BrandAnalysis/agent/agent.py

from agent import Glm, Prompt
class Agent:
    
    _instance = None
    def __new__(cls):
        if not cls._instance:
            cls._instance = super(Agent, cls).__new__(cls)
            cls._instance._initialized = False
        return cls._instance
    
    def __init__(self):
        if not self._initialized:
            self.glm = Glm()
            self._initialized = True
            
    def brand_key_word_judgement(self, brandname, title):
        """判断是否为关键词引流"""
        self.glm.set_modelname("glm-4-plus")
        prompt = Prompt.EXTRACT_INFO_FROM_TITLE + f"""
            请根据上述逻辑，分析以下商品标题，并输出结果：
            商品标题：{title}
            给定的引流品牌：{brandname}"""
            
        response = self.glm.text_response(prompt)
        return response.content
    
    def license_product_judgement(self, title, license_list):
        """判断是否为未授权商品"""
        license_list_str = ""
        for product in license_list:
            license_list_str += f"{product}\n"
            
        self.glm.set_modelname("glm-4-plus")
        prompt = Prompt.LICENSE_LIST_FILTER + f"""
        请根据上述逻辑，分析以下商品是否为授权生产的，并输出结果：
        商品名称: {title}
        已生产的产品清单：
        {license_list_str}
            
        输出结果：
        - 如果找到匹配项则输出：
        ```json
        {{
            "in_list": true,
            "march_product": 匹配到的产品
        }}
        ```
        - 如果未找到匹配项则输出:
        ```json
        {{
            "in_list": false
        }}
        ```
        """
        response = self.glm.text_response(prompt)
        response = response.content.replace(' ', '').replace('\n', '').replace('\t', '').replace(":", ": ")
        return response
    
    def image_logo_judgement(self, logo_path, image_url):
        """判断图像中是否有指定品牌的logo"""
        self.glm.set_modelname("glm-4v-plus-0111")
        prompt = Prompt.IMAGE_LOGO_JUDGEMENT
        response = self.glm.multi_epoch_image_response(logo_path, image_url, prompt)
        response = response.content
        
        return response
    
    def product_image_similarity_judgement(self, image_url1, image_url2):
        """判断两个图像中的产品是否一致"""
        self.glm.set_modelname("glm-4v-plus-0111")
        prompt = Prompt.PRODUCT_JUDGEMENT
        response = self.glm.image_response(prompt, image_url1, image_url2)
        response = response.content
        
        return response

if __name__ == "__main__":
    agent = Agent()
    image_url1 = 'http://h2.appsimg.com/a.appsimg.com/upload/merchandise/pdcvis/613214/2024/0902/118/27466cf6-fb28-4580-9009-95a3763e06bf.jpg'
    image_url2 = 'http://h2.appsimg.com/a.appsimg.com/upload/merchandise/pdcvis/613214/2024/1120/169/8ca15632-9cb9-40e7-8915-e6773e17a05e.jpg'
    agent.product_image_similarity_judgement(image_url1, image_url2)
    
    # ["http://h2.appsimg.com/a.appsimg.com/upload/merchandise/pdcvis/613214/2024/1120/88/9b9027dd-95b7-4024-b71e-fb7cbfde16a1.jpg",
    #  "http://h2.appsimg.com/a.appsimg.com/upload/merchandise/pdcvis/613214/2024/0902/118/27466cf6-fb28-4580-9009-95a3763e06bf.jpg",
    #  "http://h2.appsimg.com/a.appsimg.com/upload/merchandise/pdcvis/613214/2024/1120/169/8ca15632-9cb9-40e7-8915-e6773e17a05e.jpg",
    #  "http://h2.appsimg.com/a.appsimg.com/upload/merchandise/pdcvis/613214/2024/1120/91/d42ae626-8606-4e29-8a75-a247ab6be790.jpg"]