feat: Add JiraAnalysisResponse model and update handlers to use it for analysis record serialization

api/handlers.py

@@ -2,7 +2,7 @@ from fastapi import APIRouter, Request, HTTPException, Depends
 from fastapi.responses import JSONResponse
 from typing import Dict, Any
 import config
-from llm.models import LLMResponse, JiraWebhookPayload
+from llm.models import LLMResponse, JiraWebhookPayload, JiraAnalysisResponse
 from database.database import get_db_session  # Removed Session import here
 from sqlalchemy.orm import Session  # Added correct SQLAlchemy import
 from database.crud import get_all_analysis_records, delete_all_analysis_records, get_analysis_by_id, create_analysis_record
@@ -86,7 +86,4 @@ async def get_analysis_record_endpoint(record_id: int, db: Session = Depends(get
     record = get_analysis_by_id(db, record_id)
     if not record:
         raise HTTPException(status_code=404, detail="Analysis record not found")
-    return JSONResponse(
+    return JiraAnalysisResponse.model_validate(record)
-        status_code=200,
-        content=record.dict()  # Ensure proper data serialization
-    )

llm/models.py

@@ -53,4 +53,19 @@ class AnalysisFlags(BaseModel):
                     }
                 )
             except Exception as e:
-                logger.error(f"Failed to track model usage: {e}")
+                logger.error(f"Failed to track model usage: {e}")
+from pydantic import BaseModel, Field
+from datetime import datetime
+
+class JiraAnalysisResponse(BaseModel):
+    model_config = ConfigDict(from_attributes=True)
+    id: int
+    issue_key: str
+    status: str
+    issue_summary: str
+    request_payload: dict
+    analysis_result: Optional[dict] = None
+    created_at: datetime
+    updated_at: datetime
+    error_message: Optional[str] = None
+    raw_response: Optional[dict] = None