automatic import of python-gpt3-simple-primeropeneuler20.03

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+/gpt3_simple_primer-0.1.2.tar.gz
diff --git a/python-gpt3-simple-primer.spec b/python-gpt3-simple-primer.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-gpt3-simple-primer
+Version:	0.1.2
+Release:	1
+Summary:	GPT-3 wrapper for Python
+License:	MIT License
+URL:		https://github.com/happilyeverafter95/gpt-3
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/93/b7/47e32af4f928a355c2f87697ba5fd030939e1b2f9e795761c9fe93ee0db8/gpt3_simple_primer-0.1.2.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-openai
+
+%description
+# gpt3-simple-primer
+
+Simple GPT-3 primer using `openai`.
+
+## Background
+
+Generative Pre-trained Transformer 3 (GPT-3) is an autoregressive language model that uses deep learning to produce human-like text. For more information, visit https://openai.com/blog/openai-api/.
+
+The [OpenAI Python library](https://github.com/openai/openai-python) is the official Python wrapper for the OpenAI API. The purpose of this library is to simplify the priming process by providing easy to use methods for setting the instructions and adding examples.
+
+## Priming
+
+Priming is the practice of providing an initial prompt to the language model to improve subsequent model predictions.
+
+GPT-3 generally does very well even with short instructions and a few examples of your intended use case. Examples are typically delimited based on input and output. For instance, GPT-3 can be used to predict food ingredients based on the following prompt:
+
+```
+Given the name of a food, list the ingredients used to make this meal.
+
+Food: apple pie
+Ingredients: apple, butter, flour, egg, cinnamon, crust, sugar
+
+Food: guacamole
+Ingredients: avocado, tomato, onion, lime, salt
+```
+
+## Requirements
+
+You will need an API key from OpenAI to access GPT-3.
+
+## Installation
+
+To install, run:
+
+```
+pip install gpt3-simple-primer
+```
+
+## Usage
+
+`input_text` and `output_text` determines how input and output are delimited in the examples. The default is to use `Input` and `Output`.
+
+```
+from gpt3_simple_primer import GPT3Generator, set_api_key
+
+KEY = 'sk-xxxxx'  # openai key
+set_api_key(KEY)
+
+generator = GPT3Generator(input_text='Food',
+                          output_text='Ingredients')
+
+generator.set_instructions('List the ingredients for this meal.')
+generator.add_example('apple pie', 'apple, butter, flour, egg, cinnamon, crust, sugar')
+generator.add_example('guacamole', 'avocado, tomato, onion, lime, salt')
+
+# Ingredients: cream, egg yolk, sugar, lime, key lime juice
+generator.generate(prompt='key lime pie',
+                   engine='davinci',
+                   max_tokens=20,
+                   temperature=0.5,
+                   top_p=1)
+```
+
+To see the prompt used for priming:
+
+```
+generator.get_prompt()
+```
+
+To remove an example from the prompt:
+
+```
+generator.remove_example('apple pie')
+```
+
+## Examples
+
+The library includes examples of GPT-3 applications based off of specific prompts.
+
+```
+from gpt3_simple_primer import set_api_key
+from gpt3_simple_primer.examples import idiom_explainer
+
+KEY = 'sk-xxxxx'  # openai key
+set_api_key(KEY)
+
+idiom_explainer.generate('hill to die on', max_tokens=15, engine='davinci')
+```
+
+
+
+
+%package -n python3-gpt3-simple-primer
+Summary:	GPT-3 wrapper for Python
+Provides:	python-gpt3-simple-primer
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-gpt3-simple-primer
+# gpt3-simple-primer
+
+Simple GPT-3 primer using `openai`.
+
+## Background
+
+Generative Pre-trained Transformer 3 (GPT-3) is an autoregressive language model that uses deep learning to produce human-like text. For more information, visit https://openai.com/blog/openai-api/.
+
+The [OpenAI Python library](https://github.com/openai/openai-python) is the official Python wrapper for the OpenAI API. The purpose of this library is to simplify the priming process by providing easy to use methods for setting the instructions and adding examples.
+
+## Priming
+
+Priming is the practice of providing an initial prompt to the language model to improve subsequent model predictions.
+
+GPT-3 generally does very well even with short instructions and a few examples of your intended use case. Examples are typically delimited based on input and output. For instance, GPT-3 can be used to predict food ingredients based on the following prompt:
+
+```
+Given the name of a food, list the ingredients used to make this meal.
+
+Food: apple pie
+Ingredients: apple, butter, flour, egg, cinnamon, crust, sugar
+
+Food: guacamole
+Ingredients: avocado, tomato, onion, lime, salt
+```
+
+## Requirements
+
+You will need an API key from OpenAI to access GPT-3.
+
+## Installation
+
+To install, run:
+
+```
+pip install gpt3-simple-primer
+```
+
+## Usage
+
+`input_text` and `output_text` determines how input and output are delimited in the examples. The default is to use `Input` and `Output`.
+
+```
+from gpt3_simple_primer import GPT3Generator, set_api_key
+
+KEY = 'sk-xxxxx'  # openai key
+set_api_key(KEY)
+
+generator = GPT3Generator(input_text='Food',
+                          output_text='Ingredients')
+
+generator.set_instructions('List the ingredients for this meal.')
+generator.add_example('apple pie', 'apple, butter, flour, egg, cinnamon, crust, sugar')
+generator.add_example('guacamole', 'avocado, tomato, onion, lime, salt')
+
+# Ingredients: cream, egg yolk, sugar, lime, key lime juice
+generator.generate(prompt='key lime pie',
+                   engine='davinci',
+                   max_tokens=20,
+                   temperature=0.5,
+                   top_p=1)
+```
+
+To see the prompt used for priming:
+
+```
+generator.get_prompt()
+```
+
+To remove an example from the prompt:
+
+```
+generator.remove_example('apple pie')
+```
+
+## Examples
+
+The library includes examples of GPT-3 applications based off of specific prompts.
+
+```
+from gpt3_simple_primer import set_api_key
+from gpt3_simple_primer.examples import idiom_explainer
+
+KEY = 'sk-xxxxx'  # openai key
+set_api_key(KEY)
+
+idiom_explainer.generate('hill to die on', max_tokens=15, engine='davinci')
+```
+
+
+
+
+%package help
+Summary:	Development documents and examples for gpt3-simple-primer
+Provides:	python3-gpt3-simple-primer-doc
+%description help
+# gpt3-simple-primer
+
+Simple GPT-3 primer using `openai`.
+
+## Background
+
+Generative Pre-trained Transformer 3 (GPT-3) is an autoregressive language model that uses deep learning to produce human-like text. For more information, visit https://openai.com/blog/openai-api/.
+
+The [OpenAI Python library](https://github.com/openai/openai-python) is the official Python wrapper for the OpenAI API. The purpose of this library is to simplify the priming process by providing easy to use methods for setting the instructions and adding examples.
+
+## Priming
+
+Priming is the practice of providing an initial prompt to the language model to improve subsequent model predictions.
+
+GPT-3 generally does very well even with short instructions and a few examples of your intended use case. Examples are typically delimited based on input and output. For instance, GPT-3 can be used to predict food ingredients based on the following prompt:
+
+```
+Given the name of a food, list the ingredients used to make this meal.
+
+Food: apple pie
+Ingredients: apple, butter, flour, egg, cinnamon, crust, sugar
+
+Food: guacamole
+Ingredients: avocado, tomato, onion, lime, salt
+```
+
+## Requirements
+
+You will need an API key from OpenAI to access GPT-3.
+
+## Installation
+
+To install, run:
+
+```
+pip install gpt3-simple-primer
+```
+
+## Usage
+
+`input_text` and `output_text` determines how input and output are delimited in the examples. The default is to use `Input` and `Output`.
+
+```
+from gpt3_simple_primer import GPT3Generator, set_api_key
+
+KEY = 'sk-xxxxx'  # openai key
+set_api_key(KEY)
+
+generator = GPT3Generator(input_text='Food',
+                          output_text='Ingredients')
+
+generator.set_instructions('List the ingredients for this meal.')
+generator.add_example('apple pie', 'apple, butter, flour, egg, cinnamon, crust, sugar')
+generator.add_example('guacamole', 'avocado, tomato, onion, lime, salt')
+
+# Ingredients: cream, egg yolk, sugar, lime, key lime juice
+generator.generate(prompt='key lime pie',
+                   engine='davinci',
+                   max_tokens=20,
+                   temperature=0.5,
+                   top_p=1)
+```
+
+To see the prompt used for priming:
+
+```
+generator.get_prompt()
+```
+
+To remove an example from the prompt:
+
+```
+generator.remove_example('apple pie')
+```
+
+## Examples
+
+The library includes examples of GPT-3 applications based off of specific prompts.
+
+```
+from gpt3_simple_primer import set_api_key
+from gpt3_simple_primer.examples import idiom_explainer
+
+KEY = 'sk-xxxxx'  # openai key
+set_api_key(KEY)
+
+idiom_explainer.generate('hill to die on', max_tokens=15, engine='davinci')
+```
+
+
+
+
+%prep
+%autosetup -n gpt3-simple-primer-0.1.2
+
+%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-gpt3-simple-primer -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.2-1
+- Package Spec generated
diff --git a/sources b/sources
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+4846370d5c8719d93545c7f2f5667503  gpt3_simple_primer-0.1.2.tar.gz