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+/deeppavlov-1.1.1.tar.gz
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+%global _empty_manifest_terminate_build 0
+Name:		python-deeppavlov
+Version:	1.1.1
+Release:	1
+Summary:	An open source library for building end-to-end dialog systems and training chatbots.
+License:	Apache License, Version 2.0
+URL:		https://github.com/deeppavlov/DeepPavlov
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/63/ca/92187ea41f6a26200ba1bbdb46a4b894d088ba4cfc7ef22e716e5609e5ba/deeppavlov-1.1.1.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-aio-pika
+Requires:	python3-fastapi
+Requires:	python3-filelock
+Requires:	python3-nltk
+Requires:	python3-numpy
+Requires:	python3-overrides
+Requires:	python3-pandas
+Requires:	python3-prometheus-client
+Requires:	python3-pydantic
+Requires:	python3-pybind11
+Requires:	python3-requests
+Requires:	python3-scikit-learn
+Requires:	python3-scipy
+Requires:	python3-tqdm
+Requires:	python3-uvicorn
+Requires:	python3-sphinx-rtd-theme
+Requires:	python3-nbsphinx
+Requires:	python3-ipykernel
+Requires:	python3-jinja2
+Requires:	python3-sphinx-copybutton
+Requires:	python3-pandoc
+Requires:	python3-ipython-genutils
+Requires:	python3-sphinx
+Requires:	python3-sphinx
+Requires:	python3-boto3
+Requires:	python3-flake8
+Requires:	python3-pytest
+Requires:	python3-pytest-instafail
+Requires:	python3-pexpect
+
+%description
+[![License Apache 2.0](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://github.com/deeppavlov/DeepPavlov/blob/master/LICENSE)
+![Python 3.6, 3.7, 3.8, 3.9, 3.10](https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8%20%7C%203.9%20%7C%203.10-green.svg)
+[![Downloads](https://pepy.tech/badge/deeppavlov)](https://pepy.tech/project/deeppavlov)
+<img align="right" height="27%" width="27%" src="https://raw.githubusercontent.com/deeppavlov/DeepPavlov/master/docs/_static/deeppavlov_logo.png"/>
+
+DeepPavlov is an open-source conversational AI library built on [PyTorch](https://pytorch.org/).
+
+DeepPavlov is designed for
+* development of production ready chat-bots and complex conversational systems,
+* research in the area of NLP and, particularly, of dialog systems.
+
+## Quick Links
+
+* Demo [*demo.deeppavlov.ai*](https://demo.deeppavlov.ai/)
+* Documentation [*docs.deeppavlov.ai*](http://docs.deeppavlov.ai/)
+    * Model List [*docs:features/*](http://docs.deeppavlov.ai/en/master/features/overview.html)
+    * Contribution Guide [*docs:contribution_guide/*](http://docs.deeppavlov.ai/en/master/devguides/contribution_guide.html)
+* Issues [*github/issues/*](https://github.com/deeppavlov/DeepPavlov/issues)
+* Forum [*forum.deeppavlov.ai*](https://forum.deeppavlov.ai/)
+* Blogs [*medium.com/deeppavlov*](https://medium.com/deeppavlov)
+* [Extended colab tutorials](https://github.com/deeppavlov/dp_tutorials)
+* Docker Hub [*hub.docker.com/u/deeppavlov/*](https://hub.docker.com/u/deeppavlov/) 
+    * Docker Images Documentation [*docs:docker-images/*](http://docs.deeppavlov.ai/en/master/intro/installation.html#docker-images)
+
+Please leave us [your feedback](https://forms.gle/i64fowQmiVhMMC7f9) on how we can improve the DeepPavlov framework.
+
+**Models**
+
+[Named Entity Recognition](http://docs.deeppavlov.ai/en/master/features/models/NER.html) | [Intent/Sentence Classification](http://docs.deeppavlov.ai/en/master/features/models/classifiers.html) |
+
+[Question Answering over Text (SQuAD)](http://docs.deeppavlov.ai/en/master/features/models/SQuAD.html) | [Knowledge Base Question Answering](http://docs.deeppavlov.ai/en/master/features/models/kbqa.html)
+
+[Sentence Similarity/Ranking](http://docs.deeppavlov.ai/en/master/features/models/neural_ranking.html) | [TF-IDF Ranking](http://docs.deeppavlov.ai/en/master/features/models/tfidf_ranking.html) 
+
+[Automatic Spelling Correction](http://docs.deeppavlov.ai/en/master/features/models/spelling_correction.html) | [Entity Linking](http://docs.deeppavlov.ai/en/master/features/models/entity_linking.html)
+
+[Open Domain Questions Answering](http://docs.deeppavlov.ai/en/master/features/models/odqa.html) | [Russian SuperGLUE](http://docs.deeppavlov.ai/en/master/features/models/superglue.html)
+
+**Embeddings**
+
+[BERT embeddings for the Russian, Polish, Bulgarian, Czech, and informal English](http://docs.deeppavlov.ai/en/master/features/pretrained_vectors.html#bert)
+
+[ELMo embeddings for the Russian language](http://docs.deeppavlov.ai/en/master/features/pretrained_vectors.html#elmo)
+
+[FastText embeddings for the Russian language](http://docs.deeppavlov.ai/en/master/features/pretrained_vectors.html#fasttext)
+
+**Auto ML**
+
+[Tuning Models](http://docs.deeppavlov.ai/en/master/features/hypersearch.html)
+
+**Integrations**
+
+[REST API](http://docs.deeppavlov.ai/en/master/integrations/rest_api.html) | [Socket API](http://docs.deeppavlov.ai/en/master/integrations/socket_api.html)
+
+[Amazon AWS](http://docs.deeppavlov.ai/en/master/integrations/aws_ec2.html)
+
+## Installation
+
+0. We support `Linux` platform, `Python 3.6`, `3.7`, `3.8`, `3.9` and `3.10`
+    * **`Python 3.5` is not supported!**
+
+1. Create and activate a virtual environment:
+    * `Linux`
+    ```
+    python -m venv env
+    source ./env/bin/activate
+    ```
+2. Install the package inside the environment:
+    ```
+    pip install deeppavlov
+    ```
+
+## QuickStart
+
+There is a bunch of great pre-trained NLP models in DeepPavlov. Each model is
+determined by its config file.
+
+List of models is available on
+[the doc page](http://docs.deeppavlov.ai/en/master/features/overview.html) in
+the `deeppavlov.configs` (Python):
+
+```python
+from deeppavlov import configs
+```
+
+When you're decided on the model (+ config file), there are two ways to train,
+evaluate and infer it:
+
+* via [Command line interface (CLI)](https://github.com/deeppavlov/DeepPavlov/blob/master/#command-line-interface-cli) and
+* via [Python](https://github.com/deeppavlov/DeepPavlov/blob/master/#python).
+
+#### GPU requirements
+
+By default, DeepPavlov installs models requirements from PyPI. PyTorch from PyPI could not support your device CUDA
+capability. To run supported DeepPavlov models on GPU you should have [CUDA](https://developer.nvidia.com/cuda-toolkit)
+compatible with used GPU and [PyTorch version](https://github.com/deeppavlov/DeepPavlov/blob/master/deeppavlov/requirements/pytorch.txt) required by DeepPavlov models.
+See [docs](https://docs.deeppavlov.ai/en/master/intro/quick_start.html#using-gpu) for details.
+
+### Command line interface (CLI)
+
+To get predictions from a model interactively through CLI, run
+
+```bash
+python -m deeppavlov interact <config_path> [-d] [-i]
+```
+
+* `-d` downloads required data - pretrained model files and embeddings (optional).
+* `-i` installs model requirements (optional).
+
+You can train it in the same simple way:
+
+```bash
+python -m deeppavlov train <config_path> [-d] [-i]
+```
+
+Dataset will be downloaded regardless of whether there was `-d` flag or not.
+
+To train on your own data you need to modify dataset reader path in the
+[train config doc](http://docs.deeppavlov.ai/en/master/intro/config_description.html#train-config).
+The data format is specified in the corresponding model doc page. 
+
+There are even more actions you can perform with configs:
+
+```bash
+python -m deeppavlov <action> <config_path> [-d] [-i]
+```
+
+* `<action>` can be
+    * `install` to install model requirements (same as `-i`),
+    * `download` to download model's data (same as `-d`),
+    * `train` to train the model on the data specified in the config file,
+    * `evaluate` to calculate metrics on the same dataset,
+    * `interact` to interact via CLI,
+    * `riseapi` to run a REST API server (see
+    [doc](http://docs.deeppavlov.ai/en/master/integrations/rest_api.html)),
+    * `predict` to get prediction for samples from *stdin* or from
+      *<file_path>* if `-f <file_path>` is specified.
+* `<config_path>` specifies path (or name) of model's config file
+* `-d` downloads required data
+* `-i` installs model requirements
+
+
+### Python
+
+To get predictions from a model interactively through Python, run
+
+```python
+from deeppavlov import build_model
+
+model = build_model(<config_path>, install=True, download=True)
+
+# get predictions for 'input_text1', 'input_text2'
+model(['input_text1', 'input_text2'])
+```
+where
+* `install=True` installs model requirements (optional),
+* `download=True` downloads required data from web - pretrained model files and embeddings (optional),
+* `<config_path>` is model name (e.g. `'ner_ontonotes_bert_mult'`), path to the chosen model's config file (e.g.
+  `"deeppavlov/configs/ner/ner_ontonotes_bert_mult.json"`),  or `deeppavlov.configs` attribute (e.g.
+  `deeppavlov.configs.ner.ner_ontonotes_bert_mult` without quotation marks).
+
+You can train it in the same simple way:
+
+```python
+from deeppavlov import train_model 
+
+model = train_model(<config_path>, install=True, download=True)
+```
+
+To train on your own data you need to modify dataset reader path in the
+[train config doc](http://docs.deeppavlov.ai/en/master/intro/config_description.html#train-config).
+The data format is specified in the corresponding model doc page. 
+
+You can also calculate metrics on the dataset specified in your config file:
+
+```python
+from deeppavlov import evaluate_model 
+
+model = evaluate_model(<config_path>, install=True, download=True)
+```
+
+DeepPavlov also [allows](https://docs.deeppavlov.ai/en/master/features/python.html) to build a model from components for
+inference using Python.
+
+## License
+
+DeepPavlov is Apache 2.0 - licensed.
+
+
+%package -n python3-deeppavlov
+Summary:	An open source library for building end-to-end dialog systems and training chatbots.
+Provides:	python-deeppavlov
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-deeppavlov
+[![License Apache 2.0](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://github.com/deeppavlov/DeepPavlov/blob/master/LICENSE)
+![Python 3.6, 3.7, 3.8, 3.9, 3.10](https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8%20%7C%203.9%20%7C%203.10-green.svg)
+[![Downloads](https://pepy.tech/badge/deeppavlov)](https://pepy.tech/project/deeppavlov)
+<img align="right" height="27%" width="27%" src="https://raw.githubusercontent.com/deeppavlov/DeepPavlov/master/docs/_static/deeppavlov_logo.png"/>
+
+DeepPavlov is an open-source conversational AI library built on [PyTorch](https://pytorch.org/).
+
+DeepPavlov is designed for
+* development of production ready chat-bots and complex conversational systems,
+* research in the area of NLP and, particularly, of dialog systems.
+
+## Quick Links
+
+* Demo [*demo.deeppavlov.ai*](https://demo.deeppavlov.ai/)
+* Documentation [*docs.deeppavlov.ai*](http://docs.deeppavlov.ai/)
+    * Model List [*docs:features/*](http://docs.deeppavlov.ai/en/master/features/overview.html)
+    * Contribution Guide [*docs:contribution_guide/*](http://docs.deeppavlov.ai/en/master/devguides/contribution_guide.html)
+* Issues [*github/issues/*](https://github.com/deeppavlov/DeepPavlov/issues)
+* Forum [*forum.deeppavlov.ai*](https://forum.deeppavlov.ai/)
+* Blogs [*medium.com/deeppavlov*](https://medium.com/deeppavlov)
+* [Extended colab tutorials](https://github.com/deeppavlov/dp_tutorials)
+* Docker Hub [*hub.docker.com/u/deeppavlov/*](https://hub.docker.com/u/deeppavlov/) 
+    * Docker Images Documentation [*docs:docker-images/*](http://docs.deeppavlov.ai/en/master/intro/installation.html#docker-images)
+
+Please leave us [your feedback](https://forms.gle/i64fowQmiVhMMC7f9) on how we can improve the DeepPavlov framework.
+
+**Models**
+
+[Named Entity Recognition](http://docs.deeppavlov.ai/en/master/features/models/NER.html) | [Intent/Sentence Classification](http://docs.deeppavlov.ai/en/master/features/models/classifiers.html) |
+
+[Question Answering over Text (SQuAD)](http://docs.deeppavlov.ai/en/master/features/models/SQuAD.html) | [Knowledge Base Question Answering](http://docs.deeppavlov.ai/en/master/features/models/kbqa.html)
+
+[Sentence Similarity/Ranking](http://docs.deeppavlov.ai/en/master/features/models/neural_ranking.html) | [TF-IDF Ranking](http://docs.deeppavlov.ai/en/master/features/models/tfidf_ranking.html) 
+
+[Automatic Spelling Correction](http://docs.deeppavlov.ai/en/master/features/models/spelling_correction.html) | [Entity Linking](http://docs.deeppavlov.ai/en/master/features/models/entity_linking.html)
+
+[Open Domain Questions Answering](http://docs.deeppavlov.ai/en/master/features/models/odqa.html) | [Russian SuperGLUE](http://docs.deeppavlov.ai/en/master/features/models/superglue.html)
+
+**Embeddings**
+
+[BERT embeddings for the Russian, Polish, Bulgarian, Czech, and informal English](http://docs.deeppavlov.ai/en/master/features/pretrained_vectors.html#bert)
+
+[ELMo embeddings for the Russian language](http://docs.deeppavlov.ai/en/master/features/pretrained_vectors.html#elmo)
+
+[FastText embeddings for the Russian language](http://docs.deeppavlov.ai/en/master/features/pretrained_vectors.html#fasttext)
+
+**Auto ML**
+
+[Tuning Models](http://docs.deeppavlov.ai/en/master/features/hypersearch.html)
+
+**Integrations**
+
+[REST API](http://docs.deeppavlov.ai/en/master/integrations/rest_api.html) | [Socket API](http://docs.deeppavlov.ai/en/master/integrations/socket_api.html)
+
+[Amazon AWS](http://docs.deeppavlov.ai/en/master/integrations/aws_ec2.html)
+
+## Installation
+
+0. We support `Linux` platform, `Python 3.6`, `3.7`, `3.8`, `3.9` and `3.10`
+    * **`Python 3.5` is not supported!**
+
+1. Create and activate a virtual environment:
+    * `Linux`
+    ```
+    python -m venv env
+    source ./env/bin/activate
+    ```
+2. Install the package inside the environment:
+    ```
+    pip install deeppavlov
+    ```
+
+## QuickStart
+
+There is a bunch of great pre-trained NLP models in DeepPavlov. Each model is
+determined by its config file.
+
+List of models is available on
+[the doc page](http://docs.deeppavlov.ai/en/master/features/overview.html) in
+the `deeppavlov.configs` (Python):
+
+```python
+from deeppavlov import configs
+```
+
+When you're decided on the model (+ config file), there are two ways to train,
+evaluate and infer it:
+
+* via [Command line interface (CLI)](https://github.com/deeppavlov/DeepPavlov/blob/master/#command-line-interface-cli) and
+* via [Python](https://github.com/deeppavlov/DeepPavlov/blob/master/#python).
+
+#### GPU requirements
+
+By default, DeepPavlov installs models requirements from PyPI. PyTorch from PyPI could not support your device CUDA
+capability. To run supported DeepPavlov models on GPU you should have [CUDA](https://developer.nvidia.com/cuda-toolkit)
+compatible with used GPU and [PyTorch version](https://github.com/deeppavlov/DeepPavlov/blob/master/deeppavlov/requirements/pytorch.txt) required by DeepPavlov models.
+See [docs](https://docs.deeppavlov.ai/en/master/intro/quick_start.html#using-gpu) for details.
+
+### Command line interface (CLI)
+
+To get predictions from a model interactively through CLI, run
+
+```bash
+python -m deeppavlov interact <config_path> [-d] [-i]
+```
+
+* `-d` downloads required data - pretrained model files and embeddings (optional).
+* `-i` installs model requirements (optional).
+
+You can train it in the same simple way:
+
+```bash
+python -m deeppavlov train <config_path> [-d] [-i]
+```
+
+Dataset will be downloaded regardless of whether there was `-d` flag or not.
+
+To train on your own data you need to modify dataset reader path in the
+[train config doc](http://docs.deeppavlov.ai/en/master/intro/config_description.html#train-config).
+The data format is specified in the corresponding model doc page. 
+
+There are even more actions you can perform with configs:
+
+```bash
+python -m deeppavlov <action> <config_path> [-d] [-i]
+```
+
+* `<action>` can be
+    * `install` to install model requirements (same as `-i`),
+    * `download` to download model's data (same as `-d`),
+    * `train` to train the model on the data specified in the config file,
+    * `evaluate` to calculate metrics on the same dataset,
+    * `interact` to interact via CLI,
+    * `riseapi` to run a REST API server (see
+    [doc](http://docs.deeppavlov.ai/en/master/integrations/rest_api.html)),
+    * `predict` to get prediction for samples from *stdin* or from
+      *<file_path>* if `-f <file_path>` is specified.
+* `<config_path>` specifies path (or name) of model's config file
+* `-d` downloads required data
+* `-i` installs model requirements
+
+
+### Python
+
+To get predictions from a model interactively through Python, run
+
+```python
+from deeppavlov import build_model
+
+model = build_model(<config_path>, install=True, download=True)
+
+# get predictions for 'input_text1', 'input_text2'
+model(['input_text1', 'input_text2'])
+```
+where
+* `install=True` installs model requirements (optional),
+* `download=True` downloads required data from web - pretrained model files and embeddings (optional),
+* `<config_path>` is model name (e.g. `'ner_ontonotes_bert_mult'`), path to the chosen model's config file (e.g.
+  `"deeppavlov/configs/ner/ner_ontonotes_bert_mult.json"`),  or `deeppavlov.configs` attribute (e.g.
+  `deeppavlov.configs.ner.ner_ontonotes_bert_mult` without quotation marks).
+
+You can train it in the same simple way:
+
+```python
+from deeppavlov import train_model 
+
+model = train_model(<config_path>, install=True, download=True)
+```
+
+To train on your own data you need to modify dataset reader path in the
+[train config doc](http://docs.deeppavlov.ai/en/master/intro/config_description.html#train-config).
+The data format is specified in the corresponding model doc page. 
+
+You can also calculate metrics on the dataset specified in your config file:
+
+```python
+from deeppavlov import evaluate_model 
+
+model = evaluate_model(<config_path>, install=True, download=True)
+```
+
+DeepPavlov also [allows](https://docs.deeppavlov.ai/en/master/features/python.html) to build a model from components for
+inference using Python.
+
+## License
+
+DeepPavlov is Apache 2.0 - licensed.
+
+
+%package help
+Summary:	Development documents and examples for deeppavlov
+Provides:	python3-deeppavlov-doc
+%description help
+[![License Apache 2.0](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://github.com/deeppavlov/DeepPavlov/blob/master/LICENSE)
+![Python 3.6, 3.7, 3.8, 3.9, 3.10](https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8%20%7C%203.9%20%7C%203.10-green.svg)
+[![Downloads](https://pepy.tech/badge/deeppavlov)](https://pepy.tech/project/deeppavlov)
+<img align="right" height="27%" width="27%" src="https://raw.githubusercontent.com/deeppavlov/DeepPavlov/master/docs/_static/deeppavlov_logo.png"/>
+
+DeepPavlov is an open-source conversational AI library built on [PyTorch](https://pytorch.org/).
+
+DeepPavlov is designed for
+* development of production ready chat-bots and complex conversational systems,
+* research in the area of NLP and, particularly, of dialog systems.
+
+## Quick Links
+
+* Demo [*demo.deeppavlov.ai*](https://demo.deeppavlov.ai/)
+* Documentation [*docs.deeppavlov.ai*](http://docs.deeppavlov.ai/)
+    * Model List [*docs:features/*](http://docs.deeppavlov.ai/en/master/features/overview.html)
+    * Contribution Guide [*docs:contribution_guide/*](http://docs.deeppavlov.ai/en/master/devguides/contribution_guide.html)
+* Issues [*github/issues/*](https://github.com/deeppavlov/DeepPavlov/issues)
+* Forum [*forum.deeppavlov.ai*](https://forum.deeppavlov.ai/)
+* Blogs [*medium.com/deeppavlov*](https://medium.com/deeppavlov)
+* [Extended colab tutorials](https://github.com/deeppavlov/dp_tutorials)
+* Docker Hub [*hub.docker.com/u/deeppavlov/*](https://hub.docker.com/u/deeppavlov/) 
+    * Docker Images Documentation [*docs:docker-images/*](http://docs.deeppavlov.ai/en/master/intro/installation.html#docker-images)
+
+Please leave us [your feedback](https://forms.gle/i64fowQmiVhMMC7f9) on how we can improve the DeepPavlov framework.
+
+**Models**
+
+[Named Entity Recognition](http://docs.deeppavlov.ai/en/master/features/models/NER.html) | [Intent/Sentence Classification](http://docs.deeppavlov.ai/en/master/features/models/classifiers.html) |
+
+[Question Answering over Text (SQuAD)](http://docs.deeppavlov.ai/en/master/features/models/SQuAD.html) | [Knowledge Base Question Answering](http://docs.deeppavlov.ai/en/master/features/models/kbqa.html)
+
+[Sentence Similarity/Ranking](http://docs.deeppavlov.ai/en/master/features/models/neural_ranking.html) | [TF-IDF Ranking](http://docs.deeppavlov.ai/en/master/features/models/tfidf_ranking.html) 
+
+[Automatic Spelling Correction](http://docs.deeppavlov.ai/en/master/features/models/spelling_correction.html) | [Entity Linking](http://docs.deeppavlov.ai/en/master/features/models/entity_linking.html)
+
+[Open Domain Questions Answering](http://docs.deeppavlov.ai/en/master/features/models/odqa.html) | [Russian SuperGLUE](http://docs.deeppavlov.ai/en/master/features/models/superglue.html)
+
+**Embeddings**
+
+[BERT embeddings for the Russian, Polish, Bulgarian, Czech, and informal English](http://docs.deeppavlov.ai/en/master/features/pretrained_vectors.html#bert)
+
+[ELMo embeddings for the Russian language](http://docs.deeppavlov.ai/en/master/features/pretrained_vectors.html#elmo)
+
+[FastText embeddings for the Russian language](http://docs.deeppavlov.ai/en/master/features/pretrained_vectors.html#fasttext)
+
+**Auto ML**
+
+[Tuning Models](http://docs.deeppavlov.ai/en/master/features/hypersearch.html)
+
+**Integrations**
+
+[REST API](http://docs.deeppavlov.ai/en/master/integrations/rest_api.html) | [Socket API](http://docs.deeppavlov.ai/en/master/integrations/socket_api.html)
+
+[Amazon AWS](http://docs.deeppavlov.ai/en/master/integrations/aws_ec2.html)
+
+## Installation
+
+0. We support `Linux` platform, `Python 3.6`, `3.7`, `3.8`, `3.9` and `3.10`
+    * **`Python 3.5` is not supported!**
+
+1. Create and activate a virtual environment:
+    * `Linux`
+    ```
+    python -m venv env
+    source ./env/bin/activate
+    ```
+2. Install the package inside the environment:
+    ```
+    pip install deeppavlov
+    ```
+
+## QuickStart
+
+There is a bunch of great pre-trained NLP models in DeepPavlov. Each model is
+determined by its config file.
+
+List of models is available on
+[the doc page](http://docs.deeppavlov.ai/en/master/features/overview.html) in
+the `deeppavlov.configs` (Python):
+
+```python
+from deeppavlov import configs
+```
+
+When you're decided on the model (+ config file), there are two ways to train,
+evaluate and infer it:
+
+* via [Command line interface (CLI)](https://github.com/deeppavlov/DeepPavlov/blob/master/#command-line-interface-cli) and
+* via [Python](https://github.com/deeppavlov/DeepPavlov/blob/master/#python).
+
+#### GPU requirements
+
+By default, DeepPavlov installs models requirements from PyPI. PyTorch from PyPI could not support your device CUDA
+capability. To run supported DeepPavlov models on GPU you should have [CUDA](https://developer.nvidia.com/cuda-toolkit)
+compatible with used GPU and [PyTorch version](https://github.com/deeppavlov/DeepPavlov/blob/master/deeppavlov/requirements/pytorch.txt) required by DeepPavlov models.
+See [docs](https://docs.deeppavlov.ai/en/master/intro/quick_start.html#using-gpu) for details.
+
+### Command line interface (CLI)
+
+To get predictions from a model interactively through CLI, run
+
+```bash
+python -m deeppavlov interact <config_path> [-d] [-i]
+```
+
+* `-d` downloads required data - pretrained model files and embeddings (optional).
+* `-i` installs model requirements (optional).
+
+You can train it in the same simple way:
+
+```bash
+python -m deeppavlov train <config_path> [-d] [-i]
+```
+
+Dataset will be downloaded regardless of whether there was `-d` flag or not.
+
+To train on your own data you need to modify dataset reader path in the
+[train config doc](http://docs.deeppavlov.ai/en/master/intro/config_description.html#train-config).
+The data format is specified in the corresponding model doc page. 
+
+There are even more actions you can perform with configs:
+
+```bash
+python -m deeppavlov <action> <config_path> [-d] [-i]
+```
+
+* `<action>` can be
+    * `install` to install model requirements (same as `-i`),
+    * `download` to download model's data (same as `-d`),
+    * `train` to train the model on the data specified in the config file,
+    * `evaluate` to calculate metrics on the same dataset,
+    * `interact` to interact via CLI,
+    * `riseapi` to run a REST API server (see
+    [doc](http://docs.deeppavlov.ai/en/master/integrations/rest_api.html)),
+    * `predict` to get prediction for samples from *stdin* or from
+      *<file_path>* if `-f <file_path>` is specified.
+* `<config_path>` specifies path (or name) of model's config file
+* `-d` downloads required data
+* `-i` installs model requirements
+
+
+### Python
+
+To get predictions from a model interactively through Python, run
+
+```python
+from deeppavlov import build_model
+
+model = build_model(<config_path>, install=True, download=True)
+
+# get predictions for 'input_text1', 'input_text2'
+model(['input_text1', 'input_text2'])
+```
+where
+* `install=True` installs model requirements (optional),
+* `download=True` downloads required data from web - pretrained model files and embeddings (optional),
+* `<config_path>` is model name (e.g. `'ner_ontonotes_bert_mult'`), path to the chosen model's config file (e.g.
+  `"deeppavlov/configs/ner/ner_ontonotes_bert_mult.json"`),  or `deeppavlov.configs` attribute (e.g.
+  `deeppavlov.configs.ner.ner_ontonotes_bert_mult` without quotation marks).
+
+You can train it in the same simple way:
+
+```python
+from deeppavlov import train_model 
+
+model = train_model(<config_path>, install=True, download=True)
+```
+
+To train on your own data you need to modify dataset reader path in the
+[train config doc](http://docs.deeppavlov.ai/en/master/intro/config_description.html#train-config).
+The data format is specified in the corresponding model doc page. 
+
+You can also calculate metrics on the dataset specified in your config file:
+
+```python
+from deeppavlov import evaluate_model 
+
+model = evaluate_model(<config_path>, install=True, download=True)
+```
+
+DeepPavlov also [allows](https://docs.deeppavlov.ai/en/master/features/python.html) to build a model from components for
+inference using Python.
+
+## License
+
+DeepPavlov is Apache 2.0 - licensed.
+
+
+%prep
+%autosetup -n deeppavlov-1.1.1
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-deeppavlov -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed Apr 12 2023 Python_Bot <Python_Bot@openeuler.org> - 1.1.1-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..3bc4b9a
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+8f463db78e5e2842212a99c8afab7788  deeppavlov-1.1.1.tar.gz