01_02e.txt

# Please run this in your Google Colab Environment

!pip install llama-cpp-python==0.3.2

from llama_cpp import Llama

llm = Llama.from_pretrained(
    repo_id="bartowski/aya-23-8B-GGUF",
    filename="aya-23-8B-IQ2_M.gguf"
)

reviews = [
    "This product is amazing! The quality exceeded my expectations, and the customer service was excellent. (English)",  # Positive, highlights quality & service
    "Este producto es increíble. La entrega fue rápida y el empaque estaba bien protegido. (Spanish)",  # Positive, mentions delivery & packaging
    "Ce produit est de bonne qualité, mais le prix est un peu trop élevé pour ce qu'il offre. (French)",  # Mixed review, good quality but expensive
    "Dieses Produkt hat mich enttäuscht. Es funktioniert nicht wie erwartet und der Kundendienst reagiert langsam. (German)",  # Negative, mentions performance & customer service
    "この製品にはいくつかの良い点がありますが、耐久性に問題があります。数週間で壊れてしまいました。 (Japanese)",  # Negative, durability issue
]


prompt = (
    "<BOS_TOKEN><|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>\n"
    "Below are multiple customer reviews in different languages. Please analyze them as a whole and provide:\n"
    "1. A general sentiment analysis of the reviews collectively.\n"
    "2. A summary of the key strengths customers appreciate.\n"
    "3. A business weakness that should be improved.\n"
    "Here are the reviews:\n\n"
    f"{' '.join(reviews)}\n"
    "<|END_OF_TURN_TOKEN|>"
)