import os
from huggingface_hub import InferenceClient

# We use Meta's Llama 3 model here, which is incredibly smart and completely FREE on Hugging Face!
client = InferenceClient("meta-llama/Meta-Llama-3-8B-Instruct")

def decode_semantic_intent(corrupted_text: str) -> str:
    prompt = f"A message was destroyed by wireless noise. The demodulator outputted: '{corrupted_text}'. Reconstruct the original intent perfectly. Only output the corrected sentence and absolutely nothing else."

    messages = [
        {"role": "system", "content": "You are a highly advanced 6G Semantic Communication Decoder. You output only the fixed sentence. No conversational text. No explanations."},
        {"role": "user", "content": prompt}
    ]

    try:
        # Ask the free Hugging Face model to fix the text
        response = client.chat_completion(
            messages, 
            max_tokens=100, 
            temperature=0.1
        )
        return response.choices[0].message.content.strip()
    except Exception as e:
        return f"AI Decoding Failed: {str(e)}"