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Commit fafe0e26 authored by David Rouquet's avatar David Rouquet
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Functional demo with nice looking

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%% Cell type:code id:0d91640d-23ea-4079-b765-2eea030926c5 tags:
``` python
import importlib.util
import re
import amrlib
from amrlib.graph_processing.amr_plot import AMRPlot
import uuid
from IPython.display import SVG, display
import os
import shutil
import subprocess
from subprocess import Popen, PIPE, STDOUT
from glob import glob
import sys
import os
from IPython.display import HTML,IFrame
import ipywidgets
import dash_bootstrap_components as dbc
from dash import dcc, html, Input, Output
from jupyter_dash import JupyterDash as Dash
from dash.dependencies import Input, Output, State
import base64
AMR_BATCH_PATH = "/opt/dashboards/TetrasMARS/amrbatch/"
AMR_BATCH_PATH = "/opt/lib/TetrasMARS/amrbatch/"
sys.path.insert(0, os.path.abspath(AMR_BATCH_PATH))
import amrbatch
TENET_PATH = "/opt/dashboards/TetrasMARS/tenet/"
TENET_PATH = "/opt/lib/TetrasMARS/tenet/"
sys.path.insert(0, os.path.abspath(TENET_PATH))
import tenet
AMR_MODEL_PATH="/opt/dashboards/TetrasMARS/corpus/cm-tool/amrModel/model_parse_xfm_bart_large-v0_1_0"
AMR_MODEL_PATH="/opt/lib/TetrasMARS/corpus/cm-tool/amrModel/model_parse_xfm_bart_large-v0_1_0"
MEDIA_PATH = "/opt/dashboards/media/17/"
MEDIA_URL = "https://unsel.tetras-lab.io/dashboard/17/media/"
ROOT_PATH = "/opt/dashboards/TetrasMARS/tetras-mars-demo/"
AMRLD_PATH = "/opt/dashboards/TetrasMARS/tetras-mars-demo/lib/amrld/"
ROOT_PATH = "/opt/dashboards/TetrasMARS/tetras-mars-demo-prod/"
AMRLD_PATH = "/opt/lib/TetrasMARS/amrld/"
owl2vowlPath = '/opt/dashboards/tools/owl2vowl_0.3.7/owl2vowl.jar'
WEBVOWL_PATH = '/opt/webvowl/'
onto_prefix="ontologyTarget"
# The following is basically `import tenet`
#spec=importlib.util.spec_from_file_location("tenet",TENET_PATH+'tenet/__init__.py')
#tenet = importlib.util.module_from_spec(spec)
#spec.loader.exec_module(tenet)
```
%% Cell type:code id:295e4aef-bbd8-40f0-8d84-0b8032b7b039 tags:
``` python
#stog = amrlib.load_stog_model(model_dir="/opt/dashboards/TetrasMARS/corpus/cm-tool/amrModel/model_parse_xfm_bart_large-v0_1_0")
#prefixPath = uuidDirPath+"file"
#penmanPath = prefixPath+".amr.penman"
#svgPath = prefixPath+".amr.svg"
#ttlFilePath = uuidDirPath+onto_prefix+"-0/"+onto_prefix+"_factoid.ttl"
```
%% Cell type:code id:a410a6b3-865d-441f-9b83-90a1badae291 tags:
``` python
def clean_sting(string):
""" Sentence cleanup as needed """
return re.sub("(\.)*\\n", "", string)
def string2amr(string,stog):
stog_result = stog.parse_sents([clean_sting(string)], add_metadata=True)
return stog_result[0]
def show_svg(path):
display(SVG(filename=path))
def add_id_in_penman_if_needed(penmanStr,uuidStr):
if not(penmanStr.startswith('# ::id')):
penmanStr = '# ::id '+uuidStr+'\n'+penmanStr
return penmanStr
def owl2vowl(ttlFilePath, webvowlFileName, webvowlFilePath, uuid='', importList=[]):
# Run java parser
if importList == []:
cmd = ['java', '-jar', owl2vowlPath,
'-file', ttlFilePath]
else:
cmd = ['java', '-jar', owl2vowlPath,
'-file', ttlFilePath,
'-dependencies'] + importList
with Popen(cmd, stdout=PIPE, stderr=STDOUT) as p:
p.wait()
p.stdout.flush()
if p.returncode != 0:
print("Error in owl2vowl: \n\n"+p.stdout.read().decode())
os.rename(webvowlFileName, webvowlFilePath)
def localImage2htmlImg(imgPath):
with open(imgPath, "rb") as image_file:
img_data = base64.b64encode(image_file.read())
img_data = img_data.decode()
img_data = "data:image/svg+xml;base64,{}".format(img_data)
# ...
return html.Img(id="tag_id", src=img_data, width="100%", height="100%", className="img_class")#, alt="my image"
```
%% Cell type:code id:5fd9cf0c-990a-4776-b206-8cc94f87c7be tags:
``` python
def processStr(input):
# Define usefull variable and paths based on a uuid
uuidStr = str(uuid.uuid4())
uuidDirPath = "/opt/data/tmp/demo-tetras-mars/"+uuidStr+'/'
os.mkdir(uuidDirPath)
fullOntoPath = uuidDirPath+'full-ontology.ttl'
ontoBySentencePath = uuidDirPath+'onto-by-sentence/'
webvowlFileName = fullOntoPath.split('/')[-1].replace('ttl','json')
webvowlFilePath = WEBVOWL_PATH+uuidStr+'_'+webvowlFileName
uuidZipPath = MEDIA_PATH+uuidStr # without the .zip extention
uuidZipUrl = MEDIA_URL+uuidStr+".zip"
# Generate an AMR graph by sentence in a subfolder (with companion files such as images of the graphs)
amr_graph_list = amrbatch.parse_document_string_to_produce_amr_graph(
input, None, amr_model_path=AMR_MODEL_PATH, output_dirpath=uuidDirPath,
amrld_serialization=True)
# Construct ontologies from each AMR graph plus a "full" one that is the union
factoids = tenet.create_ontology_from_amrld_dir(
uuidDirPath,
onto_prefix="http://ontologies",
out_file_path=fullOntoPath,
technical_dir_path=ontoBySentencePath)
# Create a zip file so the user can download all generated files
owl2vowl(fullOntoPath, webvowlFileName, webvowlFilePath, uuid=uuidStr)
shutil.make_archive(uuidZipPath, 'zip', uuidDirPath)
return uuidDirPath, uuidZipUrl, webvowlFilePath
```
%% Cell type:code id:0cd10e8b-cf7a-4fd4-b8ac-540fcb943325 tags:
``` python
##################################################################################################
# THE FOLLOWING PART IS SPECIFIC TO TÉTRAS LAB
#
# The _get_tl_config function gets configuration parameters for your
# Tétras Lab instance.
# Those parameters are passed when initialising the Dash app.
##################################################################################################
def _get_tl_config():
import socket, errno, os
# Find a free port
host = "0.0.0.0"
port = 8050
end = 9999
found = False
while not found:
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
try:
s.bind((host, port))
found = True
except socket.error as e:
if e.errno == errno.EADDRINUSE:
port = port + 1
if (port > end):
raise "No available APP port"
else:
raise e
if (os.getenv("HOST", None) is not None):
proto = os.getenv("PROTO")
actualhost = os.getenv("JUPYTER_HOST", os.getenv("VOILA_HOST", ""))
localport = os.getenv("PORT", 80)
intermediatehost = os.getenv("HOST", "localhost")
base_path = f"/{actualhost}/app_proxy/{port}/"
proxified= f"{proto}://{intermediatehost}:{localport}{base_path}"
localurl = f"http://{host}:{port}"
proxy = f"{localurl}::{proxified}"
return ((proxified, host, port, proxy, base_path))
return ((f"http://localhost:{port}", host, port, None, "/"))
server_url, host, port, proxy, base_path = _get_tl_config()
app = Dash(
server_url=server_url,
requests_pathname_prefix=base_path,
external_stylesheets=[dbc.themes.BOOTSTRAP]
)
##################################################################################################
##################################################################################################
# THE FOLLOWING PART IS GENERIC (JUPYTER)-DASH CODE FROM https://dash.plotly.com/basic-callbacks
#
# The _get_tl_config function gets configuration parameters for your
# Tétras Lab instance.
# Those parameters are passed when initialising the Dash app.
##################################################################################################
app.layout = html.Div([
"Enter an english text and click on the button bellow to construct an ontology.",
html.H4("Enter an english text and click on the button bellow to construct an ontology.", style={'text-align': 'center'}),
html.Br(),
" You can then browse the results online or download them as a zip file.",
html.P("It should take about 10 sec/sentence. You can then browse the results online or download them as a zip file.", style={'text-align': 'center'}),
html.P("The text must be a simple succession of sentences. Fancy formating is not supported at the moment. ", style={'text-align': 'center'}),
html.Br(),
html.Br(),
dcc.Textarea(
html.Div(dbc.Textarea(
id='textarea-state',
value='Jupiter is a gas giant. Earth is a rock planet.',
style={'width': '80%', 'height': 100},
value='Jupiter is a gas giant. Earth is a rock planet.',style={'width': '100%', 'height': 130}),
style={'width': '60%', 'height': 130, 'margin-left': 'auto', 'margin-right': 'auto'},
),
html.Br(), html.Br(),
html.Button('Construct AMR graphs and ontology', id='textarea-state-button', n_clicks=0),
html.Div(
dbc.Button('Construct AMR graphs and ontology', id='textarea-state-button', n_clicks=0, outline=True, color="primary"),
className="text-center"),
html.Br(),
html.A(children="", href='', target="_blank",id="download-link"),
dcc.Loading(html.Div(html.A(children="", href='', target="_blank",id="download-link"), className="text-center")),
html.Br(),
html.Br(),
dcc.Loading(html.Div(id='my-output'), color='#A85431', style={"verticalAlign":"top"}),
dcc.Loading(html.Div(id='my-output'), type='circle'),
])
@app.callback(
#Output('textarea-state-output', 'children'),
Output(component_id='my-output', component_property='children'),
Output(component_id='download-link', component_property='children'),
Output(component_id='download-link', component_property='href'),
Input('textarea-state-button', 'n_clicks'),
State('textarea-state', 'value'),
prevent_initial_call=True,
)
def update_output(n_clicks, value):
if n_clicks > 0:
uuidDirPath, uuidZipUrl, webvowlFilePath = processStr(value)
#show_svg(svgPath)
#display(IFrame('''https://unsel.tetras-lab.io/webvowl/#{}">'''.format(webvowlFilePath.replace("/opt/webvowl/","").replace(".json","")),800,1200))
return [html.Div(
dbc.Accordion(
[
dbc.AccordionItem(
return [dbc.Row([dbc.Col(),
dbc.Col(dbc.Accordion(
[dbc.AccordionItem(
[
"You can click a class to see its instances in the right panel, they are not shown on the graph.",
localImage2htmlImg(svgPath)
],
title="AMR Graph for sentence "+re.sub(r'.document.*', '', svgPath.replace(uuidDirPath+"document-","")),
)
for svgPath in sorted(glob(uuidDirPath+"document-*/*.svg"))
]+
[dbc.AccordionItem(
[
"You can click a class to see its instances in the right panel, they are not shown in the graph.",
html.Br(),
'''https://unsel.tetras-lab.io/webvowl/#{}'''.format(webvowlFilePath.replace("/opt/webvowl/","").replace(".json","")),
html.Br(),
html.Iframe(src='''https://unsel.tetras-lab.io/webvowl/#{}'''.format(webvowlFilePath.replace("/opt/webvowl/","").replace(".json","")),style={"height": "800px", "width": "100%"}),
],
title="Browse ontology",
title="Browse ontology", item_id='onto'
)
]
#+ [dbc.AccordionItem(
# [
# localImage2htmlImg(svgPath)
# ],
# title="AMR Graph",
# )
#
# for svgPath in glob(uuidDirPath+"document-*/*.svg")
# ]
#
# ,
)
),
] , active_item='onto'), width=10), dbc.Col()
]),
"Download Zip File", uuidZipUrl
]
#@app.callback(
# Output("download-zip", "data"),
# Input("download-zip-button", "n_clicks"),
# prevent_initial_call=True,
#)
#def func(n_clicks):
# if n_clicks > 0:
# return dcc.send_file('https://unsel.tetras-lab.io/dashboard/17/media/9f7287d0-e7b2-4328-9137-7a7c44225b68.zip')
app.run_server(mode="inline",
#mode="external",
host=host, port=port, proxy=proxy, height=2000)
##################################################################################################
```
%% Cell type:code id:b1817beb-04b7-4e6f-9b82-675de76cf8af tags:
``` python
```
......
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