Concept linking outcommented

relation_extraction/multilingual/llm_messenger.py

@@ -2,16 +2,29 @@
 import requests
 import re
 import os
+from llama_cpp import Llama
 
 class LLMMessenger(APIHandler):
 
  def API_endpoint():
  return "http://knox-proxy01.srv.aau.dk/llama-api/llama"
 
  def send_request(request):
- HEADERS = {"Access-Authorization": os.getenv("ACCESS_SECRET")}
- response = requests.post(url=LLMMessenger.API_endpoint(), json=request, headers=HEADERS)
- return response
+ # Put the location of the GGUF model that you've download from HuggingFace here
+ model_path = "relation_extraction\multilingual\llama-2-7b-chat.Q2_K.gguf"
+
+ # Create a llama model
+ model = Llama(model_path=model_path, n_ctx=4096)
+
+ prompt = f"""<s>[INST] <<SYS>>
+ {request["system_message"]}
+ <</SYS>>
+ {request["user_message"]} [/INST]"""
+
+ # Run the model
+ output = model(prompt, max_tokens=request["max_tokens"], echo=True)
+
+ return output
 
  def process_message(response):
  print("Recieved response from Llama2...")

requirements.txt

@@ -1,7 +1,7 @@
 #For python
 #----------
 # Concept linking
--r concept_linking/requirements.txt
+# -r concept_linking/requirements.txt
 
 # Relation extraction
 -r relation_extraction/requirements.txt

requirements_docker.txt

@@ -1,7 +1,7 @@
 #For docker
 #----------
 # Concept linking
--r /code/concept_linking/requirements.txt
+# -r /code/concept_linking/requirements.txt
 
 # Relation extraction
 -r /code/relation_extraction/requirements.txt

server/server.py

@@ -2,7 +2,7 @@
 import json
 import os
 from relation_extraction.relation_extractor import RelationExtractor
-from concept_linking.main import entity_type_classification
+# from concept_linking.main import entity_type_classification
 
 app = Flask(__name__)
 
@@ -22,7 +22,7 @@ def do_triple_construction():
  post_json = json.loads(post_data)
 
  RelationExtractor.begin_extraction(post_json) # Relation Extraction
- entity_type_classification(post_json) # Concept Linking
+ # entity_type_classification(post_json) # Concept Linking
 
  message = "Post request was successfully processed. Relation Extraction and Concept Linking completed."
  return jsonify(message=message), 200