Update src/streamlit_app.py

src/streamlit_app.py

@@ -6,45 +6,27 @@ from langchain_community.embeddings import HuggingFaceEmbeddings
 
 st.set_page_config(page_title="RAG Search", page_icon="🔍")
 
-# ---------------------------------------------
-# 1️⃣ Locate your Chroma DB zip
-# ---------------------------------------------
-possible_paths = [
-    "chroma_db.zip",
-    os.path.join("src", "chroma_db.zip"),
-    os.path.join(os.path.dirname(__file__), "chroma_db.zip"),
-    os.path.join(os.path.dirname(__file__), "..", "chroma_db.zip"),
-    "/app/chroma_db.zip",
-]
+# --- 1️⃣ Define correct paths ---
+ROOT_DIR = "/app"  # Hugging Face Space root
+ZIP_PATH = os.path.join(ROOT_DIR, "chroma_db.zip")
+DB_PATH = os.path.join(ROOT_DIR, "chroma_db")
 
-ZIP_PATH = None
-for p in possible_paths:
-    if os.path.exists(p):
-        ZIP_PATH = p
-        break
-
-if ZIP_PATH is None:
-    st.error("❌ Could not find 'chroma_db.zip'. Please ensure it's in your repo root.")
-    st.stop()
-
-DB_PATH = "chroma_db"
-
-# ---------------------------------------------
-# 2️⃣ Extract only once per app session
-# ---------------------------------------------
+# --- 2️⃣ Extract only once per app session ---
 if "db_ready" not in st.session_state:
     if not os.path.exists(DB_PATH):
-        st.info("📦 Extracting Chroma DB for the first time...")
-        with zipfile.ZipFile(ZIP_PATH, "r") as zip_ref:
-            zip_ref.extractall(DB_PATH)
-        st.success("✅ Database extracted successfully!")
+        if os.path.exists(ZIP_PATH):
+            st.info("📦 Extracting Chroma DB for the first time...")
+            with zipfile.ZipFile(ZIP_PATH, "r") as zip_ref:
+                zip_ref.extractall(DB_PATH)
+            st.success("✅ Database extracted successfully!")
+        else:
+            st.error(f"❌ Database zip not found at: {ZIP_PATH}")
+            st.stop()
     else:
-        st.info("✅ Chroma DB folder already exists.")
-    st.session_state.db_ready = True  # Mark as ready
+        st.info("✅ Chroma DB already extracted.")
+    st.session_state.db_ready = True  # mark done
 
-# ---------------------------------------------
-# 3️⃣ Load embeddings (CPU safe)
-# ---------------------------------------------
+# --- 3️⃣ Load embeddings (CPU-only) ---
 @st.cache_resource(show_spinner=False)
 def load_embeddings():
     return HuggingFaceEmbeddings(
@@ -54,24 +36,19 @@ def load_embeddings():
 
 embeddings = load_embeddings()
 
-# ---------------------------------------------
-# 4️⃣ Load Chroma DB (cached)
-# ---------------------------------------------
+# --- 4️⃣ Load Chroma DB (cached) ---
 @st.cache_resource(show_spinner=False)
 def load_vectordb():
     return Chroma(persist_directory=DB_PATH, embedding_function=embeddings)
 
 vectordb = load_vectordb()
 
-# ---------------------------------------------
-# 5️⃣ Query + Display Results
-# ---------------------------------------------
+# --- 5️⃣ Query input ---
 query = st.text_input("Enter your query:", "What is SystemVerilog interface?")
 
 if st.button("Search"):
     st.write("🔎 Searching your local vector database...")
     results = vectordb.similarity_search(query, k=3)
-
     if results:
         for i, doc in enumerate(results):
             st.subheader(f"Result {i+1}")
@@ -79,5 +56,4 @@ if st.button("Search"):
             st.caption(doc.metadata)
             st.markdown("---")
     else:
-        st.warning("⚠️ No matching results found.")
-
+        st.warning("⚠️ No results found.")