Update streamlit_app.py

streamlit_app.py

@@ -1,70 +1,93 @@
-import sys, os
+import sys
+import os
 import streamlit as st
 
-# ---- Ensure root dir is always in path ----
-ROOT_DIR = os.path.abspath(os.path.dirname(__file__))
+# ---- Ensure project root is always in PYTHONPATH ----
+ROOT_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
 if ROOT_DIR not in sys.path:
-    sys.path.append(ROOT_DIR)
+    sys.path.insert(0, ROOT_DIR)
 
-# Local imports (flat repo)
-from main import run_pipeline
-from rag_node import load_pdf, rag_answer
-from weather_node import fetch_weather
-from decision_node import decide_and_execute
+# ---- Local imports ----
+from app.main import run_pipeline
+from app.rag_node import load_pdf, rag_answer
+from app.weather_node import fetch_weather
 
-st.set_page_config(page_title="🤖 AI Agent: Weather + PDF Q&A", page_icon="🤖", layout="wide")
+# ---- Page config ----
+st.set_page_config(
+    page_title="🤖 AI Agent: Weather + PDF Q&A",
+    page_icon="🤖",
+    layout="wide"
+)
 
 st.title("🤖 AI Agent: Weather + PDF Q&A")
 
-# Sidebar: Mode selection
-mode = st.sidebar.radio("Choose a mode:", ["🌦️ Weather", "📄 PDF Q&A", "🤖 Combined (Auto Detect)"])
+# ---- Sidebar ----
+mode = st.sidebar.radio(
+    "Choose a mode:",
+    ["🌦️ Weather", "📄 PDF Q&A", "🤖 Combined (Auto Detect)"]
+)
 
-# 🌦️ Weather Mode
+# ===================== WEATHER MODE =====================
 if mode == "🌦️ Weather":
     st.header("🌦️ Weather Queries")
-    city = st.text_input("Enter a city name:")
+
+    city = st.text_input("Enter a city name")
+
     if st.button("Get Weather"):
-        if city:
-            result = fetch_weather(city)
+        if city.strip():
+            with st.spinner("Fetching weather..."):
+                result = fetch_weather(city.strip())
             st.success(result)
         else:
             st.warning("Please enter a city name.")
 
-# 📄 PDF Mode
+# ===================== PDF MODE =====================
 elif mode == "📄 PDF Q&A":
     st.header("📄 Ask Questions from PDF")
 
     if "pdf_loaded" not in st.session_state:
         st.session_state.pdf_loaded = False
 
-    uploaded_pdf = st.file_uploader("Upload a PDF", type=["pdf"])
+    uploaded_pdf = st.file_uploader(
+        "Upload a PDF",
+        type=["pdf"]
+    )
+
     if uploaded_pdf:
         os.makedirs("data", exist_ok=True)
-        with open("data/sample.pdf", "wb") as f:
+        pdf_path = "data/sample.pdf"
+
+        with open(pdf_path, "wb") as f:
             f.write(uploaded_pdf.read())
-        load_pdf("data/sample.pdf")
+
+        with st.spinner("Indexing PDF into vector database..."):
+            load_pdf(pdf_path)
+
         st.session_state.pdf_loaded = True
-        st.success("✅ PDF loaded into Qdrant!")
+        st.success("✅ PDF loaded and indexed successfully!")
+
+    query = st.text_input("Ask something from the PDF")
 
-    query = st.text_input("Ask something from the PDF:")
     if st.button("Search PDF"):
-        if st.session_state.pdf_loaded:
-            if query:
-                answer = rag_answer(query)
-                st.info(f"📄 Answer: {answer}")
-            else:
-                st.warning("Please enter a query.")
+        if not st.session_state.pdf_loaded:
+            st.warning("Please upload and load a PDF first.")
+        elif not query.strip():
+            st.warning("Please enter a query.")
         else:
-            st.warning("Upload and load a PDF first!")
+            with st.spinner("Searching document..."):
+                answer = rag_answer(query.strip())
+            st.info(answer)
 
-# 🤖 Combined Mode (Decision Node + Pipeline)
+# ===================== COMBINED MODE =====================
 elif mode == "🤖 Combined (Auto Detect)":
     st.header("🤖 Combined Mode (Weather + PDF)")
-    query = st.text_input("Ask me anything:")
+
+    query = st.text_input("Ask me anything")
+
     if st.button("Ask Agent"):
-        if query:
-            with st.spinner("Processing..."):
-                answer = run_pipeline(query)  # ✅ goes through pipeline (LangGraph + LangSmith)
-            st.success(answer)
-        else:
+        if not query.strip():
             st.warning("Please enter a query.")
+        else:
+            with st.spinner("Agent is thinking..."):
+                answer = run_pipeline(query.strip())
+            st.success(answer)