workflows/sales_analysis.py

import os
import json
import logging
import traceback
from typing import Dict, List, Any, Tuple, Optional, TypedDict, Annotated, Literal, cast
from datetime import datetime
import uuid
from pydantic import BaseModel, Field
from langgraph.graph import StateGraph, END
from langchain_anthropic import ChatAnthropic
from langchain_core.messages import AIMessage, HumanMessage, SystemMessage

# Configure logging
logging.basicConfig(
    level=logging.DEBUG, 
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger("sales_analysis_workflow")

# Import the agents
from agents.planning_agent import PlanningAgent, AnalysisPlan
from agents.data_agent import DataAgent, DataRequest, DataSource
from agents.analytics_agent import AnalyticsAgent, AnalysisRequest, AnalysisResult
from agents.qa_agent import QAAgent, ValidationRequest, ValidationResult
from agents.insights_agent import InsightsAgent, InsightRequest, InsightCard

# Define the workflow state
class WorkflowState(TypedDict):
    alert: str
    status: Literal["planning", "data_collection", "analysis", "validation", "insights", "complete", "error"]
    plan: Optional[AnalysisPlan]
    data_requests: List[DataRequest]
    data_sources: Dict[str, DataSource]
    analysis_requests: List[AnalysisRequest]
    analysis_results: Dict[str, AnalysisResult]
    validation_requests: List[ValidationRequest]
    validation_results: Dict[str, ValidationResult]
    insight_requests: List[InsightRequest]
    insight_cards: Dict[str, InsightCard]
    error: Optional[str]
    logs: List[Dict[str, Any]]
    visualizations: List[str]

# Function to initialize workflow state
def create_initial_state(alert: str) -> WorkflowState:
    """Create initial workflow state from alert"""
    logger.info(f"Creating initial state for alert: {alert}")
    return WorkflowState(
        alert=alert,
        status="planning",
        plan=None,
        data_requests=[],
        data_sources={},
        analysis_requests=[],
        analysis_results={},
        validation_requests=[],
        validation_results={},
        insight_requests=[],
        insight_cards={},
        error=None,
        logs=[{
            "timestamp": datetime.now().isoformat(),
            "step": "init",
            "message": f"Workflow initialized with alert: {alert}"
        }],
        visualizations=[]
    )

# Define the agent nodes
class SalesAnalysisWorkflow:
    """Orchestrates the sales analysis workflow with multiple agents"""
    
    def __init__(self, db_path: str = "data/pharma_db.sqlite"):
        """Initialize the workflow with agents"""
        logger.info("Initializing SalesAnalysisWorkflow")
        
        try:
            # Initialize agents
            self.planning_agent = PlanningAgent()
            self.data_agent = DataAgent(db_path=db_path)
            self.analytics_agent = AnalyticsAgent()
            self.qa_agent = QAAgent()
            self.insights_agent = InsightsAgent()
            
            # Create the workflow graph
            logger.info("Building workflow graph")
            self.workflow = self._build_workflow()
            
            logger.info("SalesAnalysisWorkflow initialized successfully")
        
        except Exception as e:
            logger.error(f"Workflow initialization failed: {e}")
            logger.error(traceback.format_exc())
            raise
    
    def _build_workflow(self) -> StateGraph:
        """Build the workflow graph"""
        logger.info("Building workflow graph")
        
        try:
            # Create the state graph
            workflow = StateGraph(WorkflowState)
            
            # Add nodes for each agent
            workflow.add_node("planning", self.planning_node)
            workflow.add_node("data_collection", self.data_collection_node)
            workflow.add_node("analysis", self.analysis_node)
            workflow.add_node("validation", self.validation_node)
            workflow.add_node("insights", self.insights_node)
            
            # Define the normal workflow edges (the happy path)
            workflow.add_edge("planning", "data_collection")
            workflow.add_edge("data_collection", "analysis")
            workflow.add_edge("analysis", "validation")
            workflow.add_edge("validation", "insights")
            workflow.add_edge("insights", END)
            
            # Add error handling
            workflow.add_node("handle_error", self.handle_error_node)
            
            # Define a simple linear workflow without error handling for now
            # This should work with any version of LangGraph
            workflow.add_edge("planning", "data_collection")
            workflow.add_edge("data_collection", "analysis")
            workflow.add_edge("analysis", "validation")
            workflow.add_edge("validation", "insights")
            workflow.add_edge("insights", END)
            
            # We'll handle errors within each node function instead of using graph branching
            workflow.add_edge("handle_error", END)
            
            # Set the entry point
            workflow.set_entry_point("planning")
            
            logger.info("Workflow graph built successfully")
            return workflow.compile()
        
        except Exception as e:
            logger.error(f"Workflow graph construction failed: {e}")
            logger.error(traceback.format_exc())
            raise
    
    def run_workflow(self, alert: str) -> WorkflowState:
        """
        Run the workflow with a given alert, with comprehensive logging
        
        Args:
            alert (str): Description of the sales alert
        
        Returns:
            WorkflowState: Final state of the workflow
        """
        logger.info(f"Starting workflow run with alert: {alert}")
        
        try:
            # Create initial state
            initial_state = create_initial_state(alert)
            
            # Run the workflow
            logger.info("Invoking workflow")
            final_state = self.workflow.invoke(initial_state)
            
            logger.info(f"Workflow completed. Final status: {final_state['status']}")
            
            return final_state
        
        except Exception as e:
            logger.error(f"Workflow execution failed: {e}")
            logger.error(traceback.format_exc())
            
            # Create an error state
            error_state = create_initial_state(alert)
            error_state["status"] = "error"
            error_state["error"] = str(e)
            error_state["logs"].append({
                "timestamp": datetime.now().isoformat(),
                "step": "error",
                "message": f"Workflow execution failed: {e}"
            })
            
            return error_state
            
    # Agent node implementations need to be added here
    def planning_node(self, state: WorkflowState) -> WorkflowState:
        """Planning agent node"""
        try:
            # Log the step
            state["logs"].append({
                "timestamp": datetime.now().isoformat(),
                "step": "planning",
                "message": "Planning analysis approach"
            })
            
            # Update status
            state["status"] = "planning"
            
            # Create analysis plan
            analysis_plan, plan_dict = self.planning_agent.create_analysis_plan(state["alert"])
            
            # Store the plan in the state
            state["plan"] = analysis_plan
            
            # Create data requests from plan
            data_requests = []
            for i, data_source in enumerate(analysis_plan.required_data_sources):
                data_requests.append(DataRequest(
                    request_id=f"data_{i}",
                    description=data_source["purpose"],
                    tables=[data_source["table"]],
                    purpose=data_source["purpose"]
                ))
            
            # Store data requests in the state
            state["data_requests"] = data_requests
            
            # Update status for next step
            state["status"] = "data_collection"
            
            return state
        except Exception as e:
            # Handle error
            state["status"] = "error"
            state["error"] = f"Planning error: {str(e)}"
            return state
    
    def data_collection_node(self, state: WorkflowState) -> WorkflowState:
        """Data collection agent node"""
        try:
            # Log the step
            state["logs"].append({
                "timestamp": datetime.now().isoformat(),
                "step": "data_collection",
                "message": f"Collecting data from {len(state['data_requests'])} sources"
            })
            
            # Update status
            state["status"] = "data_collection"
            
            # Process data requests
            data_sources = self.data_agent.get_data_for_analysis(state["data_requests"])
            
            # Store data sources in the state
            state["data_sources"] = data_sources
            
            # Create analysis requests based on plan
            analysis_requests = []
            if state["plan"]:
                analysis_approaches = state["plan"].analysis_approaches
                for i, approach in enumerate(analysis_approaches):
                    analysis_requests.append(AnalysisRequest(
                        request_id=f"analysis_{i}",
                        description=approach["purpose"],
                        data_sources=list(data_sources.keys()),
                        analysis_type=approach["type"],
                        purpose=approach["purpose"]
                    ))
            
            # Store analysis requests in the state
            state["analysis_requests"] = analysis_requests
            
            # Update status for next step
            state["status"] = "analysis"
            
            return state
        except Exception as e:
            # Handle error
            state["status"] = "error"
            state["error"] = f"Data collection error: {str(e)}"
            return state
    
    def analysis_node(self, state: WorkflowState) -> WorkflowState:
        """Analytics agent node"""
        try:
            # Log the step
            state["logs"].append({
                "timestamp": datetime.now().isoformat(),
                "step": "analysis",
                "message": f"Performing {len(state['analysis_requests'])} analysis tasks"
            })
            
            # Update status
            state["status"] = "analysis"
            
            # Process analysis requests
            analysis_results = {}
            for request in state["analysis_requests"]:
                result = self.analytics_agent.perform_analysis(request, state["data_sources"])
                analysis_results[request.request_id] = result
            
            # Store analysis results in the state
            state["analysis_results"] = analysis_results
            
            # Create validation requests
            validation_requests = []
            for analysis_id, result in analysis_results.items():
                validation_requests.append(ValidationRequest(
                    request_id=analysis_id,
                    original_problem=state["alert"],
                    analysis_results=result.model_dump(),
                    data_sources=list(state["data_sources"].keys())
                ))
            
            # Store validation requests in the state
            state["validation_requests"] = validation_requests
            
            # Update status for next step
            state["status"] = "validation"
            
            return state
        except Exception as e:
            # Handle error
            state["status"] = "error"
            state["error"] = f"Analysis error: {str(e)}"
            return state
    
    def validation_node(self, state: WorkflowState) -> WorkflowState:
        """QA agent node"""
        try:
            # Log the step
            state["logs"].append({
                "timestamp": datetime.now().isoformat(),
                "step": "validation",
                "message": f"Validating {len(state['validation_requests'])} analysis results"
            })
            
            # Update status
            state["status"] = "validation"
            
            # Process validation requests
            validation_results = {}
            for request in state["validation_requests"]:
                result = self.qa_agent.validate_analysis(request, state["data_sources"])
                validation_results[request.request_id] = result
            
            # Store validation results in the state
            state["validation_results"] = validation_results
            
            # Create insight requests
            insight_requests = []
            for analysis_id, validation in validation_results.items():
                analysis_result = state["analysis_results"][analysis_id]
                insight_requests.append(InsightRequest(
                    request_id=analysis_id,
                    original_problem=state["alert"],
                    analysis_results=analysis_result.model_dump(),
                    validation_results=validation.model_dump(),
                    target_audience="executive"
                ))
            
            # Store insight requests in the state
            state["insight_requests"] = insight_requests
            
            # Update status for next step
            state["status"] = "insights"
            
            return state
        except Exception as e:
            # Handle error
            state["status"] = "error"
            state["error"] = f"Validation error: {str(e)}"
            return state
    
    def insights_node(self, state: WorkflowState) -> WorkflowState:
        """Insights agent node"""
        try:
            # Log the step
            state["logs"].append({
                "timestamp": datetime.now().isoformat(),
                "step": "insights",
                "message": f"Generating insights from {len(state['insight_requests'])} validated analyses"
            })
            
            # Update status
            state["status"] = "insights"
            
            # Process insight requests
            insight_cards = {}
            visualizations = []
            for request in state["insight_requests"]:
                # Generate insight card
                insight_card = self.insights_agent.generate_insights(request)
                insight_cards[request.request_id] = insight_card
                
                # Generate visualizations for the insight card
                viz_files = self.insights_agent.generate_visualizations(insight_card, state["data_sources"])
                visualizations.extend(viz_files)
            
            # Store insight cards and visualizations in the state
            state["insight_cards"] = insight_cards
            state["visualizations"] = visualizations
            
            # Update status for completion
            state["status"] = "complete"
            
            # Log completion
            state["logs"].append({
                "timestamp": datetime.now().isoformat(),
                "step": "complete",
                "message": f"Analysis workflow completed with {len(insight_cards)} insight cards"
            })
            
            return state
        except Exception as e:
            # Handle error
            state["status"] = "error"
            state["error"] = f"Insights error: {str(e)}"
            return state
    
    def handle_error_node(self, state: WorkflowState) -> WorkflowState:
        """Error handling node"""
        # Log the error
        state["logs"].append({
            "timestamp": datetime.now().isoformat(),
            "step": "error",
            "message": f"Workflow error: {state['error']}"
        })
        
        return state

# For testing
if __name__ == "__main__":
    # Configure logging to show all details
    logging.basicConfig(level=logging.DEBUG)
    
    # Set API key for testing
    os.environ["ANTHROPIC_API_KEY"] = "your_api_key_here"
    
    try:
        # Create workflow
        workflow = SalesAnalysisWorkflow(db_path="data/pharma_db.sqlite")
        
        # Run workflow with test alert
        alert = "Sales of DrugX down 15% in Northeast region over past 30 days compared to forecast."
        result = workflow.run_workflow(alert)
        
        # Print workflow results
        print(f"Workflow status: {result['status']}")
        if result['status'] == "error":
            print(f"Error: {result['error']}")
        else:
            print(f"Generated {len(result.get('insight_cards', {}))} insight cards")
            print(f"Generated {len(result.get('visualizations', []))} visualizations")
    
    except Exception as e:
        print(f"Test run failed: {e}")
        print(traceback.format_exc())