| 
									
										
										
										
											2019-11-27 14:02:23 +01:00
										 |  |  | from io import open | 
					
						
							|  |  |  | 
 | 
					
						
							|  |  |  | from setuptools import find_packages, setup | 
					
						
							|  |  |  | 
 | 
					
						
							|  |  |  | with open("requirements.txt") as f: | 
					
						
							|  |  |  |     parsed_requirements = f.read().splitlines() | 
					
						
							| 
									
										
										
										
											2020-01-13 19:38:37 +01:00
										 |  |  | # remove blank lines, comments and links to specific git commits | 
					
						
							| 
									
										
										
										
											2019-11-27 14:02:23 +01:00
										 |  |  | parsed_requirements = [ | 
					
						
							|  |  |  |     x.strip() | 
					
						
							|  |  |  |     for x in parsed_requirements | 
					
						
							| 
									
										
										
										
											2020-01-13 19:38:37 +01:00
										 |  |  |     if ((x.strip()[0] != "#") and (len(x.strip()) > 3) and "-e git://" not in x) | 
					
						
							| 
									
										
										
										
											2019-11-27 14:02:23 +01:00
										 |  |  | ] | 
					
						
							|  |  |  | 
 | 
					
						
							|  |  |  | setup( | 
					
						
							| 
									
										
										
										
											2019-11-27 16:17:45 +01:00
										 |  |  |     name="farm-haystack", | 
					
						
							| 
									
										
										
										
											2020-05-05 15:07:44 +02:00
										 |  |  |     version="0.2.1", | 
					
						
							| 
									
										
										
										
											2019-11-27 14:02:23 +01:00
										 |  |  |     author="Malte Pietsch, Timo Moeller, Branden Chan, Tanay Soni", | 
					
						
							|  |  |  |     author_email="malte.pietsch@deepset.ai", | 
					
						
							|  |  |  |     description="Neural Question Answering at Scale. Use modern transformer based models like BERT to find answers in large document collections", | 
					
						
							| 
									
										
										
										
											2019-11-27 17:18:05 +01:00
										 |  |  |     long_description=open("README.rst", "r", encoding="utf-8").read(), | 
					
						
							| 
									
										
										
										
											2019-11-27 14:02:23 +01:00
										 |  |  |     long_description_content_type="text/x-rst", | 
					
						
							|  |  |  |     keywords="QA Question-Answering Reader Retriever BERT roberta albert squad mrc transfer-learning language-model transformer", | 
					
						
							|  |  |  |     license="Apache", | 
					
						
							|  |  |  |     url="https://github.com/deepset-ai/haystack", | 
					
						
							| 
									
										
										
										
											2020-05-05 15:07:44 +02:00
										 |  |  |     download_url="https://github.com/deepset-ai/haystack/archive/0.2.1.tar.gz", | 
					
						
							| 
									
										
										
										
											2019-11-27 14:02:23 +01:00
										 |  |  |     packages=find_packages(exclude=["*.tests", "*.tests.*", "tests.*", "tests"]), | 
					
						
							|  |  |  |     install_requires=parsed_requirements, | 
					
						
							|  |  |  |     python_requires=">=3.6.0", | 
					
						
							|  |  |  |     tests_require=["pytest"], | 
					
						
							|  |  |  |     classifiers=[ | 
					
						
							|  |  |  |         "Intended Audience :: Science/Research", | 
					
						
							|  |  |  |         "License :: OSI Approved :: Apache Software License", | 
					
						
							|  |  |  |         "Programming Language :: Python :: 3", | 
					
						
							|  |  |  |         "Topic :: Scientific/Engineering :: Artificial Intelligence", | 
					
						
							|  |  |  |     ], | 
					
						
							|  |  |  | ) |