TikZ-Assistant / webui.py
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#!/usr/bin/env python
import re
from argparse import ArgumentParser
from functools import lru_cache
from importlib.resources import files
from inspect import signature
from multiprocessing.pool import ThreadPool
from tempfile import NamedTemporaryFile
from textwrap import dedent
from typing import Optional
from PIL import Image
import fitz
import gradio as gr
from transformers import TextIteratorStreamer, pipeline, ImageToTextPipeline, AutoModelForPreTraining, AutoProcessor
import os
# from pix2tex.cli import LatexOCR
from munch import Munch
import spaces
from infer import TikzDocument, TikzGenerator
# assets = files(__package__) / "assets" if __package__ else files("assets") / "."
models = {
# "pix2tikz": "pix2tikz/mixed_e362_step201.pth",
"llava-1.5-7b-hf": "waleko/TikZ-llava-1.5-7b",
"new llava-1.5-7b-hf": "waleko/TikZ-llava-1.5-7b v2"
}
def is_quantization(model_name):
return "waleko/TikZ-llava" in model_name
@lru_cache(maxsize=1)
def cached_load(model_name, **kwargs) -> ImageToTextPipeline:
# split
model_dict = model_name.split(" ")
revision = "main"
if len(model_dict) > 1:
model_name, revision = model_dict
gr.Info("Instantiating model. Could take a while...") # type: ignore
if not is_quantization(model_name):
return pipeline("image-to-text", model=model_name, revision=revision, **kwargs)
else:
model = AutoModelForPreTraining.from_pretrained(model_name, load_in_4bit=True, revision=revision, **kwargs)
processor = AutoProcessor.from_pretrained(model_name)
return pipeline(task="image-to-text", model=model, tokenizer=processor.tokenizer, image_processor=processor.image_processor)
def convert_to_svg(pdf):
doc = fitz.open("pdf", pdf.raw) # type: ignore
return doc[0].get_svg_image()
# def pix2tikz(
# checkpoint: str,
# image: Image.Image,
# temperature: float,
# _: float,
# __: int,
# ___: bool,
# ):
# cur_pwd = os.path.dirname(os.path.abspath(__file__))
# config_path = os.path.join(cur_pwd, 'pix2tikz/config.yaml')
# model_path = os.path.join(cur_pwd, checkpoint)
#
# print(cur_pwd, config_path, model_path, os.path.exists(config_path), os.path.exists(model_path))
#
# args = Munch({'config': config_path,
# 'checkpoint': model_path,
# 'no_resize': False,
# 'no_cuda': False,
# 'temperature': temperature})
# model = LatexOCR(args)
# res = model(image)
# text = re.sub(r'\\n(?=\W)', '\n', res)
# return text, None, True
def inference(
model_name: str,
image_dict: dict,
temperature: float,
top_p: float,
top_k: int,
expand_to_square: bool,
):
try:
image = image_dict['composite']
if "pix2tikz" in model_name:
# yield pix2tikz(model_name, image, temperature, top_p, top_k, expand_to_square)
return
generate = TikzGenerator(
cached_load(model_name, device_map="auto"),
temperature=temperature,
top_p=top_p,
top_k=top_k,
expand_to_square=expand_to_square,
)
streamer = TextIteratorStreamer(
generate.pipeline.tokenizer, # type: ignore
skip_prompt=True,
skip_special_tokens=True
)
thread = ThreadPool(processes=1)
async_result = thread.apply_async(spaces.GPU(generate), kwds=dict(image=image, streamer=streamer))
generated_text = ""
for new_text in streamer:
generated_text += new_text
yield generated_text, None, False
yield async_result.get().code, None, True
except Exception as e:
raise gr.Error(f"Internal Error! {e}")
def tex_compile(
code: str,
timeout: int,
rasterize: bool
):
tikzdoc = TikzDocument(code, timeout=timeout)
if not tikzdoc.has_content:
if tikzdoc.compiled_with_errors:
raise gr.Error("TikZ code did not compile!") # type: ignore
else:
gr.Warning("TikZ code compiled to an empty image!") # type: ignore
elif tikzdoc.compiled_with_errors:
# gr.Warning("TikZ code compiled with errors!") # type: ignore
print("TikZ code compiled with errors!")
if rasterize:
yield tikzdoc.rasterize()
else:
with NamedTemporaryFile(suffix=".svg", buffering=0) as tmpfile:
if pdf:=tikzdoc.pdf:
tmpfile.write(convert_to_svg(pdf).encode())
yield tmpfile.name if pdf else None
def check_inputs(image: Image.Image):
if not image:
raise gr.Error("Image is required")
def get_banner():
return dedent('''\
# Ti*k*Z Assistant: Sketches to Vector Graphics with Ti*k*Z
<p>
<!--<a style="display:inline-block" href="https://github.com/potamides/AutomaTikZ">
<img src="https://img.shields.io/badge/View%20on%20GitHub-green?logo=github&labelColor=gray" alt="View on GitHub">
</a>
<a style="display:inline-block" href="https://arxiv.org/abs/2310.00367">
<img src="https://img.shields.io/badge/View%20on%20arXiv-B31B1B?logo=arxiv&labelColor=gray" alt="View on arXiv">
</a>
<a style="display:inline-block" href="https://colab.research.google.com/drive/14S22x_8VohMr9pbnlkB4FqtF4n81khIh">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab">
</a>-->
<a style="display:inline-block" href="https://huggingface.co/spaces/waleko/TikZ-Assistant">
<img src="https://huggingface.co/datasets/huggingface/badges/resolve/main/open-in-hf-spaces-sm.svg" alt="Open in HF Spaces">
</a>
</p>
''')
def remove_darkness(stylable):
"""
Patch gradio to only contain light mode colors.
"""
if isinstance(stylable, gr.themes.Base): # remove dark variants from the entire theme
params = signature(stylable.set).parameters
colors = {color: getattr(stylable, color.removesuffix("_dark")) for color in dir(stylable) if color in params}
return stylable.set(**colors)
elif isinstance(stylable, gr.Blocks): # also handle components which do not use the theme (e.g. modals)
stylable.load(js="() => document.querySelectorAll('.dark').forEach(el => el.classList.remove('dark'))")
return stylable
else:
raise ValueError
def build_ui(model=list(models)[0], lock=False, rasterize=False, force_light=False, lock_reason="locked", timeout=120):
theme = remove_darkness(gr.themes.Soft()) if force_light else gr.themes.Soft()
with gr.Blocks(theme=theme, title="TikZ Assistant") as demo: # type: ignore
if force_light: remove_darkness(demo)
gr.Markdown(get_banner())
with gr.Row(variant="panel"):
with gr.Column():
info = (
"Describe what you want to generate. "
"Scientific graphics benefit from captions with at least 30 tokens (see examples below), "
"while simple objects work best with shorter, 2-3 word captions."
)
# caption = gr.Textbox(label="Caption", info=info, placeholder="Type a caption...")
# image = gr.Image(label="Image Input", type="pil")
image = gr.ImageEditor(label="Image Input", type="pil", sources=['upload', 'clipboard'], value=Image.new('RGB', (336, 336), (255, 255, 255)))
label = "Model" + (f" ({lock_reason})" if lock else "")
model = gr.Dropdown(label=label, choices=list(models.items()), value=models[model], interactive=not lock) # type: ignore
with gr.Accordion(label="Advanced Options", open=False):
temperature = gr.Slider(minimum=0, maximum=2, step=0.05, value=0.8, label="Temperature")
top_p = gr.Slider(minimum=0, maximum=1, step=0.05, value=0.95, label="Top-P")
top_k = gr.Slider(minimum=0, maximum=100, step=10, value=0, label="Top-K")
expand_to_square = gr.Checkbox(value=True, label="Expand image to square")
with gr.Row():
run_btn = gr.Button("Run", variant="primary")
stop_btn = gr.Button("Stop")
clear_btn = gr.ClearButton([image])
with gr.Column():
with gr.Tabs() as tabs:
with gr.TabItem(label:="TikZ Code", id=0):
info = "Source code of the generated image."
tikz_code = gr.Code(label=label, show_label=False, interactive=False)
with gr.TabItem(label:="Compiled Image", id=1):
result_image = gr.Image(label=label, show_label=False, show_share_button=rasterize)
clear_btn.add([tikz_code, result_image])
gr.Examples(examples=[
["https://waleko.github.io/data/image.jpg"],
["https://waleko.github.io/data/image2.jpg"],
["https://waleko.github.io/data/image3.jpg"],
["https://waleko.github.io/data/image4.jpg"],
], inputs=[image])
events = list()
finished = gr.Textbox(visible=False) # hack to cancel compile on canceled inference
for listener in [run_btn.click]:
generate_event = listener(
check_inputs,
inputs=[image],
queue=False
).success(
lambda: gr.Tabs(selected=0),
outputs=tabs, # type: ignore
queue=False
).then(
inference,
inputs=[model, image, temperature, top_p, top_k, expand_to_square],
outputs=[tikz_code, result_image, finished]
)
def tex_compile_if_finished(finished, *args):
yield from (tex_compile(*args, timeout=timeout, rasterize=rasterize) if finished == "True" else [])
compile_event = generate_event.then(
lambda finished: gr.Tabs(selected=1) if finished == "True" else gr.Tabs(),
inputs=finished,
outputs=tabs, # type: ignore
queue=False
).then(
tex_compile_if_finished,
inputs=[finished, tikz_code],
outputs=result_image
)
events.extend([generate_event, compile_event])
# model.select(lambda model_name: gr.Image(visible="clima" in model_name), inputs=model, outputs=image, queue=False)
for btn in [clear_btn, stop_btn]:
btn.click(fn=None, cancels=events, queue=False)
return demo