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| import gradio as gr | |
| import transformers | |
| import torch | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| from PIL import Image | |
| import warnings | |
| # Disable warnings and progress bars | |
| transformers.logging.set_verbosity_error() | |
| transformers.logging.disable_progress_bar() | |
| warnings.filterwarnings('ignore') | |
| # Initialize model and tokenizer | |
| def load_model(device='cpu'): | |
| model = AutoModelForCausalLM.from_pretrained( | |
| 'qnguyen3/nanoLLaVA', | |
| torch_dtype=torch.float16, | |
| device_map='auto', | |
| trust_remote_code=True | |
| ) | |
| tokenizer = AutoTokenizer.from_pretrained( | |
| 'qnguyen3/nanoLLaVA', | |
| trust_remote_code=True | |
| ) | |
| return model, tokenizer | |
| def generate_caption(image, model, tokenizer): | |
| # Prepare the prompt | |
| prompt = "Describe this image in detail" | |
| messages = [ | |
| {"role": "system", "content": "Answer the question"}, | |
| {"role": "user", "content": f'<image>\n{prompt}'} | |
| ] | |
| # Apply chat template | |
| text = tokenizer.apply_chat_template( | |
| messages, | |
| tokenize=False, | |
| add_generation_prompt=True | |
| ) | |
| # Process text and image | |
| text_chunks = [tokenizer(chunk).input_ids for chunk in text.split('<image>')] | |
| input_ids = torch.tensor(text_chunks[0] + [-200] + text_chunks[1], dtype=torch.long).unsqueeze(0) | |
| image_tensor = model.process_images([image], model.config).to(dtype=model.dtype) | |
| # Generate caption | |
| output_ids = model.generate( | |
| input_ids, | |
| images=image_tensor, | |
| max_new_tokens=2048, | |
| use_cache=True | |
| )[0] | |
| # Decode the output | |
| caption = tokenizer.decode(output_ids[input_ids.shape[1]:], skip_special_tokens=True).strip() | |
| return caption | |
| def create_persona(caption): | |
| persona_prompt = f"""<|im_start|>system | |
| Role : An entity exactly as described in your image | |
| Background : Your appearance and characteristics match the image description | |
| Personality : Reflect the mood, style, and elements captured in the image | |
| Goal : Interact authentically based on your visual characteristics | |
| You are a character with the following stats: | |
| {caption} | |
| Please stay in character and respond as this entity would, | |
| incorporating visual elements from your description into your responses.<|im_end|>""" | |
| return persona_prompt | |
| def process_image_to_persona(image, model, tokenizer): | |
| if image is None: | |
| return "Please upload an image.", "" | |
| # Convert to PIL Image if needed | |
| if not isinstance(image, Image.Image): | |
| image = Image.fromarray(image) | |
| # Generate caption from image | |
| caption = generate_caption(image, model, tokenizer) | |
| # Transform caption into persona | |
| persona = create_persona(caption) | |
| return caption, persona | |
| default_system_prompt=''' | |
| Your image shows us that you are: | |
| A small, fluffy white pig with a pink nose and small ears, | |
| standing upright. The pig has a long pink tongue, which is also pink in color. | |
| The pig's eyes are open and appear to be looking at the camera. | |
| The pig's fur is fluffy and white, and there are pink and white spots on the fur. The pig's paws are also pink and white, | |
| and they have pink nails.The pig's legs are long and pink. The pig's body is positioned in front of a black background. | |
| ''' | |
| def chat(prompt, | |
| system_prompt=default_system_prompt, | |
| model_id = "meta-llama/Meta-Llama-3.1-8B-Instruct", | |
| max_tokens=512 | |
| ): | |
| pipeline = transformers.pipeline( | |
| "text-generation", | |
| model=model_id, | |
| model_kwargs={"torch_dtype": torch.bfloat16}, | |
| device_map="auto", | |
| ) | |
| messages = [ | |
| {"role": "system", "content": system_prompt}, | |
| {"role": "user", "content": prompt}, | |
| ] | |
| outputs = pipeline( | |
| messages, | |
| max_new_tokens=max_tokens, | |
| ) | |
| output = outputs[0]["generated_text"][-1] | |
| print(output) | |
| return output | |