Upload folder using huggingface_hub

README.md

@@ -1,12 +1,6 @@
 ---
-title: Huggingface Deployment
-emoji: 📈
-colorFrom: green
-colorTo: purple
-sdk: gradio
-sdk_version: 5.42.0
+title: huggingface-deployment
 app_file: app.py
-pinned: false
+sdk: gradio
+sdk_version: 5.6.0
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,350 @@
+import gradio as gr
+import requests
+import pandas as pd
+from typing import Dict, List, Optional, Tuple
+import json
+
+# Base URL for the API
+BASE_URL = "https://gljx3devrf.execute-api.us-west-1.amazonaws.com/prod/"
+
+class ContractPaymentViewer:
+    def __init__(self):
+        self.current_contract_data = {}
+        self.current_monthly_data = {}
+    
+    def fetch_payment_history(self, contract_number: str) -> Tuple[gr.Dropdown, str, pd.DataFrame]:
+        """
+        Fetch payment history for a given contract number
+        """
+        if not contract_number:
+            return gr.Dropdown(choices=[], value=None), "Please enter a contract number", pd.DataFrame()
+        
+        try:
+            # Clean the contract number
+            contract_number = contract_number.strip()
+            
+            # Call the API
+            url = f"{BASE_URL}/contracts/{contract_number}/payments"
+            response = requests.get(url, timeout=10)
+            response.raise_for_status()
+            
+            data = response.json()
+            self.current_contract_data = data
+            
+            # Extract monthly breakdown for dropdown
+            monthly_breakdown = data.get('monthly_breakdown', {})
+            
+            if not monthly_breakdown:
+                return gr.Dropdown(choices=[], value=None), "No payment history found", pd.DataFrame()
+            
+            # Create choices for dropdown (sorted by date, newest first)
+            choices = sorted(list(monthly_breakdown.keys()), reverse=True)
+            
+            # Create summary info
+            contract_details = data.get('contract_details', {})
+            summary = data.get('summary', {})
+            
+            # Clean job description by removing carriage returns
+            job_description = contract_details.get('job_description', 'N/A').replace('\r', ' ')
+            
+            summary_info = f"""
+### Contract Summary
+- **Contract Number:** {contract_details.get('contract_number', contract_number)}
+- **Contractor:** {contract_details.get('contractor_name', 'N/A')}
+- **Job Description:** {job_description}
+- **Total Payments:** {summary.get('total_payments', 0)}
+- **Total Disbursed:** ${summary.get('total_disbursed', 0):,.2f}
+- **Total Held:** ${summary.get('total_held', 0):,.2f}
+- **Estimated Completion:** {contract_details.get('estimated_completion', 'N/A')}
+- **Last Updated:** {contract_details.get('last_updated', 'N/A')}
+"""
+            
+            # Create payment history DataFrame
+            payment_history = data.get('payment_history', [])
+            if payment_history:
+                history_df = pd.DataFrame(payment_history)
+                history_df = history_df[['estimate_number', 'type', 'payment_type', 'release_date', 'disbursed_amount', 'held_amount']]
+                history_df.columns = ['Estimate #', 'Type', 'Payment Type', 'Release Date', 'Disbursed Amount', 'Held Amount']
+                history_df['Disbursed Amount'] = history_df['Disbursed Amount'].apply(lambda x: f"${x:,.2f}")
+                history_df['Held Amount'] = history_df['Held Amount'].apply(lambda x: f"${x:,.2f}")
+            else:
+                history_df = pd.DataFrame()
+            
+            return (
+                gr.Dropdown(choices=choices, value=choices[0] if choices else None, visible=True, interactive=True),
+                summary_info,
+                history_df
+            )
+            
+        except requests.exceptions.RequestException as e:
+            return gr.Dropdown(choices=[], value=None), f"Error fetching data: {str(e)}", pd.DataFrame()
+        except Exception as e:
+            return gr.Dropdown(choices=[], value=None), f"Unexpected error: {str(e)}", pd.DataFrame()
+    
+    def fetch_monthly_details(self, contract_number: str, selected_month: str) -> Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame, pd.DataFrame, str]:
+        """
+        Fetch detailed monthly payment information
+        """
+        if not contract_number or not selected_month:
+            return pd.DataFrame(), pd.DataFrame(), pd.DataFrame(), "Please select a month"
+        
+        try:
+            # Clean inputs
+            contract_number = contract_number.strip()
+            selected_month = selected_month.strip()
+            
+            # Call the API for monthly details
+            url = f"{BASE_URL}/contracts/{contract_number}/payments/monthly/{selected_month}"
+            response = requests.get(url, timeout=10)
+            response.raise_for_status()
+            
+            monthly_data = response.json()
+            self.current_monthly_data = monthly_data
+            
+            # Process the payment data
+            payment_info = monthly_data.get('payments', [{}])[0] if monthly_data.get('payments') else {}
+            
+            # Create monthly summary DataFrame
+            summary_data = {
+                'Metric': [
+                    'Month',
+                    'Payment Count', 
+                    'Total Disbursed', 
+                    'Total Held',
+                    'Estimate Number',
+                    'Payment Type',
+                    'Release Date'
+                ],
+                'Value': [
+                    monthly_data.get('month', selected_month),
+                    monthly_data.get('payment_count', 0),
+                    f"${monthly_data.get('total_disbursed', 0):,.2f}",
+                    f"${monthly_data.get('total_held', 0):,.2f}",
+                    payment_info.get('estimate_number', 'N/A'),
+                    payment_info.get('payment_type', 'N/A'),
+                    payment_info.get('release_date', 'N/A')
+                ]
+            }
+            summary_df = pd.DataFrame(summary_data)
+            
+            # Create detailed items DataFrame
+            items_df = pd.DataFrame()
+            if payment_info and 'detailed_estimate' in payment_info:
+                detailed_estimate = payment_info['detailed_estimate']
+                prime_items = detailed_estimate.get('prime_contract', {}).get('items', [])
+                
+                if prime_items:
+                    # Process items for display
+                    items_data = []
+                    for item in prime_items:
+                        if item.get('amounts', {}).get('this_period', 0) != 0:  # Only show items with activity
+                            items_data.append({
+                                'Item #': item.get('item_number', ''),
+                                'Description': item.get('description', '')[:50] + '...' if len(item.get('description', '')) > 50 else item.get('description', ''),
+                                'Unit': item.get('units', ''),
+                                'Unit Price': f"${item.get('unit_price', 0):,.2f}",
+                                'Qty This Period': f"{item.get('quantities', {}).get('this_period', 0):,.2f}",
+                                'Amount This Period': f"${item.get('amounts', {}).get('this_period', 0):,.2f}",
+                                'Job to Date': f"${item.get('amounts', {}).get('job_to_date', 0):,.2f}",
+                                '% Complete': f"{item.get('quantities', {}).get('percent_jtd', 0):.1f}%"
+                            })
+                    
+                    if items_data:
+                        items_df = pd.DataFrame(items_data)
+                        # Sort by amount this period (descending)
+                        items_df['sort_value'] = items_df['Amount This Period'].str.replace('$', '').str.replace(',', '').astype(float)
+                        items_df = items_df.sort_values('sort_value', ascending=False).drop('sort_value', axis=1)
+                    else:
+                        # Create empty dataframe with message
+                        items_df = pd.DataFrame({'Message': ['No line items with activity for this period']})
+                else:
+                    items_df = pd.DataFrame({'Message': ['No line items available']})
+            else:
+                items_df = pd.DataFrame({'Message': ['No line items available']})
+            
+            # Create deductions DataFrame
+            deductions_df = pd.DataFrame()
+            if payment_info and 'detailed_estimate' in payment_info:
+                deductions = payment_info['detailed_estimate'].get('deductions', [])
+                if deductions:
+                    deductions_data = []
+                    for deduction in deductions:
+                        deductions_data.append({
+                            'Estimate #': deduction.get('estimate_no', ''),
+                            'Description': deduction.get('description', ''),
+                            'This Period': f"${deduction.get('this_period', 0):,.2f}",
+                            'Job to Date': f"${deduction.get('job_to_date', 0):,.2f}"
+                        })
+                    deductions_df = pd.DataFrame(deductions_data)
+                else:
+                    deductions_df = pd.DataFrame({'Message': ['No deductions for this period']})
+            else:
+                deductions_df = pd.DataFrame({'Message': ['No deductions available']})
+            
+            # Create change orders DataFrame
+            change_orders_df = pd.DataFrame()
+            if payment_info and 'detailed_estimate' in payment_info:
+                change_orders = payment_info['detailed_estimate'].get('change_orders', {}).get('items', [])
+                if change_orders:
+                    change_orders_data = []
+                    for co in change_orders:
+                        change_orders_data.append({
+                            'Change Order #': co.get('change_order_no', ''),
+                            'Description': co.get('description', '')[:50] + '...' if len(co.get('description', '')) > 50 else co.get('description', ''),
+                            'This Period': f"${co.get('this_period_amt', 0):,.2f}",
+                            'Job to Date': f"${co.get('job_to_date_amt', 0):,.2f}",
+                            'Status': co.get('status', 'N/A')
+                        })
+                    if change_orders_data:
+                        change_orders_df = pd.DataFrame(change_orders_data)
+                        # Sort by amount this period (descending)
+                        change_orders_df['sort_value'] = change_orders_df['This Period'].str.replace('$', '').str.replace(',', '').astype(float)
+                        change_orders_df = change_orders_df.sort_values('sort_value', ascending=False).drop('sort_value', axis=1)
+                    else:
+                        change_orders_df = pd.DataFrame({'Message': ['No change orders for this period']})
+                else:
+                    change_orders_df = pd.DataFrame({'Message': ['No change orders available']})
+            else:
+                change_orders_df = pd.DataFrame({'Message': ['No change orders available']})
+            
+            # Create totals summary
+            if payment_info and 'detailed_estimate' in payment_info:
+                totals = payment_info['detailed_estimate'].get('overall_totals', {})
+                totals_info = f"""
+### Payment Totals for {selected_month}
+- **Original Contract Amount:** ${totals.get('original', 0):,.2f}
+- **This Period:** ${totals.get('this_period', 0):,.2f}
+- **Job to Date:** ${totals.get('job_to_date', 0):,.2f}
+- **Extra Work This Estimate:** ${totals.get('extra_work_this_estimate', 0):,.2f}
+- **Extra Work to Date:** ${totals.get('extra_work_to_date', 0):,.2f}
+                """
+            else:
+                totals_info = "No detailed totals available"
+            
+            return summary_df, items_df, deductions_df, change_orders_df, totals_info
+            
+        except requests.exceptions.RequestException as e:
+            return pd.DataFrame(), pd.DataFrame(), pd.DataFrame(), pd.DataFrame(), f"Error fetching monthly details: {str(e)}"
+        except Exception as e:
+            return pd.DataFrame(), pd.DataFrame(), pd.DataFrame(), pd.DataFrame(), f"Unexpected error: {str(e)}"
+
+# Create instance of the viewer
+viewer = ContractPaymentViewer()
+
+# Create Gradio interface
+with gr.Blocks(title="Contract Payment Viewer", theme=gr.themes.Soft()) as app:
+    gr.Markdown("# Contract Payment Viewer")
+    gr.Markdown("Enter a contract number to view payment history and detailed monthly breakdowns")
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            contract_input = gr.Textbox(
+                label="Contract Number",
+                placeholder="e.g., 03-3F0704",
+                value="03-3F0704"
+            )
+            fetch_button = gr.Button("Fetch Payment History", variant="primary")
+    
+    with gr.Row():
+        with gr.Column():
+            summary_output = gr.Markdown(label="Contract Summary")
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            month_dropdown = gr.Dropdown(
+                label="Select Month",
+                choices=[],
+                visible=False
+            )
+            fetch_monthly_button = gr.Button("Get Monthly Details", variant="secondary", visible=False)
+    
+    with gr.Row():
+        with gr.Column():
+            with gr.Accordion("Payment History", open=False):
+                history_table = gr.Dataframe(
+                    label="Payment History",
+                    wrap=True
+                )
+    
+    # Monthly details section
+    with gr.Row(visible=False) as monthly_section:
+        with gr.Column():
+            gr.Markdown("## Monthly Payment Details")
+            
+            with gr.Tabs():
+                with gr.TabItem("Summary"):
+                    monthly_summary_table = gr.Dataframe(
+                        label="Monthly Summary",
+                        wrap=True
+                    )
+                    totals_output = gr.Markdown(label="Payment Totals")
+                
+                with gr.TabItem("Line Items"):
+                    items_table = gr.Dataframe(
+                        label="Contract Items (This Period Activity)",
+                        wrap=True
+                    )
+                
+                with gr.TabItem("Deductions"):
+                    deductions_table = gr.Dataframe(
+                        label="Deductions",
+                        wrap=True
+                    )
+                
+                with gr.TabItem("Change Orders"):
+                    change_orders_table = gr.Dataframe(
+                        label="Change Orders",
+                        wrap=True
+                    )
+    
+    # Event handlers
+    def handle_fetch_history(contract_number):
+        dropdown, summary, history = viewer.fetch_payment_history(contract_number)
+        return {
+            month_dropdown: dropdown,
+            summary_output: summary,
+            history_table: history,
+            fetch_monthly_button: gr.Button(visible=True if dropdown.choices else False),
+            monthly_section: gr.Row(visible=False)
+        }
+    
+    def handle_fetch_monthly(contract_number, selected_month):
+        summary_df, items_df, deductions_df, change_orders_df, totals = viewer.fetch_monthly_details(contract_number, selected_month)
+        return {
+            monthly_summary_table: summary_df,
+            items_table: items_df,
+            deductions_table: deductions_df,
+            change_orders_table: change_orders_df,
+            totals_output: totals,
+            monthly_section: gr.Row(visible=True)
+        }
+    
+    fetch_button.click(
+        fn=handle_fetch_history,
+        inputs=[contract_input],
+        outputs=[month_dropdown, summary_output, history_table, fetch_monthly_button, monthly_section]
+    )
+    
+    fetch_monthly_button.click(
+        fn=handle_fetch_monthly,
+        inputs=[contract_input, month_dropdown],
+        outputs=[monthly_summary_table, items_table, deductions_table, change_orders_table, totals_output, monthly_section]
+    )
+    
+    # Auto-fetch monthly details when dropdown changes
+    month_dropdown.change(
+        fn=handle_fetch_monthly,
+        inputs=[contract_input, month_dropdown],
+        outputs=[monthly_summary_table, items_table, deductions_table, change_orders_table, totals_output, monthly_section]
+    )
+
+# Launch the app
+if __name__ == "__main__":
+    app.launch(
+        share=True,
+        server_name="0.0.0.0",
+        server_port=7860,
+        show_error=True,
+        debug=False,
+        max_threads=10
+    )

requirements.txt

@@ -0,0 +1,3 @@
+gradio==5.6.0
+requests==2.32.4
+pandas==2.3.1