Create data_service.py

data_service.py

@@ -0,0 +1,90 @@
+# data_service.py
+from typing import Dict, Any
+from data_structures import WEB_DATA_REPORTS
+from gpt_analyzer import GPTAnalyzer
+
+class DataAssessmentService:
+    def __init__(self, api_key: str):
+        self.analyzer = GPTAnalyzer(api_key)
+        self.web_data = WEB_DATA_REPORTS
+
+    def check_data_availability(self, analysis_result: dict) -> dict:
+        availability = {
+            "available_in_webdata": [],
+            "needs_datalake": [],
+            "not_available": [],
+            "access_instructions": []
+        }
+
+        for required in analysis_result.get("required_reports", []):
+            category = required["category"]
+            report_type = required["report_type"]
+
+            if category in self.web_data:
+                matching_reports = []
+                for report_name, report_details in self.web_data[category].items():
+                    required_fields = set(required.get("fields_needed", []))
+                    available_fields = set(report_details["fields"].keys())
+
+                    if required_fields.issubset(available_fields):
+                        matching_reports.append({
+                            "report_name": report_name,
+                            "description": report_details["description"],
+                            "access_path": f"/web-data/{category.lower()}/{report_name}",
+                            "filters": report_details["filters"]
+                        })
+
+                if matching_reports:
+                    availability["available_in_webdata"].extend(matching_reports)
+                    availability["access_instructions"].append(
+                        f"Access {category} data through Web Data portal using filters: "
+                        f"{', '.join(matching_reports[0]['filters'])}"
+                    )
+                else:
+                    availability["needs_datalake"].append({
+                        "category": category,
+                        "report_type": report_type,
+                        "reason": "Required fields not available in Web Data"
+                    })
+            else:
+                availability["not_available"].append({
+                    "category": category,
+                    "report_type": report_type,
+                    "reason": "Category not found in Web Data"
+                })
+
+        return availability
+
+    def assess_request(self, request_text: str) -> Dict[str, Any]:
+        # 1. Analyze the request
+        analysis = self.analyzer.analyze_request(request_text, list(self.web_data.keys()))
+        if "error" in analysis:
+            return {"status": "error", "message": analysis["error"]}
+
+        # 2. Check data availability
+        availability = self.check_data_availability(analysis)
+
+        # 3. Generate response
+        response = {
+            "status": "success",
+            "request_analysis": {
+                "interpretation": analysis["interpretation"],
+                "confidence": analysis["confidence_score"]
+            },
+            "data_availability": {
+                "available_reports": availability["available_in_webdata"],
+                "access_instructions": availability["access_instructions"]
+            }
+        }
+
+        if availability["needs_datalake"]:
+            response["data_lake_requirements"] = {
+                "reports_needed": availability["needs_datalake"],
+                "estimated_processing_time": "2-3 business days",
+                "requires_it_support": True
+            }
+
+        if availability["not_available"]:
+            response["unavailable_data"] = availability["not_available"]
+
+        return response