Update text_converter.py

Closing up some loose ends

text_converter.py

@@ -22,20 +22,20 @@ def generate_user_prompt(prompt_type, base_text):
 
     return prompts[prompt_type].format(base_text=base_text)
 
-
-def user_input_readability_level(input_text):
-    reading_levels = {
+reading_levels = {
     "5th Grade (90-100)": (90, 100),
     "6th Grade (80-90)": (80, 90),
     "7th Grade (70-80)": (70, 80),
     "8th - 9th Grade (60-70)": (60, 70),
     "10th - 12th Grade (50-60)": (50, 60),
     "College (30-50)": (30, 50),
-    "College Graduate + Professionals (0-30)": (0, 30)
+    "College Graduate + Professionals (0-30)": (0, 30),
+    "Research + Nobel laureate ((-infinity)-(-1))": (-float('inf'), -1)
     }
 
-    inverse_reading_levels = {v: k for k, v in reading_levels.items()}
-    
+inverse_reading_levels = {v: k for k, v in reading_levels.items()}
+
+def user_input_readability_level(input_text):
     current_score = flesch_reading_ease(input_text)
     print(f'Reading score for user input is: {current_score}')
     current_level = ''
@@ -54,6 +54,7 @@ def generate_similar_sentence(input_text, min_reading_level, max_reading_level,
     similarity = 0
     reading_level = 0
     generated_texts = []
+    generated_text_scores = []
     result_index = -1
     closeness = float('inf')
 
@@ -78,12 +79,15 @@ def generate_similar_sentence(input_text, min_reading_level, max_reading_level,
             
             response = get_gpt_response(user_prompt, system_prompt)
 
-            # First we add the generated text to the list of generated texts.
+            # We add the generated text to the list of generated texts.
             generated_texts.append(response)
 
             similarity = get_similarity(response, input_text)
             reading_level = flesch_reading_ease(response)
 
+            # We add the generated text's reading level to the list.
+            generated_text_scores.append((similarity, reading_level))
+
             # Determine the closeness of the reading level to the target reading level and store.
             if similarity >= min_entailment and min_reading_level <= reading_level <= max_reading_level:
                 result_index = i
@@ -100,10 +104,16 @@ def generate_similar_sentence(input_text, min_reading_level, max_reading_level,
 
         # Printing all generated texts to the console.
         for index, text in enumerate(generated_texts):
-            print(f"Generated text {index}: {text}")
+            print(f"Generated text {index + 1}: {text}")
+
+        # Printing the selected index and text.
+        print(f"Selected Iteration: {result_index + 1}")
+        print(f"Selected Result: {generated_texts[result_index]}")
+        print(f"Selected Result's Similarity score: {generated_text_complexities[result_index][0]}")
+        print(f"Selected Result's Readability score: {generated_text_complexities[result_index][1]}")
 
         # Returning the final result.
         if completed:
-            return generated_texts[result_index], similarity, reading_level, "Success! Please see the converted text at your target reading level."
+            return generated_texts[result_index], generated_text_complexities[result_index][0], generated_text_complexities[result_index][1], "Success! Please see the converted text at your target reading level."
         else:
-            return generated_texts[result_index], similarity, reading_level, "Failed. We could not reach the target reading level while maintaining the text meaning."
+            return generated_texts[result_index], generated_text_complexities[result_index][0], generated_text_complexities[result_index][1], "Failed. We could not reach the target reading level while maintaining the text meaning."