Added response aligner.

requirements.txt

@@ -1,4 +1,5 @@
+datetime
 flask
 flask_CORS
-datetime
+nltk
 openai

therapist.py

@@ -1,3 +1,4 @@
+from nltk.metrics.distance import edit_distance
 import openai
 import os
 import questionnaires
@@ -17,8 +18,21 @@ def listify(options: list, end_and=True, lower=True, use_format=None):
     return ", ".join(options) if len(options) > 2 else " ".join(options)
 
 def content_summarizer():
+    """
+    Summarize previous messages for new prompts to pass as context.
+    """
     pass
 
+def response_aligner(options:list, response:str): 
+    """
+    Takes a series of options, and a response as given by Openai.
+    Align the response to the nearest option (edit distance).
+    This is necessary as sometimes openai will return a response slightly different to the ones in prompt.
+    """
+    distances = [(option, edit_distance(option, response)) for option in options]
+    distances = sorted(distances, key=lambda item: item[1])
+    return distances[0][0]
+
 def assess_response(question: str, response:str, options: list, uses_scale=True, context="a psychological evaluation"):
     context_prompt = "" if context=="" else f"The context of this discussion is {context}. "
     if uses_scale is True:
@@ -51,6 +65,8 @@ def questionnaire_chooser(message):
         options = options,
         uses_scale = False
         )
+    
+    if topic not in options: topic = response_aligner(options, topic)
 
     match topic.lower():
         case "suicidal":
@@ -76,7 +92,6 @@ def bot_response(next_question=None):
     pass
 
 def get_question(questionnaire, number):
-    print(questionnaire, number)
     return questionnaires.questions[questionnaire][number]
 
 def generate_response(user, message):