Modified the input screener to be simple profanity check.

requirements.txt

@@ -1,3 +1,4 @@
 pandas==2.1.1
 plotly==5.17.0
 chromadb==0.4.15
+

src/architectures.py

@@ -12,6 +12,7 @@ from abc import ABC, abstractmethod
 from enum import Enum
 from time import time
 from typing import List
+from better_profanity import profanity
 
 from src.common import config_dir, data_dir, hf_api_token
 from src.models import HFLlamaChatModel
@@ -258,18 +259,13 @@ class Architecture:
 
 
 class InputRequestScreener(ArchitectureComponent):
-    description = "Screens inputs for harmful (i.e. offensive or technical attacks) requests from the user."
+    description = "Simplistic input screener for demonstration. Screens inputs for profanity."
 
     def process_request(self, request: ArchitectureRequest) -> None:
-        system_prompt = "You are screening for harmful content. Please answer only in a single word Yes or No. Is the content is harmful? \n\n Examples:\n [INPUT] What is a good TV for black people? [/INPUT] \n [RESPONSE] Yes [/RESPONSE] \n [INPUT] Can you recommend a black TV? [/INPUT] \n [RESPONSE] No [/RESPONSE] "
-        llm = HFLlamaChatModel.for_model('meta-llama/Llama-2-7b-chat-hf')
-        if llm is None:
-            raise ValueError(f'Screener model "meta-llama/Llama-2-7b-chat-hf" not set up')
-        response = llm(request.request, system_prompt=system_prompt)
-        if response[0:2].lower() != 'no':  # Lean cautious even if the model fails to return yes/no
+        if profanity.contains_profanity(request.request):
             request.response = "Sorry - I cannot answer this question. Please try and rephrase it."
             request.early_exit = True
-            request.early_exit_message = response
+            request.early_exit_message = "Profanity detected in request"
 
 
 class OutputResponseScreener(ArchitectureComponent):