调用llama3.2-vision,自动识别图片，输出prompt

app/api/api_prompt_generation.py

@@ -4,9 +4,10 @@ import time
 
 from fastapi import APIRouter, HTTPException
 
-from app.schemas.prompt_generation import PromptGenerationImageModel
+from app.schemas.prompt_generation import PromptGenerationImageModel, ImageRequest
 from app.schemas.response_template import ResponseModel
-from app.service.prompt_generation.chatgpt_for_translation import translate_to_en, get_translation_from_llama3
+from app.service.prompt_generation.chatgpt_for_translation import get_translation_from_llama3, \
+    get_prompt_from_image
 
 router = APIRouter()
 logger = logging.getLogger()
@@ -32,3 +33,20 @@ def prompt_generation(request_data: PromptGenerationImageModel):
         logger.warning(f"prompt_generation Run Exception @@@@@@:{e}")
         raise HTTPException(status_code=404, detail=str(e))
     return ResponseModel(data=data)
+
+
+@router.post("/img2prompt")
+def get_prompt_from_img(img: ImageRequest):
+    """
+    自动识别图片并输出为prompt
+
+    :param img: 图片的minio地址
+    :return: 图片的文字描述
+    """
+    text = ("Please describe the clothing in the image and provide a line art description of the outfit. "
+            "The description should allow for the reconstruction of the corresponding line art based on the details "
+            "given.")
+    logger.info(f"get_prompt_from_img request item is : @@@@@@:{img}")
+    description = get_prompt_from_image(img, text)
+    logger.info(f"生成的图片描述 response @@@@@@:{description}")
+    return description

app/schemas/prompt_generation.py

@@ -3,3 +3,7 @@ from pydantic import BaseModel
 
 class PromptGenerationImageModel(BaseModel):
     text: str
+
+
+class ImageRequest(BaseModel):
+    img: str

app/service/prompt_generation/chatgpt_for_translation.py

@@ -9,6 +9,7 @@ from retry import retry
 
 from app.core.config import QWEN_API_KEY
 from app.service.chat_robot.script.service.CallQWen import get_language
+from app.service.prompt_generation.util import minio_util
 
 logger = logging.getLogger(__name__)
 
@@ -143,6 +144,38 @@ def get_translation_from_llama3(text):
 #     response = requests.post(url, data=json.dumps(payload), headers=headers)
 
 
+def get_prompt_from_image(image_path, text):
+    start_time = time.time()
+    # url = "http://localhost:11434/api/generate"
+    url = "http://10.1.1.243:11434/api/generate"
+
+    image_base64 = minio_util.minio_url_to_base64(image_path.img)
+    # image_base64 = minio_url_to_base64(image_path)
+
+    # 创建请求的负载 translator是自定义的翻译模型
+    payload = {
+        "model": "llama3.2-vision",
+        "images": [image_base64],
+        "prompt": f"{text}",
+        "stream": False
+    }
+    # 将负载转换为 JSON 格式
+    headers = {'Content-Type': 'application/json'}
+    response = requests.post(url, data=json.dumps(payload), headers=headers)
+    # 处理响应
+    if response.status_code == 200:
+        # print("Response from server:")
+        # print(response.json())
+        resp = json.loads(response.content).get("response")
+        logger.info(f"sketch re-generate server runtime is {time.time() - start_time} \n, response is {resp}")
+        # print("input : {}, sketch re-generate result : {}".format(text, resp))
+        return resp
+    else:
+        logger.info(f"sketch re-generate server runtime is {time.time() - start_time} , response is {response.content}")
+        print(f"Request failed with status code {response.status_code}")
+        print(response.text)
+
+
 def main():
     """Main function"""
     text = get_translation_from_llama3("[火焰]")

app/service/prompt_generation/util/minio_util.py

@@ -0,0 +1,21 @@
+import base64
+
+from minio import Minio
+
+from app.core.config import MINIO_URL, MINIO_ACCESS, MINIO_SECRET, MINIO_SECURE
+
+minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
+
+
+def minio_url_to_base64(minio_url: str) -> str:
+    bucket_name, object_name = minio_url.split("/", 1)
+
+    try:
+        response = minio_client.get_object(bucket_name, object_name)
+        image_data = response.read()
+        return base64.b64encode(image_data).decode('utf-8')
+    except Exception as e:
+        raise RuntimeError(f"Failed to get object: {e}")
+    finally:
+        if 'response' in locals():
+            response.close()