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https://github.com/deeppavlov/stand_ranking_en


https://github.com/deeppavlov/stand_ranking_en

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# Demo stand. Model: Ranking (English)

## Installation and start
1. Clone the repo and `cd` to project root:
```
git clone https://github.com/deepmipt/stand_ranking_en.git
cd stand_ranking_en
```
2. Create a virtual environment with `Python 3.6`:
```
virtualenv env -p python3.6
```
3. Activate the environment:
```
source ./env/bin/activate
```
4. Install DeepPavlov:
1. Clone the repo and `cd` to project root
```
git clone https://github.com/deepmipt/DeepPavlov.git
cd DeepPavlov
```
2. Install the requirements:
```
python setup.py develop
```
3. Install `spacy` dependencies:
```
pip install http://lnsigo.mipt.ru/export/en_core_web_sm-2.0.0.tar.gz
python3.6 -m spacy link en_core_web_sm en --force
```
4. Download model components:
```
python3.6 -m deeppavlov.deep download deeppavlov/configs/ranking/insurance_config.json
```
5. Download NLTK data:
```
$ python3
>>> import nltk
>>> nltk.download('punkt')
>>> exit()
```
5. Specify model endpoint host (`host`) and port (`port`) in `common_defaults` or corresponding model section of `utils/server_utils/server_config.json`
6. Return to the `stand_ranking_en` dir
7. Specify virtual environment path (if necessary) in `run_en_ranking.sh`
8. Run model:
```
./run_en_ranking.sh
```

## Building and running with Docker:
1. If necessary, build base docker_cuda and docker_deeppavlov images from:

https://github.com/deepmipt/stand_docker_base

2. Clone the repo and `cd` to project root:
```
git clone https://github.com/deepmipt/stand_ranking_en.git
cd stand_ranking_en
```
3. Build Docker image:
```
sudo docker build -t stand/ranking_en .
```
4. Run Docker image:
```
sudo docker run -p :6009 -v /path/to/host/vol/map/dir:/logs stand/ranking_en
```