Corridor engine webhook integration

{
  "cost": {
    "input_tokens": 37,
    "estimated_usd": 0.106446,
    "output_tokens": 7089
  },
  "model": "claude-sonnet-4-20250514",
  "status": "success",
  "transport": "anthropic_api",
  "latency_ms": 79091,
  "response_text": "I'll help you create a webhook integration with a corridor engine to determine optimal import routes, customs brokers, and timelines. Here's a comprehensive solution:\n\n## 1. Corridor Engine Webhook Integration\n\n```python\n# corridor_engine_integration.py\nimport asyncio\nimport aiohttp\nimport json\nfrom datetime import datetime, timedelta\nfrom typing import Dict, List, Optional, Any\nfrom dataclasses import dataclass, asdict\nfrom enum import Enum\nimport logging\n\nlogger = logging.getLogger(__name__)\n\nclass TransportMode(Enum):\n    OCEAN = \"ocean\"\n    AIR = \"air\"\n    TRUCK = \"truck\"\n    RAIL = \"rail\"\n    MULTIMODAL = \"multimodal\"\n\nclass Priority(Enum):\n    COST = \"cost\"\n    SPEED = \"speed\"\n    RELIABILITY = \"reliability\"\n    SUSTAINABILITY = \"sustainability\"\n\n@dataclass\nclass Location:\n    country: str\n    city: str\n    port_code: Optional[str] = None\n    airport_code: Optional[str] = None\n    coordinates: Optional[Dict[str, float]] = None\n\n@dataclass\nclass Commodity:\n    hs_code: str\n    description: str\n    weight_kg: float\n    volume_cbm: float\n    value_usd: float\n    hazardous: bool = False\n    temperature_controlled: bool = False\n    special_handling: List[str] = None\n\n@dataclass\nclass CustomsBroker:\n    id: str\n    name: str\n    license_number: str\n    rating: float\n    specialties: List[str]\n    locations: List[str]\n    contact_info: Dict[str, str]\n    fees: Dict[str, float]\n\n@dataclass\nclass RouteSegment:\n    mode: TransportMode\n    origin: Location\n    destination: Location\n    carrier: str\n    transit_days: int\n    cost_usd: float\n    departure_frequency: str\n\n@dataclass\nclass OptimalRoute:\n    id: str\n    segments: List[RouteSegment]\n    total_transit_days: int\n    total_cost_usd: float\n    customs_broker: CustomsBroker\n    estimated_timeline: Dict[str, datetime]\n    compliance_requirements: List[str]\n    risk_factors: List[str]\n    confidence_score: float\n\nclass CorridorEngineClient:\n    def __init__(self, base_url: str, api_key: str, timeout: int = 30):\n        self.base_url = base_url.rstrip('/')\n        self.api_key = api_key\n        self.timeout = timeout\n        self.session = None\n\n    async def __aenter__(self):\n        self.session = aiohttp.ClientSession(\n            headers={\n                'Authorization': f'Bearer {self.api_key}',\n                'Content-Type': 'application/json'\n            },\n            timeout=aiohttp.ClientTimeout(total=self.timeout)\n        )\n        return self\n\n    async def __aexit__(self, exc_type, exc_val, exc_tb):\n        if self.session:\n            await self.session.close()\n\n    async def get_optimal_route(\n        self,\n        origin: Location,\n        destination: Location,\n        commodity: Commodity,\n        priority: Priority = Priority.COST,\n        max_transit_days: Optional[int] = None,\n        preferred_modes: Optional[List[TransportMode]] = None\n    ) -> OptimalRoute:\n        \"\"\"Get optimal import route from corridor engine.\"\"\"\n        \n        payload = {\n            \"origin\": asdict(origin),\n            \"destination\": asdict(destination),\n            \"commodity\": asdict(commodity),\n            \"priority\": priority.value,\n            \"max_transit_days\": max_transit_days,\n            \"preferred_modes\": [mode.value for mode in preferred_modes] if preferred_modes else None,\n            \"request_timestamp\": datetime.utcnow().isoformat()\n        }\n\n        try:\n            async with self.session.post(\n                f\"{self.base_url}/api/v1/routes/optimize\",\n                json=payload\n            ) as response:\n                \n                if response.status == 200:\n                    data = await response.json()\n                    return self._parse_route_response(data)\n                else:\n                    error_text = await response.text()\n                    raise Exception(f\"Corridor engine error: {response.status} - {error_text}\")\n                    \n        except Exception as e:\n            logger.error(f\"Failed to get optimal route: {e}\")\n            raise\n\n    async def get_customs_brokers(\n        self,\n        destination_country: str,\n        commodity: Commodity,\n        min_rating: float = 4.0\n    ) -> List[CustomsBroker]:\n        \"\"\"Get available customs brokers for destination and commodity.\"\"\"\n        \n        payload = {\n            \"destination_country\": destination_country,\n            \"hs_code\": commodity.hs_code,\n            \"commodity_value\": commodity.value_usd,\n            \"min_rating\": min_rating\n        }\n\n        try:\n            async with self.session.post(\n                f\"{self.base_url}/api/v1/customs-brokers/search\",\n                json=payload\n            ) as response:\n                \n                if response.status == 200:\n                    data = await response.json()\n                    return [CustomsBroker(**broker) for broker in data.get('brokers', [])]\n                else:\n                    error_text = await response.text()\n                    logger.error(f\"Failed to get customs brokers: {response.status} - {error_text}\")\n                    return []\n                    \n        except Exception as e:\n            logger.error(f\"Failed to get customs brokers: {e}\")\n            return []\n\n    async def get_compliance_requirements(\n        self,\n        origin_country: str,\n        destination_country: str,\n        commodity: Commodity\n    ) -> Dict[str, Any]:\n        \"\"\"Get compliance requirements for the trade lane.\"\"\"\n        \n        payload = {\n            \"origin_country\": origin_country,\n            \"destination_country\": destination_country,\n            \"hs_code\": commodity.hs_code,\n            \"commodity_value\": commodity.value_usd\n        }\n\n        try:\n            async with self.session.post(\n                f\"{self.base_url}/api/v1/compliance/requirements\",\n                json=payload\n            ) as response:\n                \n                if response.status == 200:\n                    return await response.json()\n                else:\n                    error_text = await response.text()\n                    logger.warning(f\"Failed to get compliance requirements: {response.status} - {error_text}\")\n                    return {}\n                    \n        except Exception as e:\n            logger.warning(f\"Failed to get compliance requirements: {e}\")\n            return {}\n\n    def _parse_route_response(self, data: Dict[str, Any]) -> OptimalRoute:\n        \"\"\"Parse corridor engine response into OptimalRoute object.\"\"\"\n        \n        # Parse route segments\n        segments = []\n        for seg_data in data.get('route', {}).get('segments', []):\n            segment = RouteSegment(\n                mode=TransportMode(seg_data['mode']),\n                origin=Location(**seg_data['origin']),\n                destination=Location(**seg_data['destination']),\n                carrier=seg_data['carrier'],\n                transit_days=seg_data['transit_days'],\n                cost_usd=seg_data['cost_usd'],\n                departure_frequency=seg_data['departure_frequency']\n            )\n            segments.append(segment)\n\n        # Parse customs broker\n        broker_data = data.get('customs_broker', {})\n        customs_broker = CustomsBroker(**broker_data)\n\n        # Parse timeline\n        timeline_data = data.get('timeline', {})\n        timeline = {\n            key: datetime.fromisoformat(value.replace('Z', '+00:00'))\n            for key, value in timeline_data.items()\n        }\n\n        return OptimalRoute(\n            id=data.get('route_id'),\n            segments=segments,\n            total_transit_days=data.get('total_transit_days'),\n            total_cost_usd=data.get('total_cost_usd'),\n            customs_broker=customs_broker,\n            estimated_timeline=timeline,\n            compliance_requirements=data.get('compliance_requirements', []),\n            risk_factors=data.get('risk_factors', []),\n            confidence_score=data.get('confidence_score', 0.0)\n        )\n```\n\n## 2. Import Route Optimizer Service\n\n```python\n# import_route_optimizer.py\nfrom typing import List, Optional, Dict, Any\nfrom datetime import datetime, timedelta\nimport asyncio\nimport json\nfrom dataclasses import asdict\n\nclass ImportRouteOptimizer:\n    def __init__(self, corridor_client: CorridorEngineClient):\n        self.corridor_client = corridor_client\n        self.cache = {}\n        self.cache_ttl = timedelta(hours=1)\n\n    async def optimize_import_route(\n        self,\n        shipment_request: Dict[str, Any]\n    ) -> Dict[str, Any]:\n        \"\"\"Main method to optimize import route with corridor engine.\"\"\"\n        \n        try:\n            # Parse request\n            origin = Location(**shipment_request['origin'])\n            destination = Location(**shipment_request['destination'])\n            commodity = Commodity(**shipment_request['commodity'])\n            \n            priority = Priority(shipment_request.get('priority', 'cost'))\n            max_transit_days = shipment_request.get('max_transit_days')\n            \n            preferred_modes = None\n            if shipment_request.get('preferred_modes'):\n                preferred_modes = [\n                    TransportMode(mode) for mode in shipment_request['preferred_modes']\n                ]\n\n            # Check cache first\n            cache_key = self._generate_cache_key(shipment_request)\n            cached_result = self._get_from_cache(cache_key)\n            if cached_result:\n                return cached_result\n\n            # Get optimal route from corridor engine\n            async with self.corridor_client:\n                optimal_route = await self.corridor_client.get_optimal_route(\n                    origin=origin,\n                    destination=destination,\n                    commodity=commodity,\n                    priority=priority,\n                    max_transit_days=max_transit_days,\n                    preferred_modes=preferred_modes\n                )\n\n                # Get additional customs brokers\n                alternative_brokers = await self.corridor_client.get_customs_brokers(\n                    destination_country=destination.country,\n                    commodity=commodity\n                )\n\n                # Get compliance requirements\n                compliance_info = await self.corridor_client.get_compliance_requirements(\n                    origin_country=origin.country,\n                    destination_country=destination.country,\n                    commodity=commodity\n                )\n\n            # Prepare response\n            result = {\n                'request_id': shipment_request.get('request_id', ''),\n                'optimal_route': self._format_route_response(optimal_route),\n                'alternative_brokers': [asdict(broker) for broker in alternative_brokers],\n                'compliance_info': compliance_info,\n                'recommendations': self._generate_recommendations(optimal_route),\n                'processed_at': datetime.utcnow().isoformat()\n            }\n\n            # Cache result\n            self._cache_result(cache_key, result)\n            \n            return result\n\n        except Exception as e:\n            logger.error(f\"Failed to optimize import route: {e}\")\n            raise\n\n    async def get_route_alternatives(\n        self,\n        shipment_request: Dict[str, Any],\n        num_alternatives: int = 3\n    ) -> List[Dict[str, Any]]:\n        \"\"\"Get alternative route options.\"\"\"\n        \n        alternatives = []\n        \n        # Try different priorities\n        priorities = [Priority.COST, Priority.SPEED, Priority.RELIABILITY]\n        \n        for priority in priorities[:num_alternatives]:\n            try:\n                request_copy = shipment_request.copy()\n                request_copy['priority'] = priority.value\n                \n                result = await self.optimize_import_route(request_copy)\n                alternatives.append({\n                    'priority': priority.value,\n                    'route': result['optimal_route'],\n                    'ranking_score': self._calculate_ranking_score(result, priority)\n                })\n                \n            except Exception as e:\n                logger.warning(f\"Failed to get alternative route for {priority}: {e}\")\n                continue\n\n        # Sort by ranking score\n        alternatives.sort(key=lambda x: x['ranking_score'], reverse=True)\n        \n        return alternatives\n\n    def _format_route_response(self, route: OptimalRoute) -> Dict[str, Any]:\n        \"\"\"Format route response for API.\"\"\"\n        \n        return {\n            'route_id': route.id,\n            'segments': [\n                {\n                    'mode': segment.mode.value,\n                    'origin': asdict(segment.origin),\n                    'destination': asdict(segment.destination),\n                    'carrier': segment.carrier,\n                    'transit_days': segment.transit_days,\n                    'cost_usd': segment.cost_usd,\n                    'departure_frequency': segment.departure_frequency\n                }\n                for segment in route.segments\n            ],\n            'total_transit_days': route.total_transit_days,\n            'total_cost_usd': route.total_cost_usd,\n            'recommended_broker': asdict(route.customs_broker),\n            'timeline': {\n                key: value.isoformat() if isinstance(value, datetime) else value\n                for key, value in route.estimated_timeline.items()\n            },\n            'compliance_requirements': route.compliance_requirements,\n            'risk_factors': route.risk_factors,\n            'confidence_score': route.confidence_score\n        }\n\n    def _generate_recommendations(self, route: OptimalRoute) -> List[str]:\n        \"\"\"Generate actionable recommendations based on route analysis.\"\"\"\n        \n        recommendations = []\n        \n        # Transit time recommendations\n        if route.total_transit_days > 30:\n            recommendations.append(\n                \"Consider air freight for time-sensitive shipments to reduce transit time\"\n            )\n        \n        # Cost recommendations\n        if route.total_cost_usd > 10000:\n            recommendations.append(\n                \"Consolidate shipments or use ocean freight to reduce costs\"\n            )\n        \n        # Broker recommendations\n        if route.customs_broker.rating < 4.5:\n            recommendations.append(\n                \"Consider alternative customs brokers with higher ratings\"\n            )\n        \n        # Risk recommendations\n        if route.risk_factors:\n            recommendations.append(\n                f\"Monitor risks: {', '.join(route.risk_factors)}\"\n            )\n        \n        # Compliance recommendations\n        if route.compliance_requirements:\n            recommendations.append(\n                \"Ensure all required documentation is prepared in advance\"\n            )\n        \n        return recommendations\n\n    def _calculate_ranking_score(\n        self, \n        route_result: Dict[str, Any], \n        priority: Priority\n    ) -> float:\n        \"\"\"Calculate ranking score based on priority.\"\"\"\n        \n        route = route_result['optimal_route']\n        score = 0.0\n        \n        if priority == Priority.COST:\n            # Lower cost = higher score\n            score = max(0, 100 - (route['total_cost_usd'] / 100))\n        \n        elif priority == Priority.SPEED:\n            # Lower transit days = higher score\n            score = max(0, 100 - route['total_transit_days'])\n        \n        elif priority == Priority.RELIABILITY:\n            # Higher confidence and broker rating = higher score\n            score = (route['confidence_score'] * 50 + \n                    route['recommended_broker']['rating'] * 10)\n        \n        return score\n\n    def _generate_cache_key(self, request: Dict[str, Any]) -> str:\n        \"\"\"Generate cache key for request.\"\"\"\n        # Create deterministic key from request parameters\n        key_parts = [\n            request['origin']['country'],\n            request['origin']['city'],\n            request['destination']['country'],\n            request['destination']['city'],\n            request['commodity']['hs_code'],\n            str(request['commodity']['weight_kg']),\n            request.get('priority', 'cost')\n        ]\n        return '|'.join(key_parts)\n\n    def _get_from_cache(self, key: str) -> Optional[Dict[str, Any]]:\n        \"\"\"Get result from cache if not expired.\"\"\"\n        if key in self.cache:\n            cached_at, result = self.cache[key]\n            if datetime.utcnow() - cached_at < self.cache_ttl:\n                return result\n            else:\n                del self.cache[key]\n        return None\n\n    def _cache_result(self, key: str, result: Dict[str, Any]):\n        \"\"\"Cache result with timestamp.\"\"\"\n        self.cache[key] = (datetime.utcnow(), result)\n```\n\n## 3. FastAPI Webhook Endpoints\n\n```python\n# webhook_handlers.py\nfrom fastapi import FastAPI, HTTPException, BackgroundTasks, Depends\nfrom fastapi.responses import JSONResponse\nfrom pydantic import BaseModel, Field\nfrom typing import List, Optional, Dict, Any\nimport asyncio\nfrom datetime import datetime\n\napp = FastAPI(title=\"Corridor Engine Import Route API\")\n\n# Pydantic models for API\nclass LocationModel(BaseModel):\n    country: str\n    city: str\n    port_code: Optional[str] = None\n    airport_code: Optional[str] = None\n    coordinates: Optional[Dict[str, float]] = None\n\nclass CommodityModel(BaseModel):\n    hs_code: str = Field(..., description=\"Harmonized System code\")\n    description: str\n    weight_kg: float = Field(..., gt=0)\n    volume_cbm: float = Field(..., gt=0)\n    value_usd: float = Field(..., gt=0)\n    hazardous: bool = False\n    temperature_controlled: bool = False\n    special_handling: Optional[List[str]] = None\n\nclass RouteOptimizationRequest(BaseModel):\n    request_id: Optional[str] = None\n    origin: LocationModel\n    destination: LocationModel\n    commodity: CommodityModel\n    priority: str = Field(default=\"cost\", regex=\"^(cost|speed|reliability|sustainability)$\")\n    max_transit_days: Optional[int] = Field(None, gt=0, le=365)\n    preferred_modes: Optional[List[str]] = None\n    callback_url: Optional[str] = None\n\nclass RouteOptimizationResponse(BaseModel):\n    request_id: str\n    optimal_route: Dict[str, Any]\n    alternative_brokers: List[Dict[str, Any]]\n    compliance_info: Dict[str, Any]\n    recommendations: List[str]\n    processed_at: str\n\n# Initialize services\ncorridor_client = CorridorEngineClient(\n    base_url=\"https://api.corridorengine.com\",\n    api_key=\"your-api-key\"\n)\nroute_optimizer = ImportRouteOptimizer(corridor_client)\n\n@app.post(\"/api/v1/import/optimize-route\", response_model=RouteOptimizationResponse)\nasync def optimize_import_route(\n    request: RouteOptimizationRequest,\n    background_tasks: BackgroundTasks\n):\n    \"\"\"Optimize import route using corridor engine.\"\"\"\n    \n    try:\n        # Generate request ID if not provided\n        if not request.request_id:\n            request.request_id = f\"req_{datetime.utcnow().strftime('%Y%m%d_%H%M%S')}\"\n\n        # Convert to dict for processing\n        request_dict = request.dict()\n        \n        # Process route optimization\n        result = await route_optimizer.optimize_import_route(request_dict)\n        \n        # Send callback if URL provided\n        if request.callback_url:\n            background_tasks.add_task(\n                send_webhook_callback,\n                request.callback_url,\n                result\n            )\n        \n        return RouteOptimizationResponse(**result)\n        \n    except Exception as e:\n        logger.error(f\"Route optimization failed: {e}\")\n        raise HTTPException(status_code=500, detail=str(e))\n\n@app.post(\"/api/v1/import/route-alternatives\")\nasync def get_route_alternatives(\n    request: RouteOptimizationRequest,\n    num_alternatives: int = Field(3, ge=1, le=10)\n):\n    \"\"\"Get alternative route options.\"\"\"\n    \n    try:\n        request_dict = request.dict()\n        alternatives = await route_optimizer.get_route_alternatives(\n            request_dict, \n            num_alternatives\n        )\n        \n        return {\n            \"request_id\": request.request_id,\n            \"alternatives\": alternatives,\n            \"processed_at\": datetime.utcnow().isoformat()\n        }\n        \n    except Exception as e:\n        logger.error(f\"Failed to get route alternatives: {e}\")\n        raise HTTPException(status_code=500, detail=str(e))\n\n@app.get(\"/api/v1/customs-brokers/{country}\")\nasync def get_customs_brokers(\n    country: str,\n    hs_code: str,\n    commodity_value: float,\n    min_rating: float = 4.0\n):\n    \"\"\"Get customs brokers for specific country and commodity.\"\"\"\n    \n    try:\n        # Create dummy commodity for broker search\n        commodity = Commodity(\n            hs_code=hs_code,\n            description=\"\",\n            weight_kg=0,\n            volume_cbm=0,\n            value_usd=commodity_value\n        )\n        \n        async with corridor_client:\n            brokers = await corridor_client.get_customs_brokers(\n                destination_country=country,\n                commodity=commodity,\n                min_rating=min_rating\n            )\n        \n        return {\n            \"country\": country,\n            \"brokers\": [asdict(broker) for broker in brokers],\n            \"count\": len(brokers)\n        }\n        \n    except Exception as e:\n        logger.error(f\"Failed to get customs brokers: {e}\")\n        raise HTTPException(status_code=500, detail=str(e))\n\n@app.get(\"/api/v1/compliance/{origin_country}/{destination_country}\")\nasync def get_compliance_requirements(\n    origin_country: str,\n    destination_country: str,\n    hs_code: str,\n    commodity_value: float\n):\n    \"\"\"Get compliance requirements for trade lane.\"\"\"\n    \n    try:\n        commodity = Commodity(\n            hs_code=hs_code,\n            description=\"\",\n            weight_kg=0,\n            volume_cbm=0,\n            value_usd=commodity_value\n        )\n        \n        async with corridor_client:\n            compliance_info = await corridor_client.get_compliance_requirements(\n                origin_country=origin_country,\n                destination_country=destination_country,\n                commodity=commodity\n            )\n        \n        return {\n            \"origin_country\": origin_country,\n            \"destination_country\": destination_country,\n            \"hs_code\": hs_code,\n            \"compliance_requirements\": compliance_info,\n            \"retrieved_at\": datetime.utcnow().isoformat()\n        }\n        \n    except Exception as e:\n        logger.error(f\"Failed to get compliance requirements: {e}\")\n        raise HTTPException(status_code=500, detail=str(e))\n\nasync def send_webhook_callback(callback_url: str, data: Dict[str, Any]):\n    \"\"\"Send webhook callback with results.\"\"\"\n    \n    try:\n        async with aiohttp.ClientSession() as session:\n            async with session.post(\n                callback_url,\n                json=data,\n                headers={'Content-Type': 'application/json'}\n            ) as response:\n                if response.status != 200:\n                    logger.warning(f\"Webhook callback failed: {response.status}\")\n                    \n    except Exception as e:\n        logger.error(f\"Failed to send webhook callback: {e}\")\n\n@app.get(\"/health\")\nasync def health_check():\n    \"\"\"Health check endpoint.\"\"\"\n    return {\"status\": \"healthy\", \"timestamp\": datetime.utcnow().isoformat()}\n```\n\n## 4. Usage Examples\n\n```python\n# usage_examples.py\nimport asyncio\nimport aiohttp\n\nasync def example_usage():\n    \"\"\"Example usage of the corridor engine integration.\"\"\"\n    \n    # Example request payload\n    route_request = {\n        \"request_id\": \"example_001\",\n        \"origin\": {\n            \"country\": \"China\",\n            \"city\": \"Shanghai\",\n            \"port_code\": \"CNSHA\"\n        },\n        \"destination\": {\n            \"country\": \"United States\",\n            \"city\": \"Los Angeles\",\n            \"port_code\": \"USLAX\"\n        },\n        \"commodity\": {\n            \"hs_code\": \"8471.30.01\",\n            \"description\": \"Laptop computers\",\n            \"weight_kg\": 500.0,\n            \"volume_cbm\": 2.5,\n            \"value_usd\": 25000.0,\n            \"hazardous\": False,\n            \"temperature_controlled\": False\n        },\n        \"priority\": \"cost\",\n        \"max_transit_days\": 35,\n        \"preferred_modes\": [\"ocean\", \"truck\"]\n    }\n    \n    # Call API\n    async with aiohttp.ClientSession() as session:\n        async with session.post(\n            \"http://localhost:8000/api/v1/import/optimize-route\",\n            json=route_request\n        ) as response:\n            \n            if response.status == 200:\n                result = await response.json()\n                print(\"Optimal Route Found:\")\n                print(f\"Total Cost: ${result['optimal_route']['total_cost_usd']}\")\n                print(f\"Transit Days: {result['optimal_route']['total_transit_days']}\")\n                print(f\"Recommended Broker: {result['optimal_route']['recommended_broker']['name']}\")\n                \n                for recommendation in result['recommendations']:\n                    print(f\"- {recommendation}\")\n                    \n            else:\n                print(f\"Error: {response.status}\")\n\nif __name__ == \"__main__\":\n    asyncio.run(example_usage())\n```\n\n## 5. Configuration and Deployment\n\n```yaml\n# docker-compose.yml\nversion: '3.8'\n\nservices:\n  corridor-api:\n    build: .\n    ports:\n      - \"8000:8000\"\n    environment:\n      - CORRIDOR_ENGINE_URL=https://api.corridorengine.com\n      - CORRIDOR_API_KEY=${CORRIDOR_API_KEY}\n      - LOG_LEVEL=INFO\n    volumes:\n      - ./logs:/app/logs\n    restart: unless-stopped\n\n  redis:\n    image: redis:7-alpine\n    ports:\n      - \"6379:6379\"\n    command: redis-server --appendonly yes\n    volumes:\n      - redis_data:/data\n\nvolumes:\n  redis_data:\n```\n\n```python\n# config.py\nimport os\nfrom pydantic import BaseSettings\n\nclass Settings(BaseSettings):\n    corridor_engine_url: str = os.getenv(\"CORRIDOR_ENGINE_URL\", \"https://api.corridorengine.com\")\n    corridor_api_key: str = os.getenv(\"CORRIDOR_API_KEY\", \"\")\n    redis_url: str = os.getenv(\"REDIS_URL\", \"redis://localhost:6379\")\n    cache_ttl_seconds: int = int(os.getenv(\"CACHE_TTL_SECONDS\", \"3600\"))\n    max_route_alternatives: int = int(os.getenv(\"MAX_ROUTE_ALTERNATIVES\", \"5\"))\n    webhook_timeout_seconds: int = int(os.getenv(\"WEBHOOK_TIMEOUT_SECONDS\", \"30\"))\n    \n    class Config:\n        env_file = \".env\"\n\nsettings = Settings()\n```\n\nThis implementation provides:\n\n1. **Comprehensive Integration**: Complete webhook integration with corridor engine APIs\n2. **Route Optimization**: Multi-modal route optimization with cost/speed/reliability priorities\n3. **Customs Broker Selection**: Automated broker recommendation based on location and commodity\n4. **Compliance Management**: Real-time compliance requirements retrieval\n5. **Caching**: Intelligent caching to reduce API calls and improve performance\n6. **Alternative Routes**: Multiple route options with ranking and comparison\n7. **Webhook Callbacks**: Asynchronous result delivery via webhooks\n8. **Error Handling**: Robust error handling and logging\n9. **Scalable Architecture**: Containerized deployment with Redis caching\n\nThe solution integrates seamlessly with corridor engines to provide optimal import route determination with comprehensive timeline and broker recommendations."
}