update/dashboard

src/chatbot/app_interface.py

@@ -89,11 +89,6 @@ def update_form_information_handler(form_information):
     expense_justification_input = form_information.get("Expense Description", None)
     expense_justification_input = None if expense_justification_input == "None" else expense_justification_input
 
-    # form_amount_input = form_information.get("Total Payment Amount", None)
-    # if form_information is not None:
-    #     form_amount_input = float(form_amount_input)
-    # form_account_input = form_information.get("Payer's Name", None)
-    # seller_phone_number_input
     return seller_name_input, seller_address_input, seller_phone_number_input, buyer_name_input, buyer_address_input, transaction_date_input, total_payment_amount_input, expense_justification_input
 
 _chat_prefill = [
@@ -122,82 +117,87 @@ def chat_handler(message, history):
             raise e
     
     # Update form information after processing
-    form_information = get_form_info()
+    form_information = get_form_info()    
     update_form_information_handler(form_information)
     
-    return response
+    return response, form_information
 
 # Create the Gradio app with tabs
-with gr.Blocks() as app:
-    form_information = gr.State(form_info)
-    
-    # Reset button at the top
-    new_btn = gr.Button("เริ่มใหม่", variant="primary")
-    
-    with gr.Tabs():
-        # Chat tab using ChatInterface
-        with gr.Tab("แชท"):
-            chat_interface = gr.ChatInterface(
-                fn=chat_handler,
-                type="messages",
-                chatbot=gr.Chatbot(value=_chat_prefill, type="messages", label="กล่องข้อความ"),
-                multimodal=True,  # Enable image uploads
-                submit_btn="ส่งข้อความ",
-                autofocus=True,
-                examples=None
-            )
-
-        # Function to reset the chat and generate a new session ID
-        def reset_chat():
-            global CURRENT_SESSION_ID
-            CURRENT_SESSION_ID = generate_session_id()
-            logger.info(f"Chat reset with new session ID: {CURRENT_SESSION_ID}")
-            # Reset form info
-            form_info.clear()
-            # Return the initial chat message
-            return _chat_prefill
-
-        new_btn.click(fn=reset_chat, inputs=[], outputs=chat_interface.chatbot_value)
-
-        # Form tab (unchanged)
-        with gr.Tab("ฟอร์ม"):
-            gr.Markdown("**ชื่อผู้ขาย**")
-            seller_name_input = gr.Textbox(value = ast.literal_eval(form_info["Seller Name"]), label="", container=False)
-
-            gr.Markdown("**ที่อยู่ผู้ขาย**")
-            seller_address_input = gr.Textbox(value = ast.literal_eval(form_info["Seller Address"]), label="", container=False)
-
-            gr.Markdown("**เบอร์โทรศัพท์ผู้ขาย**")
-            seller_phone_number_input = gr.Textbox(value = ast.literal_eval(form_info["Seller Phone Number"]), label="", container=False)
-
-            gr.Markdown("**ชื่อผู้ซื้อ**")
-            buyer_name_input = gr.Textbox(value = ast.literal_eval(form_info["Buyer Name"]), label="", container=False)
-
-            gr.Markdown("**ที่อยู่ผู้ซื้อ**")
-            buyer_address_input = gr.Textbox(value = ast.literal_eval(form_info["Buyer Address"]), label="", container=False)
-
-            gr.Markdown("**วันที่ทำธุรกรรม**")
-            transaction_date_input = gr.Textbox(value = ast.literal_eval(form_info["Transaction Date"]), label="", container=False)
-
-            gr.Markdown("**จำนวนเงินที่ชำระทั้งหมด**")
-            with gr.Row():
-                total_payment_amount_input = gr.Number(value = ast.literal_eval(form_info['Total Payment Amount']), label="", container=False)
-                gr.Markdown("บาท")
-
-            gr.Markdown("**การพิสูจน์ค่าใช้จ่าย**")
-            expense_justification_input = gr.Textbox(value=ast.literal_eval(form_info["Expense Description"]), label="", container=False, lines=4)
-
-            submit_btn = gr.Button("Submit", variant="primary")
-
-            seller_name_input.change(update_seller_name_input, inputs=[seller_name_input], outputs=[form_information])
-            seller_address_input.change(update_seller_address_input, inputs=[seller_address_input], outputs=[form_information])
-            seller_phone_number_input.change(update_seller_phone_number_input, inputs=[seller_phone_number_input], outputs=[form_information])
-            buyer_name_input.change(update_buyer_name_input, inputs=[buyer_name_input], outputs=[form_information])
-            buyer_address_input.change(update_buyer_address_input, inputs=[buyer_address_input], outputs=[form_information])
-            transaction_date_input.change(update_transaction_date_input, inputs=[transaction_date_input], outputs=[form_information])
-            total_payment_amount_input.change(update_total_payment_amount_input, inputs=[total_payment_amount_input], outputs=[form_information])
-
-            form_information.change(update_form_information_handler, inputs=[form_information], outputs=[seller_name_input, seller_address_input, seller_phone_number_input, buyer_name_input, buyer_address_input, transaction_date_input, total_payment_amount_input, expense_justification_input])
+def create_expense_register_page():
+    with gr.Blocks() as page:
+        form_information = gr.State(form_info)
+        
+        # Reset button at the top
+        new_btn = gr.Button("เริ่มใหม่", variant="primary")
+        
+        with gr.Tabs():
+            # Chat tab using ChatInterface
+            with gr.Tab("แชท"):
+                chat_interface = gr.ChatInterface(
+                    fn=chat_handler,
+                    type="messages",
+                    chatbot=gr.Chatbot(value=_chat_prefill, type="messages", label="กล่องข้อความ"),
+                    multimodal=True,  # Enable image uploads
+                    submit_btn="ส่งข้อความ",
+                    autofocus=True,
+                    examples=None,
+                    additional_outputs=[form_information]
+                )
+
+            # Function to reset the chat and generate a new session ID
+            def reset_chat():
+                global CURRENT_SESSION_ID
+                CURRENT_SESSION_ID = generate_session_id()
+                logger.info(f"Chat reset with new session ID: {CURRENT_SESSION_ID}")
+                # Reset form info
+                form_info.clear()
+                # Return the initial chat message
+                return _chat_prefill
+
+            new_btn.click(fn=reset_chat, inputs=[], outputs=chat_interface.chatbot_value)
+
+            # Form tab (unchanged)
+            with gr.Tab("ฟอร์ม"):
+                gr.Markdown("**ชื่อผู้ขาย**")
+                seller_name_input = gr.Textbox(value = ast.literal_eval(form_info["Seller Name"]), label="", container=False)
+
+                gr.Markdown("**ที่อยู่ผู้ขาย**")
+                seller_address_input = gr.Textbox(value = ast.literal_eval(form_info["Seller Address"]), label="", container=False)
+
+                gr.Markdown("**เบอร์โทรศัพท์ผู้ขาย**")
+                seller_phone_number_input = gr.Textbox(value = ast.literal_eval(form_info["Seller Phone Number"]), label="", container=False)
+
+                gr.Markdown("**ชื่อผู้ซื้อ**")
+                buyer_name_input = gr.Textbox(value = ast.literal_eval(form_info["Buyer Name"]), label="", container=False)
+
+                gr.Markdown("**ที่อยู่ผู้ซื้อ**")
+                buyer_address_input = gr.Textbox(value = ast.literal_eval(form_info["Buyer Address"]), label="", container=False)
+
+                gr.Markdown("**วันที่ทำธุรกรรม**")
+                transaction_date_input = gr.DateTime(include_time=False, type="datetime", show_label=False)
+
+                gr.Markdown("**จำนวนเงินที่ชำระทั้งหมด**")
+                with gr.Row():
+                    total_payment_amount_input = gr.Number(value = ast.literal_eval(form_info['Total Payment Amount']), label="", container=False)
+                    gr.Markdown("บาท")
+
+                gr.Markdown("**การพิสูจน์ค่าใช้จ่าย**")
+                expense_justification_input = gr.Textbox(value=ast.literal_eval(form_info["Expense Description"]), label="", container=False, lines=4)
+
+                submit_btn = gr.Button("Submit", variant="primary")
+
+                seller_name_input.change(update_seller_name_input, inputs=[seller_name_input], outputs=[form_information])
+                seller_address_input.change(update_seller_address_input, inputs=[seller_address_input], outputs=[form_information])
+                seller_phone_number_input.change(update_seller_phone_number_input, inputs=[seller_phone_number_input], outputs=[form_information])
+                buyer_name_input.change(update_buyer_name_input, inputs=[buyer_name_input], outputs=[form_information])
+                buyer_address_input.change(update_buyer_address_input, inputs=[buyer_address_input], outputs=[form_information])
+                transaction_date_input.change(update_transaction_date_input, inputs=[transaction_date_input], outputs=[form_information])
+                total_payment_amount_input.change(update_total_payment_amount_input, inputs=[total_payment_amount_input], outputs=[form_information])
+
+                form_information.change(update_form_information_handler, inputs=[form_information], outputs=[seller_name_input, seller_address_input, seller_phone_number_input, buyer_name_input, buyer_address_input, transaction_date_input, total_payment_amount_input, expense_justification_input])
+
+    return page
 
 if __name__ == "__main__":
-    app.launch()
+    page = create_expense_register_page()
+    page.launch()

src/chatbot/dashboard/dashboard_page.py

@@ -16,7 +16,7 @@ from dashboard.visualize_component import (
     render_deliverable_summary_cards
 )
 
-DB_PATH = "database/hello_earth_data.db"
+DB_PATH = "../database/hello_earth_data_2.db"
 
 # ------------------------ Database Utilities ------------------------
 
@@ -46,7 +46,19 @@ def get_all_deliverable_budgets(project_id):
 
 def get_all_expenses(project_id):
     query = """
-        SELECT e.*
+        SELECT 
+            e.expense_id,
+            e.associated_deliverable_id,
+            d.title AS deliverable_title,
+            e.seller_name,
+            e.seller_address,
+            e.seller_phone_number,
+            e.buyer_name,
+            e.buyer_address,
+            e.transaction_date,
+            e.total_payment_amount,
+            e.expense_description,
+            e.status
         FROM Expense e
         JOIN Deliverable d ON e.associated_deliverable_id = d.deliverable_id
         WHERE d.project_id = ?
@@ -72,14 +84,18 @@ def filter_expenses(search_term, df):
     search_term = search_term.lower()
     mask = pd.Series(False, index=df.index)
     for col in [
-        'expense_id', 'associated_deliverable_id', 'seller_name',
-        'seller_address', 'seller_phone_number', 'buyer_name',
-        'buyer_address', 'transaction_date', 'total_payment_amount',
-        'expense_description', 'status'
+        'deliverable_title', 'seller_name', 'seller_address', 'seller_phone_number',
+        'buyer_name', 'buyer_address', 'transaction_date',
+        'total_payment_amount', 'expense_description', 'status'
     ]:
         mask |= df[col].astype(str).str.lower().str.contains(search_term)
     return df[mask]
 
+def update_project_detail(project_id):
+    project = get_project_data()
+    info = project.loc[project['project_id'] == project_id, 'detail_information'].values
+    return info[0] if len(info) > 0 else "No description available."
+
 # ------------------------ UI Setup ------------------------
 
 def create_dashboard_page():
@@ -102,30 +118,44 @@ def create_dashboard_page():
         # --- Page 2: Dashboard View ---
         with gr.Column(visible=False) as dashboard_page:
             dashboard_header = gr.Markdown("")
+            project_detail_md = gr.Markdown()
             back_button = gr.Button("⬅ Back to Projects")
 
             with gr.Column():
-                gr.Markdown("## Overall Project Financial Snapshot")
+                gr.Markdown("## 💰 Overall Project Financial Snapshot")
+                
+                gr.Markdown("### Budget Summary")
                 with gr.Row():
                     total_budget_md = gr.Markdown()
                     total_expense_md = gr.Markdown()
                     leftover_md = gr.Markdown()
+
+                gr.Markdown("### Utilization Gauge")
                 gauge_plot = gr.Plot()
 
-                gr.Markdown("## Deliverable-Level Financial Insights")
+                gr.Markdown("## 📦 Deliverable-Level Financial Insights")
+
+                gr.Markdown("### Budget vs Expense")
                 with gr.Row():
                     bar_chart_plot = gr.Plot()
                     pie_chart_plot = gr.Plot()
+
+                gr.Markdown("### Spending Over Time")
                 with gr.Row():
                     daily_plot = gr.Plot()
                     cum_plot = gr.Plot()
+
+                gr.Markdown("### Risk & Deliverables")
                 with gr.Row():
                     with gr.Column(scale=1):
                         risk_plot = gr.Plot()
                     with gr.Column(scale=2):
                         cards_html = gr.HTML()
+
+                gr.Markdown("### Deliverable Timeline (Gantt Chart)")
                 gantt_plot = gr.Plot()
 
+
                 gr.Markdown("## 💵 Expense Table")
                 search_box = gr.Textbox(placeholder="Search expenses", label="Search")
                 expense_table = gr.DataFrame()
@@ -154,11 +184,14 @@ def create_dashboard_page():
             else:
                 status, color = "✅ Budget on track", "green"
 
+            detail_text = update_project_detail(project_id)
+
             return [
                 project_id,
                 gr.update(visible=False),
                 gr.update(visible=True),
                 gr.update(value=f"# 📊 Financial Dashboard — {get_title_by_id(project_options, project_id)}"),
+                gr.update(value=detail_text),
                 gr.update(value=f"### Total Money Granted\n## {total_budget:,.0f}"),
                 gr.update(value=f"### Total Expense Spendings\n## {total_expense:,.0f}\n({(total_expense / total_budget * 100):.1f}% of budget)"),
                 gr.update(value=f"### Leftover Budget\n## {leftover:,.0f}\n<span style='color: {color};'>{status}</span>"),
@@ -170,7 +203,7 @@ def create_dashboard_page():
                 gr.update(value=generate_risk_level_distribution_pie_chart(deliverables)),
                 gr.update(value=generate_deliverable_timeline_gantt_chart(deliverables)),
                 gr.update(value=render_deliverable_summary_cards(deliverables)),
-                gr.update(value=expenses),
+                gr.update(value=expenses.drop(columns=["expense_id", "associated_deliverable_id"])),
                 expenses
             ]
 
@@ -187,6 +220,7 @@ def create_dashboard_page():
                 project_selector_page,
                 dashboard_page,
                 dashboard_header,
+                project_detail_md,
                 total_budget_md,
                 total_expense_md,
                 leftover_md,

src/chatbot/dashboard/visualize_component.py

@@ -1,7 +1,6 @@
 import plotly.graph_objects as go
 import plotly.express as px
 import pandas as pd 
-from datetime import datetime
 
 def generate_budget_utilization_gauge_chart(total_budget, total_expense):
     """Generate a gauge chart comparing budget vs. total expense."""
@@ -24,8 +23,8 @@ def generate_budget_utilization_gauge_chart(total_budget, total_expense):
         title={'text': "Total Expense", 'font': {'size': 24}},
         delta={
             'reference': total_budget,
-            'increasing': {'color': 'red'},
-            'decreasing': {'color': 'green'}
+            'increasing': {'color': 'red', 'symbol': "\u25B2"},
+            'decreasing': {'color': 'green', 'symbol': "\u25BC"}
         },
         gauge={
             'axis': {'range': [None, total_budget * 1.2], 'tickwidth': 1},
@@ -312,30 +311,6 @@ def generate_deliverable_timeline_gantt_chart(deliverable_df):
     # Reverse Y-axis to have earliest on top
     fig.update_yaxes(autorange='reversed')
 
-    # Add vertical "Today" line
-    today = datetime.today()
-
-    fig.add_shape(
-        type='line',
-        x0=today,
-        x1=today,
-        y0=0,
-        y1=1,
-        xref='x',
-        yref='paper',
-        line=dict(color='red', width=2, dash='dash')
-    )
-
-    fig.add_annotation(
-        x=today,
-        y=1.02,
-        xref='x',
-        yref='paper',
-        text='Today',
-        showarrow=False,
-        font=dict(color='red', size=12)
-    )
-
     # Layout customization
     fig.update_layout(
         paper_bgcolor='rgba(0,0,0,0)',
@@ -347,14 +322,13 @@ def generate_deliverable_timeline_gantt_chart(deliverable_df):
     return fig
 
 def render_deliverable_summary_cards(deliverable_df):
-    """Render a grid of HTML cards summarizing deliverables with risk level and status indicators."""
+    """Render HTML cards for deliverables with expandable risk rationale using <details>/<summary> (JS-free, Gradio-safe)."""
 
     def format_date(date_str):
         if pd.isna(date_str):
             return "-"
         return pd.to_datetime(date_str).strftime("%d %b %Y")
 
-    # Define color mappings
     risk_level_colors = {
         "green": "#28a745",
         "yellow": "#ffc107",
@@ -369,7 +343,6 @@ def render_deliverable_summary_cards(deliverable_df):
         "approved": "#28a745"
     }
 
-    # Start HTML grid
     cards_html = """
     <div style='display: grid; grid-template-columns: repeat(auto-fill, minmax(300px, 1fr)); gap: 20px;'>
     """
@@ -379,6 +352,7 @@ def render_deliverable_summary_cards(deliverable_df):
         deliverable_id = row.get('deliverable_id', '-')
         status = str(row.get('status', 'N/A')).lower()
         risk_level = str(row.get('risk_level', 'unknown')).lower()
+        rationale = row.get('risk_level_rationale', 'No rationale provided')
 
         status_color = status_colors.get(status, "#6c757d")
         risk_color = risk_level_colors.get(risk_level, "#6c757d")
@@ -387,7 +361,7 @@ def render_deliverable_summary_cards(deliverable_df):
         end_date = format_date(row.get('end_date'))
 
         cards_html += f"""
-        <div style='border: 1px solid #dee2e6; border-radius: 10px; padding: 15px; background-color: #ffffff;'>
+        <div style='border: 1px solid #dee2e6; border-radius: 10px; padding: 15px; background-color: #ffffff; box-shadow: 0 2px 6px rgba(0,0,0,0.05);'>
             <div style='font-weight: bold; font-size: 1.1em; margin-bottom: 5px;'>
                 {title}
                 <div style='font-size: 0.85em; color: #6c757d;'>ID: {deliverable_id}</div>
@@ -404,6 +378,12 @@ def render_deliverable_summary_cards(deliverable_df):
                 <strong>Start:</strong> {start_date}<br>
                 <strong>End:</strong> {end_date}
             </div>
+            <details style='margin-top: 12px; font-size: 0.85em; color: #495057;'>
+                <summary style='cursor: pointer; color: #007bff;'>Show Risk Rationale</summary>
+                <div style='margin-top: 6px; padding: 8px; background-color: #f8f9fa; border-radius: 5px; border: 1px solid #dee2e6;'>
+                    <strong>Risk Rationale:</strong><br>{rationale}
+                </div>
+            </details>
         </div>
         """
 

src/chatbot/database/Deliverable.csv

@@ -1,9 +0,0 @@
-deliverable_id,project_id,title,status,risk_level,risk_level_rationale,start_date,end_date
-14eff22b-ca43-45d3-8e29-37c8eb8bcaba,626e47da-76ae-4650-9d78-31072c1b5b0d,Area Assessment,done,green,No environmental threats detected.,2023-01-05,2023-03-01
-4fba146b-b655-4cb5-8760-245b3cc1cff9,626e47da-76ae-4650-9d78-31072c1b5b0d,Planting Phase,ongoing,yellow,Tide schedule interference.,2023-03-15,2023-08-30
-c0819e22-02bf-4dd9-9936-710c40f26701,626e47da-76ae-4650-9d78-31072c1b5b0d,Monitoring Phase,ongoing,green,Stable growth rates observed.,2023-09-01,2023-11-01
-51ee4582-bd59-4b0e-91f8-c3288ccff1c5,626e47da-76ae-4650-9d78-31072c1b5b0d,Community Education,ongoing,yellow,Low turnout in workshops.,2023-09-15,2023-12-15
-40b469db-7b99-4002-89a5-d5622558dd88,f56b2354-ac70-4682-82f2-727ce13f4b71,Community Engagement,done,green,High public interest and participation.,2023-02-05,2023-04-01
-114583cd-2522-4721-855d-e0ad7ffd1b05,f56b2354-ac70-4682-82f2-727ce13f4b71,Planting Execution,ongoing,red,Insufficient volunteer workforce.,2023-04-10,2023-10-15
-3cddb3f6-6950-4f83-9142-b69f7352fd51,00cfa2f7-acb1-40aa-a420-d6c127c38c64,Equipment Procurement,done,green,Procurement completed on time.,2023-03-05,2023-04-01
-d8c0554d-f4f2-4fa7-96df-e3d4b45bbd40,00cfa2f7-acb1-40aa-a420-d6c127c38c64,Volunteer Training,ongoing,yellow,Training attendance dropped by 10%.,2023-04-10,2023-06-30

src/chatbot/database/Deliverable_Budget.csv

@@ -1,6 +0,0 @@
-id,deliverable_id,wage,materials,tools_equipment,services,misc
-02ad1d05-6444-4007-99bf-03acd46338ff,14eff22b-ca43-45d3-8e29-37c8eb8bcaba,1000.0,1500.0,500.0,800.0,100.0
-80e373d0-edb9-45bd-a14e-54e8e8acf57f,4fba146b-b655-4cb5-8760-245b3cc1cff9,1200.0,2000.0,700.0,1000.0,150.0
-dbe0fd74-ca7e-4792-b49f-0812dba78778,c0819e22-02bf-4dd9-9936-710c40f26701,1100.0,800.0,400.0,600.0,90.0
-ff2964e9-d8e6-46c7-b604-246add155edc,51ee4582-bd59-4b0e-91f8-c3288ccff1c5,950.0,500.0,300.0,750.0,120.0
-416e697e-6e28-4fc8-81bf-496731d8486a,40b469db-7b99-4002-89a5-d5622558dd88,1500.0,1000.0,300.0,500.0,50.0

src/chatbot/database/Expense.csv

@@ -1,7 +0,0 @@
-expense_id,associated_deliverable_id,seller_name,seller_address,seller_phone_number,buyer_name,buyer_address,transaction_date,total_payment_amount,expense_description,status
-c3fac245-20ef-4ab9-8a02-afe9e2f59952,14eff22b-ca43-45d3-8e29-37c8eb8bcaba,EcoTools Ltd.,101 Earth Ave,0811111111,Mangrove Org,900 Forest Blvd,2023-01-20,1800.0,Survey equipment rental,approved
-75135cca-df34-4f24-bed9-90ac1456c737,4fba146b-b655-4cb5-8760-245b3cc1cff9,Green Nursery Supplies,202 Plant Rd,0822222222,Mangrove Org,900 Forest Blvd,2023-04-10,2200.0,Mangrove saplings and planting tools,approved
-7dda7444-4762-40d3-ba00-17fd1e297ab0,4fba146b-b655-4cb5-8760-245b3cc1cff9,TideLogistics,303 Coastal Lane,0833333333,Mangrove Org,900 Forest Blvd,2023-06-05,1300.0,Transport service for volunteers and gear,pending
-81590aa0-fdb6-4de3-b756-39ee8b30a5e1,c0819e22-02bf-4dd9-9936-710c40f26701,DroneVision Inc.,404 Sky Blvd,0844444444,Mangrove Org,900 Forest Blvd,2023-09-10,1600.0,Aerial monitoring drone rental,approved
-6660e3a4-3329-4105-b411-551fa09fc3d3,51ee4582-bd59-4b0e-91f8-c3288ccff1c5,EduLeaf,505 Learning St,0855555555,Mangrove Org,900 Forest Blvd,2023-10-01,900.0,Educational materials and workshop kits,approved
-69aa3f56-167b-49ba-8039-d72ff84390bc,51ee4582-bd59-4b0e-91f8-c3288ccff1c5,CommVoice,606 Broadcast Ave,0866666666,Mangrove Org,900 Forest Blvd,2023-11-05,450.0,Public awareness campaign ads,pending

src/chatbot/database/Project.csv

@@ -1,4 +0,0 @@
-project_id,title,status,detail_information,start_date,end_date
-626e47da-76ae-4650-9d78-31072c1b5b0d,Mangrove Restoration,started,Restoring coastal ecosystems using mangrove plantations.,2023-01-01,2023-12-31
-f56b2354-ac70-4682-82f2-727ce13f4b71,Urban Tree Planting,started,Planting trees across the city for shade and air quality.,2023-02-01,2023-11-30
-00cfa2f7-acb1-40aa-a420-d6c127c38c64,River Clean-up Campaign,started,Mobilizing volunteers to clean plastic from major rivers.,2023-03-01,2023-09-30

src/chatbot/database/create_sqlite_db.py

@@ -1,64 +0,0 @@
-import sqlite3
-
-conn = sqlite3.connect('hello_earth_data.db')
-cursor = conn.cursor()
-
-cursor.execute('''
-CREATE TABLE IF NOT EXISTS Project (
-    project_id TEXT PRIMARY KEY,
-    title TEXT,
-    status TEXT,
-    detail_information TEXT,
-    start_date DATETIME,
-    end_date DATETIME
-)
-''')
-
-cursor.execute('''
-CREATE TABLE IF NOT EXISTS Deliverable (
-    deliverable_id TEXT PRIMARY KEY,
-    project_id TEXT,
-    title TEXT,
-    status TEXT CHECK(status IN ('done', 'ongoing')),
-    risk_level TEXT CHECK(risk_level IN ('green', 'yellow', 'red')),
-    risk_level_rationale TEXT,
-    start_date DATETIME,
-    end_date DATETIME,
-    FOREIGN KEY (project_id) REFERENCES Project(project_id)
-)
-''')
-
-cursor.execute('''
-CREATE TABLE IF NOT EXISTS Expense (
-    expense_id TEXT PRIMARY KEY,
-    associated_deliverable_id TEXT,
-    seller_name TEXT,
-    seller_address TEXT,
-    seller_phone_number TEXT,
-    buyer_name TEXT,
-    buyer_address TEXT,
-    transaction_date DATETIME,
-    total_payment_amount REAL,
-    expense_description TEXT,
-    status TEXT,
-    FOREIGN KEY (associated_deliverable_id) REFERENCES Deliverable(deliverable_id)
-)
-''')
-
-cursor.execute('''
-CREATE TABLE IF NOT EXISTS Deliverable_Budget (
-    id TEXT PRIMARY KEY,
-    deliverable_id TEXT,
-    wage REAL,
-    materials REAL,
-    tools_equipment REAL,
-    services REAL,
-    misc REAL,
-    FOREIGN KEY (deliverable_id) REFERENCES Deliverable(deliverable_id)
-)
-''')
-
-conn.commit()
-conn.close()
-
-print("SQLite database created with the specified schema.")

src/chatbot/database/export_data.py

@@ -1,22 +0,0 @@
-import sqlite3
-import pandas as pd
-
-def export_all_tables_to_csv(db_path='hello_earth_data.db', output_dir='.'):
-    conn = sqlite3.connect(db_path)
-    cursor = conn.cursor()
-
-    # Get list of all tables
-    cursor.execute("SELECT name FROM sqlite_master WHERE type='table';")
-    tables = [row[0] for row in cursor.fetchall()]
-
-    # Export each table
-    for table in tables:
-        df = pd.read_sql_query(f"SELECT * FROM {table}", conn)
-        output_path = f"{output_dir}/{table}.csv"
-        df.to_csv(output_path, index=False)
-        print(f"✅ Exported {table} to {output_path}")
-
-    conn.close()
-
-if __name__ == '__main__':
-    export_all_tables_to_csv()

src/chatbot/database/mockup_data.py

@@ -1,317 +0,0 @@
-import sqlite3
-import uuid
-
-def generate_uuid():
-    return str(uuid.uuid4())
-
-def insert_mock_data():
-    conn = sqlite3.connect('hello_earth_data.db')
-    cursor = conn.cursor()
-
-    mock_data = []
-
-    # Project 1
-    project_1_id = generate_uuid()
-    deliverable_1_1_id = generate_uuid()
-    deliverable_1_2_id = generate_uuid()
-    deliverable_1_3_id = generate_uuid()  # New Deliverable
-    deliverable_1_4_id = generate_uuid()  # New Deliverable
-    mock_data.append({
-        "project": {
-            "project_id": project_1_id,
-            "title": "Mangrove Restoration",
-            "status": "started",
-            "detail_information": "Restoring coastal ecosystems using mangrove plantations.",
-            "start_date": "2023-01-01",
-            "end_date": "2023-12-31"
-        },
-        "deliverables": [
-            {
-                "deliverable_id": deliverable_1_1_id,
-                "title": "Area Assessment",
-                "status": "done",
-                "risk_level": "green",
-                "risk_level_rationale": "No environmental threats detected.",
-                "start_date": "2023-01-05",
-                "end_date": "2023-03-01"
-            },
-            {
-                "deliverable_id": deliverable_1_2_id,
-                "title": "Planting Phase",
-                "status": "ongoing",
-                "risk_level": "yellow",
-                "risk_level_rationale": "Tide schedule interference.",
-                "start_date": "2023-03-15",
-                "end_date": "2023-08-30"
-            },
-            {
-                "deliverable_id": deliverable_1_3_id,
-                "title": "Monitoring Phase",
-                "status": "ongoing",
-                "risk_level": "green",
-                "risk_level_rationale": "Stable growth rates observed.",
-                "start_date": "2023-09-01",
-                "end_date": "2023-11-01"
-            },
-            {
-                "deliverable_id": deliverable_1_4_id,
-                "title": "Community Education",
-                "status": "ongoing",
-                "risk_level": "yellow",
-                "risk_level_rationale": "Low turnout in workshops.",
-                "start_date": "2023-09-15",
-                "end_date": "2023-12-15"
-            }
-        ],
-        "budgets": [
-            {
-                "id": generate_uuid(),
-                "deliverable_id": deliverable_1_1_id,
-                "wage": 1000.0,
-                "materials": 1500.0,
-                "tools_equipment": 500.0,
-                "services": 800.0,
-                "misc": 100.0
-            },
-            {
-                "id": generate_uuid(),
-                "deliverable_id": deliverable_1_2_id,
-                "wage": 1200.0,
-                "materials": 2000.0,
-                "tools_equipment": 700.0,
-                "services": 1000.0,
-                "misc": 150.0
-            },
-            {
-                "id": generate_uuid(),
-                "deliverable_id": deliverable_1_3_id,
-                "wage": 1100.0,
-                "materials": 800.0,
-                "tools_equipment": 400.0,
-                "services": 600.0,
-                "misc": 90.0
-            },
-            {
-                "id": generate_uuid(),
-                "deliverable_id": deliverable_1_4_id,
-                "wage": 950.0,
-                "materials": 500.0,
-                "tools_equipment": 300.0,
-                "services": 750.0,
-                "misc": 120.0
-            }
-        ],
-        "expenses": [
-            {
-                "expense_id": generate_uuid(),
-                "associated_deliverable_id": deliverable_1_1_id,
-                "seller_name": "EcoTools Ltd.",
-                "seller_address": "101 Earth Ave",
-                "seller_phone_number": "0811111111",
-                "buyer_name": "Mangrove Org",
-                "buyer_address": "900 Forest Blvd",
-                "transaction_date": "2023-01-20",
-                "total_payment_amount": 1800.0,
-                "expense_description": "Survey equipment rental",
-                "status": "approved"
-            },
-            {
-                "expense_id": generate_uuid(),
-                "associated_deliverable_id": deliverable_1_2_id,
-                "seller_name": "Green Nursery Supplies",
-                "seller_address": "202 Plant Rd",
-                "seller_phone_number": "0822222222",
-                "buyer_name": "Mangrove Org",
-                "buyer_address": "900 Forest Blvd",
-                "transaction_date": "2023-04-10",
-                "total_payment_amount": 2200.0,
-                "expense_description": "Mangrove saplings and planting tools",
-                "status": "approved"
-            },
-            {
-                "expense_id": generate_uuid(),
-                "associated_deliverable_id": deliverable_1_2_id,
-                "seller_name": "TideLogistics",
-                "seller_address": "303 Coastal Lane",
-                "seller_phone_number": "0833333333",
-                "buyer_name": "Mangrove Org",
-                "buyer_address": "900 Forest Blvd",
-                "transaction_date": "2023-06-05",
-                "total_payment_amount": 1300.0,
-                "expense_description": "Transport service for volunteers and gear",
-                "status": "pending"
-            },
-            {
-                "expense_id": generate_uuid(),
-                "associated_deliverable_id": deliverable_1_3_id,
-                "seller_name": "DroneVision Inc.",
-                "seller_address": "404 Sky Blvd",
-                "seller_phone_number": "0844444444",
-                "buyer_name": "Mangrove Org",
-                "buyer_address": "900 Forest Blvd",
-                "transaction_date": "2023-09-10",
-                "total_payment_amount": 1600.0,
-                "expense_description": "Aerial monitoring drone rental",
-                "status": "approved"
-            },
-            {
-                "expense_id": generate_uuid(),
-                "associated_deliverable_id": deliverable_1_4_id,
-                "seller_name": "EduLeaf",
-                "seller_address": "505 Learning St",
-                "seller_phone_number": "0855555555",
-                "buyer_name": "Mangrove Org",
-                "buyer_address": "900 Forest Blvd",
-                "transaction_date": "2023-10-01",
-                "total_payment_amount": 900.0,
-                "expense_description": "Educational materials and workshop kits",
-                "status": "approved"
-            },
-            {
-                "expense_id": generate_uuid(),
-                "associated_deliverable_id": deliverable_1_4_id,
-                "seller_name": "CommVoice",
-                "seller_address": "606 Broadcast Ave",
-                "seller_phone_number": "0866666666",
-                "buyer_name": "Mangrove Org",
-                "buyer_address": "900 Forest Blvd",
-                "transaction_date": "2023-11-05",
-                "total_payment_amount": 450.0,
-                "expense_description": "Public awareness campaign ads",
-                "status": "pending"
-            }
-        ]
-    })
-
-
-    # Project 2
-    project_2_id = generate_uuid()
-    deliverable_2_1_id = generate_uuid()
-    deliverable_2_2_id = generate_uuid()
-    mock_data.append({
-        "project": {
-            "project_id": project_2_id,
-            "title": "Urban Tree Planting",
-            "status": "started",
-            "detail_information": "Planting trees across the city for shade and air quality.",
-            "start_date": "2023-02-01",
-            "end_date": "2023-11-30"
-        },
-        "deliverables": [
-            {
-                "deliverable_id": deliverable_2_1_id,
-                "title": "Community Engagement",
-                "status": "done",
-                "risk_level": "green",
-                "risk_level_rationale": "High public interest and participation.",
-                "start_date": "2023-02-05",
-                "end_date": "2023-04-01"
-            },
-            {
-                "deliverable_id": deliverable_2_2_id,
-                "title": "Planting Execution",
-                "status": "ongoing",
-                "risk_level": "red",
-                "risk_level_rationale": "Insufficient volunteer workforce.",
-                "start_date": "2023-04-10",
-                "end_date": "2023-10-15"
-            }
-        ],
-        "budgets": [
-            {
-                "id": generate_uuid(),
-                "deliverable_id": deliverable_2_1_id,
-                "wage": 1500.0,
-                "materials": 1000.0,
-                "tools_equipment": 300.0,
-                "services": 500.0,
-                "misc": 50.0
-            }
-        ],
-        "expenses": []
-    })
-
-    # Project 3
-    project_3_id = generate_uuid()
-    deliverable_3_1_id = generate_uuid()
-    deliverable_3_2_id = generate_uuid()
-    mock_data.append({
-        "project": {
-            "project_id": project_3_id,
-            "title": "River Clean-up Campaign",
-            "status": "started",
-            "detail_information": "Mobilizing volunteers to clean plastic from major rivers.",
-            "start_date": "2023-03-01",
-            "end_date": "2023-09-30"
-        },
-        "deliverables": [
-            {
-                "deliverable_id": deliverable_3_1_id,
-                "title": "Equipment Procurement",
-                "status": "done",
-                "risk_level": "green",
-                "risk_level_rationale": "Procurement completed on time.",
-                "start_date": "2023-03-05",
-                "end_date": "2023-04-01"
-            },
-            {
-                "deliverable_id": deliverable_3_2_id,
-                "title": "Volunteer Training",
-                "status": "ongoing",
-                "risk_level": "yellow",
-                "risk_level_rationale": "Training attendance dropped by 10%.",
-                "start_date": "2023-04-10",
-                "end_date": "2023-06-30"
-            }
-        ],
-        "budgets": [],
-        "expenses": []
-    })
-
-    # === INSERT DATA INTO DB ===
-    for item in mock_data:
-        project = item["project"]
-        cursor.execute('''
-            INSERT INTO Project (project_id, title, status, detail_information, start_date, end_date)
-            VALUES (?, ?, ?, ?, ?, ?)
-        ''', (
-            project["project_id"], project["title"], project["status"],
-            project["detail_information"], project["start_date"], project["end_date"]
-        ))
-
-        for d in item.get("deliverables", []):
-            cursor.execute('''
-                INSERT INTO Deliverable (deliverable_id, project_id, title, status, risk_level,
-                                         risk_level_rationale, start_date, end_date)
-                VALUES (?, ?, ?, ?, ?, ?, ?, ?)
-            ''', (
-                d["deliverable_id"], project["project_id"], d["title"], d["status"],
-                d["risk_level"], d["risk_level_rationale"], d["start_date"], d["end_date"]
-            ))
-
-        for b in item.get("budgets", []):
-            cursor.execute('''
-                INSERT INTO Deliverable_Budget (id, deliverable_id, wage, materials, tools_equipment, services, misc)
-                VALUES (?, ?, ?, ?, ?, ?, ?)
-            ''', (
-                b["id"], b["deliverable_id"], b["wage"], b["materials"],
-                b["tools_equipment"], b["services"], b["misc"]
-            ))
-
-        for e in item.get("expenses", []):
-            cursor.execute('''
-                INSERT INTO Expense (expense_id, associated_deliverable_id, seller_name, seller_address, seller_phone_number,
-                                     buyer_name, buyer_address, transaction_date, total_payment_amount, expense_description, status)
-                VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
-            ''', (
-                e["expense_id"], e["associated_deliverable_id"], e["seller_name"], e["seller_address"],
-                e["seller_phone_number"], e["buyer_name"], e["buyer_address"],
-                e["transaction_date"], e["total_payment_amount"], e["expense_description"], e["status"]
-            ))
-
-    conn.commit()
-    conn.close()
-    print("✅ Multiple projects inserted with UUIDs.")
-
-if __name__ == '__main__':
-    insert_mock_data()

src/chatbot/kie.py

@@ -78,7 +78,10 @@ def extract_form_information(client, receipt_text, max_retries=2):
             "Seller Phone Number": {"type": "string"},
             "Buyer Name": {"type": "string"},
             "Buyer Address": {"type": "string"},
-            "Transaction Date": {"type": "string"},
+            "Transaction Date": {
+                "type": "string",
+                "description": "Date of transaction in ISO 8601 format (YYYY-MM-DD)"
+            },
 
             # "Payment Details Table": {
             #     "type": "object",

src/chatbot/llm_engine.py

@@ -26,9 +26,8 @@ def generate_expense_info_feedback(acceptance_criteria: dict, form_info: dict) -
     Generate feedback using OpenAI Chat Completion based on form_info.
     """
     current_date = datetime.now()
-    buddhist_year = current_date.year + 543  # Convert to Buddhist year
-    formatted_date = current_date.strftime(f"%d %B {buddhist_year}")  # Format with Buddhist year
-    print("current date (Buddhist year): {}".format(formatted_date))
+    formatted_date = current_date.strftime(f"%d %B {current_date.year}")  # Format with Buddhist year
+    print("current date: {}".format(formatted_date))
 
     response = client.responses.create(
         model="gpt-4.1-mini",

src/chatbot/prompts/agent_prompts.py

@@ -15,6 +15,7 @@ Associated Deliverable: The deliverable associated with the payment.
 Expense Description: The description of the expense as it pertains to the project.
 
 Users cannot add new fields to the form, but they can edit the existing fields.
+When inputting the 'Transaction Date', automatically convert the date to ISO 8601 format (YYYY-MM-DD).
 Each time the form is revised, feedback will be provided, and your job to summarize current form information and convey the feedback to the user.
 Do not stray from the feedback provided. 
 Do not mention the correct fields to the user, focus on the invalid one shown in the provided feedback.

src/chatbot/prompts/kie_prompts.py

@@ -1,5 +1,6 @@
 kie_prompt = """
-You are an AI model tasked with extracting key information from a Thai receipt document for payment confirmation. The image of the receipt will be provided as input. Your goal is to generate a JSON object containing the following keys:
+You are an AI model tasked with extracting key information from a Thai receipt document for payment confirmation. 
+The image of the receipt will be provided as input. Your goal is to generate a JSON object containing the following keys:
 
 Seller Name: The name of the person or entity making the sale.
 Seller Address: The address of the seller.

src/poetry.lock

@@ -201,104 +201,104 @@ pycparser = "*"
 
 [[package]]
 name = "charset-normalizer"
-version = "3.4.1"
+version = "3.4.2"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
-    {file = "charset_normalizer-3.4.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:91b36a978b5ae0ee86c394f5a54d6ef44db1de0815eb43de826d41d21e4af3de"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7461baadb4dc00fd9e0acbe254e3d7d2112e7f92ced2adc96e54ef6501c5f176"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e218488cd232553829be0664c2292d3af2eeeb94b32bea483cf79ac6a694e037"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:80ed5e856eb7f30115aaf94e4a08114ccc8813e6ed1b5efa74f9f82e8509858f"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b010a7a4fd316c3c484d482922d13044979e78d1861f0e0650423144c616a46a"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4532bff1b8421fd0a320463030c7520f56a79c9024a4e88f01c537316019005a"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d973f03c0cb71c5ed99037b870f2be986c3c05e63622c017ea9816881d2dd247"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:3a3bd0dcd373514dcec91c411ddb9632c0d7d92aed7093b8c3bbb6d69ca74408"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:d9c3cdf5390dcd29aa8056d13e8e99526cda0305acc038b96b30352aff5ff2bb"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:2bdfe3ac2e1bbe5b59a1a63721eb3b95fc9b6817ae4a46debbb4e11f6232428d"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:eab677309cdb30d047996b36d34caeda1dc91149e4fdca0b1a039b3f79d9a807"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-win32.whl", hash = "sha256:c0429126cf75e16c4f0ad00ee0eae4242dc652290f940152ca8c75c3a4b6ee8f"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-win_amd64.whl", hash = "sha256:9f0b8b1c6d84c8034a44893aba5e767bf9c7a211e313a9605d9c617d7083829f"},
-    {file = "charset_normalizer-3.4.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:8bfa33f4f2672964266e940dd22a195989ba31669bd84629f05fab3ef4e2d125"},
-    {file = "charset_normalizer-3.4.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:28bf57629c75e810b6ae989f03c0828d64d6b26a5e205535585f96093e405ed1"},
-    {file = "charset_normalizer-3.4.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f08ff5e948271dc7e18a35641d2f11a4cd8dfd5634f55228b691e62b37125eb3"},
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 ]
 
 [[package]]
@@ -475,14 +475,14 @@ tqdm = ["tqdm"]
 
 [[package]]
 name = "gradio"
-version = "5.28.0"
+version = "5.29.0"
 description = "Python library for easily interacting with trained machine learning models"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "gradio-5.28.0-py3-none-any.whl", hash = "sha256:f4c56bfbf6d1343728de4f6104e559ec26dbea3771efbba0cd8e4f0046e864db"},
-    {file = "gradio-5.28.0.tar.gz", hash = "sha256:31f259f35beba6b58ef0b942d44891f9f8e05e466778cb1c830b75fe75ac5b65"},
+    {file = "gradio-5.29.0-py3-none-any.whl", hash = "sha256:6b58321c3b2d596a701e9b1660334772a160262e4c67f18848bd54b6c0db7d89"},
+    {file = "gradio-5.29.0.tar.gz", hash = "sha256:56fdd8b7cb31de8e4c382677560ef8a79f4ae0c3fbb139341bce052aab728064"},
 ]
 
 [package.dependencies]
@@ -520,6 +520,24 @@ uvicorn = {version = ">=0.14.0", markers = "sys_platform != \"emscripten\""}
 mcp = ["mcp (>=1.6.0,<2.0.0)", "pydantic (>=2.11) ; sys_platform != \"emscripten\""]
 oauth = ["authlib", "itsdangerous"]
 
+[[package]]
+name = "gradio-calendar"
+version = "0.0.6"
+description = "Gradio component for selecting dates with a calendar 📆"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "gradio_calendar-0.0.6-py3-none-any.whl", hash = "sha256:2431b84ee2228be96770e907a478a4724cc36cc970a10e2b4209c85aa2373e2c"},
+    {file = "gradio_calendar-0.0.6.tar.gz", hash = "sha256:728addfc07c350d46b69459447eb1e390d87ada0ddaed3457bd78da480eca2ec"},
+]
+
+[package.dependencies]
+gradio = ">=4.0,<6.0"
+
+[package.extras]
+dev = ["build", "twine"]
+
 [[package]]
 name = "gradio-client"
 version = "1.10.0"
@@ -935,18 +953,18 @@ files = [
 
 [[package]]
 name = "langchain"
-version = "0.3.24"
+version = "0.3.25"
 description = "Building applications with LLMs through composability"
 optional = false
-python-versions = "<4.0,>=3.9"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "langchain-0.3.24-py3-none-any.whl", hash = "sha256:596c5444716644ddd0cd819fb2bc9d0fd4221503b219fdfb5016edcfaa7da8ef"},
-    {file = "langchain-0.3.24.tar.gz", hash = "sha256:caf1bacdabbea429bc79b58b118c06c3386107d92812e15922072b91745f070f"},
+    {file = "langchain-0.3.25-py3-none-any.whl", hash = "sha256:931f7d2d1eaf182f9f41c5e3272859cfe7f94fc1f7cef6b3e5a46024b4884c21"},
+    {file = "langchain-0.3.25.tar.gz", hash = "sha256:a1d72aa39546a23db08492d7228464af35c9ee83379945535ceef877340d2a3a"},
 ]
 
 [package.dependencies]
-langchain-core = ">=0.3.55,<1.0.0"
+langchain-core = ">=0.3.58,<1.0.0"
 langchain-text-splitters = ">=0.3.8,<1.0.0"
 langsmith = ">=0.1.17,<0.4"
 pydantic = ">=2.7.4,<3.0.0"
@@ -975,14 +993,14 @@ xai = ["langchain-xai"]
 
 [[package]]
 name = "langchain-core"
-version = "0.3.56"
+version = "0.3.58"
 description = "Building applications with LLMs through composability"
 optional = false
-python-versions = "<4.0,>=3.9"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "langchain_core-0.3.56-py3-none-any.whl", hash = "sha256:a20c6aca0fa0da265d96d3b14a5a01828ac5d2d9d27516434873d76f2d4839ed"},
-    {file = "langchain_core-0.3.56.tar.gz", hash = "sha256:de896585bc56e12652327dcd195227c3739a07e86e587c91a07101e0df11dffe"},
+    {file = "langchain_core-0.3.58-py3-none-any.whl", hash = "sha256:266f90d2a079fe9510190ad3be88bd993baad43e6cee0f822a883767a4bfdd5b"},
+    {file = "langchain_core-0.3.58.tar.gz", hash = "sha256:6ee2282b02fa65bf4ee1afa869d431505536757ff2f1f9f0b432d8ca755d66c6"},
 ]
 
 [package.dependencies]
@@ -996,18 +1014,18 @@ typing-extensions = ">=4.7"
 
 [[package]]
 name = "langchain-openai"
-version = "0.3.14"
+version = "0.3.16"
 description = "An integration package connecting OpenAI and LangChain"
 optional = false
-python-versions = "<4.0,>=3.9"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "langchain_openai-0.3.14-py3-none-any.whl", hash = "sha256:b8e648d2d7678a5540818199d141ff727c6f1514294b3e1e999a95357c9d66a0"},
-    {file = "langchain_openai-0.3.14.tar.gz", hash = "sha256:0662db78620c2e5c3ccfc1c36dc959c0ddc80e6bdf7ef81632cbf4b2cc9b9461"},
+    {file = "langchain_openai-0.3.16-py3-none-any.whl", hash = "sha256:eae74a6758d38a26159c5fde5abf8ef313e6400efb01a08f12dd7410c9f4fd0f"},
+    {file = "langchain_openai-0.3.16.tar.gz", hash = "sha256:4e423e39d072f1432adc9430f2905fe635cc019f01ad1bdffa5ed8d0dda32149"},
 ]
 
 [package.dependencies]
-langchain-core = ">=0.3.53,<1.0.0"
+langchain-core = ">=0.3.58,<1.0.0"
 openai = ">=1.68.2,<2.0.0"
 tiktoken = ">=0.7,<1"
 
@@ -1096,14 +1114,14 @@ orjson = ">=3.10.1"
 
 [[package]]
 name = "langsmith"
-version = "0.3.39"
+version = "0.3.42"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "langsmith-0.3.39-py3-none-any.whl", hash = "sha256:0c2af42e943e112bd0a1bd7452922141945b71f08df32cc5d6faa637100bc5e3"},
-    {file = "langsmith-0.3.39.tar.gz", hash = "sha256:1624a70efe1c9378ed0802618e9f7cc14e45d50ec4a9b3af45137fa27ad95690"},
+    {file = "langsmith-0.3.42-py3-none-any.whl", hash = "sha256:18114327f3364385dae4026ebfd57d1c1cb46d8f80931098f0f10abe533475ff"},
+    {file = "langsmith-0.3.42.tar.gz", hash = "sha256:2b5cbc450ab808b992362aac6943bb1d285579aa68a3a8be901d30a393458f25"},
 ]
 
 [package.dependencies]
@@ -1121,6 +1139,22 @@ openai-agents = ["openai-agents (>=0.0.3,<0.1)"]
 otel = ["opentelemetry-api (>=1.30.0,<2.0.0)", "opentelemetry-exporter-otlp-proto-http (>=1.30.0,<2.0.0)", "opentelemetry-sdk (>=1.30.0,<2.0.0)"]
 pytest = ["pytest (>=7.0.0)", "rich (>=13.9.4,<14.0.0)"]
 
+[[package]]
+name = "markdown"
+version = "3.8"
+description = "Python implementation of John Gruber's Markdown."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
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+    {file = "markdown-3.8.tar.gz", hash = "sha256:7df81e63f0df5c4b24b7d156eb81e4690595239b7d70937d0409f1b0de319c6f"},
+]
+
+[package.extras]
+docs = ["mdx_gh_links (>=0.2)", "mkdocs (>=1.6)", "mkdocs-gen-files", "mkdocs-literate-nav", "mkdocs-nature (>=0.6)", "mkdocs-section-index", "mkdocstrings[python]"]
+testing = ["coverage", "pyyaml"]
+
 [[package]]
 name = "markdown-it-py"
 version = "3.0.0"
@@ -1246,6 +1280,31 @@ files = [
     {file = "mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"},
 ]
 
+[[package]]
+name = "narwhals"
+version = "1.39.1"
+description = "Extremely lightweight compatibility layer between dataframe libraries"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
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+    {file = "narwhals-1.39.1.tar.gz", hash = "sha256:cf15389e6f8c5321e8cd0ca8b5bace3b1aea5f5622fa59dfd64821998741d836"},
+]
+
+[package.extras]
+cudf = ["cudf (>=24.10.0)"]
+dask = ["dask[dataframe] (>=2024.8)"]
+duckdb = ["duckdb (>=1.0)"]
+ibis = ["ibis-framework (>=6.0.0)", "packaging", "pyarrow-hotfix", "rich"]
+modin = ["modin"]
+pandas = ["pandas (>=0.25.3)"]
+polars = ["polars (>=0.20.3)"]
+pyarrow = ["pyarrow (>=11.0.0)"]
+pyspark = ["pyspark (>=3.5.0)"]
+pyspark-connect = ["pyspark[connect] (>=3.5.0)"]
+sqlframe = ["sqlframe (>=3.22.0)"]
+
 [[package]]
 name = "numpy"
 version = "2.2.5"
@@ -1313,14 +1372,14 @@ files = [
 
 [[package]]
 name = "openai"
-version = "1.76.2"
+version = "1.77.0"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "openai-1.76.2-py3-none-any.whl", hash = "sha256:9c1d9ad59e6e3bea7205eedc9ca66eeebae18d47b527e505a2b0d2fb1538e26e"},
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+    {file = "openai-1.77.0-py3-none-any.whl", hash = "sha256:07706e91eb71631234996989a8ea991d5ee56f0744ef694c961e0824d4f39218"},
+    {file = "openai-1.77.0.tar.gz", hash = "sha256:897969f927f0068b8091b4b041d1f8175bcf124f7ea31bab418bf720971223bc"},
 ]
 
 [package.dependencies]
@@ -1698,6 +1757,27 @@ tests = ["check-manifest", "coverage (>=7.4.2)", "defusedxml", "markdown2", "ole
 typing = ["typing-extensions ; python_version < \"3.10\""]
 xmp = ["defusedxml"]
 
+[[package]]
+name = "plotly"
+version = "6.1.0"
+description = "An open-source interactive data visualization library for Python"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "plotly-6.1.0-py3-none-any.whl", hash = "sha256:a29d3ed523c9d7960095693af1ee52689830df0f9c6bae3e5e92c20c4f5684c3"},
+    {file = "plotly-6.1.0.tar.gz", hash = "sha256:f13f497ccc2d97f06f771a30b27fab0cbd220f2975865f4ecbc75057135521de"},
+]
+
+[package.dependencies]
+narwhals = ">=1.15.1"
+packaging = "*"
+
+[package.extras]
+dev = ["black (==25.1.0)"]
+express = ["numpy"]
+kaleido = ["kaleido (==1.0.0rc13)"]
+
 [[package]]
 name = "prompt-toolkit"
 version = "3.0.51"
@@ -2195,31 +2275,31 @@ jupyter = ["ipywidgets (>=7.5.1,<9)"]
 
 [[package]]
 name = "ruff"
-version = "0.11.7"
+version = "0.11.8"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 markers = "sys_platform != \"emscripten\""
 files = [
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+    {file = "ruff-0.11.8.tar.gz", hash = "sha256:6d742d10626f9004b781f4558154bb226620a7242080e11caeffab1a40e99df8"},
 ]
 
 [[package]]
@@ -2427,6 +2507,21 @@ anyio = ">=3.6.2,<5"
 [package.extras]
 full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.18)", "pyyaml"]
 
+[[package]]
+name = "tabulate"
+version = "0.9.0"
+description = "Pretty-print tabular data"
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
+files = [
+    {file = "tabulate-0.9.0-py3-none-any.whl", hash = "sha256:024ca478df22e9340661486f85298cff5f6dcdba14f3813e8830015b9ed1948f"},
+    {file = "tabulate-0.9.0.tar.gz", hash = "sha256:0095b12bf5966de529c0feb1fa08671671b3368eec77d7ef7ab114be2c068b3c"},
+]
+
+[package.extras]
+widechars = ["wcwidth"]
+
 [[package]]
 name = "tenacity"
 version = "9.1.2"
@@ -2977,4 +3072,4 @@ cffi = ["cffi (>=1.11)"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.12.4,<4.0.0"
-content-hash = "efbddde7effbf9adb8d0fd2294ffca2d5f4460bf12f75cfab57a0a47ca868c0e"
+content-hash = "83328808e618fc1322ad57b7279040ddcd509dd60d4582ca4056ec1a8ea8e5d2"

src/pyproject.toml

@@ -14,7 +14,11 @@ dependencies = [
     "langgraph (>=0.4.1,<0.5.0)",
     "langchain (>=0.3.24,<0.4.0)",
     "langchain-openai (>=0.3.14,<0.4.0)",
-    "ipython (>=9.2.0,<10.0.0)"
+    "ipython (>=9.2.0,<10.0.0)",
+    "gradio-calendar (>=0.0.6,<0.0.7)",
+    "tabulate (>=0.9.0,<0.10.0)",
+    "markdown (>=3.8,<4.0)",
+    "plotly (>=6.1.0,<7.0.0)"
 ]