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| import subprocess | |
| # Installing flash_attn | |
| subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True) | |
| import gradio as gr | |
| from PIL import Image | |
| from transformers import AutoModelForCausalLM | |
| from transformers import AutoProcessor | |
| from transformers import TextIteratorStreamer | |
| import time | |
| from threading import Thread | |
| import torch | |
| import spaces | |
| model_id = "microsoft/Phi-3-vision-128k-instruct" | |
| model = AutoModelForCausalLM.from_pretrained(model_id, device_map="cuda", trust_remote_code=True, torch_dtype="auto") | |
| processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True) | |
| model.to("cuda:0") | |
| PLACEHOLDER = """ | |
| <div style="padding: 30px; text-align: center; display: flex; flex-direction: column; align-items: center;"> | |
| <img src="https://cdn-thumbnails.huggingface.co/social-thumbnails/models/microsoft/Phi-3-vision-128k-instruct.png" style="width: 80%; max-width: 550px; height: auto; opacity: 0.55; "> | |
| <h1 style="font-size: 28px; margin-bottom: 2px; opacity: 0.55;">Microsoft's Phi3-Vision-128k-Context</h1> | |
| <p style="font-size: 18px; margin-bottom: 2px; opacity: 0.65;">Phi-3-Vision is a 4.2B parameter multimodal model that brings together language and vision capabilities.</p> | |
| </div> | |
| """ | |
| def bot_streaming(message, history): | |
| print(f'message is - {message}') | |
| print(f'history is - {history}') | |
| if message["files"]: | |
| # message["files"][-1] is a Dict or just a string | |
| if type(message["files"][-1]) == dict: | |
| image = message["files"][-1]["path"] | |
| else: | |
| image = message["files"][-1] | |
| else: | |
| # if there's no image uploaded for this turn, look for images in the past turns | |
| # kept inside tuples, take the last one | |
| for hist in history: | |
| if type(hist[0]) == tuple: | |
| image = hist[0][0] | |
| try: | |
| if image is None: | |
| # Handle the case where image is None | |
| raise gr.Error("You need to upload an image for Phi3-Vision to work. Close the error and try again with an Image.") | |
| except NameError: | |
| # Handle the case where 'image' is not defined at all | |
| raise gr.Error("You need to upload an image for Phi3-Vision to work. Close the error and try again with an Image.") | |
| conversation = [] | |
| flag=False | |
| for user, assistant in history: | |
| if assistant is None: | |
| #pass | |
| flag=True | |
| conversation.extend([{"role": "user", "content":""}]) | |
| continue | |
| if flag==True: | |
| conversation[0]['content'] = f"<|image_1|>\n{user}" | |
| conversation.extend([{"role": "assistant", "content": assistant}]) | |
| flag=False | |
| continue | |
| conversation.extend([{"role": "user", "content": user}, {"role": "assistant", "content": assistant}]) | |
| if len(history) == 0: | |
| conversation.append({"role": "user", "content": f"<|image_1|>\n{message['text']}"}) | |
| else: | |
| conversation.append({"role": "user", "content": message['text']}) | |
| print(f"prompt is -\n{conversation}") | |
| prompt = processor.tokenizer.apply_chat_template(conversation, tokenize=False, add_generation_prompt=True) | |
| image = Image.open(image) | |
| inputs = processor(prompt, image, return_tensors="pt").to("cuda:0") | |
| streamer = TextIteratorStreamer(processor, **{"skip_special_tokens": True, "skip_prompt": True, 'clean_up_tokenization_spaces':False,}) | |
| generation_kwargs = dict(inputs, streamer=streamer, max_new_tokens=1024, do_sample=False, temperature=0.0, eos_token_id=processor.tokenizer.eos_token_id,) | |
| thread = Thread(target=model.generate, kwargs=generation_kwargs) | |
| thread.start() | |
| buffer = "" | |
| for new_text in streamer: | |
| buffer += new_text | |
| yield buffer | |
| chatbot=gr.Chatbot(scale=1, placeholder=PLACEHOLDER) | |
| chat_input = gr.MultimodalTextbox(interactive=True, file_types=["image"], placeholder="Enter message or upload file...", show_label=False) | |
| with gr.Blocks(fill_height=True, ) as demo: | |
| gr.ChatInterface( | |
| fn=bot_streaming, | |
| title="Phi3 Vision 128K Instruct", | |
| examples=[{"text": "Describe the image in details?", "files": ["./robo.jpg"]}, | |
| {"text": "What does the chart display?", "files": ["./dataviz.png"]}, | |
| {"text": "What is 3?", "files": ["./setofmark1.jpg"]}, | |
| {"text": "Can you list the categories of each mark with spatial identifier??", "files": ["./setofmark4.png"]}, | |
| {"text": "Which Watermelon is sweeter?", "files": ["./setofmark3.jpeg"]}, | |
| ], | |
| description="Try [microsoft/Phi-3-vision-128k-instruct](https://huggingface.co/microsoft/Phi-3-vision-128k-instruct). Upload an image and start chatting about it, or simply try one of the examples below. If you won't upload an image, you will receive an error. This is not the official demo.", | |
| stop_btn="Stop Generation", | |
| multimodal=True, | |
| textbox=chat_input, | |
| chatbot=chatbot, | |
| cache_examples=False, | |
| examples_per_page=3 | |
| ) | |
| demo.queue() | |
| demo.launch(debug=True, quiet=True) | |