Saravanan666/pypi-org huggingface dataset:
Package: allak
allakA CLI tool to produce an IPv6 address with the host portion being a modified EUI-64.InstallationPython version: >=3.11Using pipInside a virtual environmentpip install allak
allak-cli --helpWithout a virtual environmentpip install --user allak
allak-cli --helpUsagePackage functionality is provided by an entrypointallak-cli.allak-cli [OPTIONS] PREFIX MAC

  Given IPv6 PREFIX of prefix-length 64 and MAC address returns IPv6 host
  address with interface identifier as modified EUI-64.

Options:
  --version  Show the version and exit.
  --help     Show this message and exit.MetaAllak is a mountain in Sweden, a village in Altai, a train station in Korea.
Package: allalgorithms
The All ▲lgorithms Python library<br>
<br>
<br>
<br>

[`python.allalgorithms.com`](https://python.allalgorithms.com)Why?Why not 😂Clean and focusedActively maintainedBecause All Algorithms should easy to use in PythonRead the detailed documentation atpython.allalgorithms.comor see thedocsdirectory on Github. SeeTree.Installpip install allalgorithmsUsage Examplefromallalgorithms.searchesimportbinary_searcharr=[-2,1,2,7,10,77]print(binary_search(arr,7))# -> 3print(binary_search(arr,3))# -> NoneTreeSearchesBinary SearchSortingMerge SortRelatedjavascript-lib: All ▲lgorithms Javascript libraryMaintainersCarlos AbrahamLicenseMITLicense ©Carlos Abraham
Package: allanc-sphinx
Custom Sphinx themes for the documentation ofmy projects.Themesyeen: Slight modification of theTriAx Corptheme.Defaults to blue colours and sidebar on the left.Field lists now use themainlightcoloroption for the background colour for headers, rather than a hardcoded blue colour.Optionally adds a Github “Octocat” banner to the repository (created byTim Holman).UsageTo use the theme, specifyallanc_sphinx[yeen]as a dependency, and in yourconf.pyfile:html_theme = 'yeen'If you want to add the Octocat banner, you just need to define the link you want to go to - for example:html_theme_options = {'github_url': 'https://github.com/the-allanc/allanc_sphinx'}
Package: allauth-jinja
allauth-jinjaThe complete set ofdjango-allauthtemplates rewritten in jinja.Installation & Usage[not published yet]Add allauth_jinja to your installed apps above allauth, e.g.INSTALLED_APPS = [
  ...
  allauth_jinja,
  allauth,
  ...
]In your templates settings for jinja you must have at least the following{
  "APP_DIRS": True,
  "OPTIONS": {
    "match_extension": None,
    "app_dirname": "jinja2",
    "undefined": "jinja2.Undefined",
    "context_processors": [
      "django.template.context_processors.request",
      "django.contrib.messages.context_processors.messages",
      ...
    ],
    "globals": {
      ...,
      "user_display": "allauth_jinja.account.templatetags.account.user_display",
      ...
    }
  }
}Depending on what templates you use you'll need to add the relevant global functions.
Package: allauth-socialaccount-provider-keycloak
allauth-socialaccount-provider-keycloakinstallpip install allauth-socialaccount-provider-keycloakconfigureINSTALLED_APPS=[...'django.contrib.sites',...#'allauth','allauth.account','allauth.socialaccount','allauth_socialaccount_provider_keycloak',...]AUTHENTICATION_BACKENDS=('django.contrib.auth.backends.ModelBackend','allauth.account.auth_backends.AuthenticationBackend',)SOCIALACCOUNT_PROVIDERS={'keycloak':{'KEYCLOAK_URL':"https://sso.grafcan.es/auth/realms/demo",}}
Package: allauth-watchdog-id
allauth-watchdog_idA django-allauth provider for Watchdog ID.Free software: MIT licenseDocumentation:https://allauth-watchdog-id.readthedocs.io.FeaturesProvides integration of Django withid.siecobywatelska.plthroughdjango-allauth.CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2016-12-03)First release on PyPI.
Package: allbaro-chunilpathfinder
AllbaroAllbaro한국환경공단 올바로 시스템 스크래핑을 위한 파이썬 라이브러리>>>importdatetime>>>fromallbaroimportAllbaro>>>>>>allbaro=Allbaro()>>>>>># 올바로 시스템 로그인>>>allbaro.authenticate('올바로 시스템 아이디','올바로 시스템 패스워드')>>># 인계서진행상황확인 - 인계서진행상황 정보 조회>>>start_date=datetime.date(2023,5,1)>>>end_date=datetime.date(2023,5,31)>>>>>>result_list=allbaro.handover_process_list(start_date,end_date)
Package: allcasts
allcasts 📻 🗃A Python package for downloading all available episodes from a podcast RSS feed. Useful for making private archives of your favourite podcasts.Installationpip install allcastsUsageCommand Line: Interactive ModeFrom your terminal runallcastswhich will kindly ask you for the an RSS feed's URL and download all available episodes for that podcast.$allcasts===================================================================WelcometotheAllCastsApp!==================================================================PleaseentertheURLofthepodcastfeedyouwanttodownload:https://atp.fm/rss
Pleaseenterthedirectoryyouwanttodownloadthepodcastto[leaveblankforcurrentdir]:Downloadingallpodcastsfromhttps://atp.fm/rssto/Users/lewis/Documents/Python-Projects/allcasts
Downloadinghttps://traffic.libsyn.com/atpfm/atp464.mp3[............................................................................................]🎧Downloaded464:MonksatDraftingTables
Downloadinghttps://traffic.libsyn.com/atpfm/atp463.mp3[............................................................................................]🎧Downloaded463:NoIndicationofProgress
Downloadinghttps://traffic.libsyn.com/atpfm/atp462.mp3[............................................................................................]🎧Downloaded462:XcodeX
Downloadinghttps://traffic.libsyn.com/atpfm/atp461.mp3[...........]Command Line: ArgumentsAllcasts supports a variety of command line arguments. To display help message below useallcasts -husage: allcasts.py [-h] [-d <DIRECTORY>] -f <URL> [-s <NUMBER>] [-e <NUMBER>] [-a] [-n <NUMBER>]

A friendly command line podcast downloader - supports downloading entire feeds, individual episodes, and a range of episodes

optional arguments:
  -h, --help            show this help message and exit
  -d <DIRECTORY>, --directory <DIRECTORY>
                        the directory to save the podcast episodes
  -f <URL>, --feed <URL>
                        the url of the podcast feed
  -s <NUMBER>, --start <NUMBER>
                        the number of the first episode to download
  -e <NUMBER>, --end <NUMBER>
                        the number of the last episode to download
  -a, --all             download all episodes
  -n <NUMBER>, --number <NUMBER>
                        download a specific episodeExample Commands:Download episodes 100 to 120allcasts-f"https://atp.fm/rss"-s100-e120Download all episodes of a podcastallcasts-f"https://atp.fm/rss"-aDownload episode 200allcasts-f"https://atp.fm/rss"-n100As a Python moduleallcasts is a Python module that can be imported and used in your own Python code too!fromallcastsimportAllCastsAllCasts.download_all('https://atp.fm/rss','/Users/lewis/Documents/Python-Projects/allcasts')LimitationsPrivate Patreon RSS feeds are not currently supported due to their strange DRM measures.TodoAdd support for downloading multiple podcasts at once.Add support for command line arguments.Add itunes API support to search for podcasts and select the correct feed.
Package: allcities
allcitiesa Python library to work with all the cities of the world with a population of at least 1000 inhabitants.NoteThis library was whipped up in an afternoon when I got a little carried away when I really needed something much simpler. It is not fully tested and will need revisiting/cleanup.InstallationpipinstallallcitiesUsage exampleUsage of this library is quite simple.fromallcitiesimportcitiesresults=cities.filter(name='Los Angeles')forresultinresults:print(result)citiesis a set-like object that contains objects that represent cities. The above code will output:<Santa Rosa los Angeles, 11, MX>
<Los Angeles, 10, MX>
<Los Angeles, CA, US>
<Los Angeles, 25, MX>
<Lake Los Angeles, CA, US>
<East Los Angeles, CA, US>
<Los Angeles, 13, PH>You can chain/combine filters as follows:results=cities.filter(name='Los Angeles').filter(country_code='US')results2=cities.filter(name='Los Angeles',country_code='US')print(results==results2)forresultinresults:print(result)gives youTrue
<Los Angeles, CA, US>
<East Los Angeles, CA, US>
<Lake Los Angeles, CA, US>You can also filter on numeric properties. The syntax to do so is a comparison operator<, <=, ==, !=, >=, >followed by a numeric value.results=cities.filter(elevation='>1000')results2=cities.filter(elevation='>1000').filter(elevation='<1500')print(results)print(results2)Gives you<CitySet (1339)>
<CitySet (795)>Each city object has properties that can be accessed normally or filtered on. You can also export a dictionary with the.dictproperty.pprint.pprint(city_object.dict)Here is the resulting dict{'admin1_code':'CA','admin2_code':'037','alternatenames':['East Los Angeles','Este de Los Angeles','Este de Los Ángeles','Ist Los Andzeles','Orienta Losangeleso','Orienta Losanĝeleso','dong luo shan ji','iseuteuloseuaenjelleseu','ista lasa enjelsa','isutorosanzerusu','Ист Лос Анџелес','इस्ट लस एन्जेल्स','イーストロサンゼルス','东洛杉矶','이스트로스앤젤레스'],'asciiname':'East Los Angeles','country_code':'US','dem':63,'elevation':61,'feature_class':'P','feature_code':'PPL','geonameid':5344994,'latitude':34.0239,'longitude':-118.17202,'modification_date':'2011-05-14','name':'East Los Angeles','population':126496,'timezone':'America/Los_Angeles'}LicenseThis project is licensed under the MIT License - see theLICENSE.mdfile for detailsRelease History1.0.0Initial ReleaseContributingFork it (https://github.com/Jonchun/allcities/fork)Create your feature branch (git checkout -b feature/fooBar)Commit your changes (git commit -am 'Add some fooBar')Push to the branch (git push origin feature/fooBar)Create a new Pull Request
Package: all-clip
all_clipLoad any clip model with a standardized interfaceInstallpip install all_clipPython examplesfromall_clipimportload_clipimporttorchfromPILimportImageimportpathlibmodel,preprocess,tokenizer=load_clip("open_clip:ViT-B-32/laion2b_s34b_b79k",device="cpu",use_jit=False)image=preprocess(Image.open(str(pathlib.Path(__file__).parent.resolve())+"/CLIP.png")).unsqueeze(0)text=tokenizer(["a diagram","a dog","a cat"])withtorch.no_grad(),torch.cuda.amp.autocast():image_features=model.encode_image(image)text_features=model.encode_text(text)image_features/=image_features.norm(dim=-1,keepdim=True)text_features/=text_features.norm(dim=-1,keepdim=True)text_probs=(100.0*image_features@text_features.T).softmax(dim=-1)print("Label probs:",text_probs)# prints: [[1., 0., 0.]]Checkout these examples to call this as a lib:example.pyAPIThis module exposes a single functionload_clip:clip_modelCLIP model to load (defaultViT-B/32). See below supported models section.use_jituses jit for the clip model (defaultTrue)warmup_batch_sizewarmup batch size (default1)clip_cache_pathcache path for clip (defaultNone)devicedevice (defaultNone)Related projectsclip-retrievalto use clip for inference, and retrievalopen_clipto train clip modelsCLIP_benchmarkto evaluate clip modelsSupported modelsOpenAISpecify the model as "ViT-B-32"Openclip"open_clip:ViT-B-32/laion2b_s34b_b79k"to use theopen_clipHF CLIP"hf_clip:patrickjohncyh/fashion-clip"to use thehugging faceDeepsparse backendDeepSparseis an inference runtime for fast sparse model inference on CPUs. There is a backend available within clip-retrieval by installing it withpip install deepsparse-nightly[clip], and specifying aclip_modelwith a prepended"nm:", such as"nm:neuralmagic/CLIP-ViT-B-32-256x256-DataComp-s34B-b86K-quant-ds"or"nm:mgoin/CLIP-ViT-B-32-laion2b_s34b_b79k-ds".Japanese clipjapanese-clipprovides some models for japanese.
For example one isja_clip:rinna/japanese-clip-vit-b-16For developmentEither locally, or ingitpod(doexport PIP_USER=falsethere)Setup a virtualenv:python3 -m venv .env
source .env/bin/activate
pip install -e .to run tests:pip install -r requirements-test.txtthenmake lint
make testYou can usemake blackto reformat the codepython -m pytest -x -s -v tests -k "ja_clip"to run a specific test
Package: allcrypt
Allcrypt Encryption/DecryptionAllcrypt is a Python application for file and message encryption/decryption using Fernet symmetric key cryptography.FeaturesEncrypt and decrypt files securelyEncrypt and decrypt messagesGenerate and manage encryption keys on a USB driveInstallationInstall the package using pip:pipinstallallcryptRun the Allcrypt GUI:allcryptUsageEncrypt a MessageLaunch the Allcrypt GUI.Enter the path to the USB drive in the provided field.Enter the message or encrypted bytes in the text box.Click the "Encrypt Message" button.Follow any prompts to enter the password for key encryption.Decrypt a MessageLaunch the Allcrypt GUI.Enter the path to the USB drive in the provided field.Enter the encrypted message in the text box.Click the "Decrypt Message" button.Follow any prompts to enter the password for key decryption.Encrypt a FileLaunch the Allcrypt GUI.Enter the path to the USB drive in the provided field.Click the "Encrypt File" button.Choose the source file to encrypt.Choose the destination file for the encrypted output.Optionally, check the "Compress Files" and "Shred Original File" checkboxes.Click the "Encrypt File" button.Decrypt a FileLaunch the Allcrypt GUI.Enter the path to the USB drive in the provided field.Click the "Decrypt File" button.Choose the source file to decrypt.Choose the destination file for the decrypted output.Optionally, check the "Shred Original File" checkbox.Click the "Decrypt File" button.Generate a New KeyLaunch the Allcrypt GUI.Enter the path to the USB drive in the provided field.Click the "Generate New Key for this USB" button.Enter a password for key encryption when prompted.The new key will be generated and saved on the USB drive.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details.About Me:My name is PranavVisit myGithubTo look at source code on github and raise issues:Allcrypt Source code
Package: alldata
This is a Package in which you can Extract Images,Text and Tables from 1 packageFree software: BSD 2-Clause LicenseInstallationpip install alldataYou can also install the in-development version with:pip install git+ssh://git@https://github.com/shehrozkapoor/alldata.git/shehrozkapoor/python-alldata.git@masterDocumentationhttps://python-alldata.readthedocs.io/DevelopmentTo run all the tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.0.0 (2020-12-13)First release on PyPI.
Package: allegro5
ALLEGRO 5 OFFICIAL DISTRIBUTIONAllegro is a cross-platform library mainly aimed at video game and multimedia programming. It handles common, low-level tasks such as creating windows, accepting user input, loading data, drawing images, playing sounds, etc. and generally abstracting away the underlying platform...This is the official allegro 5 wrapper in python. It was built from theofficial github repousing cmake.Tested onwindows 10with a32-bitpython interpreter(It is preferable to use a 32-bit interpreter because 64-bit hasn't been testedyet)Demo scriptimportosos.environ['ALLEGRO5_DLL']=r'path\to\allegro5\dlls'os.environ['ALLEGRO5_VERSION']='5.0.10'# this is just an examplefromallegro5import*al_run_demo()The demo game is hostedhereDocumentationYou can find official documentationhere
Package: allenai-common
AllenAI-CommonThis repository is a copy-paste of the common components
from the1.1.0version ofAllenNLP library.The following classes were extracted:FromParamsParamsLazyRegistrableAnd freed from ML/DL/NLP dependencies (e.g.scikit-learn,torch,nltk,spacy,tensorboardX,transformers).Usagepipinstallallenai-commonfromallenai_commonimportRegistrable,Params,Lazy,FromParams# Do something you would normally do when solving NLP tasks using AllenNLP# But at this time use imported modules for non-NLP tasks
Package: allencell-ml-segmenter
allencell-ml-segmenterA plugin to leverage ML segmentation in napari.Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installallencell-ml-segmenterviapip:pip install allencell-ml-segmenterTo install latest development version :pip install git+https://github.com/AllenCell/allencell-ml-segmenter.gitContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theBSD-3license,
"allencell-ml-segmenter" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: allencrf
#AllenCRF
A full features CRF for PyTorch extracted from theAllenNLP FrameworkDocsSee the AllenNLPdocumentation about CRFfor full API docs.WhyThe CRF implementation in the AllenNLP framework is very good and easy to use. It notably has a convenient API
for specifying allowed (and thus forbidden) transitions.We extracted the CRF implementation from the framework, so that we can use it without the other dependencies
that AllenNLP includes.CreditsTheoriginal implementationwas written byJoel Gruswith ongoing work from the good folks at AllenNLP.
Package: allenlib
init:
logo_allenlib():a logo of allenlib
computer_os:
dfrgui():open dfrgui
repairdisk(a):repair a disk
cleanmgr():clean the computer
message:
info(t,m):show info t:title m:message
warning(t,m):show warning t:title m:message
error(t,m):show error t:title m:message
ask(t,m):ask t:title m:message
ok(t,m):ask ok t:title m:message
yes(t,m):ask yes t:title m:message
retry(t,m):ask retry t:title m:message
ync(t,m):ask ync t:title m:message
printfun:
printfun(a):print fun a
raise:
raise(a):raise Exception(a)
speak:
speak(a):speak a
translate(a):translate a
print_load:
progess_bar(title,range):bar for linux
progess_bar_win(title,range):bar for windows
simplepygame:
it is simple than pygame,but it is only a pygame tool!
font(filename,size):set font
text(text,colorlist,bgcolor=None):show text
update():update
isquit():is quit?
autoquit():quit
quitis():auto isquit autoquit
quitwhile():quit is for while ...:
bgmsc:play background music
msc():sound value
playmsc(msc):msc() + autoplay
nobgm():stop background music
readini:
class readini(file):
read(section,value)
getbool(section,value)
-----The End of readini
Package: allennlp-dataframe-mapper
AllenNLP integration for sklearn-pandasallennlp-dataframe-mapperis a Python library that providesAllenNLPintegration forsklearn-pandas.InstallationInstalling the library and dependencies is simple usingpip.$pipinstallallennlp-dataframe-mapperExampleThis library enables users to specify the in a jsonnet config file.
Here is an example of the mapper for a famousiris dataset.Configallennlp-dataframe-mapperis specified the transformations of the mapper injsonnetconfig file like followingmapper_iris.jsonnet:{"type":"default","features":[[["sepal length (cm)"],null],[["sepal width (cm)"],null],[["petal length (cm)"],null],[["petal width (cm)"],null],[["species"],[{"type":"flatten"},{"type":"label-encoder"}]],],"df_out":true,}MapperThe mapper takes a param of transformations from the config file.
We can use thefit_transformshortcut to both fit the mapper and see what transformed data.fromallennlp.commonimportParamsfromallennlp_dataframe_mapperimportDataFrameMapperparams=Params.from_file("mapper_iris.jsonnet")mapper=DataFrameMapper.from_params(params=params)print(mapper)# DataFrameMapper(df_out=True,#                 features=[(['sepal length (cm)'], None, {}),#                           (['sepal width (cm)'], None, {}),#                           (['petal length (cm)'], None, {}),#                           (['petal width (cm)'], None, {}),#                           (['species'], [FlattenTransformer(), LabelEncoder()], {})])mapper.fit_transform(df)LicenseMIT
Package: allennlp-hydra
AllenNLP-HydraPlugin ForAllenNLPthat enables
composing configs through the use of theHydra Library from Facebook Research.NOTEthere is no affiliation between this project and AllenNLP or the Allen
Institute for AI.We use the samecontributions guidelineas AllenNLP in order to maintain similar code styles. For this reasonour style
guideis
the same asthat found in their repository.Install InstructionsClone the repopipinstall.echoallennlp_hydra>>~.allennlp_pluginsThe second line addsallennlp-hydrato the allennlp plugins file so that it
can globally be recognized.Basic GuideSay you have the following directory structure:project
+-- conf
|   +-- dataset_readers
|   |   +-- A.yaml
|   |   +-- B.yaml
|   +-- models
|   |   +-- C.yaml
|   |   +-- D.yaml
|   +-- config.yaml
+-- experimentsconf/dataset_readers/A.yaml:type: A
start_token: 

end_token: 
conf/dataset_readers/B.yaml:type: B
start_token: [CLS]
end_token: [SEP]conf/models/C.yaml:type: C
layers: 5conf/models/D.yaml:type:Dinput_dim:10config.yamldefaults:
    - dataset_reader: A
    - model: C

debug: falseThen running the commandallennlpcomposeconfconfigexample-sexperimentsProduces the fileproject/experiments/config.json{"dataset_reader":{"type":"A","start_token":"
","end_token":"
"},"model":{"type":"C","layers":5},"debug":false}If you want to override the config and use theBdataset reader with theDmodel, you would modify the previous command:allennlpcomposeconfconfigexample-sexperiments-omodel=Ddataset_reader=BProduces the fileproject/experiments/config.json{"dataset_reader":{"type":"B","start_token":"[CLS]","end_token":"[SEP]"},"model":{"type":"D","input_dim":10},"debug":false}And if you wanted to changeinput_dimof modelDto 25:allennlpcomposeconfconfigexample-sexperiments-omodel=Ddataset_reader=Bmodel.input_dim=25Produces the fileproject/experiments/config.json{"dataset_reader":{"type":"B","start_token":"[CLS]","end_token":"[SEP]"},"model":{"type":"D","input_dim":25},"debug":false}
Package: allennlp-runmodel
allennlp-runmodelRun aAllenNLPtrained model, and serve it with WebAPI.UsageRun the programExecute the program in terminator, the option--helpwill show help message:$allennlp-runmodel--helpUsage: allennlp-runmodel [OPTIONS] COMMAND1 [ARGS]... [COMMAND2 [ARGS]...]...Start a webservice for running AllenNLP models.Options:-V, --version-h, --host TEXT                 TCP/IP host for HTTP server.  [default:localhost]-p, --port INTEGER              TCP/IP port for HTTP server.  [default:8000]-a, --path TEXT                 File system path for HTTP server Unix domainsocket. Listening on Unix domain sockets isnot supported by all operating systems.-l, --logging-config FILE       Path to logging configuration file (JSON,YAML or INI) (ref: https://docs.python.org/library/logging.config.html#logging-config-dictschema)-v, --logging-level [critical|fatal|error|warn|warning|info|debug|notset]Sets the logging level, only affected when`--logging-config` not specified.  [default:info]--help                          Show this message and exit.Commands:load  Load a pre-trained AllenNLP model from it's archive file, and putit...and$allennlp-runmodelload--help
Usage:allennlp-runmodelload[OPTIONS]ARCHIVELoadapre-trainedAllenNLPmodelfromit'sarchivefile,andputitintothewebservicecontrainer.

Options:-m,--model-nameTEXTModelnameusedinURL.eg:http://xxx.xxx.xxx.xxx:8000/?model=model_name-t,--num-threadsINTEGERSetsthenumberofOpenMPthreadsusedforparallelizingCPUoperations.[default:4(onthismachine)]-w,--max-workersINTEGERUsesapoolofatmostmax_workersthreadstoexecutecallsasynchronously.[default:num_threads/cpu_count(1onthismachine)]-w,--worker-type[process|thread]Setstheworkersexecuteinthreadorprocess.[default:process]-d,--cuda-deviceINTEGERIfCUDA_DEVICEis>=0,themodelwillbeloadedontothecorrespondingGPU.OtherwiseitwillbeloadedontotheCPU.[default:-1]-e,--predictor-nameTEXTOptionallyspecifywhich`Predictor`subclass;otherwise,thedefaultoneforthemodelwillbeused.--helpShowthismessageandexit.loadsub-command can be called many times to load multiple models.eg:allennlp-runmodel--port8080load--model-namemodel1/path/of/model1.tar.gzload--model-namemodel2/path/of/model2.tar.gzMake prediction from HTTP clientcurl\--header"Content-Type: application/json"\--requestPOST\--data'{"premise":"Two women are embracing while holding to go packages.","hypothesis":"The sisters are hugging goodbye while holding to go packages after just eating lunch."}'\http://localhost:8080/?model=model1