feat: remove gpt35 answering

public-prediction/get_gpt_answer.py

@@ -4,19 +4,8 @@ from langchain_core.messages import HumanMessage, SystemMessage
 
 class GetGPTAnswer:
     def __init__(self):
-        self.llm_gpt35 = ChatOpenAI(model="gpt-3.5-turbo")
         self.llm_gpt4o = ChatOpenAI(model="gpt-4o")
 
-    def generate_gpt35_answer(self, question: str):
-        messages = [
-            SystemMessage(
-                content="Please answer the following question based solely on your internal knowledge, without external references. Assume you are the human."),
-            HumanMessage(question)
-        ]
-
-        gpt35_answer = self.llm_gpt35.invoke(messages)
-        return gpt35_answer.content
-
     def generate_gpt4o_answer(self, question: str):
         messages = [
             SystemMessage(

public-prediction/kafka_consumer.py

@@ -10,7 +10,6 @@ from google.protobuf.json_format import MessageToDict
 
 
 def get_gpt_responses(data: dict[str, any], gpt_helper: GetGPTAnswer):
-    data["gpt35_answer"] = gpt_helper.generate_gpt35_answer(data["question"])
     data["gpt4o_answer"] = gpt_helper.generate_gpt4o_answer(data["question"])
     return data
 
@@ -79,7 +78,8 @@ def consume_messages():
             print("Continuing...")
             continue
 
-        print(f"Parsing successful. Processing job_app_id {incoming_message['job_application_id']}")
+        print("Parsing successful. Processing job_app_id {0}".format(
+            incoming_message['job_application_id']))
 
         full_results = []
         for i in range(0, len(full_batch), BATCH_SIZE):