Merge branch 'master' of github.com:deepset-ai/haystack

.travis.yml

@@ -0,0 +1,9 @@
+language: python
+sudo: false
+cache: pip
+python:
+  - "3.7"
+install:
+  - "pip install -e ."
+script:
+  - "cd test && pytest"

setup.py

@@ -14,7 +14,7 @@ parsed_requirements = [
 
 setup(
     name="farm-haystack",
-    version="0.1.2",
+    version="0.1.3",
     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",
@@ -23,7 +23,7 @@ setup(
     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",
-    download_url="https://github.com/deepset-ai/haystack/archive/0.1.2.tar.gz",
+    download_url="https://github.com/deepset-ai/haystack/archive/0.1.3.tar.gz",
     packages=find_packages(exclude=["*.tests", "*.tests.*", "tests.*", "tests"]),
     install_requires=parsed_requirements,
     python_requires=">=3.6.0",

test/test_db.py

@@ -8,7 +8,6 @@ def test_db_write_read():
     db.create_all()
 
     write_documents_to_db(document_dir="samples/docs")
-    documents = db.session.query(Document).all()
+    documents = db.session.query(Document).order_by(Document.text).all()
     assert len(documents) == 2
     assert documents[0].text == 'A Doc specifically talking about haystack.\nHaystack can be used to scale QA models to large document collections.'
-    print(documents)