from typing import Dict from django.utils.translation import gettext from langchain_community.chat_models import ChatZhipuAI from langchain_core.messages import HumanMessage from zhipuai import ZhipuAI from common.config.tokenizer_manage_config import TokenizerManage from models_provider.base_model_provider import MaxKBBaseModel from models_provider.impl.base_tti import BaseTextToImage def custom_get_token_ids(text: str): tokenizer = TokenizerManage.get_tokenizer() return tokenizer.encode(text) class ZhiPuTextToImage(MaxKBBaseModel, BaseTextToImage): api_key: str model: str params: dict def __init__(self, **kwargs): super().__init__(**kwargs) self.api_key = kwargs.get('api_key') self.model = kwargs.get('model') self.params = kwargs.get('params') @staticmethod def is_cache_model(): return False @staticmethod def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs): optional_params = {'params': {'size': '1024x1024'}} for key, value in model_kwargs.items(): if key not in ['model_id', 'use_local', 'streaming']: optional_params['params'][key] = value return ZhiPuTextToImage( model=model_name, api_key=model_credential.get('api_key'), **optional_params, ) def is_cache_model(self): return False def check_auth(self): chat = ChatZhipuAI( zhipuai_api_key=self.api_key, model_name=self.model, ) chat.invoke([HumanMessage([{"type": "text", "text": gettext('Hello')}])]) # self.generate_image('生成一个小猫图片') def generate_image(self, prompt: str, negative_prompt: str = None): # chat = ChatZhipuAI( # zhipuai_api_key=self.api_key, # model_name=self.model, # ) chat = ZhipuAI(api_key=self.api_key) response = chat.images.generations( model=self.model, # 填写需要调用的模型编码 prompt=prompt, # 填写需要生成图片的文本 **self.params # 填写额外参数 ) file_urls = [] for content in response.data: url = content.url file_urls.append(url) return file_urls