Update app.py

app.py

@@ -10,8 +10,6 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 
 device = torch.device("cuda:0")
 
-llm = AutoModelForCausalLM.from_pretrained("Azure99/blossom-v5-9b", torch_dtype=torch.float16, device_map="auto")
-tokenizer = AutoTokenizer.from_pretrained("Azure99/blossom-v5-9b")
 diffusion_pipe = DiffusionPipeline.from_pretrained(
     "playgroundai/playground-v2.5-1024px-aesthetic",
     torch_dtype=torch.float16,
@@ -21,68 +19,22 @@ diffusion_pipe = DiffusionPipeline.from_pretrained(
 ).to(device)
 
 
-def get_input_ids(inst, bot_prefix):
-    return tokenizer.encode("A chat between a human and an artificial intelligence bot. "
-                            "The bot gives helpful, detailed, and polite answers to the human's questions.\n"
-                            f"|Human|: {inst}\n|Bot|: {bot_prefix}", add_special_tokens=True)
-
-
 def save_image(img):
     unique_name = str(uuid.uuid4()) + ".png"
     img.save(unique_name)
     return unique_name
 
 
-LLM_PROMPT = '''你的任务是从输入的[作画要求]中抽取画面描述(description)，然后description翻译为英文(en_description)，最后对en_description进行扩写(expanded_description)，增加足够多的细节，且符合人类的第一直觉。
-[输出]是一个json，包含description、en_description、expanded_description三个字符串字段，请直接输出一个完整的json，不要输出任何解释或其他无关内容。
-    
-下面是一些示例：
-[作画要求]->"画一幅画：落霞与孤鹜齐飞，秋水共长天一色。"
-[输出]->{"description": "落霞与孤鹜齐飞，秋水共长天一色", "en_description": "The setting sun and the solitary duck fly together, the autumn water shares a single hue with the vast sky", "expanded_description": "A lone duck gracefully gliding across the tranquil surface of a shimmering lake, bathed in the warm golden glow of the setting sun, creating a breathtaking scene of natural beauty and tranquility."}
-    
-[作画要求]->"原神中的可莉"
-[输出]->{"description": "原神中的可莉", "en_description": "Klee in Genshin Impact", "expanded_description": "An artistic portrait of Klee from Genshin Impact, standing in a vibrant meadow with colorful explosions of her elemental abilities in the background."}
-    
-[作画要求]->"create an image for me. a close up of a woman wearing a transparent, prismatic, elaborate nemeses headdress, over the should pose, brown skin-tone"
-[输出]->{"description": "a close up of a woman wearing a transparent, prismatic, elaborate nemeses headdress, over the should pose, brown skin-tone", "en_description": "a close up of a woman wearing a transparent, prismatic, elaborate nemeses headdress, over the should pose, brown skin-tone", "expanded_description": "A close-up portrait of an elegant woman with rich brown skin, wearing a stunning transparent, prismatic, and intricately detailed Nemes headdress, striking a confident and alluring over-the-shoulder pose."}
-    
-[作画要求]->"一只高贵的柯基犬，素描画风格\n根据上面的描述生成一张图片吧！"
-[输出]->{"description": "一只高贵的柯基犬，素描画风格", "en_description": "A noble corgi dog, sketch style", "expanded_description": "A majestic corgi with a regal bearing, depicted in a detailed and intricate pencil sketch, capturing the essence of its noble lineage and dignified presence."}
-    
-[作画要求]->$USER_PROMPT
-[输出]->'''
-
-BOT_PREFIX = '{"description": "'
-
-
 @spaces.GPU(enable_queue=True)
 def generate(
         prompt: str,
         progress=gr.Progress(track_tqdm=True),
 ):
-    input_ids = get_input_ids(LLM_PROMPT.replace("$USER_PROMPT", json.dumps(prompt, ensure_ascii=False)), BOT_PREFIX)
-    generation_kwargs = dict(input_ids=torch.tensor([input_ids]).to(llm.device), do_sample=True,
-                             max_new_tokens=512, temperature=0.5, top_p=0.85, top_k=50, repetition_penalty=1.05)
-    llm_result = llm.generate(**generation_kwargs)
-    llm_result = llm_result.cpu()[0][len(input_ids):]
-    llm_result = BOT_PREFIX + tokenizer.decode(llm_result, skip_special_tokens=True)
-    print("----------")
-    print(prompt)
-    print(llm_result)
-    en_prompt = prompt
-    expanded_prompt = prompt
-    try:
-        en_prompt = json.loads(llm_result)["en_description"]
-        expanded_prompt = json.loads(llm_result)["expanded_description"]
-    except:
-        print("error, fallback to original prompt")
-        pass
-
     seed = random.randint(0, 2147483647)
     generator = torch.Generator().manual_seed(seed)
 
     images = diffusion_pipe(
-        prompt=[expanded_prompt, en_prompt],
+        prompt=[prompt],
         negative_prompt=None,
         width=1024,
         height=1024,