Docker Endpoint for DRILL

Part of RAKI D6.1

1. Creating an endpoint for DRILL manually

Here, we provide each command to create an endpoint to use DRILL

# (1) clone the repo & unzip necessary files.
git clone https://github.com/dice-group/RAKI-Drill-Endpoint && cd RAKI-Drill-Endpoint 
unzip embeddings.zip && unzip LPs.zip && unzip pre_trained_agents.zip
# (2) close the most recent dev. branch of ontolearn
git clone https://github.com/dice-group/Ontolearn.git -b develop && cd Ontolearn
# (3) Create an anaconda virtual environment and install dependencies.
conda create --name temp python=3.8  && conda activate temp
pip install -e . && cd ..
# (4) Execute python script to create flask based endpoint.
python Ontolearn/examples/simple_drill_endpoint.py --path_knowledge_base 'Ontolearn/KGs/Biopax/biopax.owl' --path_knowledge_base_embeddings 'embeddings/ConEx_Biopax/ConEx_entity_embeddings.csv' --pretrained_drill_avg_path 'pre_trained_agents/Biopax/DrillHeuristic_averaging/DrillHeuristic_averaging.pth'
#...
# Running on http://192.168.2.108:9080/ # Copy this address

How to use the endpoint

pick one of the example learning problems and submit it to the system: (requires jq)

# (1) Open a new terminal (Ctrl+Alt+T on ubuntu) to verify the endpoint.
curl http://192.168.2.108:9080/status # => {"status":"ready"} # If you see this  all went well :)
# (2) Use an example learning problem
jq '
     .problems
       ."((pathwayStep ⊓ (∀INTERACTION-TYPE.Thing)) ⊔ (sequenceInterval ⊓ (∀ID-VERSION.Thing)))"
     | {
        "positives": .positive_examples,
        "negatives": .negative_examples
       }' LPs/Biopax/lp.json \
		   | curl -d@- http://192.168.2.108:9080/concept_learning

2. Creating an endpoint for DRILL via Docker

git clone https://github.com/dice-group/RAKI-Drill-Endpoint && cd RAKI-Drill-Endpoint 
unzip LPs # unzip learning problems file to use it later on
sudo docker build -t drill:latest "." 
# Successfully tagged drill:latest # if you see **done**, all went well
sudo docker images # to see installed image

Run the docker image.

sudo docker run drill
# expected to see 
# Running on http://172.17.0.3:9080/

How to use the endpoint

pick one of the example learning problems and submit it to the system: (requires jq)

# (1) Open a new terminal (Ctrl+Alt+T on ubuntu) to verify the endpoint.
curl http://172.17.0.3:9080/status
{"status":"ready"} # If you see this  all went well :)
# (2) Use an example learning problem
jq '
   .problems
     ."((pathwayStep ⊓ (∀INTERACTION-TYPE.Thing)) ⊔ (sequenceInterval ⊓ (∀ID-VERSION.Thing)))"
   | {
      "positives": .positive_examples,
      "negatives": .negative_examples
     }' LPs/Biopax/lp.json \
  	   | curl -d@- http://172.17.0.3:9080/concept_learning

response: (OWL rdf/xml)

<?xml version="1.0"?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
         xmlns:xsd="http://www.w3.org/2001/XMLSchema#"
         xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#"
         xmlns:owl="http://www.w3.org/2002/07/owl#"
         xml:base="https://dice-research.org/predictions/1619526593.1690164"
         xmlns="https://dice-research.org/predictions/1619526593.1690164#">

<owl:Ontology rdf:about="https://dice-research.org/predictions/1619526593.1690164">
  <owl:imports rdf:resource="file:///OntoPy/KGs/Biopax/biopax.owl"/>
</owl:Ontology>

<owl:Class rdf:about="#Pred_0">
  <owl:equivalentClass rdf:resource="http://www.biopax.org/examples/glycolysis#pathwayStep"/>
  <rdfs:label rdf:datatype="http://www.w3.org/2001/XMLSchema#string">pathwayStep</rdfs:label>
</owl:Class>


</rdf:RDF>

Congrats!

Contact

For any questions, please contact: caglar.demir@upb.de / caglardemir8@gmail.com