merve's picture
merve HF staff
Update app.py
340a6dd verified
raw
history blame
2.34 kB
import gradio as gr
from transformers import LlavaNextProcessor, LlavaNextForConditionalGeneration, TextIteratorStreamer
from threading import Thread
import re
import time
from PIL import Image
import torch
import spaces
processor = LlavaNextProcessor.from_pretrained("llava-hf/llava-v1.6-mistral-7b-hf")
model = LlavaNextForConditionalGeneration.from_pretrained("llava-hf/llava-v1.6-mistral-7b-hf", torch_dtype=torch.float16, low_cpu_mem_usage=True)
model.to("cuda:0")
@spaces.GPU
def bot_streaming(message, history):
print(message)
if message["files"]:
image = message["files"][-1]["path"]
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]
if image is None:
gr.Error("You need to upload an image for LLaVA to work.")
prompt=f"[INST] <image>\n{message['text']} [/INST]"
image = Image.open(image).convert("RGB")
inputs = processor(prompt, image, return_tensors="pt").to("cuda:0")
streamer = TextIteratorStreamer(processor, **{"skip_special_tokens": True})
generation_kwargs = dict(inputs, streamer=streamer, max_new_tokens=100)
generated_text = ""
thread = Thread(target=model.generate, kwargs=generation_kwargs)
thread.start()
text_prompt =f"[INST] \n{message['text']} [/INST]"
buffer = ""
for new_text in streamer:
buffer += new_text
generated_text_without_prompt = buffer[len(text_prompt):]
time.sleep(0.04)
yield generated_text_without_prompt
demo = gr.ChatInterface(fn=bot_streaming, title="LLaVA NeXT", examples=[{"text": "What is on the flower?", "files":["./bee.jpg"]},
{"text": "How to make this pastry?", "files":["./baklava.png"]}],
description="Try [LLaVA NeXT](https://huggingface.co/docs/transformers/main/en/model_doc/llava_next) in this demo (more specifically, the [Mistral-7B variant](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf)). 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)
demo.launch(debug=True)