Some haystack test

requirements.txt

farm-haystack[all,inference]==1.19.0
Flask-SQLAlchemy
torch
sentence-transformers

test.py

from haystack.utils import *
from haystack.nodes import *
from haystack.nodes.retriever import *
from haystack.nodes.reader import FARMReader
from haystack.pipelines import *

doc_dir = "."

from haystack.document_stores import InMemoryDocumentStore

document_store = InMemoryDocumentStore(use_bm25=True)

# Clean & load your documents into the DocumentStore
dicts = convert_files_to_docs(doc_dir, clean_func=clean_wiki_text)
document_store.write_documents(dicts)

# Retriever: A Fast and simple algo to identify the most promising candidate documents
retriever = BM25Retriever(document_store)

# Reader: Powerful but slower neural network trained for QA
model_name = "deepset/roberta-base-squad2"
reader = FARMReader(model_name)

# Pipeline: Combines all the components
pipe = ExtractiveQAPipeline(reader, retriever)

# Voilà! Ask a question!
question = "Which is you best python file ?"
prediction = pipe.run(query=question)
print_answers(prediction)