show context

streamlit.py

@@ -9,9 +9,8 @@ logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
 # Set page config
-st.set_page_config(page_title="Certification Chat", layout="centered")
-
-st.title("🎓 Certification Chat Assistant")
+st.set_page_config(page_title="Certification Chat", layout="wide")
+st.title("🎓 Hydrogen Certification Chat Assistant")
 
 # Create a function to handle the async call
 async def async_query(query_text):
@@ -29,22 +28,97 @@ def run_async(coroutine):
     return loop.run_until_complete(coroutine)
 
 # User input
-user_input = st.text_area("💬 Enter your prompt:", height=150)
+user_input = st.text_area("💬 Enter your question about hydrogen certification:", height=100)
 
 if user_input:
-    st.markdown("## 🧠 Response")
-    
     try:
         # Use try-except to handle errors
         with st.spinner("Processing your query..."):
             # Run the async function
             result = run_async(async_query(user_input))
             
-            # Display output
-            st.write("**Certification:**", result["certification"])
-            st.write("**Answer from '.' chunking method:**", result["certif_index"])
-            st.write("**Answer from hybrid chunking method:**", result["certification_index"])
+            # Display output in tabs
+            st.markdown("## 🧠 Response")
+            
+            # Certification info
+            st.subheader(f"Detected Certification: {result['certification']}")
+            
+            # Create tabs for answers and contexts
+            tab1, tab2, tab3, tab4 = st.tabs([
+                "Answers", 
+                "Context Details", 
+                "Raw Context (Dot Chunking)", 
+                "Raw Context (Hybrid Chunking)"
+            ])
+            
+            with tab1:
+                st.markdown("### Basic Chunking Answer:")
+                st.write(result["certif_index"])
+                
+                st.markdown("### Hybrid Chunking Answer:")
+                st.write(result["certification_index"])
+            
+            with tab2:
+                col1, col2 = st.columns(2)
+                
+                with col1:
+                    st.markdown("### Basic Chunking Context Sources:")
+                    for i, context_item in enumerate(result["context_certif"]):
+                        with st.expander(f"Source {i+1}"):
+                            st.write(context_item)
+                
+                with col2:
+                    st.markdown("### Hybrid Chunking Context Sources:")
+                    for i, context_item in enumerate(result["context_certifications"]):
+                        with st.expander(f"Source {i+1}"):
+                            st.write(context_item)
+            
+            with tab3:
+                st.markdown("### Raw Context (Dot Chunking):")
+                for i, chunk in enumerate(result["context_certif"]):
+                    st.text_area(f"Chunk {i+1}", chunk, height=150)
+            
+            with tab4:
+                st.markdown("### Raw Context (Hybrid Chunking):")
+                for i, chunk in enumerate(result["context_certifications"]):
+                    st.text_area(f"Chunk {i+1}", chunk, height=150)
+                    
+            # Add a section for feedback
+            st.markdown("---")
+            st.markdown("### Feedback")
+            feedback = st.radio(
+                "How helpful was this response?",
+                ["Very helpful", "Somewhat helpful", "Not helpful"]
+            )
+            feedback_text = st.text_area("Additional feedback (optional):", height=100)
+            if st.button("Submit Feedback"):
+                st.success("Thank you for your feedback!")
             
     except Exception as e:
         st.error(f"An error occurred: {str(e)}")
-        logger.error(f"Error processing query: {e}", exc_info=True)
+        logger.error(f"Error processing query: {e}", exc_info=True)
+else:
+    st.info("👆 Enter your question about hydrogen certifications above to get started!")
+
+# Add sidebar with information
+with st.sidebar:
+    st.markdown("## About")
+    st.markdown("""
+    This tool helps answer questions about hydrogen certification standards using 
+    a Retrieval-Augmented Generation (RAG) system.
+    
+    The system:
+    1. Classifies which certification your question is about
+    2. Optimizes your query
+    3. Retrieves relevant information
+    4. Generates a precise answer
+    """)
+    
+    st.markdown("## Available Certifications")
+    try:
+        from app import list_certifications
+        certifications = run_async(list_certifications())
+        for cert in certifications:
+            st.markdown(f"- {cert}")
+    except Exception as e:
+        st.warning("Could not load certification list")