text = completion.choices[0].message.content.strip().lower()  # Normalize the text
    # Simplify the comparison using keywords, assuming each category is distinct enough
    if "writing assessment" in classification_text:
        return 4
    elif "vocabulary building" in classification_text:
        return 3
    elif "writing instruction" in classification_text:
        return 2
    elif "speaking practice" in classification_text:
        return 1
    else:
        return 0


if __name__ == '__main__':
    print(classify_learning_content("Vocabulary"))