Update app.py

app.py

@@ -1,5 +1,6 @@
 import streamlit as st
 import os
+import json
 from model import load_vectorstore, ask_question
 
 st.set_page_config(page_title="Simple RAG Q&A", layout="centered")
@@ -7,21 +8,21 @@ st.title("RAG Q&A with Mistral AI")
 st.write("Upload a PDF and ask questions about its content.")
 
 # PDF upload
-uploaded_file = st.file_uploader("Upload PDF", type=["pdf"])
 pdf_path = "/app/data/document.pdf"
+uploaded_file = st.file_uploader("Upload PDF", type=["pdf"])
 
 if uploaded_file:
     os.makedirs("/app/data", exist_ok=True)
-    with open(pdf_path, "wb") as f:
-        f.write(uploaded_file.read())
-    st.success("PDF uploaded!")
-    
-    with st.spinner("Indexing document..."):
-        try:
+    try:
+        with open(pdf_path, "wb") as f:
+            f.write(uploaded_file.read())
+        st.success("PDF uploaded!")
+        
+        with st.spinner("Indexing document..."):
             load_vectorstore(pdf_path)
             st.success("Document indexed!")
-        except Exception as e:
-            st.error(f"Indexing failed: {str(e)}")
+    except Exception as e:
+        st.error(f"Failed to upload/index PDF: {str(e)}")
 
 # Query input
 query = st.text_input("Enter your question", 
@@ -41,4 +42,14 @@ if st.button("Ask") and query:
                     with st.expander(f"Context {i}"):
                         st.write(context)
             except Exception as e:
-                st.error(f"Failed to generate answer: {str(e)}")
+                st.error(f"Failed to generate answer: {str(e)}")
+
+# Query endpoint for testing
+if "query" in st.experimental_get_query_params():
+    query = st.experimental_get_query_params().get("query", [""])[0]
+    if query and os.path.exists(pdf_path):
+        try:
+            result = ask_question(query, pdf_path)
+            st.json(result)
+        except Exception as e:
+            st.json({"error": str(e)})