alexcg1

from jina import Client
from docarray import Document

client = Client("https://8bae9ebaf9.wolf.jina.ai")

query = Document(text="Can I catch COVID from my pet armadillo?")

search_filter = {"source": {"$eq": "biomedical"}}

results = client.search(query, parameters={"filter": search_filter})

alexcg1

docs = DocumentArray.from_csv(
  "data/community.csv",
  field_resolver={"question": "text"}
)

alexcg1

client = Client(host=<Flow URL>)
client.index(docs)

alexcg1

jtype: Flow
with:
  protocol: http  # remove the port
executors:
  - name: encoder
    uses: jinahub+docker://SpacyTextEncoder/v0.4  # run everything in docker
    uses_with:
      model_name: 'en_core_web_md'
    replicas: 2  # 2 replicas for faster encoding
    resources:

alexcg1

from jina import Client
from docarray import Document

client = Client(host='localhost', port=23456)

query = Document(text="Can I catch COVID from my pet armadillo?")

search_filter = {"source": {"$eq": "biomedical"}}

results = client.search(query, parameters={"filter": search_filter})

alexcg1

from jina import Client
from docarray import Document

client = Client(host='localhost', port=23456)

query = Document(text="Can I catch COVID from my pet armadillo?")

results = client.search(query)

for result in results:

alexcg1

flow = Flow.load_config("flow.yml")

alexcg1

jtype: Flow
with:
  protocol: http
  port: 23456
executors:
  - name: encoder
    uses: jinahub+docker://SpacyTextEncoder/v0.4
    uses_with:
      model_name: 'en_core_web_md'
    install_requirements: true

alexcg1

jtype: Flow
with:
  protocol: http
  port: 23456
executors:
  - name: encoder
    uses: jinahub+://SpacyTextEncoder/v0.4
    uses_with:
      model_name: 'en_core_web_md'
    install_requirements: true

alexcg1

jtype: Flow
with:
  protocol: http
executors:
  - name: encoder
    uses: jinahub+docker://CLIPEncoder
    resources:
      memory: 8G
  - name: tensor_deleter
    uses: jinahub+docker://TensorDeleter