Initial WorkWise backend GPU

app/routes/ingest_routes.py

@@ -1,7 +1,9 @@
 """Routes for data ingestion"""
+import os
+import tempfile
 import spaces
-from fastapi import APIRouter, HTTPException
-from app.models.jira_schema import IngestRequest, IngestResponse
+from fastapi import APIRouter, HTTPException, UploadFile, File
+from app.models.jira_schema import IngestResponse
 from app.services.data_ingestion import DataIngestionService
 from app.services.embeddings import embedding_service
 from app.services.vector_store import vector_store
@@ -11,19 +13,41 @@ logger = setup_logger(__name__)
 router = APIRouter()
 
 @router.post("/ingest", response_model=IngestResponse)
-async def ingest_data(request: IngestRequest):
+async def ingest_data(file: UploadFile = File(...)):
     """
-    Ingest Jira data from CSV/JSON file
+    Ingest Jira data from uploaded CSV/JSON file
     
+    - Accepts file upload
     - Parses the file
     - Generates embeddings
-    - Stores in Qdrant vector database
+    - Stores in vector database
     """
+    temp_file_path = None
+    
     try:
-        logger.info(f"Starting ingestion from: {request.file_path}")
+        logger.info(f"Receiving file upload: {file.filename}")
+        
+        # Validate file type
+        if not file.filename.endswith(('.csv', '.json')):
+            raise HTTPException(
+                status_code=400, 
+                detail="Invalid file type. Only CSV and JSON files are supported."
+            )
+        
+        # Create temporary file to store upload
+        suffix = os.path.splitext(file.filename)[1]
+        with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as temp_file:
+            temp_file_path = temp_file.name
+            
+            # Read and write uploaded file content
+            contents = await file.read()
+            temp_file.write(contents)
+            temp_file.flush()
         
-        # Load data
-        records = DataIngestionService.load_data(request.file_path)
+        logger.info(f"File saved temporarily at: {temp_file_path}")
+        
+        # Load data from temporary file
+        records = DataIngestionService.load_data(temp_file_path)
         
         if not records:
             raise HTTPException(status_code=400, detail="No records found in file")
@@ -40,14 +64,25 @@ async def ingest_data(request: IngestRequest):
         # Store vectors
         count = vector_store.upsert_vectors(embeddings, records)
         
-        logger.info(f"Successfully indexed {count} records")
+        logger.info(f"Successfully indexed {count} records from {file.filename}")
         
         return IngestResponse(
             status="success",
             records_indexed=count,
-            message=f"Successfully ingested and indexed {count} Jira tickets"
+            message=f"Successfully ingested and indexed {count} Jira tickets from {file.filename}"
         )
     
+    except HTTPException:
+        raise
     except Exception as e:
         logger.error(f"Ingestion failed: {str(e)}")
         raise HTTPException(status_code=500, detail=str(e))
+    
+    finally:
+        # Clean up temporary file
+        if temp_file_path and os.path.exists(temp_file_path):
+            try:
+                os.unlink(temp_file_path)
+                logger.info(f"Cleaned up temporary file: {temp_file_path}")
+            except Exception as e:
+                logger.warning(f"Failed to delete temporary file: {e}")