Update src/streamlit_app.py

src/streamlit_app.py

@@ -5,24 +5,23 @@ import io
 import re
 
 # ==========================================
-# 1. BASE INITIALIZATION & GLOBAL SCOPE
+# 1. UI CONFIGURATION & INTERFACE SETUP
 # ==========================================
 st.set_page_config(page_title="CX Architect Auto-Mapper", layout="wide", page_icon="🏗️")
 st.title("🏗️ CX Architect: Omni-Channel Generator")
 st.markdown("Upload your PRD, VOC data, or an existing spreadsheet. The AI engine will instantly map the customer journey and generate a structured VA Design Sheet.")
 
-# Explicitly initialize variables at the top to protect against older engine versions
+# Global state variables initialization
 api_key = ""
 demo_mode = False
 
-# Sidebar Configuration Panel (Hyper-compatible Layout)
+# Sidebar Configuration Panel
 with st.sidebar:
     st.header("⚙️ Configuration")
     
-    # Switched from st.toggle to st.checkbox for 100% version compatibility
+    # 100% stable checkbox for system compatibility
     demo_mode = st.checkbox("🚀 Activate Demo Simulation Mode", value=False)
     
-    # Render key input based on the chosen mode
     if not demo_mode:
         api_key = st.text_input("Enter Gemini API Key", type="password", placeholder="Paste your AIza... key here")
         if api_key and api_key.startswith("AQ."):
@@ -37,10 +36,10 @@ with st.sidebar:
 uploaded_file = st.file_uploader("Drop your Lending Document here (PDF, TXT, or CSV)", type=["pdf", "txt", "csv"])
 
 # ==========================================
-# 2. FAIL-SAFE SIMULATION STORAGE
+# 2. FAIL-SAFE DATA MATRICES
 # ==========================================
 def get_simulation_assets():
-    """Returns perfect layout data matrices modeled directly from real lending datasets"""
+    """Returns layout datasets modeled directly from real lending configurations"""
     flow_text = (
         "📍 MILESTONE 1: USER_AUTHENTICATION\n"
         "   - Happy Path: Identity verified instantly via core onboarding APIs.\n"
@@ -70,13 +69,12 @@ def get_simulation_assets():
     return flow_text, pd.DataFrame(rows, columns=headers)
 
 def safe_read_file(file):
-    name = file.name
     try:
-        if name.endswith('.pdf'):
+        if file.name.endswith('.pdf'):
             import PyPDF2
             pdf_reader = PyPDF2.PdfReader(io.BytesIO(file.getvalue()))
             return "".join([page.extract_text() or "" for page in pdf_reader.pages])
-        elif name.endswith('.csv'):
+        elif file.name.endswith('.csv'):
             df = pd.read_csv(io.BytesIO(file.getvalue()), errors='ignore')
             return df.to_string()
         else:
@@ -85,80 +83,78 @@ def safe_read_file(file):
         return f"Error: {str(e)}"
 
 # ==========================================
-# 3. RUNTIME CONTROLLER
+# 3. RUNTIME OPERATION CONTROLLER
 # ==========================================
 if st.button("🚀 Generate Design Sheets & Flow"):
+    # Fail-safe condition adjustment: Bypasses file validation rules if user has Demo Mode activated
     if not demo_mode and not api_key:
         st.error("⚠️ Configuration Key Required! Please input your Gemini API Key or activate Demo Simulation Mode in the sidebar.")
-    elif not uploaded_file:
+    elif not demo_mode and not uploaded_file:
         st.error("⚠️ Data Source Missing! Please upload a PDF, TXT, or CSV file to analyze.")
     else:
-        with st.spinner("Processing document datasets and structural journey parameters..."):
+        with st.spinner("Processing customer journey parameters..."):
             try:
                 flow_output = ""
                 dataframe_output = None
                 
-                # SCENARIO A: Direct Presentation Simulation Mode
+                # SCENARIO A: Direct Demo Mode (No File or Key requirements enforced)
                 if demo_mode:
                     flow_output, dataframe_output = get_simulation_assets()
                     
-                # SCENARIO B: Native Parsing for existing CSV design matrices
-                elif uploaded_file.name.endswith('.csv'):
-                    raw_df = pd.read_csv(io.BytesIO(uploaded_file.getvalue()), errors='ignore')
-                    dataframe_output = raw_df
-                    flow_output = f"📋 Native Document File Detected: '{uploaded_file.name}'\nSuccessfully loaded {len(raw_df)} configuration layout rows directly into the dashboard matrix."
-                    
-                # SCENARIO C: Live AI Extraction Core
+                # SCENARIO B: Live Data Extraction Pipeline
                 else:
-                    doc_text = safe_read_file(uploaded_file)
-                    genai.configure(api_key=api_key)
-                    model = genai.GenerativeModel('gemini-1.5-flash')
-                    
-                    prompt = f"""
-                    You are an elite Fintech CX Architect mapping a Virtual Assistant (VA) flow for Loan Against Mutual Funds (LAMF).
-                    Analyze the data and output exactly two chunks inside these XML containers. Do not use markdown backticks.
-                    
-                    <FLOW>
-                    List the Happy Path milestones, and then list the Unhappy Path scenarios along with recommended Bot Actions.
-                    </FLOW>
-                    
-                    <TABLE>
-                    Current Milestone | Scenario | Context Message | User Selection | Short Note | Ticket Creation | Group | Issue / GTIS | TAG
-                    Provide at least 4 custom rows separated by standard pipe characters (|) matching this column sequence.
-                    </TABLE>
-                    
-                    Data text:
-                    {doc_text}
-                    """
-                    ai_response = model.generate_content(prompt).text
-                    
-                    flow_match = re.search(r"<FLOW>(.*?)</FLOW>", ai_response, re.DOTALL)
-                    table_match = re.search(r"<TABLE>(.*?)</TABLE>", ai_response, re.DOTALL)
-                    
-                    flow_output = flow_match.group(1).strip() if flow_match else "Journey breakdown completed."
-                    raw_table_str = table_match.group(1).strip() if table_match else ""
-                    
-                    table_lines = [l.strip() for l in raw_table_str.split('\n') if l.strip() and '---' not in l]
-                    if table_lines:
-                        headers = [h.strip() for h in table_lines[0].split('|')]
-                        data_rows = [[cell.strip() for cell in r.split('|')] for r in table_lines[1:] if '|' in r]
+                    if uploaded_file.name.endswith('.csv'):
+                        raw_df = pd.read_csv(io.BytesIO(uploaded_file.getvalue()), errors='ignore')
+                        dataframe_output = raw_df
+                        flow_output = f"📋 Loaded configuration layout rows directly from '{uploaded_file.name}'."
+                    else:
+                        doc_text = safe_read_file(uploaded_file)
+                        genai.configure(api_key=api_key)
+                        model = genai.GenerativeModel('gemini-1.5-flash')
+                        
+                        prompt = f"""
+                        You are an elite Fintech CX Architect mapping a Virtual Assistant flow for Loan Against Mutual Funds (LAMF).
+                        Output exactly two structural segments inside these XML tag elements. Do not use markdown backticks.
+                        
+                        <FLOW>
+                        List the Happy Path milestones, and then list the Unhappy Path scenarios along with recommended Bot Actions.
+                        </FLOW>
+                        
+                        <TABLE>
+                        Current Milestone | Scenario | Context Message | User Selection | Short Note | Ticket Creation | Group | Issue / GTIS | TAG
+                        Provide at least 4 custom rows separated by standard pipe characters (|) matching this sequence.
+                        </TABLE>
+                        
+                        Data text: {doc_text}
+                        """
+                        ai_response = model.generate_content(prompt).text
+                        
+                        flow_match = re.search(r"<FLOW>(.*?)</FLOW>", ai_response, re.DOTALL)
+                        table_match = re.search(r"<TABLE>(.*?)</TABLE>", ai_response, re.DOTALL)
+                        
+                        flow_output = flow_match.group(1).strip() if flow_match else "Journey breakdown completed."
+                        raw_table_str = table_match.group(1).strip() if table_match else ""
                         
-                        clean_rows = []
-                        for row in data_rows:
-                            if len(row) < len(headers): row += ["NA"] * (len(headers) - len(row))
-                            elif len(row) > len(headers): row = row[:len(headers)]
-                            clean_rows.append(row)
-                        dataframe_output = pd.DataFrame(clean_rows, columns=headers)
+                        table_lines = [l.strip() for l in raw_table_str.split('\n') if l.strip() and '---' not in l]
+                        if table_lines:
+                            headers = [h.strip() for h in table_lines[0].split('|')]
+                            data_rows = [[cell.strip() for cell in r.split('|')] for r in table_lines[1:] if '|' in r]
+                            
+                            clean_rows = []
+                            for row in data_rows:
+                                if len(row) < len(headers): row += ["NA"] * (len(headers) - len(row))
+                                elif len(row) > len(headers): row = row[:len(headers)]
+                                clean_rows.append(row)
+                            dataframe_output = pd.DataFrame(clean_rows, columns=headers)
             
                 # ==========================================
-                # 4. RENDER INTERACTIVE PRESENTATION TABS
+                # 4. OUTPUT DISPLAY LAYOUT
                 # ==========================================
-                st.success("🎯 Assets Computed Successfully!")
+                st.success("🎯 Omni-Channel Assets Rendered Successfully!")
                 tab1, tab2 = st.tabs(["🗺️ Visual Journey Path", "📊 VA Design Sheet (Excel)"])
                 
                 with tab1:
                     st.subheader("Process Flow Optimization Strategy")
-                    st.info("The structural user-journey steps mapped out from your document parameters:")
                     st.code(flow_output, language="text")
                     
                 with tab2:
@@ -174,7 +170,7 @@ if st.button("🚀 Generate Design Sheets & Flow"):
                             mime='text/csv',
                         )
                     else:
-                        st.warning("Data rows could not be arranged into a standard matrix framework layout.")
+                        st.warning("Data rows could not be arranged into a standard matrix format layout.")
                         
             except Exception as runtime_err:
                 st.error(f"Execution Interrupted: {str(runtime_err)}")