"""Run interactively.""" # pylint: disable=invalid-name, too-many-arguments, unused-argument, redefined-builtin, unused-import, wrong-import-position, too-many-locals, too-many-statements from typing import Any, Tuple, Optional, Union # noqa import sys from pathlib import Path # noqa import subprocess as sp import shlex import platform import signal from random import randint from textwrap import dedent from itertools import zip_longest # import socket from socket import socket, AF_INET, SOCK_STREAM from sklearn.cluster import DBSCAN # noqa import joblib from varname import nameof from icecream import install as ic_install, ic import logzero from logzero import logger # import numpy as np import pandas as pd import seaborn as sns import matplotlib.pyplot as plt # noqa # from tabulate import tabulate from fastlid import fastlid # for embeddable python if "." not in sys.path: sys.path.insert(0, ".") import gradio as gr # from radiobee.error_msg import error_msg from radiobee.process_upload import process_upload from radiobee.gradiobee import gradiobee ic_install() ic.configureOutput( includeContext=True, outputFunction=logger.info, ) ic.enable() # ic.disenable() # to turn off sns.set() sns.set_style("darkgrid") fastlid.set_languages = ["en", "zh"] signal.signal(signal.SIGINT, signal.SIG_DFL) print("Press Ctrl+C to quit\n") def savelzma(obj, fileloc: str = None): """Aux funciton.""" if fileloc is None: fileloc = nameof(obj) # this wont work joblib.dump(obj, f"data/{fileloc}.lzma") def greet(input): """Greet yo.""" return f"'Sup yo! (your input: {input})" def upfile1(file1, file2=None) -> Tuple[str, str]: """Upload file1, file2.""" del file2 return file1.name, f"'Sup yo! (your input: {input})" def process_2upoads(file1, file2): """Process stuff.""" # return f"{process_upload(file1)}\n===***\n{process_upload(file2)}" text1 = [_.strip() for _ in process_upload(file1).splitlines() if _.strip()] text2 = [_.strip() for _ in process_upload(file2).splitlines() if _.strip()] text1, text2 = zip(*zip_longest(text1, text2, fillvalue="")) df = pd.DataFrame({"text1": text1, "text2": text2}) # return tabulate(df) # return tabulate(df, tablefmt="grid") # return tabulate(df, tablefmt='html') return df if __name__ == "__main__": debug = True # debug = False uname = platform.uname() # match = re.search(r'[a-z\d]{10,}', gethostname()) # hf spaces release: '4.14.248-189.473.amzn2.x86_64' # match = re.search(r'[a-z\d]{10,}', node) # if match and node.system.lower() in ["linux"]: if "amzn2" in uname.release: # likely hf spaces server_name = "0.0.0.0" debug = False debug = True share = True # set UTC+8, probably wont work in hf spaces, no permission try: sp.check_output(shlex.split("ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime")) except Exception as exc: logger.error(" set timezonef failed: %s", exc) else: server_name = "127.0.0.1" share = False if debug: logzero.loglevel(10) logger.debug(" debug ") logger.info(" info ") # _ = """ inputs = [ gr.inputs.Textbox( # placeholder="Input something here", default="test text" ) ] inputs = ["file", "file"] inputs = [ gr.inputs.File(label="file 1"), # gr.inputs.File(file_count="multiple", label="file 2", optional=True), gr.inputs.File(label="file 2", optional=True), ] _ = """ tf_type: Literal[linear, sqrt, log, binary] = 'linear' idf_type: Optional[Literal[standard, smooth, bm25]] = None dl_type: Optional[Literal[linear, sqrt, log]] = None norm: norm: Optional[Literal[l1, l2]] = None x min_df: int | float = 1 x max_df: int | float = 1.0 # """ input_tf_type = gr.inputs.Dropdown( ["linear", "sqrt", "log", "binary"], default="linear" ) input_idf_type = gr.inputs.Radio( ["None", "standard", "smooth", "bm25"], default="None" ) # need to convert "None" this to None in fn input_dl_type = gr.inputs.Radio( ["None", "linear", "sqrt", "log"], default="None" ) # ditto input_norm_type = gr.inputs.Radio(["None", "l1", "l2"], default="None") # ditto # modi inputs 1, definitions sent_ali_algo = gr.inputs.Radio(["None", "fast", "slow"], default="None") inputs = [ # tot. 9, meed to modify input of gradio & examples gr.inputs.File(label="file 1"), gr.inputs.File(label="file 2", optional=True), input_tf_type, # modi inputs 2 input_idf_type, input_dl_type, input_norm_type, gr.inputs.Slider( minimum=1, maximum=20, step=0.1, default=10, ), gr.inputs.Slider( minimum=1, maximum=20, step=1, default=6, ), sent_ali_algo, ] examples = [ [ "data/test_zh.txt", "data/test_en.txt", "linear", "None", "None", "None", 10, 6, "None", ], [ "data/test_zh.txt", "data/test_en.txt", "linear", "None", "None", "None", 10, 6, "fast", ], [ "data/test_zh.txt", "data/test_en.txt", "linear", "None", "None", "None", 10, 6, "slow", ], [ "data/test_en.txt", "data/test_zh.txt", "linear", "None", "None", "None", 10, 6, "None", ], [ "data/shakespeare_zh500.txt", "data/shakespeare_en500.txt", "linear", "None", "None", "None", 10, 6, "None", ], [ "data/shakespeare_en500.txt", "data/shakespeare_zh500.txt", "linear", "None", "None", "None", 10, 6, "None", ], [ "data/hlm-ch1-zh.txt", "data/hlm-ch1-en.txt", "linear", "None", "None", "None", 10, 6, "None", ], [ "data/hlm-ch1-en.txt", "data/hlm-ch1-zh.txt", "linear", "None", "None", "None", 10, 6, "None", ], [ "data/ps-cn.txt", "data/ps-en.txt", "linear", "None", "None", "None", 10, 4, "None", ], [ "data/test-dual.txt", "data/empty.txt", "linear", "None", "None", "None", 10, 6, "None", ], [ "data/英译中国现代散文选1(汉外对照丛书).txt", "data/empty.txt", "linear", "None", "None", "None", 10, 6, "None", ], [ "data/test-zh-ja.txt", "data/empty.txt", "linear", "None", "None", "None", 10, 6, "None", ], [ "data/xiyouji-ch1-zh.txt", "data/xiyouji-ch1-de.txt", "linear", "None", "None", "None", 10, 6, "None", ], [ "data/demian-hesse-de.txt", "data/demian-hesse-en.txt", "linear", "None", "None", "None", 10, 6, "None", ], [ "data/catcher-in-the-rye-shixianrong-zh.txt", "data/catcher-in-the-rye-boll-de.txt", "linear", "None", "None", "None", 10, 6, "None", ], ] # modi examples setup outputs = ["dataframe", "plot"] outputs = ["plot"] outputs = ["dataframe", "plot"] out_df = gr.outputs.Dataframe( headers=None, max_rows=12, # 20 max_cols=None, overflow_row_behaviour="paginate", type="auto", label="To be aligned", ) out_df_aligned = gr.outputs.Dataframe( headers=None, # max_rows=12, # 20 max_cols=3, overflow_row_behaviour="paginate", type="auto", label="aligned pairs", ) out_file_dl = gr.outputs.File( label="Click to download csv", ) out_file_dl_excel = gr.outputs.File( label="Click to download xlsx", ) out_sents_dl = gr.outputs.File( label="Click to download sents csv", ) out_sents_dl_excel = gr.outputs.File( label="Click to download sents xlsx", ) # modi outputs 1, definitions # modi outputs 2, need to modify gradio error_msg outputs = [ # tot. 8 out_df, gr.outputs.Image(label="plot"), out_file_dl, out_file_dl_excel, out_sents_dl, out_sents_dl_excel, out_df_aligned, gr.outputs.HTML(), ] # outputs = ["dataframe", "plot", "plot"] # wont work # outputs = ["dataframe"] # outputs = ["dataframe", "dataframe", ] server_port = 7860 with socket(AF_INET, SOCK_STREAM) as sock: sock.settimeout(0.01) # 10ms # try numb times before giving up numb = 5 for _ in range(numb): if sock.connect_ex(("127.0.0.1", server_port)) != 0: # port idle break server_port = server_port + randint(0, 50) else: raise SystemExit(f"Tried {numb} times to no avail, giving up...") description = "WIP showcasing a blazing fast dualtext aligner, currrently supported language pairs: en-zh/zh-en for fast-track, other language pairs are handled by slow-track" # moved to userguide.rst in docs article = dedent( """ ## NB * `radiobee aligner` is a sibling of `bumblebee aligner`. To know more about these aligners, please join qq group `316287378`. * Uploaded files should be in pure text format (txt, md, csv etc). `docx`, `pdf`, `srt`, `html` etc may be supported later on. * Click "Clear" first for subsequent submits when uploading files. * `tf_type` `idf_type` `dl_type` `norm`: Normally there is no need to touch these unless you know what you are doing. * Suggested `esp` and `min_samples` values -- `esp` (minimum epsilon): 8-12, `min_samples`: 4-8. - Smaller larger `esp` or `min_samples` will result in more aligned pairs but also more **false positives** (pairs falsely identified as candidates). On the other hand, larger smaller `esp` or `min_samples` values tend to miss 'good' pairs. * If you need to have a better look at the image, you can right-click on the image and select copy-image-address and open a new tab in the browser with the copied image address. * `Flag`: Should something go wrong, you can click Flag to save the output and inform the developer. """ ).strip() article = dedent( """
readiobee docs: readthedocs or in Chinese but rather short 中文使用说明
""" ).strip() css_image = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}" # css = ".output_image, .input_image {height: 20rem !important; width: 100% !important;}" css_input_file = ".input_file {height: 8rem !important; width: 100% !important;}" css_output_file = ".output_file {height: 4rem !important; width: 100% !important;}" logger.info("running at port %s", server_port) _ = """ inputs = ... outputs = ... # properly # define gradiobee to take inputs and spil out outputs iface = gr.Interface( fn=gradiobee, inputs, outputs, ) # """ iface = gr.Interface( # fn=greet, # inputs="text", # fn=process_upload, # fn=process_2upoads, # inputs=["file", "file"], # outputs="text", # outputs="html", # fn=fn, fn=gradiobee, inputs=inputs, outputs=outputs, title="radiobee-aligner🔠", description=description, article=article, examples=examples, examples_per_page=4, # theme="darkgrass", theme="grass", layout="vertical", # horizontal unaligned allow_flagging="manual", # "auto" flagging_options=[ "fatal", "bug", "brainstorm", "excelsior", ], # "paragon"], css=f"{css_image} {css_input_file} {css_output_file}", enable_queue=True, ) iface.launch( share=share, debug=debug, show_error=True, server_name=server_name, # server_name="127.0.0.1", server_port=server_port, # show_tips=True, enable_queue=True, # height=150, # 500 width=900, # 900 ) _ = """ ax = sns.heatmap(cmat, cmap="viridis_r") ax.invert_yaxis() ax.set_xlabel(fastlid(df.text1)[0]) ax.set_xlabel(fastlid(df.text2)[0]) # return df, plt return plt.gca() https://colab.research.google.com/drive/1Gz9624VeAQLT7wlETgjOjPVURzQckXI0#scrollTo=qibtTvwecgsL colab gradio-file-inputs-upload.ipynb iface = gr.Interface(plot_text, "file", "image") def is_port_in_use(port): import socket with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: return s.connect_ex(('localhost', port)) == 0 socket.socket(socket.AF_INET, socket.SOCK_STREAM).connect_ex(('127.0.0.1', 7911)) --- css https://huggingface.co/spaces/nielsr/LayoutLMv2-FUNSD/blob/main/app.py#L83 css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}" #css = "@media screen and (max-width: 600px) { .output_image, .input_image {height:20rem !important; width: 100% !important;} }" # css = ".output_image, .input_image {height: 600px !important}" mod = 'en2zh' packname = packx.__name__ globals()[mod] = getattr(importlib.import_module(f"{packname}.{mod}"), mod) """