Update app.py

app.py

@@ -2,49 +2,73 @@ import os
 import streamlit as st
 from git import Repo
 import shutil
-from llama_index import VectorStoreIndex, SimpleDirectoryReader, ServiceContext
+
+from llama_index.core import (
+    VectorStoreIndex,
+    SimpleDirectoryReader,
+    ServiceContext,
+    SentenceSplitter,
+)
 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}")
+from llama_index.embeddings.huggingface import HuggingFaceEmbedding
+
+st.set_page_config(page_title="GitHub Repo Explainer", layout="wide")
+st.title("📘 GitHub Repository Explainer (100% Free)")
+
+github_url = st.text_input("GitHub URL", placeholder="https://github.com/user/repo")
+
+if st.button("Load and Analyze"):
+    if github_url:
+        try:
+            # Clean previous repo if exists
+            if os.path.exists("repo"):
+                shutil.rmtree("repo")
+
+            with st.spinner("📥 Cloning GitHub repository..."):
+                Repo.clone_from(github_url, "repo")
+                st.success("✅ Repo cloned successfully.")
+
+            with st.spinner("🔧 Loading LLM and 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,
+                    generate_kwargs={"top_p": 0.95, "top_k": 50},
+                    model_kwargs={"n_gpu_layers": 20, "n_batch": 512},
+                    verbose=True,
+                )
+
+                embed_model = HuggingFaceEmbedding(
+                    model_name="sentence-transformers/all-MiniLM-L6-v2"
+                )
+
+                service_context = ServiceContext.from_defaults(
+                    llm=llm,
+                    embed_model=embed_model,
+                    node_parser=SentenceSplitter(chunk_size=512, chunk_overlap=50),
+                )
+
+            with st.spinner("📄 Reading and parsing files..."):
+                docs = SimpleDirectoryReader("repo").load_data()
+                st.write(f"📚 {len(docs)} documents loaded.")
+
+            with st.spinner("🔍 Building index..."):
+                index = VectorStoreIndex.from_documents(docs, service_context=service_context)
+                query_engine = index.as_query_engine()
+
+            with st.spinner("🧠 Querying the model..."):
+                query = "Explain the purpose, structure, and setup steps of this GitHub repository."
+                response = query_engine.query(query)
+
+            st.subheader("🧾 Repository Summary")
+            st.write(str(response))
+
+        except Exception as e:
+            st.error(f"❌ Something went wrong:\n\n{e}")
+    else:
+        st.warning("⚠️ Please enter a GitHub repo URL.")
+
+if st.button("Reset"):
+    shutil.rmtree("repo", ignore_errors=True)
+    st.experimental_rerun()