Update app.py

app.py

@@ -0,0 +1,50 @@
+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}")