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/Divyansh12/check"

# 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
downloaded_files = os.listdir(model_dir)
st.write("Downloaded model files:", downloaded_files)

model_path = os.path.join(model_dir, "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)