edit : imagen -> gemini로 변경, bingimg -> 사용불가 , 벡터검색api 이미지저장이아닌 데이터 전송하는 api 추가 , vactor -> vector 오타 수정

This commit is contained in:
2025-07-30 13:29:24 +09:00
parent 8e28a22825
commit 44bd86562d
45 changed files with 507 additions and 223 deletions

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@@ -9,7 +9,7 @@
@brief: services api
"""
import requests, json, traceback, os
import requests, json, traceback, os, shutil
from fastapi import APIRouter, Depends, Body
from starlette.requests import Request
from typing import Annotated, List
@@ -17,109 +17,111 @@ 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 custom_logger.main_log import main_logger as LOG
from custom_apps.bingimagecreator.utils import DallEArgument,dalle3_generate_image
from custom_apps.bingart.bingart import BingArtGenerator
from custom_apps.imagen.custom_imagen import imagen_generate_image, imagen_generate_image_path, imagen_generate_temp_image_path
from main_rest.app.utils.parsing_utils import download_range
from custom_apps.utils import cookie_manager
from custom_apps.gemini.main import gemini_image
from main_rest.app.utils.parsing_utils import download_range
from utils.custom_sftp import sftp_client
from config import rest_config
from const import TEMP_FOLDER
router = APIRouter(prefix="/services")
@router.post("/bing/cookie/set", summary="bing 관련 쿠키 set", response_model=M.BingCookieSetRes)
async def bing_cookie_set(request: Request, request_body_info: M.BingCookieSetReq):
"""
## Bing cookie set
> 쿠키정보 set
# @router.post("/bing/cookie/set", summary="bing 관련 쿠키 set", response_model=M.BingCookieSetRes)
# async def bing_cookie_set(request: Request, request_body_info: M.BingCookieSetReq):
# """
# ## Bing cookie set
# > 쿠키정보 set
## 정보
> cookie 값이 빈 값일경우 쿠키정보를 set 하지 않고 현재 쿠키값 return 함
> cookie 값이 정상 쿠키 인지는 확인안함
# ## 정보
# > cookie 값이 빈 값일경우 쿠키정보를 set 하지 않고 현재 쿠키값 return 함
# > cookie 값이 정상 쿠키 인지는 확인안함
"""
response = M.BingCookieSetRes()
try:
if len(request_body_info.cookie) == 0:
pass
else:
cookie_manager.set_cookie(request_body_info.cookie)
# """
# response = M.BingCookieSetRes()
# try:
# if len(request_body_info.cookie) == 0:
# pass
# else:
# cookie_manager.set_cookie(request_body_info.cookie)
return response.set_message(current_cookie=cookie_manager.get_cookie())
# return response.set_message(current_cookie=cookie_manager.get_cookie())
except Exception as e:
LOG.error(traceback.format_exc())
return response.set_error(e,current_cookie=cookie_manager.get_cookie())
# except Exception as e:
# LOG.error(traceback.format_exc())
# return response.set_error(e,current_cookie=cookie_manager.get_cookie())
@router.post("/imageGenerate/bingimg", summary="이미지 생성(AI) - bing image generator (DALL-E 3)", response_model=M.ImageGenerateRes)
async def bing_img_generate(request: Request, request_body_info: M.ImageGenerateReq):
"""
## 이미지 생성(AI) - bing image generator (DALL-E 3)
> bing image generator를 이용하여 이미지 생성
# @router.post("/imageGenerate/bingimg", summary="이미지 생성(AI) - bing image generator (DALL-E 3)", response_model=M.ImageGenerateRes)
# async def bing_img_generate(request: Request, request_body_info: M.ImageGenerateReq):
# """
# ## 이미지 생성(AI) - bing image generator (DALL-E 3)
# > bing image generator를 이용하여 이미지 생성
### Requriements
# ### Requriements
## 정보
> 오류 발생시 오류 발생한 파일은 에러 메세지에만 남기고 저장은 안함
> *동작 안함.
# ## 정보
# > 오류 발생시 오류 발생한 파일은 에러 메세지에만 남기고 저장은 안함
"""
response = M.ImageGenerateRes()
try:
if not download_range(request_body_info.downloadCount):
raise Exception(f"downloadCount is 1~4 (current value = {request_body_info.downloadCount})")
# """
# response = M.ImageGenerateRes()
# try:
# if not download_range(request_body_info.downloadCount):
# raise Exception(f"downloadCount is 1~4 (current value = {request_body_info.downloadCount})")
args = DallEArgument(
prompt=request_body_info.prompt,
download_count=request_body_info.downloadCount
)
# args = DallEArgument(
# prompt=request_body_info.prompt,
# download_count=request_body_info.downloadCount
# )
info = dalle3_generate_image(args)
# info = dalle3_generate_image(args)
if info.get_error_messages():
error_message = f"파일생성 error: {info.get_error_messages()}"
LOG.error(error_message)
return response.set_error(error=error_message, img_len=info.get_counter())
# if info.get_error_messages():
# error_message = f"파일생성 error: {info.get_error_messages()}"
# LOG.error(error_message)
# return response.set_error(error=error_message, img_len=info.get_counter())
return response.set_message(img_len=info.get_counter())
# return response.set_message(img_len=info.get_counter())
except Exception as e:
LOG.error(traceback.format_exc())
return response.set_error(e)
# except Exception as e:
# LOG.error(traceback.format_exc())
# return response.set_error(e)
@router.post("/imageGenerate/bingart", summary="이미지 생성(AI) - bing art (DALL-E 3)", response_model=M.ImageGenerateRes)
async def bing_art(request: Request, request_body_info: M.ImageGenerateReq):
"""
## 이미지 생성(AI) - bing art (DALL-E 3)
> bing art를 이용하여 이미지 생성
# @router.post("/imageGenerate/bingart", summary="이미지 생성(AI) - bing art (DALL-E 3)", response_model=M.ImageGenerateRes)
# async def bing_art(request: Request, request_body_info: M.ImageGenerateReq):
# """
# ## 이미지 생성(AI) - bing art (DALL-E 3)
# > bing art를 이용하여 이미지 생성
### Requriements
# ### Requriements
## 정보
> 오류 발생시 오류 발생한 파일은 에러 메세지에만 남기고 저장은 안함
> *동작 안함.
# ## 정보
# > 오류 발생시 오류 발생한 파일은 에러 메세지에만 남기고 저장은 안함
# > *동작 안함.
"""
response = M.ImageGenerateRes()
try:
if not download_range(request_body_info.downloadCount):
raise Exception(f"downloadCount is 1~4 (current value = {request_body_info.downloadCount})")
# """
# response = M.ImageGenerateRes()
# try:
# if not download_range(request_body_info.downloadCount):
# raise Exception(f"downloadCount is 1~4 (current value = {request_body_info.downloadCount})")
bing_art = BingArtGenerator()
# bing_art = BingArtGenerator()
info = bing_art.get_images(prompt=request_body_info.prompt,image_len=request_body_info.downloadCount)
# info = bing_art.get_images(prompt=request_body_info.prompt,image_len=request_body_info.downloadCount)
return response.set_message(img_len=info)
# return response.set_message(img_len=info)
except Exception as e:
LOG.error(traceback.format_exc())
return response.set_error(e)
# except Exception as e:
# LOG.error(traceback.format_exc())
# return response.set_error(e)
@router.post("/imageGenerate/imagen", summary="이미지 생성(AI) - imagen", response_model=M.ImageGenerateRes)
async def imagen(request: Request, request_body_info: M.ImageGenerateReq):
@@ -127,78 +129,102 @@ async def imagen(request: Request, request_body_info: M.ImageGenerateReq):
## 이미지 생성(AI) - imagen
> imagen AI를 이용하여 이미지 생성
### Requriements
> - googlecli 설치(https://cloud.google.com/sdk/docs/install?hl=ko#linux)
> - const.py 에 지정한 OUTPUT_FOLDER 하위에 imagen 폴더가 있어야함.
"""
# imagen 사용중단 gemini로 변경
response = M.ImageGenerateRes()
try:
if not download_range(request_body_info.downloadCount):
raise Exception(f"downloadCount is 1~4 (current value = {request_body_info.downloadCount})")
img_length = imagen_generate_image(prompt=request_body_info.prompt,
download_count=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
# )
temp_image_path = gemini_image(request_body_info.prompt)
_remote_folder = os.path.join(rest_config.remote_folder,"imagen")
# remote save
sftp_client.remote_copy_data(
temp_image_path,
os.path.join(_remote_folder,f"imagen_{request_body_info.prompt}_{1}_{D.date_file_name()}.png"))
return response.set_message(img_len=img_length)
# 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(img_len=1)
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("/vactorImageSearch/imagenet/imageGenerate/imagen", summary="벡터 이미지 검색(imagenet) - imagen", response_model=M.ResponseBase)
async def vactor_imagenet(request: Request, request_body_info: M.VactorImageSearchReq):
"""
## 벡터 이미지 검색 - imagen
> imagen AI를 이용하여 이미지 생성 후 vactor 검색
# @router.post("/vactorImageSearch/imagenet/imageGenerate/imagen", summary="벡터 이미지 검색(imagenet) - imagen", response_model=M.ResponseBase)
# async def vactor_imagenet(request: Request, request_body_info: M.VactorImageSearchReq):
# """
# ## 벡터 이미지 검색 - imagen
# > imagen AI를 이용하여 이미지 생성 후 vector 검색
### Requriements
> - googlecli 설치(https://cloud.google.com/sdk/docs/install?hl=ko#linux)
> - const.py 에 지정한 OUTPUT_FOLDER 하위에 imagen 폴더가 있어야함.
# ### Requriements
# > - googlecli 설치(https://cloud.google.com/sdk/docs/install?hl=ko#linux)
# > - const.py 에 지정한 OUTPUT_FOLDER 하위에 imagen 폴더가 있어야함.
"""
response = M.ResponseBase()
try:
if request_body_info.indexType not in [M.IndexType.hnsw, M.IndexType.l2]:
raise Exception(f"indexType is hnsw or l2 (current value = {request_body_info.indexType})")
# """
# # NOTE(JWKIM) : GPU 메모리 이슈로 사용 중단
# response = M.ResponseBase()
# try:
# if request_body_info.indexType not in [M.IndexType.hnsw, M.IndexType.l2]:
# raise Exception(f"indexType is hnsw or l2 (current value = {request_body_info.indexType})")
img_path = imagen_generate_image_path(image_prompt=request_body_info.prompt)
# _temp_folder = f"{request_body_info.prompt}_{D.date_file_name()}"
vactor_request_data = {'query_image_path' : img_path,
'index_type' : request_body_info.indexType,
'search_num' : request_body_info.searchNum}
vactor_response = requests.post('http://localhost:51002/api/services/faiss/vactor/search/imagenet', data=json.dumps(vactor_request_data))
# # img_path = imagen_generate_image_path(image_prompt=request_body_info.prompt) #imagen
# img_path = gemini_image(request_body_info.prompt, os.path.join(TEMP_FOLDER, _temp_folder)) #gemini
if vactor_response.status_code != 200:
raise Exception(f"response error: {json.loads(vactor_response.text)['error']}")
# vector_request_data = {'query_image_path' : img_path,
# 'index_type' : request_body_info.indexType,
# 'search_num' : request_body_info.searchNum}
# vector_response = requests.post('http://localhost:51002/api/services/faiss/vector/search/imagenet', data=json.dumps(vector_request_data))
if json.loads(vactor_response.text)["error"] != None:
raise Exception(f"vactor error: {json.loads(vactor_response.text)['error']}")
# if vector_response.status_code != 200:
# raise Exception(f"response error: {json.loads(vector_response.text)['error']}")
# remote
_directory_path, _file = os.path.split(img_path)
_base_bame = os.path.basename(_directory_path)
# if json.loads(vector_response.text)["error"] != None:
# raise Exception(f"vector error: {json.loads(vector_response.text)['error']}")
# remote 폴더 생성
sftp_client.remote_mkdir(os.path.join(rest_config.remote_folder, _base_bame))
# # remote
# _directory_path, _file = os.path.split(img_path)
# remote 폴더에 이미지 저장
for i in os.listdir(_directory_path):
sftp_client.remote_copy_data(local_path=os.path.join(_directory_path, i), remote_path=os.path.join(rest_config.remote_folder, _base_bame, i))
# # remote 폴더 생성
# sftp_client.remote_mkdir(os.path.join(rest_config.remote_folder, _temp_folder))
return response.set_message()
# # remote 폴더에 이미지 저장
# for i in os.listdir(_directory_path):
# sftp_client.remote_copy_data(local_path=os.path.join(_directory_path, i),
# remote_path=os.path.join(rest_config.remote_folder, _temp_folder, i))
# shutil.rmtree(_directory_path)
# return response.set_message()
except Exception as e:
LOG.error(traceback.format_exc())
return response.set_error(error=e)
# except Exception as e:
# LOG.error(traceback.format_exc())
# return response.set_error(error=e)
@router.post("/vactorImageSearch/vit/imageGenerate/imagen", summary="벡터 이미지 검색(clip-vit) - imagen", response_model=M.ResponseBase)
async def vactor_vit_report(request: Request, request_body_info: M.VactorImageSearchVitReq):
async def vactor_vit(request: Request, request_body_info: M.VectorImageSearchVitReq):
"""
## 벡터 이미지 검색(clip-vit) - imagen
> imagen AI를 이용하여 이미지 생성 후 vactor 검색 그후 결과 이미지 생성
> 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)
@@ -219,14 +245,15 @@ async def vactor_vit_report(request: Request, request_body_info: M.VactorImageSe
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 = imagen_generate_temp_image_path(image_prompt=request_body_info.prompt)
# query_image_path = imagen_generate_temp_image_path(image_prompt=request_body_info.prompt) #imagen
query_image_path = gemini_image(request_body_info.prompt) #gemini
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/vactor/search/vit', data=json.dumps(vector_request_data))
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)
@@ -234,7 +261,7 @@ async def vactor_vit_report(request: Request, request_body_info: M.VactorImageSe
raise Exception(f"response error: {vector_response_dict['error']}")
if vector_response_dict["error"] != None:
raise Exception(f"vactor error: {vector_response_dict['error']}")
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')
@@ -267,12 +294,92 @@ async def vactor_vit_report(request: Request, request_body_info: M.VactorImageSe
del query_image_path
return response.set_error(error=e)
@router.post("/vactorImageSearch/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):
"""
## 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
"""
response = M.VectorImageSerachDataRes()
query_image_data = ''
try:
if not download_range(request_body_info.searchNum, max=10):
raise Exception(f"downloadCound is invalid (current value = {request_body_info.searchNum})")
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 = imagen_generate_temp_image_path(image_prompt=request_body_info.prompt) #imagen
query_image_path = gemini_image(request_body_info.prompt) #gemini
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)
if request_body_info.querySend:
query_image_data = image_to_base64_string(query_image_path)
# 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("/vactorImageSearch/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.VactorImageSearchVitReportReq):
async def vactor_vit_report(request: Request, request_body_info: M.VectorImageSearchVitReportReq):
"""
## 벡터 이미지 검색(clip-vit) - imagen, report 생성
> imagen AI를 이용하여 이미지 생성 후 vactor 검색 그후 종합결과 이미지 생성
> imagen AI를 이용하여 이미지 생성 후 vector 검색 그후 종합결과 이미지 생성
### Requriements
> - googlecli 설치(https://cloud.google.com/sdk/docs/install?hl=ko#linux)
@@ -290,7 +397,8 @@ async def vactor_vit_report(request: Request, request_body_info: M.VactorImageSe
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 = imagen_generate_temp_image_path(image_prompt=request_body_info.prompt)
# query_image_path = imagen_generate_temp_image_path(image_prompt=request_body_info.prompt) #imagen
query_image_path = gemini_image(request_body_info.prompt) #gemini
report_image_path = f"{os.path.splitext(query_image_path)[0]}_report.png"
vactor_request_data = {'query_image_path' : query_image_path,
@@ -298,13 +406,13 @@ async def vactor_vit_report(request: Request, request_body_info: M.VactorImageSe
'model_type' : request_body_info.modelType,
'report_path' : report_image_path}
vactor_response = requests.post('http://localhost:51002/api/services/faiss/vactor/search/vit/report', data=json.dumps(vactor_request_data))
vactor_response = requests.post('http://localhost:51002/api/services/faiss/vector/search/vit/report', data=json.dumps(vactor_request_data))
if vactor_response.status_code != 200:
raise Exception(f"response error: {json.loads(vactor_response.text)['error']}")
if json.loads(vactor_response.text)["error"] != None:
raise Exception(f"vactor error: {json.loads(vactor_response.text)['error']}")
raise Exception(f"vector error: {json.loads(vactor_response.text)['error']}")
# remote 폴더에 이미지 저장
sftp_client.remote_copy_data(local_path=report_image_path,