import os
import streamlit as st
from git import Repo
import shutil
from llama_index import VectorStoreIndex, SimpleDirectoryReader, ServiceContext
from llama_index.llms.llama_cpp import LlamaCPP
from llama_index.embeddings import HuggingFaceEmbedding
from llama_index.node_parser import SimpleNodeParser

st.set_page_config(page_title="📘 GitHub Repo Explainer", layout="wide")
st.title("📘 GitHub Repository Explainer")

github_url = st.text_input("Enter GitHub URL:", placeholder="https://github.com/user/repo")

if st.button("Analyze Repo") and github_url:
    try:
        # Cleanup old repo
        if os.path.exists("repo"):
            shutil.rmtree("repo")

        # Clone repo
        Repo.clone_from(github_url, "repo")

        # Load model + embeddings
        llm = LlamaCPP(
            model_path="tinyllama-1.1b-chat-v1.0.Q4_K_M.gguf",
            temperature=0.7,
            max_new_tokens=512,
            context_window=2048,
            model_kwargs={"n_gpu_layers": 0},
            verbose=True
        )

        embed_model = HuggingFaceEmbedding(model_name="sentence-transformers/all-MiniLM-L6-v2")
        service_context = ServiceContext.from_defaults(llm=llm, embed_model=embed_model)
        
        # Load documents and build index
        documents = SimpleDirectoryReader("repo").load_data()
        parser = SimpleNodeParser()
        nodes = parser.get_nodes_from_documents(documents)
        index = VectorStoreIndex(nodes, service_context=service_context)

        # Query the index
        query_engine = index.as_query_engine()
        response = query_engine.query("Explain the purpose, structure, and setup of this repository.")
        st.subheader("🧠 Repository Summary")
        st.write(str(response))

    except Exception as e:
        st.error(f"Error: {e}")