Create ui/pipeline.py

ui/pipeline.py

@@ -0,0 +1,61 @@
+"""
+Pipeline details UI component for the pharmaceutical data management agent.
+"""
+
+import streamlit as st
+
+def render_pipeline_tab(session_state):
+    """
+    Render the pipeline details tab in the UI.
+    
+    Args:
+        session_state: Streamlit session state
+    """
+    st.subheader("Pipeline Details")
+    
+    # Intent Understanding
+    st.markdown("### User Intent")
+    if session_state.conversation["user_intent"]:
+        st.markdown(session_state.conversation["user_intent"].get("description", "No intent captured yet"))
+        if "confidence_scores" in session_state.conversation and "intent_understanding" in session_state.conversation["confidence_scores"]:
+            score = session_state.conversation["confidence_scores"]["intent_understanding"] * 100
+            st.progress(score / 100, text=f"Intent Understanding Confidence: {score:.1f}%")
+    else:
+        st.info("No user intent has been captured yet. Start a conversation to extract intent.")
+    
+    # Pipeline Plan
+    st.markdown("### Pipeline Plan")
+    if session_state.conversation["pipeline_plan"]:
+        st.markdown(session_state.conversation["pipeline_plan"].get("description", "No plan created yet"))
+        if "confidence_scores" in session_state.conversation and "plan_quality" in session_state.conversation["confidence_scores"]:
+            score = session_state.conversation["confidence_scores"]["plan_quality"] * 100
+            st.progress(score / 100, text=f"Plan Quality Confidence: {score:.1f}%")
+    else:
+        st.info("No pipeline plan has been created yet. Continue the conversation to develop a plan.")
+    
+    # SQL Queries
+    st.markdown("### SQL Queries")
+    if session_state.conversation["sql_queries"]:
+        for i, query in enumerate(session_state.conversation["sql_queries"]):
+            with st.expander(f"Query {i+1}: {query.get('name', 'Unnamed Query')}"):
+                st.code(query.get("sql", ""), language="sql")
+    else:
+        st.info("No SQL queries have been generated yet. Continue the conversation to generate queries.")
+    
+    # Execution Results
+    st.markdown("### Execution Results")
+    if session_state.conversation["execution_results"] and "details" in session_state.conversation["execution_results"]:
+        st.markdown(session_state.conversation["execution_results"].get("summary", ""))
+        
+        if "success_rate" in session_state.conversation["execution_results"]:
+            score = session_state.conversation["execution_results"]["success_rate"] * 100
+            st.progress(score / 100, text=f"Execution Success Rate: {score:.1f}%")
+        
+        results = session_state.conversation["execution_results"]["details"]
+        for i, result in enumerate(results):
+            status = "✅" if result["success"] else "❌"
+            with st.expander(f"{status} {result.get('query_name', f'Query {i+1}')}"):
+                st.markdown(f"**Result:** {result.get('result_summary', 'No summary available')}")
+                st.markdown(f"**Rows Processed:** {result.get('row_count', 0)}")
+    else:
+        st.info("No execution results available yet. Complete the pipeline creation to see results.")