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| 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 FalconVLM 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 FalconVLM 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 += f"""User:<image>\n{user} Falcon:{assistant} """ | |
| 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 = f"""User:<image>\n{message['text']} Falcon:""" | |
| 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") | |
| #inputs = processor(prompt, image, return_tensors='pt').to(0, torch.float16) | |
| streamer = TextIteratorStreamer(processor, **{"skip_special_tokens": True, "skip_prompt": True, 'clean_up_tokenization_spaces':False,}) # "eos_token_id":processor.tokenizer.eos_token_id}) | |
| 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: | |
| # find <|eot_id|> and remove it from the new_text | |
| #if "<|eot_id|>" in new_text: | |
| # new_text = new_text.split("<|eot_id|>")[0] | |
| 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="FalconVLM", | |
| examples=[{"text": "What is on the flower?", "files": ["./bee.jpg"]}, | |
| {"text": "How to make this pastry?", "files": ["./baklava.png"]}], | |
| description="Try [tiiuae/falcon-11B-VLM](https://huggingface.co/tiiuae/falcon-11B-vlm). Upload an image and start chatting about it, or simply try one of the examples below. If you don't upload an image, you will receive an error.", | |
| stop_btn="Stop Generation", | |
| multimodal=True, | |
| textbox=chat_input, | |
| chatbot=chatbot, | |
| cache_examples=False, | |
| ) | |
| demo.queue() | |
| demo.launch(debug=True, quiet=True) | |