edit : 이미지생성 api 생성갯수 삭제, 이미지생성 api 데이터를 return해주는 api 추가, 입력이미지 입력받아 검색하는 api 추가

main_rest/app/routes/services.py

@@ -17,7 +17,7 @@ from typing import Annotated, List
 from main_rest.app.common import consts
 from main_rest.app import models as M
 from main_rest.app.utils.date_utils import D
-from main_rest.app.utils.parsing_utils import image_to_base64_string
+from main_rest.app.utils.parsing_utils import image_to_base64_string,save_base64_as_image_file
 from custom_logger.main_log import main_logger as LOG
 
 # from custom_apps.bingimagecreator.utils import DallEArgument,dalle3_generate_image
@@ -123,22 +123,16 @@ router = APIRouter(prefix="/services")
 #         LOG.error(traceback.format_exc())
 #         return response.set_error(e)
     
-@router.post("/imageGenerate/imagen", summary="이미지 생성(AI) - imagen", response_model=M.ImageGenerateRes)
+@router.post("/imageGenerate/imagen", summary="이미지 생성(AI) - imagen", response_model=M.ResponseBase)
 async def imagen(request: Request, request_body_info: M.ImageGenerateReq):
     """
     ## 이미지 생성(AI) - imagen
     > imagen AI를 이용하여 이미지 생성
-    
-    
     """
     # imagen 사용중단 gemini로 변경
     
-    response = M.ImageGenerateRes()
+    response = M.ResponseBase()
     try:
-        
-        if not download_range(request_body_info.downloadCount):
-            raise Exception(f"downloadCount is 1~4 (current value = {request_body_info.downloadCount})")
-        
         # NOTE(JWKIM) : imagen 사용 중단
         # img_length = imagen_generate_image(prompt=request_body_info.prompt,
         #                       download_count=request_body_info.downloadCount
@@ -162,7 +156,44 @@ async def imagen(request: Request, request_body_info: M.ImageGenerateReq):
                 os.remove(temp_image_path)
                 del temp_image_path
         
-        return response.set_message(img_len=1)
+        return response.set_message()
+    
+    except Exception as e:
+        LOG.error(traceback.format_exc())
+        
+        # Clean up temporary files
+        if 'query_image_path' in locals():
+            if os.path.exists(query_image_path):
+                os.remove(query_image_path)
+                del query_image_path
+        
+        return response.set_error(error=e)
+    
+@router.post("/imageGenerate/imagen/data", summary="이미지 생성(AI) - imagen(data)", response_model=M.ImageGenerateDataRes)
+async def imagen_data(request: Request, request_body_info: M.ImageGenerateReq):
+    """
+    ## 이미지 생성(AI) - imagen
+    > imagen AI를 이용하여 이미지 데이터생성
+    """
+    # imagen 사용중단 gemini로 변경
+    
+    response = M.ImageGenerateDataRes()
+    try:
+        # NOTE(JWKIM) : imagen 사용 중단
+        # img_length = imagen_generate_image(prompt=request_body_info.prompt,
+        #                       download_count=request_body_info.downloadCount
+        #                       )
+        temp_image_path = gemini_image(request_body_info.prompt)
+        
+        b64data = image_to_base64_string(temp_image_path)
+        
+        # Clean up temporary files
+        if 'temp_image_path' in locals():
+            if os.path.exists(temp_image_path):
+                os.remove(temp_image_path)
+                del temp_image_path
+        
+        return response.set_message(b64data)
     
     except Exception as e:
         LOG.error(traceback.format_exc())
@@ -231,9 +262,6 @@ async def vactor_vit(request: Request, request_body_info: M.VectorImageSearchVit
     ## 벡터 이미지 검색(clip-vit) - imagen
     > imagen AI를 이용하여 이미지 생성 후 vector 검색 그후 결과 이미지 생성
     
-    ### Requriements
-    > - googlecli 설치(https://cloud.google.com/sdk/docs/install?hl=ko#linux)
-    
     ### options
     > - modelType -> b32,b16,l14,l14_336
     > - indexType -> l2,cos
@@ -311,14 +339,11 @@ async def vactor_vit(request: Request, request_body_info: M.VectorImageSearchVit
         return response.set_error(error=e)
     
 @router.post("/vectorImageSearch/vit/imageGenerate/imagen/data", summary="벡터 이미지 검색(clip-vit) - imagen(data)", response_model=M.VectorImageSerachDataRes)
-async def vactor_vit_report_data(request: Request, request_body_info: M.VectorImageSearchVitDataReq):
+async def vactor_vit_data(request: Request, request_body_info: M.VectorImageSearchVitDataReq):
     """
     ## 벡터 이미지 검색(clip-vit) - imagen
     > imagen AI를 이용하여 이미지 생성 후 vector 검색 그후 결과 이미지데이터 return
     
-    ### Requriements
-    > - googlecli 설치(https://cloud.google.com/sdk/docs/install?hl=ko#linux)
-    
     ### options
     > - modelType -> b32,b16,l14,l14_336
     > - indexType -> l2,cos
@@ -389,6 +414,82 @@ async def vactor_vit_report_data(request: Request, request_body_info: M.VectorIm
                 del query_image_path
                 
         return response.set_error(error=e)
+
+
+@router.post("/vectorImageSearch/vit/inputImage/data", summary="벡터 이미지 검색(clip-vit) - input image(data)", response_model=M.VectorImageSerachDataRes)
+async def vactor_vit_input_img_data(request: Request, request_body_info: M.VectorImageSearchVitInputImgReq):
+    """
+    ## 벡터 이미지 검색(clip-vit) - inputimage
+    > 입력된 이미지로 vector 검색 그후 결과 이미지데이터 return
+    
+    ### Requriements
+    > - googlecli 설치(https://cloud.google.com/sdk/docs/install?hl=ko#linux)
+    
+    ### options
+    > - modelType -> b32,b16,l14,l14_336
+    > - indexType -> l2,cos
+    
+    """
+    response = M.VectorImageSerachDataRes()
+    query_image_data = ''
+    
+    try: 
+        if request_body_info.modelType not in [M.VitModelType.b32, M.VitModelType.b16, M.VitModelType.l14, M.VitModelType.l14_336]:
+            raise Exception(f"modelType is invalid (current value = {request_body_info.modelType})")
+        
+        if request_body_info.indexType not in [M.VitIndexType.cos, M.VitIndexType.l2]:
+            raise Exception(f"indexType is invalid (current value = {request_body_info.indexType})")
+        
+        query_image_path = os.path.join(TEMP_FOLDER, f'input_{D.date_file_name()}_query.png')
+        save_base64_as_image_file(request_body_info.inputImage ,query_image_path)
+               
+        vector_request_data = {'query_image_path' : query_image_path,
+                               'index_type' : request_body_info.indexType, 
+                               'model_type' : request_body_info.modelType,
+                               'search_num' : request_body_info.searchNum}
+
+        vector_response = requests.post('http://localhost:51002/api/services/faiss/vector/search/vit', data=json.dumps(vector_request_data))
+        
+        vector_response_dict = json.loads(vector_response.text)
+        
+        if vector_response.status_code != 200:
+            raise Exception(f"response error: {vector_response_dict['error']}")
+        
+        if vector_response_dict["error"] != None:
+            raise Exception(f"vector error: {vector_response_dict['error']}")
+        
+        result_image_paths = vector_response_dict.get('img_list').get('result_image_paths')
+        result_percents = vector_response_dict.get('img_list').get('result_percents')
+        
+        # 이미지 데이터 생성
+        vector_image_results = []
+        for img, percents in zip(result_image_paths, result_percents):
+            b64_data = image_to_base64_string(img)
+            float_percent = float(percents)
+            
+            info = M.VectorImageResult(image=b64_data,percents=float_percent)
+            
+            vector_image_results.append(info)
+            
+        # Clean up temporary files
+        if 'query_image_path' in locals():
+            if os.path.exists(query_image_path):
+                os.remove(query_image_path)
+                del query_image_path
+        
+        return response.set_message(vector_result=vector_image_results,query_img=query_image_data)
+    
+    except Exception as e:
+        LOG.error(traceback.format_exc())
+        
+        # Clean up temporary files
+        if 'query_image_path' in locals():
+            if os.path.exists(query_image_path):
+                os.remove(query_image_path)
+                del query_image_path
+                
+        return response.set_error(error=e)
+
  
 @router.post("/vectorImageSearch/vit/imageGenerate/imagen/report", summary="벡터 이미지 검색(clip-vit) - imagen, report 생성", response_model=M.ResponseBase)
 async def vactor_vit_report(request: Request, request_body_info: M.VectorImageSearchVitReportReq):