Merge branch 'main' of https://code.sdsdev.co.kr/SDSRV-IDP/sbt-idp into feature/inference-ui

cope2n-api/fwd_api/celery_worker/internal_task.py

@@ -194,10 +194,12 @@ def process_pdf(rq_id, sub_id, p_type, user_id, files):
             for j in range(len(_b_urls)):
                 _b_urls[j]["doc_type"] = file["file_type"]
                 _b_urls[j]["page_number"] = idx
+                _b_urls[j]["index_to_image_type"] = file["index_in_request"]      
             return idx, _b_urls[0]
         elif extension in image_extensions:
             this_url = ProcessUtil.process_image_local_file(file["file_name"], file["file_path"], new_request, user, file["file_type"], file["index_in_request"])[0]
             this_url["page_number"] = idx
+            this_url["index_to_image_type"] = file["index_in_request"]
             if file["file_type"]:   
                 this_url["doc_type"] = file["file_type"]
             return idx, this_url
@@ -222,6 +224,7 @@ def process_pdf(rq_id, sub_id, p_type, user_id, files):
         file_meta["ai_inference_profile"] = {}
         file_meta["index_in_request"] = i
         file_meta["preprocessing_time"] = preprocessing_time
+        file_meta["index_to_image_type"] = b_url["index_to_image_type"]
         to_queue.append((fractorized_request_id, sub_id, [b_url], user_id, p_type, file_meta))
 
     # Send to next queue

cope2n-api/fwd_api/celery_worker/process_result_tasks.py

@@ -8,7 +8,7 @@ from copy import deepcopy
 from fwd_api.celery_worker.worker import app
 from fwd_api.models import SubscriptionRequest
 from fwd_api.exception.exceptions import InvalidException
-from fwd_api.models import SubscriptionRequest
+from fwd_api.models import SubscriptionRequest, SubscriptionRequestFile
 from fwd_api.constant.common import ProcessType
 from fwd_api.utils.redis import RedisUtils
 from fwd_api.utils import process as ProcessUtil
@@ -147,9 +147,11 @@ def process_invoice_sbt_result(rq_id, result, metadata):
         rq_id = rq_id.split("_sub_")[0]
         rq: SubscriptionRequest = SubscriptionRequest.objects.filter(request_id=rq_id).first()
 
-
+        image_type = metadata["doc_type"]
+        index_in_request = metadata.pop("index_to_image_type", 0)
         result["metadata"] = metadata
-        # status = to_status(result)
+        _update_subscription_rq_file(request_id=rq, index_in_request=index_in_request, doc_type=image_type, result=result)
+
         status = result.get("status", 200)
         redis_client.set_cache(rq_id, page_index, result)
         done = rq.pages == redis_client.get_size(rq_id)
@@ -171,12 +173,10 @@ def process_invoice_sbt_result(rq_id, result, metadata):
                 rq.preprocessing_time = result.get("metadata", {}).get("preprocessing_time", 0) # advancing the last result
                 rq.ai_inference_time = time.time() - rq.ai_inference_start_time
                 rq.save()
-
         else:
             rq.status = 404 # stop waiting
             rq.predict_result = result
             rq.save()
-
         update_user(rq)
     except IndexError as e:
         print(e)
@@ -191,3 +191,45 @@ def process_invoice_sbt_result(rq_id, result, metadata):
         rq.save()
         return "FailInvoice"
     
+
+def _update_subscription_rq_file(request_id, index_in_request, doc_type, result):
+    image = SubscriptionRequestFile.objects.filter(request=request_id, index_in_request=index_in_request, doc_type=doc_type).first()
+
+    retailer_name = None
+    sold_to_party = None
+    purchase_date = []
+    imei_number = []
+    predicted_res = __get_actual_predict_result(result=result)
+    if len(predicted_res)!=0:
+        for elem in predicted_res:
+            if elem["label"] == "retailername":
+                retailer_name = elem['value']
+            elif elem["label"] == "sold_to_party":
+                sold_to_party = elem['value']
+            elif elem["label"] == "purchase_date":
+                purchase_date = elem['value']
+            else:
+                imei_number = elem['value']
+    if doc_type=='invoice':
+        _predict_result = {
+            "retailername": retailer_name, 
+            "sold_to_party": sold_to_party, 
+            "purchase_date": purchase_date, 
+            "imei_number": [] 
+            }
+    else:
+        _predict_result = {
+            "retailername": None, 
+            "sold_to_party": None, 
+            "purchase_date": [], 
+            "imei_number": imei_number 
+            }
+    image.predict_result = _predict_result
+    image.save()
+
+def __get_actual_predict_result(result: dict):
+    predicted_res = result.get('content', {}).get('document', [])
+    if len(predicted_res)==0:
+        return []
+    predicted_res = predicted_res[0].get('content', [])
+    return predicted_res