feat: add page doc gen

src/pages/{Passport_Power_Explorer.py → 02_Passport_Power_Explorer.py}

@@ -1,169 +1,164 @@
-import streamlit as st
-import pandas as pd
-import numpy as np
-import re
-import os
-
-# --- Page Configuration ---
-st.set_page_config(
-    page_title="Passport Power Explorer",
-    page_icon="✈️",
-    layout="wide"
-)
-
-# --- Data Loading and Processing ---
-
-@st.cache_data
-def load_and_process_data(filepath):
-    """
-    Loads visa data from a CSV, cleans it, and extracts structured information.
-    Caches the result for performance.
-    """
-    try:
-        df = pd.read_csv(filepath)
-    except FileNotFoundError:
-        st.error(f"Error: The file was not found at '{filepath}'. Please make sure 'asean_visa_avaibility_playwright.csv' is in the project's src/data directory.")
-        return pd.DataFrame()
-
-    # --- Feature Engineering: Extract Visa Type and Duration ---
-    
-    # 1. Extract Duration in Days
-    def extract_days(text):
-        if not isinstance(text, str):
-            return np.nan
-        # Find numbers followed by 'days'
-        matches = re.findall(r'(\d+)\s*days', text, re.IGNORECASE)
-        if matches:
-            return int(matches[0])
-        return np.nan
-
-    df['duration_days'] = df['text'].apply(extract_days)
-
-    # 2. Categorize Visa Type
-    def categorize_visa(text):
-        if not isinstance(text, str):
-            return "Unknown"
-        text_lower = text.lower()
-        if 'visa-free' in text_lower:
-            return "✅ Visa-Free"
-        if 'visa on arrival' in text_lower:
-            return "🛬 Visa on Arrival"
-        if 'evisa' in text_lower or 'eta' in text_lower:
-            return "📧 eVisa / eTA"
-        if 'visa required' in text_lower:
-            return "❌ Visa Required"
-        return "📄 Other / Pre-enrollment"
-
-    df['visa_category'] = df['text'].apply(categorize_visa)
-    
-    # Clean up column names for display
-    df.rename(columns={
-        'text': 'Requirement',
-        'pass': 'Passport',
-        'dest': 'Destination',
-        'source': 'Source Country',
-        'duration_days': 'Duration (Days)',
-        'visa_category': 'Visa Category'
-    }, inplace=True)
-    
-    return df
-
-# --- Main Application UI ---
-
-st.title("✈️ Passport Power & Visa Explorer")
-st.markdown("Analyze inbound and outbound visa requirements for Southeast Asian countries based on the provided dataset.")
-
-# Load the data
-# Adjust the path to be relative to the script's location if needed
-# Assuming the script is in src/pages and the CSV is in the root
-# The path should be ../../visa_avaibility_playwright_20251015.csv
-file_path = "src/data/asean_visa_avaibility_playwright.csv"
-visa_df = load_and_process_data(file_path)
-
-if not visa_df.empty:
-    
-    # --- Sidebar Filters ---
-    st.sidebar.header("🔍 Filters")
-
-    # 1. Select Focus Country
-    focus_countries = ['Indonesia', 'Vietnam', 'Philippines', 'Thailand']
-    selected_country = st.sidebar.selectbox(
-        "Select your focus country:",
-        options=focus_countries
-    )
-
-    # 2. Select Travel Direction (Inbound/Outbound)
-    travel_direction = st.sidebar.radio(
-        "Select travel direction:",
-        options=['Outbound', 'Inbound'],
-        horizontal=True
-    )
-
-    # --- Filtering Logic ---
-    if travel_direction == 'Outbound':
-        filtered_df = visa_df[visa_df['Source Country'] == selected_country].copy()
-        st.header(f"🛂 Outbound Travel for {selected_country} Passport Holders")
-    else: # Inbound
-        filtered_df = visa_df[visa_df['Destination'] == selected_country].copy()
-        st.header(f"🛬 Inbound Travel to {selected_country}")
-
-    # --- Dynamic Filters Based on Data ---
-    
-    # 3. Filter by Visa Category
-    visa_categories = sorted(filtered_df['Visa Category'].unique())
-    selected_categories = st.sidebar.multiselect(
-        "Filter by Visa Category:",
-        options=visa_categories,
-        default=visa_categories # Default to all selected
-    )
-
-    # 4. Filter by Duration
-    min_duration, max_duration = 0, int(filtered_df['Duration (Days)'].max())
-    
-    duration_range = st.sidebar.slider(
-        "Filter by Stay Duration (Days):",
-        min_value=min_duration,
-        max_value=max_duration,
-        value=(min_duration, max_duration) # Default to full range
-    )
-
-    # Apply category and duration filters
-    filtered_df = filtered_df[filtered_df['Visa Category'].isin(selected_categories)]
-
-    # Handle slider filtering, including NaNs
-    min_select, max_select = duration_range
-    # Keep rows where duration is within range OR where duration is NaN (not specified)
-    filtered_df = filtered_df[
-        (filtered_df['Duration (Days)'].between(min_select, max_select)) | 
-        (filtered_df['Duration (Days)'].isnull())
-    ]
-    
-    # --- Display Results ---
-    
-    st.markdown("---")
-    
-    # Display summary metrics
-    col1, col2, col3 = st.columns(3)
-    col1.metric("Total Countries Found", f"{len(filtered_df)}")
-    
-    visa_free_count = len(filtered_df[filtered_df['Visa Category'] == '✅ Visa-Free'])
-    col2.metric("Visa-Free Destinations", f"{visa_free_count}")
-    
-    visa_required_count = len(filtered_df[filtered_df['Visa Category'] == '❌ Visa Required'])
-    col3.metric("Visa Required", f"{visa_required_count}")
-
-    st.markdown("### Visa Requirements Data")
-    
-    # Define columns to display
-    display_cols_outbound = ['Destination', 'Visa Category', 'Requirement', 'Duration (Days)']
-    display_cols_inbound = ['Source Country', 'Passport', 'Visa Category', 'Requirement', 'Duration (Days)']
-    
-    display_columns = display_cols_outbound if travel_direction == 'Outbound' else display_cols_inbound
-    
-    st.dataframe(
-        filtered_df[display_columns].reset_index(drop=True),
-        use_container_width=True,
-        hide_index=True
-    )
-else:
+import streamlit as st
+import pandas as pd
+import numpy as np
+import re
+import os
+
+# --- Page Configuration ---
+st.set_page_config(
+    page_title="Passport Power Explorer",
+    page_icon="✈️",
+    layout="wide"
+)
+
+
+@st.cache_data
+def load_and_process_data(filepath):
+    """
+    Loads visa data from a CSV, cleans it, and extracts structured information.
+    Caches the result for performance.
+    """
+    try:
+        df = pd.read_csv(filepath)
+    except FileNotFoundError:
+        st.error(f"Error: The file was not found at '{filepath}'. Please make sure 'asean_visa_avaibility_playwright.csv' is in the project's src/data directory.")
+        return pd.DataFrame()
+
+    def extract_days(text):
+        if not isinstance(text, str):
+            return np.nan
+        matches = re.findall(r'(\d+)\s*days', text, re.IGNORECASE)
+        if matches:
+            return int(matches[0])
+        return np.nan
+
+    df['duration_days'] = df['text'].apply(extract_days)
+
+    # 2. Categorize Visa Type
+    def categorize_visa(text):
+        if not isinstance(text, str):
+            return "Unknown"
+        text_lower = text.lower()
+        if 'visa-free' in text_lower:
+            return "✅ Visa-Free"
+        if 'visa on arrival' in text_lower:
+            return "🛬 Visa on Arrival"
+        if 'evisa' in text_lower or 'eta' in text_lower:
+            return "📧 eVisa / eTA"
+        if 'visa required' in text_lower:
+            return "❌ Visa Required"
+        return "📄 Other / Pre-enrollment"
+
+    df['visa_category'] = df['text'].apply(categorize_visa)
+    
+    # Clean up column names for display
+    df.rename(columns={
+        'text': 'Requirement',
+        'pass': 'Passport',
+        'dest': 'Destination',
+        'source': 'Source Country',
+        'duration_days': 'Duration (Days)',
+        'visa_category': 'Visa Category'
+    }, inplace=True)
+    
+    return df
+
+# --- Main Application UI ---
+
+st.title("✈️ Passport Power & Visa Explorer")
+st.markdown("Analyze inbound and outbound visa requirements for Southeast Asian countries based on the provided dataset.")
+
+# Load the data
+# Adjust the path to be relative to the script's location if needed
+# Assuming the script is in src/pages and the CSV is in the root
+# The path should be ../../visa_avaibility_playwright_20251015.csv
+file_path = "src/data/asean_visa_avaibility_playwright.csv"
+visa_df = load_and_process_data(file_path)
+
+if not visa_df.empty:
+    
+    # --- Sidebar Filters ---
+    st.sidebar.header("🔍 Filters")
+
+    # 1. Select Focus Country
+    focus_countries = ['Indonesia', 'Vietnam', 'Philippines', 'Thailand']
+    selected_country = st.sidebar.selectbox(
+        "Select your focus country:",
+        options=focus_countries
+    )
+
+    # 2. Select Travel Direction (Inbound/Outbound)
+    travel_direction = st.sidebar.radio(
+        "Select travel direction:",
+        options=['Outbound', 'Inbound'],
+        horizontal=True
+    )
+
+    # --- Filtering Logic ---
+    if travel_direction == 'Outbound':
+        filtered_df = visa_df[visa_df['Source Country'] == selected_country].copy()
+        st.header(f"🛂 Outbound Travel for {selected_country} Passport Holders")
+    else: # Inbound
+        filtered_df = visa_df[visa_df['Destination'] == selected_country].copy()
+        st.header(f"🛬 Inbound Travel to {selected_country}")
+
+    # --- Dynamic Filters Based on Data ---
+    
+    # 3. Filter by Visa Category
+    visa_categories = sorted(filtered_df['Visa Category'].unique())
+    selected_categories = st.sidebar.multiselect(
+        "Filter by Visa Category:",
+        options=visa_categories,
+        default=visa_categories # Default to all selected
+    )
+
+    # 4. Filter by Duration
+    min_duration, max_duration = 0, int(filtered_df['Duration (Days)'].max())
+    
+    duration_range = st.sidebar.slider(
+        "Filter by Stay Duration (Days):",
+        min_value=min_duration,
+        max_value=max_duration,
+        value=(min_duration, max_duration) # Default to full range
+    )
+
+    # Apply category and duration filters
+    filtered_df = filtered_df[filtered_df['Visa Category'].isin(selected_categories)]
+
+    # Handle slider filtering, including NaNs
+    min_select, max_select = duration_range
+    # Keep rows where duration is within range OR where duration is NaN (not specified)
+    filtered_df = filtered_df[
+        (filtered_df['Duration (Days)'].between(min_select, max_select)) | 
+        (filtered_df['Duration (Days)'].isnull())
+    ]
+    
+    # --- Display Results ---
+    
+    st.markdown("---")
+    
+    # Display summary metrics
+    col1, col2, col3 = st.columns(3)
+    col1.metric("Total Countries Found", f"{len(filtered_df)}")
+    
+    visa_free_count = len(filtered_df[filtered_df['Visa Category'] == '✅ Visa-Free'])
+    col2.metric("Visa-Free Destinations", f"{visa_free_count}")
+    
+    visa_required_count = len(filtered_df[filtered_df['Visa Category'] == '❌ Visa Required'])
+    col3.metric("Visa Required", f"{visa_required_count}")
+
+    st.markdown("### Visa Requirements Data")
+    
+    # Define columns to display
+    display_cols_outbound = ['Destination', 'Visa Category', 'Requirement', 'Duration (Days)']
+    display_cols_inbound = ['Source Country', 'Passport', 'Visa Category', 'Requirement', 'Duration (Days)']
+    
+    display_columns = display_cols_outbound if travel_direction == 'Outbound' else display_cols_inbound
+    
+    st.dataframe(
+        filtered_df[display_columns].reset_index(drop=True),
+        use_container_width=True,
+        hide_index=True
+    )
+else:
     st.warning("Could not load visa data to display.")

src/pages/03_Document_Generator.py

@@ -0,0 +1,350 @@
+import streamlit as st
+import requests
+import datetime
+import pandas as pd
+import base64 
+
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+
+API_BASE_URL = os.getenv("BASE_URI", "https://localhost:5000")
+TODAY = datetime.date.today()
+
+# --- Helper Function ---
+def generate_and_download(endpoint, payload, filename):
+    """
+    Handles the API POST request, displays the PDF in an iframe,
+    and provides a download button.
+    """
+    try:
+        url = f"{API_BASE_URL}{endpoint}"
+        
+        # Display the JSON payload for debugging
+        with st.expander("View Request JSON Payload"):
+            st.json(payload)
+
+        response = requests.post(url, json=payload)
+
+        if response.status_code == 200 and response.headers.get('Content-Type') == 'application/pdf':
+            st.success("✅ PDF Generated Successfully!")
+            
+            # Get the PDF content
+            pdf_content = response.content
+            
+            # --- NEW: Display PDF in iframe (using st.markdown) ---
+            # Base64 encode the PDF content
+            base64_pdf = base64.b64encode(pdf_content).decode('utf-8')
+            
+            # Create the HTML for the iframe
+            st.subheader("📄 PDF Preview")
+            pdf_display_html = f'<iframe src="data:application/pdf;base64,{base64_pdf}" width="100%" height="800" type="application/pdf" style="border: 1px solid #ddd; border-radius: 8px;"></iframe>'
+            st.markdown(pdf_display_html, unsafe_allow_html=True)
+            # --- END NEW ---
+
+            # Keep the download button as well
+            st.download_button(
+                label="Download PDF",
+                data=pdf_content, # Use the stored content
+                file_name=filename,
+                mime="application/pdf"
+            )
+        else:
+            st.error(f"❌ Error generating PDF (Status Code: {response.status_code}):")
+            try:
+                # Try to display the JSON error message from the API
+                st.json(response.json())
+            except requests.exceptions.JSONDecodeError:
+                # Fallback if the error response isn't JSON
+                st.text(response.text)
+
+    except requests.exceptions.ConnectionError:
+        st.error(f"❌ Connection Error: Could not connect to the API at {API_BASE_URL}.")
+        st.info("Please ensure your local Flask API server is running.")
+    except Exception as e:
+        st.error(f"An unexpected error occurred: {e}")
+
+# --- Streamlit App UI ---
+st.set_page_config(page_title="Visa Letter PDF Generator", layout="wide")
+st.title("🌍 Visa Letter PDF Generator")
+st.caption(f"Frontend for the Visa Letter API (assumed running at `{API_BASE_URL}`)")
+
+tab1, tab2, tab3, tab4, tab5 = st.tabs([
+    "🇪🇺 Schengen Visa",
+    "🇯🇵 Japan Multi-Entry",
+    "🤝 Sponsorship Letter",
+    "STATEMENT Housewife Statement",
+    "COLLECTION Passport Collection"
+])
+
+# --- Tab 1: Schengen Visa ---
+with tab1:
+    st.header("🇪🇺 Schengen Visa Cover Letter")
+    
+    trip_type = st.radio("Select Trip Type", ["Individual", "Group"], horizontal=True)
+    
+    with st.form("schengen_form"):
+        col1, col2 = st.columns(2)
+        
+        with col1:
+            st.subheader("Trip Details")
+            country = st.text_input("Country of Embassy (e.g., Germany)", "Germany")
+            city = st.text_input("City of Application (e.g., Jakarta)", "Jakarta")
+            purpose = st.text_input("Purpose of Trip (e.g., tourism)", "tourism")
+            main_destination = st.text_input("Main Destination", "Germany")
+            event = st.text_input("Event (e.g., personal vacation)", "personal vacation")
+            other_destinations = st.text_input("Other Destinations (e.g., France and Italy)", "France and Italy")
+            travel_start = st.text_input("Travel Start Date", "1st August 2024")
+            travel_end = st.text_input("Travel End Date", "16th August 2024")
+            duration = st.text_input("Duration", "16 days and 15 nights")
+        
+        with col2:
+            st.subheader("Main Applicant Details")
+            pa_name = st.text_input("Full Name", "John Doe")
+            pa_dob = st.text_input("Date of Birth", "1st January 1985")
+            pa_nationality = st.text_input("Nationality", "Indonesian")
+            pa_occupation = st.text_input("Occupation", "Software Engineer")
+            pa_passport = st.text_input("Passport Number", "A1234567")
+            
+            st.subheader("Contact & Financials")
+            trip_highlight = st.text_area("Trip Highlight", "visit cultural landmarks, museums, and enjoy sightseeing in Germany")
+            contact_email = st.text_input("Contact Email", "john@example.com")
+            contact_phone = st.text_input("Contact Phone", "+62 812 3456 7890")
+            job_commitment = st.text_input("Job Commitment", "Software Engineer at PT. Example Indonesia")
+            financial_status = st.text_input("Financial Status", "sound")
+
+        # Group Members Section
+        if trip_type == "Group":
+            st.subheader("Group Members")
+            st.info("Add your travel companions below. Click '+' to add rows.")
+            group_members_df = pd.DataFrame([
+                {
+                    "relationship": "Wife", "name": "Jane Doe", "dob": "5th May 1987",
+                    "occupation": "Teacher", "nationality": "Indonesian", "passport_number": "B7654321"
+                },
+                {
+                    "relationship": "Son", "name": "Jack Doe", "dob": "10th August 2010",
+                    "occupation": "Student", "nationality": "Indonesian", "passport_number": "C9988776"
+                }
+            ])
+            edited_group_members = st.data_editor(
+                group_members_df,
+                num_rows="dynamic",
+                use_container_width=True
+            )
+
+        submit_schengen = st.form_submit_button("Generate Schengen PDF")
+
+    if submit_schengen:
+        personal_details = {
+            "name": pa_name,
+            "dob": pa_dob,
+            "nationality": pa_nationality,
+            "occupation": pa_occupation,
+            "passport_number": pa_passport
+        }
+        
+        payload = {
+            "country": country,
+            "city": city,
+            "purpose": purpose,
+            "main_destination": main_destination,
+            "event": event,
+            "other_destinations": other_destinations,
+            "travel_start": travel_start,
+            "travel_end": travel_end,
+            "duration": duration,
+            "personal_details": personal_details,
+            "trip_highlight": trip_highlight,
+            "contact_email": contact_email,
+            "contact_phone": contact_phone,
+            "job_commitment": job_commitment,
+            "financial_status": financial_status
+        }
+
+        endpoint = "/generate/schengen"
+
+        
+        if trip_type == "Group":
+            # Convert DataFrame to list of dicts
+            payload["group_members"] = edited_group_members.to_dict('records')
+            filename = "Schengen_Group_Cover_Letter.pdf"
+        else:
+            filename = "Schengen_Individual_Cover_Letter.pdf"
+            
+        generate_and_download(endpoint, payload, filename)
+
+
+# --- Tab 2: Japan Multi-Entry ---
+with tab2:
+    st.header("🇯🇵 Japan Multi-Entry Visa Letter")
+    with st.form("japan_form"):
+        col1, col2 = st.columns(2)
+        with col1:
+            st.subheader("Applicant Details")
+            name = st.text_input("Full Name", "John Doe")
+            address = st.text_area("Address", "Gatot Subroto St., Senayan")
+            city = st.text_input("City", "Jakarta Selatan")
+            
+        with col2:
+            st.subheader("Contact & Location")
+            postal_code = st.text_input("Postal Code", "51001")
+            email = st.text_input("Email", "john@example.com")
+            phone = st.text_input("Phone", "+62 812 3456 7890")
+
+        submit_japan = st.form_submit_button("Generate Japan PDF")
+
+    if submit_japan:
+        payload = {
+            "name": name,
+            "address": address,
+            "city": city,
+            "postal_code": postal_code,
+            "email": email,
+            "phone": phone
+        }
+        generate_and_download("/generate/japan-multientry-tourist", payload, "Japan_MultiEntry_Visa_Letter.pdf")
+
+
+# --- Tab 3: Sponsorship Letter ---
+with tab3:
+    st.header("🤝 Sponsorship Letter")
+    with st.form("sponsorship_form"):
+        col1, col2, col3 = st.columns(3)
+        
+        with col1:
+            st.subheader("Sponsor Details")
+            sponsor_name = st.text_input("Sponsor Name", "Mr. John Sponsor")
+            sponsor_address = st.text_area("Sponsor Address", "123 Sponsor St, Appt 4B")
+            sponsor_postal_code = st.text_input("Sponsor City, State, Postal", "New York, NY 10001")
+            sponsor_email = st.text_input("Sponsor Email", "john.sponsor@email.com")
+            sponsor_contact_number = st.text_input("Sponsor Contact Number", "+1 (555) 123-4567")
+
+        with col2:
+            st.subheader("Embassy Details")
+            officer_title = st.text_input("Officer Title", "Visa Officer")
+            embassy_name = st.text_input("Embassy Name", "Embassy of [Country]")
+            embassy_address = st.text_area("Embassy Address", "456 Embassy Row")
+            embassy_city_state_postal = st.text_input("Embassy City, State, Postal", "Washington, D.C. 20008")
+            
+            st.subheader("Applicant Details")
+            applicant_name = st.text_input("Applicant Name", "Ms. Jane Applicant")
+            applicant_dob = st.text_input("Applicant Date of Birth", "January 15, 1995")
+            applicant_passport_no = st.text_input("Applicant Passport Number", "X12345678")
+            
+        with col3:
+            st.subheader("Visit Details")
+            visa_name = st.text_input("Visa Type (e.g., B-2 Visitor Visa)", "B-2 Visitor Visa")
+            sponsor_relationship = st.text_input("Sponsor's Relationship to Applicant", "friend")
+            visit_reason = st.text_input("Reason for Visit", "attend my wedding and for tourism")
+            destination_country = st.text_input("Destination Country", "the United States")
+            visit_start_date = st.text_input("Visit Start Date", "December 1, 2024")
+            visit_end_date = st.text_input("Visit End Date", "December 20, 2024")
+            visit_purpose_details = st.text_area("Detailed Purpose of Visit", "a personal visit to attend my wedding ceremony on December 5th and to tour New York City")
+
+        submit_sponsorship = st.form_submit_button("Generate Sponsorship PDF")
+
+    if submit_sponsorship:
+        payload = {
+            "sponsor_name": sponsor_name,
+            "sponsor_address": sponsor_address,
+            "sponsor_postal_code": sponsor_postal_code,
+            "sponsor_email": sponsor_email,
+            "sponsor_contact_number": sponsor_contact_number,
+            "officer_title": officer_title,
+            "embassy_name": embassy_name,
+            "embassy_address": embassy_address,
+            "embassy_city_state_postal": embassy_city_state_postal,
+            "applicant_name": applicant_name,
+            "applicant_dob": applicant_dob,
+            "applicant_passport_no": applicant_passport_no,
+            "visa_name": visa_name,
+            "sponsor_relationship": sponsor_relationship,
+            "visit_reason": visit_reason,
+            "destination_country": destination_country,
+            "visit_start_date": visit_start_date,
+            "visit_end_date": visit_end_date,
+            "visit_purpose_details": visit_purpose_details
+        }
+        generate_and_download("/generate/sponsorship", payload, "Sponsorship_Letter.pdf")
+
+
+# --- Tab 4: Housewife Statement ---
+with tab4:
+    st.header("STATEMENT Housewife Statement Letter")
+    with st.form("housewife_form"):
+        col1, col2 = st.columns(2)
+        with col1:
+            applicant_name = st.text_input("Applicant Name", "Mrs. Sarah Wijaya")
+            applicant_dob = st.text_input("Applicant Place & Date of Birth", "Jakarta, April 10, 1985")
+            applicant_passport = st.text_input("Applicant Passport Number", "B1234567")
+            sponsor_name = st.text_input("Sponsor's Name (Husband)", "Mr. Budi Wijaya")
+            sponsor_bank_details = st.text_input("Sponsor's Bank Details", "Bank Central Asia (BCA): 123-456-7890")
+            
+        with col2:
+            destination_country = st.text_input("Destination Country", "Japan")
+            visa_type = st.text_input("Visa Type", "tourism")
+            visit_end_date = st.text_input("Visit End Date", "November 20, 2024")
+            travel_companions = st.text_input("Travel Companions", "my husband, Budi Wijaya, and my son, Putra Wijaya")
+            letter_location = st.text_input("Location of Letter Signing", "Jakarta")
+            letter_date = st.text_input("Date of Letter", "October 28, 2024")
+
+        submit_housewife = st.form_submit_button("Generate Housewife Statement PDF")
+
+    if submit_housewife:
+        payload = {
+            "applicant_name": applicant_name,
+            "applicant_dob": applicant_dob,
+            "applicant_passport": applicant_passport,
+            "sponsor_name": sponsor_name,
+            "sponsor_bank_details": sponsor_bank_details,
+            "destination_country": destination_country,
+            "visa_type": visa_type,
+            "visit_end_date": visit_end_date,
+            "travel_companions": travel_companions,
+            "letter_location": letter_location,
+            "letter_date": letter_date
+        }
+        generate_and_download("/generate/housewife-statement", payload, "Housewife_Statement.pdf")
+
+
+# --- Tab 5: Passport Collection ---
+with tab5:
+    st.header("COLLECTION Passport Collection Consent Letter")
+    
+    with st.form("passport_collection_form"):
+        col1, col2 = st.columns(2)
+        with col1:
+            st.subheader("Applicant Details")
+            applicant_name = st.text_input("Applicant Name", "Budi Hartono")
+            applicant_nik = st.text_input("Applicant NIK (ID Number)", "3171234567890001")
+            applicant_address = st.text_area("Applicant Address", "Jl. Kemerdekaan No. 17, Jakarta Pusat")
+            passport_no = st.text_input("Applicant Passport Number", "C1234567")
+
+        with col2:
+            st.subheader("Agent/Representative Details")
+            agent_name = st.text_input("Agent's Name", "Citra Lestari")
+            agent_nik = st.text_input("Agent's NIK (ID Number)", "3171098765432100")
+            agent_address = st.text_area("Agent's Address", "Jl. Melati No. 8, Jakarta Selatan")
+            
+            st.subheader("Letter Details")
+            letter_location = st.text_input("Location of Letter Signing", "Jakarta")
+            letter_date = st.text_input("Date of Letter", "18th July 2024")
+
+        submit_passport_collection = st.form_submit_button("Generate Passport Collection PDF")
+
+    if submit_passport_collection:
+        payload = {
+            "applicant_name": applicant_name,
+            "applicant_nik": applicant_nik,
+            "applicant_address": applicant_address,
+            "agent_name": agent_name,
+            "agent_nik": agent_nik,
+            "agent_address": agent_address,
+            "passport_no": passport_no,
+            "letter_location": letter_location,
+            "letter_date": letter_date
+        }
+        generate_and_download("/generate/passport-collection", payload, "Passport_Collection_Letter.pdf")
+