DeLFT: packages are not available from conda channels

[andrei-volkau]

I have a question regarding creating a conda env in case DeLFT. The documentation provides the following command.

conda create --name grobidDelft --file requirements.conda.delft.cpu.txt
So we have the following error.

It looks like those packages are not really available through any conda channels. It looks like such packages need to be installed using pip while having env activated. Am I right?

@lfoppiano I would appreciate your thought regarding the problem if possible. Thank you in advance for the info!

[lfoppiano]

Dear @andrei-volkau my bad, this requirement files is old and I've stopped using it some time ago, but I forgot to update the documentation.

The best solution so far I found is the following:

1. create a conda environment
   conda create --name delft_grobid pip should install pip within the environment...

2. make sure you are using the pip inside the environment (sometimes conda uses the root pip and mess up with your system):
   which pip should return a path within your environment

3. import the delft packages using pip

Could you give it a try?

Conda gave me other problems on Linux, reason why I install delft via pip now

[andrei-volkau]

Hi @lfoppiano ! Thank you for the comments!

• create a conda environment
  conda create --name delft_grobid pip should install pip within the environment...

Yeah, I created the conda env.

• make sure you are using the pip inside the environment (sometimes conda uses the root pip and mess up with your system):
  which pip should return a path within your environment

Yeah, I checked that. Thank you. I am using pip inside the conda environment.

3. import the delft packages using pip

I installed packages from requirements.txt I installed jep also since jep is missing there.

I have a kind of failure you was facing in this thread.

It looks like such a kind of failure should be solved while doing the following stuff

conda install libgcc
export LD_PRELOAD=/home/ubuntu/anaconda3/lib/libstdc++.so.6.0.25

I did that. No luck.

I am using Ubuntu 16.04 (AWS EC2 instance). I am using Python3.6. All of the dependencies from requremnts.txt are successfully installed as a part of the conda virtual environment. The virtual environment was activated before running ./gradlew run I am using 0.6.1 version of GROBID.

grobid-service.log

I was using a regular python virtual environment as well in this issue. I faced the same error as shown on the screenshot.

I am sure that you was able to run GROBID+DELFT on Linux somehow. Could try to formulate some ideas regarding approaching the issue?

[lfoppiano]

Dear @andrei-volkau the sigterm there is frigthening but just a consequence of some previous error.

In the grobid-service.log I see:

ERROR [2020-09-30 19:17:20,041] org.grobid.core.jni.JEPThreadPool: JEP initialization failed
! jep.JepException: <class 'ImportError'>: Traceback (most recent call last):
!   File "/home/ubuntu/anaconda3/envs/delft_grobid361/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
!     from tensorflow.python.pywrap_tensorflow_internal import *
!   File "/home/ubuntu/anaconda3/envs/delft_grobid361/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
!     _pywrap_tensorflow_internal = swig_import_helper()
!   File "/home/ubuntu/anaconda3/envs/delft_grobid361/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
!     _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
!   File "/home/ubuntu/anaconda3/envs/delft_grobid361/lib/python3.6/imp.py", line 243, in load_module
!     return load_dynamic(name, filename, file)
!   File "/home/ubuntu/anaconda3/envs/delft_grobid361/lib/python3.6/imp.py", line 343, in load_dynamic
!     return _load(spec)
! ImportError: libcublas.so.9.0: cannot open shared object file: No such file or directory
! 
! 
! Failed to load the native TensorFlow runtime.
! 
! See https://www.tensorflow.org/install/errors
! 
! for some common reasons and solutions.  Include the entire stack trace
! above this error message when asking for help.
! at /home/ubuntu/anaconda3/envs/delft_grobid361/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow.<module>(pywrap_tensorflow.py:74)
! at /home/ubuntu/anaconda3/envs/delft_grobid361/lib/python3.6/site-packages/tensorflow/python/__init__.<module>(__init__.py:49)
! at /home/ubuntu/anaconda3/envs/delft_grobid361/lib/python3.6/site-packages/tensorflow/__init__.<module>(__init__.py:24)
! at /home/ubuntu/anaconda3/envs/delft_grobid361/lib/python3.6/site-packages/keras/backend/tensorflow_backend.<module>(tensorflow_backend.py:5)
! at /home/ubuntu/anaconda3/envs/delft_grobid361/lib/python3.6/site-packages/keras/backend/__init__.<module>(__init__.py:89)
! at /home/ubuntu/anaconda3/envs/delft_grobid361/lib/python3.6/site-packages/keras/utils/conv_utils.<module>(conv_utils.py:9)
! at /home/ubuntu/anaconda3/envs/delft_grobid361/lib/python3.6/site-packages/keras/utils/__init__.<module>(__init__.py:6)
! at /home/ubuntu/anaconda3/envs/delft_grobid361/lib/python3.6/site-packages/keras/__init__.<module>(__init__.py:3)
! at <string>.<module>(<string>:1)
! at jep.Jep.eval(Native Method)
! at jep.Jep.eval(Jep.java:451)
! at org.grobid.core.jni.JEPThreadPool.initializeJepInstance(JEPThreadPool.java:87)
! at org.grobid.core.jni.JEPThreadPool.createJEPInstance(JEPThreadPool.java:107)
! at org.grobid.core.jni.JEPThreadPool.getJEPInstance(JEPThreadPool.java:137)
! at org.grobid.core.jni.DeLFTModel$InitModel.run(DeLFTModel.java:53)
! at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
! at java.util.concurrent.FutureTask.run(FutureTask.java:266)
! at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
! at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
! at java.lang.Thread.run(Thread.java:748)

AFAIK the problem is coming from tensorlfow:

from tensorflow.python.pywrap_tensorflow_internal import *

and in particular

! ImportError: libcublas.so.9.0: cannot open shared object file: No such file or directory

Something is wrong with your tensorflow initialisation. Can you run delft wihtout problems, using the same environment?

For example could you run python3 grobidTagger.py date tag or python3 grobidTagger.py date train_eval? The first will ran faster.

[andrei-volkau]

Hi @lfoppiano!

Something is wrong with your tensorflow initialisation.

Yes, I was using requirements.txt in the case of EC2 t2.medium instance. Such an instance is obviously don't have GPU. So requirements.txt was not the right choice because of tensorflow_gpu . Really sorry, that was my silly mistake. I am using
requirements.test.txt now.

I am sending a screenshot containing the output of python3 grobidTagger.py date tag. So that works since I installed requirements.test.txt.

Unfortunately, I still experience an error.

grobid-service.log

Could you try to look into logs, please?

[andrei-volkau]

@lfoppiano Let me provide information regarding the steps I used to set up everything.

Step 1. Download grobid
wget https://github.com/kermitt2/grobid/archive/0.6.1.zip
unzip 0.6.1.zip

Step 2. Create conda env
conda create -n py36 python=3.6 --name delft_grobid363
pip3 install -r requirements.test.txt
pip3 install jep

Step 3 Change config file as shown below

@kermitt2 was able to suggest the following points. Please see the screenshot below. I was able to try them also. No luck.

The above ideas are from this thread

I am using Python3.6. The virtual environment was activated before running ./gradlew run. I am using 0.6.1 version of GROBID.

The value of JAVA_HOME variable is /usr/lib/jvm/java-8-openjdk-amd64/

I am using Ubuntu 16.04 (AWS EC2 instance). t2 medium instance (4GB RAM, 2 vCPUs)

[lfoppiano]

Dear @andrei-volkau,
somehow we are progressing forward. Although this seems your initial error 😅

I think now it's just a matter of using jep 3.9.0 as the error you see seems related to that.

could you send the result of conda list | grep jep and the line of the jep dependencies in the build.gradle?

Regards
Luca

[lfoppiano]

I'm sending you the parameters of my environment. I configured tensorflow to work with CPU:

See my pip environment:

(tensorflowC) [Luca@falcon grobidl]$ pip list
Package                          Version   
-------------------------------- ----------
absl-py                          0.7.1     
asn1crypto                       1.3.0     
astor                            0.7.1     
boto                             2.49.0    
boto3                            1.11.0    
botocore                         1.14.0    
bz2file                          0.98      
certifi                          2019.11.28
cffi                             1.13.2    
chardet                          3.0.4     
cryptography                     2.8       
docutils                         0.15.2    
gast                             0.2.2     
gensim                           3.8.0     
google-pasta                     0.1.7     
grpcio                           1.16.1    
h5py                             2.9.0     
idna                             2.8       
jep                              3.8.2     
jmespath                         0.9.4     
joblib                           0.13.2    
Keras                            2.2.4     
Keras-Applications               1.0.8     
keras-bert                       0.70.1    
keras-embed-sim                  0.7.0     
keras-layer-normalization        0.12.0    
keras-multi-head                 0.20.0    
keras-pos-embd                   0.11.0    
keras-position-wise-feed-forward 0.6.0     
Keras-Preprocessing              1.1.0     
keras-self-attention             0.41.0    
keras-transformer                0.29.0    
langdetect                       1.0.7     
lmdb                             0.94      
Markdown                         3.1.1     
mkl-fft                          1.0.12    
mkl-random                       1.0.2     
mock                             3.0.5     
nltk                             3.4.4     
numpy                            1.16.4    
pandas                           0.25.3    
pip                              19.1.1    
protobuf                         3.8.0     
pycparser                        2.19      
pyOpenSSL                        19.1.0    
PySocks                          1.7.1     
python-dateutil                  2.8.1     
pytz                             2019.3    
PyYAML                           5.1.1     
regex                            2019.6.5  
requests                         2.22.0    
s3transfer                       0.3.0     
scikit-learn                     0.21.2    
scipy                            1.2.1     
setuptools                       41.0.1    
six                              1.12.0    
sklearn                          0.0       
smart-open                       1.9.0     
tensorboard                      1.12.2    
tensorflow                       1.12.0    
tensorflow-estimator             1.13.0    
termcolor                        1.1.0     
textblob                         0.15.3    
tqdm                             4.32.1    
urllib3                          1.25.7    
Werkzeug                         0.15.4    
wheel                            0.33.4    
wrapt                            1.11.2

here the conda list (In this environment I've installed most of the packages with conda):

(tensorflowC) [Luca@falcon grobidl]$ conda list
# packages in environment at /home/Luca/.conda/envs/tensorflowC:
#
# Name                    Version                   Build  Channel
_libgcc_mutex             0.1                        main  
_tflow_select             2.3.0                       mkl  
absl-py                   0.7.1                    py36_0  
asn1crypto                1.3.0                    py36_0  
astor                     0.7.1                    py36_0  
blas                      1.0                         mkl  
boto                      2.49.0                   py36_0  
boto3                     1.11.0                     py_0  
botocore                  1.14.0                     py_0  
bz2file                   0.98                     py36_1  
c-ares                    1.15.0               h7b6447c_1  
ca-certificates           2019.11.28           hecc5488_0    conda-forge
certifi                   2019.11.28               py36_0    conda-forge
cffi                      1.13.2           py36h2e261b9_0  
chardet                   3.0.4                 py36_1003  
cryptography              2.8              py36h1ba5d50_0  
docutils                  0.15.2                   py36_0  
gast                      0.2.2                    py36_0  
gensim                    3.8.0            py36h962f231_0  
google-pasta              0.1.7                      py_0  
grpcio                    1.16.1           py36hf8bcb03_1  
h5py                      2.9.0            py36h7918eee_0  
hdf5                      1.10.4               hb1b8bf9_0  
idna                      2.8                      py36_0  
intel-openmp              2019.4                      243  
jep                       3.8.2                    pypi_0    pypi
jmespath                  0.9.4                      py_0  
joblib                    0.13.2                   pypi_0    pypi
keras                     2.2.4                         0  
keras-applications        1.0.8                      py_0  
keras-base                2.2.4                    py36_0  
keras-bert                0.70.1                   pypi_0    pypi
keras-embed-sim           0.7.0                    pypi_0    pypi
keras-layer-normalization 0.12.0                   pypi_0    pypi
keras-multi-head          0.20.0                   pypi_0    pypi
keras-pos-embd            0.11.0                   pypi_0    pypi
keras-position-wise-feed-forward 0.6.0                    pypi_0    pypi
keras-preprocessing       1.1.0                      py_1  
keras-self-attention      0.41.0                   pypi_0    pypi
keras-transformer         0.29.0                   pypi_0    pypi
langdetect                1.0.7                      py_0    conda-forge
libedit                   3.1.20181209         hc058e9b_0  
libffi                    3.2.1                hd88cf55_4  
libgcc                    7.2.0                h69d50b8_2  
libgcc-ng                 9.1.0                hdf63c60_0  
libgfortran-ng            7.3.0                hdf63c60_0  
libprotobuf               3.8.0                hd408876_0  
libstdcxx-ng              9.1.0                hdf63c60_0  
markdown                  3.1.1                    py36_0  
mkl                       2019.4                      243  
mkl_fft                   1.0.12           py36ha843d7b_0  
mkl_random                1.0.2            py36hd81dba3_0  
mock                      3.0.5                    py36_0  
ncurses                   6.1                  he6710b0_1  
nltk                      3.4.4                      py_0    conda-forge
numpy                     1.16.4           py36h7e9f1db_0  
numpy-base                1.16.4           py36hde5b4d6_0  
openssl                   1.1.1d               h516909a_0    conda-forge
pandas                    0.25.3           py36he6710b0_0  
pip                       19.1.1                   py36_0  
protobuf                  3.8.0            py36he6710b0_0  
pycparser                 2.19                       py_0  
pyopenssl                 19.1.0                   py36_0  
pysocks                   1.7.1                    py36_0  
python                    3.6.8                h0371630_0  
python-dateutil           2.8.1                      py_0  
python-lmdb               0.94             py36h14c3975_0  
pytz                      2019.3                     py_0  
pyyaml                    5.1.1            py36h7b6447c_0  
readline                  7.0                  h7b6447c_5  
regex                     2019.06.05       py36h7b6447c_0  
requests                  2.22.0                   py36_1  
s3transfer                0.3.0                    py36_0  
scikit-learn              0.21.2                   pypi_0    pypi
scipy                     1.2.1            py36h7c811a0_0  
setuptools                41.0.1                   py36_0  
six                       1.12.0                   py36_0  
sklearn                   0.0                      pypi_0    pypi
smart_open                1.9.0                      py_0  
sqlite                    3.29.0               h7b6447c_0  
tensorboard               1.12.2           py36he6710b0_0  
tensorflow                1.12.0          mkl_py36h69b6ba0_0  
tensorflow-base           1.12.0          mkl_py36h3c3e929_0  
tensorflow-estimator      1.13.0                     py_0  
termcolor                 1.1.0                    py36_1  
textblob                  0.15.3                     py_0    conda-forge
tk                        8.6.8                hbc83047_0  
tqdm                      4.32.1                     py_0  
urllib3                   1.25.7                   py36_0  
werkzeug                  0.15.4                     py_0  
wheel                     0.33.4                   py36_0  
wrapt                     1.11.2           py36h7b6447c_0  
xz                        5.2.4                h14c3975_4  
yaml                      0.1.7                had09818_2  
zlib                      1.2.11               h7b6447c_3  

My jep version is the old one:

(tensorflowC) [Luca@falcon grobidl]$ cat build.gradle | grep jep
        implementation 'black.ninia:jep:3.8.2'

(tensorflowC) [Luca@falcon grobidl]$ pip list | grep jep
jep                              3.8.2  

Let me know if you need more information, but in your case you should maybe try downgrade the jep version on your python environment.

[lfoppiano]

With the latest delft version (which I haven't updated) you should install 'truecase' as well, if I'm not mistaken.

[andrei-volkau]

Hi @lfoppiano!

I am sorry for the late reply. Thank you very much for the lists of packages! Let me please take my time to carefully install the packages needed. I hope to come back on weekends.

I will try to use jep 3.8.2. Thank you.

[andrei-volkau]

Hi @lfoppiano!

With the latest delft version (which I haven't updated) you should install 'truecase' as well, if I'm not mistaken.

Yes, that is mentioned in requirements.test.txt. I am using the requirements.test.txt. So 'truecase' was installed.

---

I did all of the stuff from the very beginning. I mean that installed DeLFT/GROBID using a new EC2 instance as per instructions.

Thank you for sending your pip list. This is my pip environment:

Package                          Version
-------------------------------- ----------------------
absl-py                          0.10.0
astor                            0.8.1
bleach                           3.2.1
blinker                          1.3
chardet                          2.3.0
click                            7.1.2
cloud-init                       20.3
command-not-found                0.3
configobj                        5.0.6
cryptography                     1.2.3
gast                             0.4.0
gensim                           3.4.0
grpcio                           1.32.0
h5py                             2.7.1
hibagent                         1.0.1
idna                             2.0
importlib-metadata               2.0.0
jep                              3.8.2
Jinja2                           2.8
joblib                           0.17.0
jsonpatch                        1.10
jsonpointer                      1.9
Keras                            2.2.4
Keras-Applications               1.0.8
keras-bert                       0.39.0
keras-embed-sim                  0.3.0
keras-layer-normalization        0.11.0
keras-multi-head                 0.18.0
keras-pos-embd                   0.9.0
keras-position-wise-feed-forward 0.4.0
Keras-Preprocessing              1.1.2
keras-self-attention             0.39.0
keras-transformer                0.21.0
langdetect                       1.0.7
language-selector                0.1
lmdb                             0.94
Markdown                         3.3
MarkupSafe                       0.23
nltk                             3.5
numpy                            1.16.1
oauthlib                         1.0.3
packaging                        20.4
pandas                           0.22.0
pip                              20.2.3
pkg-resources                    0.0.0
prettytable                      0.7.2
protobuf                         3.13.0
pyasn1                           0.1.9
pycurl                           7.43.0
pydot                            1.2.4
pygobject                        3.20.0
PyJWT                            1.3.0
pyparsing                        2.4.7
pyserial                         3.0.1
python-apt                       1.1.0b1+ubuntu0.16.4.9
python-dateutil                  2.8.1
python-debian                    0.1.27
python-systemd                   231
pytz                             2020.1
PyYAML                           3.11
regex                            2018.2.21
requests                         2.9.1
scikit-learn                     0.19.1
scipy                            1.5.2
setuptools                       50.3.0
six                              1.10.0
smart-open                       3.0.0
ssh-import-id                    5.5
tensorboard                      1.12.2
tensorflow                       1.12.0
termcolor                        1.1.0
textblob                         0.15.1
tqdm                             4.21.0
truecase                         0.0.11
ufw                              0.35
unattended-upgrades              0.1
Unidecode                        1.0.22
urllib3                          1.13.1
virtualenv                       15.0.1
webencodings                     0.5.1
Werkzeug                         1.0.1
wheel                            0.35.1
zipp                             3.3.0

My environment looks pretty similar if I am not mistaken.

Let me know if you need more information, but in your case you should maybe try downgrade the jep version on your python environment.

I am using jep 3.8.2. Thank you.

I still experience an issue.

Could you please take a look at the logs? Thank you very much in advance for any hints!
grobid-service.log

[lfoppiano]

OK, I've been in this situation and I remember I needed to find a way to understand which model is actually causing the issue.

Could you please

1. switch to the branch bugfix/delft-integration-experiments
   • git checkout bugfix/delft-integration-experiments
2. stash and pull:
   • git stash
   • git pull
   • git stash pop

And try again, and send the log?

we are close to the solution ;-)

[andrei-volkau]

Hi @lfoppiano, thank you!

I am sending you the logs. I experienced the same error. I am using bugfix/delft-integration-experiments branch.

grobid-service.log

[lfoppiano]

@andrei-volkau thanks. As of now I'm trying to figure out what is not working. I pushed some more logging information.

could you update(git pull) and try again?

[andrei-volkau]

Hi @lfoppiano, thank you! Sorry for my late reply.

I am sending you the logs. I am using the latest bugfix/delft-integration-experiments
grobid-service.log

[lfoppiano]

Hi @lfoppiano, thank you! Sorry for my late reply.

I am sending you the logs. I am using the latest bugfix/delft-integration-experiments
grobid-service.log

@andrei-volkau are you sure you activate the conda environment? here the log says it cannot find jep

Could you check and re-try?

[andrei-volkau]

@lfoppiano Sorry, I forgot to do that. I am sending you the correct logs.

grobid-service.log

I am sending relevant screenshots also. Thank you.

[lfoppiano]

@andrei-volkau thanks. No need to send the screenshots. The important part of the log is before. However from your log I can see only

ERROR [2020-10-16 19:39:15,405] org.grobid.core.jni.JEPThreadPool: JEP initialization failed
! jep.JepException: <class 'ModuleNotFoundError'>: No module named 'delft'
! at <string>.<module>(<string>:1)
! at jep.Jep.eval(Native Method)
! at jep.Jep.eval(Jep.java:507)
! at org.grobid.core.jni.JEPThreadPool.initializeJepInstance(JEPThreadPool.java:89)
! at org.grobid.core.jni.JEPThreadPool.createJEPInstance(JEPThreadPool.java:107)
! at org.grobid.core.jni.JEPThreadPool.getJEPInstance(JEPThreadPool.java:137)
! at org.grobid.core.jni.DeLFTModel$InitModel.run(DeLFTModel.java:53)
! at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
! at java.util.concurrent.FutureTask.run(FutureTask.java:266)
! at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
! at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
! at java.lang.Thread.run(Thread.java:748)
INFO  [2020-10-16 19:39:15,533] org.grobid.core.jni.DeLFTModel: Loading DeLFT model for name-header...
INFO  [2020-10-16 19:39:15,534] org.grobid.core.jni.JEPThreadPool: Creating JEP instance for thread 29

Are you sure the setup is correct?

[andrei-volkau]

@lfoppiano I forgot to specify one of two paths in the GROBID setting file. I mean either DELFT path or DELFT env path. I do not remember which one. Silly mistake as the previous one. Anyway, thank you for your patience! The following logs are for 100% correct setup.

grobid-service.log

[lfoppiano]

@andrei-volkau sorry, there is still something not clear.. are you sure you pull the latest version?
could you send me the result of git log --oneline --decorate --graph? I don't see the additional logs I added.

[andrei-volkau]

could you send me the result of git log --oneline --decorate --graph?

@lfoppiano Sure! I am sending that. Thank you.

* 294c2b5 (HEAD -> bugfix/delft-integration-experiments, origin/bugfix/delft-integration-experiments) adding some more logging
* 50b784b output the model name for debugging
* b0560b5 (master) improve documentation on delft configuration
* bda9314 more self-explaining property file regarding DL models
* 2fd52bd add jni class for DeLFT classifier via JEP
* ad5276c review benchmarking doc and licenses
* 570c8c0 update citation deep learning model and add corresponding benchmarks
* 41d5e6a update doc
* 01ab5c9 fix error case sentence segmentation without sentence
* f43e301 support for page number ranges with postfix letter
*   ebdbb89 Merge branch 'master' of https://github.com/kermitt2/grobid
|\
| * a62daf3 fix on page range string manipulation
* | 32b3123 upate citation model
|/
* 39fa6a9 better normalisation of page ranges
* 295e468 review serialization of series and editors in bib. ref.
*   4be789e Merge branch 'master' of https://github.com/kermitt2/grobid
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| * 0a22345 typo in formatting doc
* | d18f5e4 add specific series field in the citation model
|/
* a69290a fix issue with space characters in generated training data for citation model, add specific <series> label
* ac47e1f updated citation model for better identifier coverage
* 295be65 review handling of identifiers in ref bib, add training data
*   4d1938c Merge pull request #640 from OrionNebula/OrionNebula--gradle_sentence_segmentation
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| * 6d3d927 Add "sentence-segmentation/**" to Gradle package
|/
* 51ec543 update url with https://
* 6d82c9e customize pmc eval
* e262107 add doi, pmid and pmcid fields in the end-to-end eval
*   f56c7af Merge pull request #636 from elifesciences/enable-dist-zip-for-docker-build
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| * d43df05 enabled service dist zip for docker build

[lfoppiano]

@andrei-volkau I'm sorry I could not find time to look in your issue. I'm going to work on the #662 so that we can solve the issue in a clean way.

[andrei-volkau]

@lfoppiano I was able to successfully run GROBID with DeLFT while following step-by-step instructions. I am closing the issue because of that. Thank you for the great support along the way!