import gradio as gr
import openai
import requests
import json
import os
from typing import Dict, List, Any
from datetime import datetime
from pydantic import BaseModel

# Set up OpenAI client
openai.api_key = os.getenv("OPENAI_API_KEY")
client = openai.OpenAI()

# SAP API Configuration
SAP_API_KEY = os.getenv("SAP_API_KEY")
BASE_URL = "https://sandbox.api.sap.com/s4hanacloud/sap/opu/odata/sap/API_BUSINESS_PARTNER"
CREDIT_API_URL = "https://sandbox.api.sap.com/s4hanacloud/sap/opu/odata/sap/API_CRDTMBUSINESSPARTNER"

class WorkflowStep(BaseModel):
    """Model for workflow step tracking"""
    step_number: int
    description: str
    status: str  # pending, in_progress, completed, failed
    result: Any = None
    timestamp: datetime = datetime.now()

class MultiStepWorkflow(BaseModel):
    """Model for tracking multi-step workflows"""
    workflow_id: str
    name: str
    steps: List[WorkflowStep]
    current_step: int = 0
    status: str = "pending"  # pending, running, completed, failed
    final_result: Any = None

class SAPBusinessPartnerAgent:
    def __init__(self):
        self.conversation_history = []
        self.active_workflows = {}
    
    def parse_search_query(self, query: str) -> Dict[str, Any]:
        """Parse natural language query into SAP API parameters using OpenAI"""
        system_prompt = """
        Parse this business partner search query into SAP OData parameters.
        
        Available fields for A_BusinessPartner:
        - BusinessPartner (ID)
        - BusinessPartnerFullName (Name)
        - BusinessPartnerCategory (1=Person, 2=Organization, 3=Group)
        - BusinessPartnerGrouping
        - CreationDate
        - IsMarkedForArchiving
        - SearchTerm1, SearchTerm2
        
        For country-specific queries, use contains() with country names.
        
        Return JSON with OData query parameters.
        
        Examples:
        - "Find customers in Germany" → {"$filter": "contains(BusinessPartnerFullName,'Germany') or contains(SearchTerm1,'DE')", "$top": "20"}
        - "Show me organizations" → {"$filter": "BusinessPartnerCategory eq '2'", "$top": "10"}
        - "Active partners only" → {"$filter": "IsMarkedForArchiving eq false", "$top": "10"}
        
        Always include $top with a reasonable limit (max 50 for workflows).
        """
        
        try:
            response = client.chat.completions.create(
                model="gpt-4o-mini",
                messages=[
                    {"role": "system", "content": system_prompt},
                    {"role": "user", "content": f"Query: {query}"}
                ],
                response_format={"type": "json_object"}
            )
            
            result = json.loads(response.choices[0].message.content)
            if "$top" not in result:
                result["$top"] = "20"
            return result
            
        except Exception as e:
            # Fallback for Germany search
            if "germany" in query.lower():
                return {
                    "$filter": "contains(BusinessPartnerFullName,'Germany')",
                    "$top": "20"
                }
            return {
                "$filter": f"contains(BusinessPartnerFullName,'{query}')",
                "$top": "10"
            }
    
    def call_sap_api(self, entity_set: str, params: Dict[str, Any], base_url: str = None) -> Dict[str, Any]:
        """Execute SAP API call"""
        url = f"{base_url or BASE_URL}/{entity_set}"
        
        # Build query parameters
        query_params = {
            "$format": "json",
            "$inlinecount": "allpages"
        }
        
        # Add user parameters
        for key, value in params.items():
            query_params[key] = value
        
        headers = {
            "Accept": "application/json",
            "APIKey": SAP_API_KEY or "demo_key"
        }
        
        try:
            response = requests.get(url, params=query_params, headers=headers, timeout=30)
            
            if response.status_code == 200:
                return response.json()
            else:
                # Return mock data for demo if API fails
                return self.get_mock_data(entity_set)
                
        except Exception as e:
            # Return mock data for demo
            return self.get_mock_data(entity_set)
    
    def get_mock_data(self, entity_set: str) -> Dict[str, Any]:
        """Return mock SAP data for demo purposes"""
        if entity_set == "CreditManagementAccount":
            return {
                "d": {
                    "results": [
                        {
                            "BusinessPartner": "1000000001",
                            "CreditLimitAmount": "50000.00",
                            "Currency": "EUR",
                            "CreditLimitValidFrom": "/Date(1640995200000)/",
                            "CreditLimitValidTo": "/Date(1672531200000)/",
                            "CreditExposureAmount": "25000.00"
                        },
                        {
                            "BusinessPartner": "1000000002",
                            "CreditLimitAmount": "75000.00",
                            "Currency": "EUR", 
                            "CreditLimitValidFrom": "/Date(1640995200000)/",
                            "CreditLimitValidTo": "/Date(1672531200000)/",
                            "CreditExposureAmount": "15000.00"
                        }
                    ],
                    "__count": "2"
                }
            }
        else:
            return {
                "d": {
                    "results": [
                        {
                            "BusinessPartner": "1000000001",
                            "BusinessPartnerFullName": "Munich Manufacturing GmbH",
                            "BusinessPartnerCategory": "2",
                            "CreationDate": "/Date(1640995200000)/",
                            "IsMarkedForArchiving": False,
                            "SearchTerm1": "MUNICH"
                        },
                        {
                            "BusinessPartner": "1000000002",
                            "BusinessPartnerFullName": "Berlin Tech Solutions AG",
                            "BusinessPartnerCategory": "2",
                            "CreationDate": "/Date(1641081600000)/",
                            "IsMarkedForArchiving": False,
                            "SearchTerm1": "BERLIN"
                        },
                        {
                            "BusinessPartner": "1000000003",
                            "BusinessPartnerFullName": "Hamburg Logistics Ltd",
                            "BusinessPartnerCategory": "2",
                            "CreationDate": "/Date(1641168000000)/",
                            "IsMarkedForArchiving": False,
                            "SearchTerm1": "HAMBURG"
                        }
                    ],
                    "__count": "3"
                }
            }
    
    def execute_multi_step_workflow(self, workflow_type: str, query: str) -> str:
        """Execute multi-step workflows with progress tracking"""
        
        if workflow_type == "credit_analysis":
            return self.execute_credit_analysis_workflow(query)
        else:
            return f"❌ Unknown workflow type: {workflow_type}"
    
    def execute_credit_analysis_workflow(self, query: str) -> str:
        """Execute the credit limit analysis workflow"""
        workflow_id = f"credit_analysis_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
        
        # Define workflow steps
        workflow = MultiStepWorkflow(
            workflow_id=workflow_id,
            name="Credit Limit Analysis for German Customers",
            steps=[
                WorkflowStep(step_number=1, description="Search for customers in Germany", status="pending"),
                WorkflowStep(step_number=2, description="Extract customer IDs", status="pending"),
                WorkflowStep(step_number=3, description="Fetch credit limits for each customer", status="pending"),
                WorkflowStep(step_number=4, description="Analyze and summarize findings", status="pending")
            ]
        )
        
        self.active_workflows[workflow_id] = workflow
        
        try:
            # Step 1: Search for customers in Germany
            workflow.steps[0].status = "in_progress"
            workflow.current_step = 1
            
            # Parse the Germany search query
            if "germany" not in query.lower():
                query = "Find customers in Germany"
            
            params = self.parse_search_query(query)
            customers_response = self.call_sap_api("A_BusinessPartner", params)
            
            workflow.steps[0].status = "completed"
            workflow.steps[0].result = customers_response
            
            # Step 2: Extract customer IDs
            workflow.steps[1].status = "in_progress"
            workflow.current_step = 2
            
            customers = customers_response.get('d', {}).get('results', [])
            if not customers:
                workflow.status = "failed"
                return "❌ No customers found in Germany"
            
            customer_ids = [customer['BusinessPartner'] for customer in customers]
            workflow.steps[1].status = "completed"
            workflow.steps[1].result = customer_ids
            
            # Step 3: Fetch credit limits
            workflow.steps[2].status = "in_progress" 
            workflow.current_step = 3
            
            credit_data = []
            for customer_id in customer_ids:
                credit_params = {
                    "$filter": f"BusinessPartner eq '{customer_id}'",
                    "$top": "1"
                }
                credit_response = self.call_sap_api("CreditManagementAccount", credit_params, CREDIT_API_URL)
                
                credit_results = credit_response.get('d', {}).get('results', [])
                if credit_results:
                    credit_info = credit_results[0]
                    # Match credit info with customer info
                    customer_info = next((c for c in customers if c['BusinessPartner'] == customer_id), {})
                    
                    credit_data.append({
                        'customer_id': customer_id,
                        'customer_name': customer_info.get('BusinessPartnerFullName', 'Unknown'),
                        'credit_limit': credit_info.get('CreditLimitAmount', '0'),
                        'currency': credit_info.get('Currency', 'EUR'),
                        'exposure': credit_info.get('CreditExposureAmount', '0'),
                        'utilization': self.calculate_utilization(
                            credit_info.get('CreditExposureAmount', '0'),
                            credit_info.get('CreditLimitAmount', '0')
                        )
                    })
            
            workflow.steps[2].status = "completed"
            workflow.steps[2].result = credit_data
            
            # Step 4: Analyze and summarize
            workflow.steps[3].status = "in_progress" 
            workflow.current_step = 4
            
            summary = self.generate_credit_analysis_summary(credit_data, customers)
            
            workflow.steps[3].status = "completed"
            workflow.steps[3].result = summary
            workflow.status = "completed"
            workflow.final_result = summary
            
            return summary
            
        except Exception as e:
            workflow.status = "failed"
            return f"❌ Workflow failed at step {workflow.current_step}: {str(e)}"
    
    def calculate_utilization(self, exposure: str, limit: str) -> float:
        """Calculate credit utilization percentage"""
        try:
            exposure_val = float(exposure)
            limit_val = float(limit)
            if limit_val > 0:
                return round((exposure_val / limit_val) * 100, 2)
            return 0.0
        except:
            return 0.0
    
    def generate_credit_analysis_summary(self, credit_data: List[Dict], customers: List[Dict]) -> str:
        """Generate comprehensive credit analysis summary"""
        
        if not credit_data:
            return "❌ No credit data found for German customers"
        
        # Calculate statistics
        total_customers = len(customers)
        customers_with_credit = len(credit_data)
        total_credit_limit = sum(float(item['credit_limit']) for item in credit_data)
        total_exposure = sum(float(item['exposure']) for item in credit_data)
        avg_utilization = sum(item['utilization'] for item in credit_data) / len(credit_data)
        
        # Find high-risk customers (>80% utilization)
        high_risk = [item for item in credit_data if item['utilization'] > 80]
        low_risk = [item for item in credit_data if item['utilization'] < 30]
        
        # Generate summary
        summary = f"""## 📊 Credit Limit Analysis - German Customers

### 🔍 **Workflow Execution Summary**
✅ **Step 1:** Found {total_customers} German customers
✅ **Step 2:** Extracted customer IDs 
✅ **Step 3:** Retrieved credit data for {customers_with_credit} customers
✅ **Step 4:** Completed analysis and summary

### 📈 **Key Financial Metrics**
- **Total Credit Limits:** €{total_credit_limit:,.2f}
- **Total Credit Exposure:** €{total_exposure:,.2f}
- **Average Utilization:** {avg_utilization:.1f}%
- **Overall Exposure Ratio:** {(total_exposure/total_credit_limit*100):.1f}%

### 🚨 **Risk Analysis**

#### High Risk Customers (>80% utilization):
"""
        
        if high_risk:
            for customer in high_risk:
                summary += f"""
**{customer['customer_name']}** (ID: {customer['customer_id']})
- Credit Limit: €{float(customer['credit_limit']):,.2f}
- Current Exposure: €{float(customer['exposure']):,.2f}
- Utilization: **{customer['utilization']}%** ⚠️
"""
        else:
            summary += "\n✅ No high-risk customers found\n"
        
        summary += f"""
#### Low Risk Customers (<30% utilization):
"""
        
        if low_risk:
            for customer in low_risk[:3]:  # Show top 3
                summary += f"""
**{customer['customer_name']}** (ID: {customer['customer_id']})
- Credit Limit: €{float(customer['credit_limit']):,.2f}  
- Utilization: {customer['utilization']}% ✅
"""
            if len(low_risk) > 3:
                summary += f"\n... and {len(low_risk) - 3} more low-risk customers\n"
        else:
            summary += "\n⚠️ No low-risk customers found\n"
        
        summary += f"""
### 💡 **Recommendations**
1. **Monitor High-Risk Accounts:** Review customers with >80% utilization
2. **Credit Line Reviews:** Consider adjusting limits based on utilization patterns
3. **Payment Terms:** Evaluate payment terms for high-exposure customers
4. **Regular Monitoring:** Set up alerts for utilization threshold breaches

### 📋 **Detailed Customer List**
"""
        
        for i, customer in enumerate(credit_data, 1):
            risk_indicator = "🔴" if customer['utilization'] > 80 else "🟡" if customer['utilization'] > 50 else "🟢"
            summary += f"""
{i}. {risk_indicator} **{customer['customer_name']}**
   - ID: {customer['customer_id']}
   - Credit Limit: €{float(customer['credit_limit']):,.2f}
   - Exposure: €{float(customer['exposure']):,.2f} ({customer['utilization']}%)
"""
        
        return summary
    
    def format_business_partner_response(self, response: Dict, original_query: str) -> str:
        """Format business partner API response into readable text"""
        try:
            if 'd' in response and 'results' in response['d']:
                results = response['d']['results']
                total_count = response['d'].get('__count', len(results))
                
                if not results:
                    return f"❌ No business partners found for: '{original_query}'"
                
                # Format the response
                formatted_response = f"## 📊 Business Partner Search Results\n\n"
                formatted_response += f"**Query:** {original_query}\n"
                formatted_response += f"**Found:** {total_count} business partner(s)\n\n"
                
                for i, partner in enumerate(results, 1):
                    bp_id = partner.get('BusinessPartner', 'N/A')
                    bp_name = partner.get('BusinessPartnerFullName', 'N/A')
                    bp_category = partner.get('BusinessPartnerCategory', 'N/A')
                    is_archived = partner.get('IsMarkedForArchiving', False)
                    
                    category_text = {
                        '1': '👤 Person',
                        '2': '🏢 Organization',
                        '3': '🏭 Group'
                    }.get(bp_category, '❓ Unknown')
                    
                    status = '🟢 Active' if not is_archived else '🔴 Archived'
                    
                    formatted_response += f"### {i}. {bp_name}\n"
                    formatted_response += f"- **ID:** {bp_id}\n"
                    formatted_response += f"- **Type:** {category_text}\n"
                    formatted_response += f"- **Status:** {status}\n\n"
                
                return formatted_response
            else:
                return f"⚠️ Received unexpected response format for: '{original_query}'"
                
        except Exception as e:
            return f"❌ Error formatting response: {str(e)}"
    
    def search_business_partners(self, query: str) -> str:
        """Main search function for business partners"""
        try:
            # Parse the query
            params = self.parse_search_query(query)
            
            # Call SAP API
            response = self.call_sap_api("A_BusinessPartner", params)
            
            # Format response
            return self.format_business_partner_response(response, query)
            
        except Exception as e:
            return f"❌ Error searching business partners: {str(e)}"
    
    def process_user_query(self, user_query: str, history: List) -> tuple:
        """Process user query and return response with updated history"""
        
        # Add user message to history
        history.append([user_query, None])
        
        try:
            # Check for multi-step workflow requests
            if any(keyword in user_query.lower() for keyword in ['credit limit', 'credit analysis', 'germany credit', 'german customers credit']):
                response = self.execute_multi_step_workflow("credit_analysis", user_query)
            elif any(keyword in user_query.lower() for keyword in ['search', 'find', 'show', 'list', 'get']):
                response = self.search_business_partners(user_query)
            else:
                # Use OpenAI to understand intent and provide guidance
                system_prompt = """
                You are a SAP Business Partner Assistant with multi-step workflow capabilities.
                
                Available capabilities:
                1. Search business partners
                2. Credit limit analysis workflows 
                3. Multi-step customer analysis
                
                Guide users to:
                - Use search terms for finding partners
                - Ask for "credit analysis for German customers" for workflows
                - Request specific business partner operations
                
                Be helpful and explain what you can do.
                """
                
                ai_response = client.chat.completions.create(
                    model="gpt-4o-mini",
                    messages=[
                        {"role": "system", "content": system_prompt},
                        {"role": "user", "content": user_query}
                    ]
                )
                
                response = ai_response.choices[0].message.content
            
            # Update history with response
            history[-1][1] = response
            
        except Exception as e:
            error_response = f"❌ Sorry, I encountered an error: {str(e)}\n\nTry asking: 'Run credit analysis for German customers'"
            history[-1][1] = error_response
        
        return "", history

# Initialize the agent
sap_agent = SAPBusinessPartnerAgent()

# Create Gradio interface
def create_interface():
    with gr.Blocks(
        title="SAP Business Partner Agent with Workflows",
        theme=gr.themes.Soft(),
        css="""
        .gradio-container {
            max-width: 1200px !important;
        }
        .agent-header {
            text-align: center;
            background: linear-gradient(90deg, #0070f3, #00d4ff);
            color: white;
            padding: 20px;
            border-radius: 10px;
            margin-bottom: 20px;
        }
        """
    ) as demo:
        
        # Header
        gr.HTML("""
        <div class="agent-header">
            <h1>🤖 SAP Business Partner Agent</h1>
            <p>Intelligent assistant with multi-step workflow capabilities</p>
        </div>
        """)
        
        # Main chat interface
        with gr.Row():
            with gr.Column(scale=4):
                chatbot = gr.Chatbot(
                    height=600,
                    label="Chat with SAP Business Partner Agent",
                    placeholder="Start by asking about business partners or request a workflow..."
                )
                
                with gr.Row():
                    msg = gr.Textbox(
                        placeholder="Try: 'Run credit analysis for German customers' or 'Find partners with name Demo'",
                        label="Your Message",
                        scale=4
                    )
                    submit_btn = gr.Button("Send", variant="primary", scale=1)
                
                # Example buttons
                gr.Markdown("### 💡 Quick Examples:")
                with gr.Row():
                    example1 = gr.Button("Credit Analysis Workflow", size="sm", variant="primary")
                    example2 = gr.Button("Find German customers", size="sm")
                    example3 = gr.Button("Search Demo partners", size="sm")
                    clear_btn = gr.Button("Clear Chat", size="sm", variant="secondary")
            
            # Sidebar with information
            with gr.Column(scale=1):
                gr.Markdown("""
                ### 🔧 Agent Capabilities
                
                **Multi-Step Workflows:**
                - 🏦 Credit limit analysis
                - 📊 Risk assessment
                - 🔄 Sequential API calls
                
                **Search & Retrieve:**
                - Find business partners
                - Filter by criteria
                - Location-based search
                
                **Partner Types:**
                - 👤 Persons
                - 🏢 Organizations 
                - 🏭 Groups
                
                ### 🚀 Advanced Features
                - **Workflow Tracking:** Step-by-step progress
                - **Error Handling:** Graceful failure recovery
                - **Data Integration:** Multiple SAP APIs
                - **Smart Analysis:** AI-powered insights
                
                ### 📝 Workflow Examples
                - "Run credit analysis for German customers"
                - "Analyze credit limits for suppliers"
                - "Find high-risk customers"
                """)
        
        # Event handlers
        msg.submit(
            sap_agent.process_user_query,
            inputs=[msg, chatbot],
            outputs=[msg, chatbot]
        )
        
        submit_btn.click(
            sap_agent.process_user_query,
            inputs=[msg, chatbot], 
            outputs=[msg, chatbot]
        )
        
        # Example button events
        example1.click(lambda: "Run credit analysis for German customers", outputs=msg)
        example2.click(lambda: "Find customers in Germany", outputs=msg)
        example3.click(lambda: "Find partners with name Demo", outputs=msg)
        clear_btn.click(lambda: [], outputs=chatbot)
        
        # Footer
        gr.Markdown("""
        ---
        **SAP Business Partner Agent with Multi-Step Workflows** | Powered by OpenAI & SAP APIs | Built for Advanced Agentic AI Learning
        """)
    
    return demo

# Launch the app
if __name__ == "__main__":
    demo = create_interface()
    demo.launch()