Update telcom_core.py

telcom_core.py

@@ -1,6 +1,6 @@
 import re
-from llama_index.core import PromptTemplate
 from llama_index.llms.openai import OpenAI
+from llama_index.core import PromptTemplate
 
 teamplate_prompt_upsell = '''You are a virtual assistant for a telecom company, designed to assist users with their queries and potentially upsell services. Your task is to analyze the customer's data from context, their query, and offer the most appropriate assistance.
 
@@ -183,23 +183,16 @@ def query_graph_rag_qa(graph_rag_index,query,search_level):
 
     return response, reference , reference_text
 
-def eval_llm(query,rag_response,grag_response):
-    data = {'QUERY': query,
-            'RESPONSE': rag_response
-            }
-    prompt = PromptTemplate(llm_eval_prompt) 
-    query_ready = prompt.format(**data)
-    rag_eval = OpenAI().complete(query_ready)
-
-    data = {'QUERY': query,
-            'RESPONSE': grag_response
-            }
-    prompt = PromptTemplate(llm_eval_prompt) 
-    query_ready = prompt.format(**data)
-    grag_eval = OpenAI().complete(query_ready)
-    return grag_eval,rag_eval
 
 
+def evaluate_llm(query,response):
+    """
+    Evaluates the provided query and response using a PromptTemplate and returns the completion from OpenAI.
+    """
+    data = {'QUERY': query, 'RESPONSE': response}
+    prompt = PromptTemplate(llm_eval_prompt).format(**data)
+    return OpenAI().complete(prompt)
+
 def plot_full_kg(kg_plot_path):
     """Plot the full knowledge graph and return the HTML representation."""
     # return HTML(filename=kg_plot_path)