import streamlit as st
from llama_cpp import Llama
from huggingface_hub import snapshot_download
import os

st.title("GGUF Model Streamlit App")

st.write("Downloading the model...")
repo_id = "Divyansh12/check"
model_dir = "model"

# Download the model
if not os.path.exists(model_dir):
    snapshot_download(repo_id=repo_id, cache_dir=model_dir)
    st.write("Model downloaded successfully!")

# List downloaded files for debugging
for root, dirs, files in os.walk(model_dir):
    st.write(f"Files in {root}: {files}")

# Update this path based on the actual file structure found
model_path = "model/models--Divyansh12--check/unsloth.F16.gguf"
if not os.path.exists(model_path):
    st.error(f"Model file not found at {model_path}")
else:
    st.write(f"Found model file at {model_path}")
    llm = Llama.from_pretrained(model_path=model_path)
    st.write("Model loaded successfully!")

    # Example query
    response = llm.create_chat_completion(
        messages=[
            {"role": "user", "content": "What is the capital of France?"}
        ]
    )
    st.write("Response:", response)