bsod90

import faiss
from encoder import UniversalEncoder

# Don't forget to start the encoder container locally and open the 8501 port

encoder = UniversalEncoder(host='localhost', port=8501)
data = [
    'What color is chameleon?',
    'When is the festival of colors?',
    'When is the next music festival?',

bsod90

state_dir = './search_data/'

faiss.write_index(
    index,
    os.path.join(state_dir, "faiss.index")
)

index = faiss.read_index(
    os.path.join(state_dir, "faiss.index")
)

bsod90

import tensorflow as tf
import tensorflow_hub as hub
from tensorflow.saved_model import simple_save

export_dir = "./models/use/00000001"
with tf.Session(graph=tf.Graph()) as sess:
    module = hub.Module("https://tfhub.dev/google/universal-sentence-encoder-multilingual-large/1")
    text_input = tf.placeholder(dtype=tf.string, shape=[None])

    sess.run([tf.global_variables_initializer(), tf.tables_initializer()])

bsod90

FROM python:3.6

RUN apt-get update -y
RUN apt-get install -y unzip wget
RUN apt-get install -y default-jdk

RUN wget http://h2o-release.s3.amazonaws.com/h2o/rel-wolpert/8/h2o-3.18.0.8.zip
RUN unzip ./h2o-3.18.0.8.zip
RUN mv h2o-3.18.0.8/h2o.jar /tmp/

bsod90

# Connect to the semantic-search service and run the query
con = get_victor_connection()
response = con.FindTopKProblems(
    victor_pb2.TopKProblemsRequest(
        query=search_query,
        # In our implementation -1 means "return all matches"
        k=-1,
    ),
)