Upload 2 files

app.py

@@ -8,13 +8,10 @@ MIN_ENTAILMENT = 0.5
 MAX_ITER = 5
 SYSTEM_PROMPT = "You are a writing assistant. You help convert complex texts to simpler texts while maintaining the core meaning of the text."
 
-def convert_text(input_text, grade_level, input_reading_score, model_type):
-    if model_type == "FRE":
-        reading_levels = fre_levels
-    else:
-        reading_levels = sbert_levels
+def convert_text(input_text, grade_level, input_reading_score, is_fre):
+    reading_levels = fre_levels if is_fre else sbert_levels
     min_level, max_level = reading_levels[grade_level]
-    output_text, similarity, reading_level, message = generate_similar_sentence(input_text, min_level, max_level, MIN_ENTAILMENT, SYSTEM_PROMPT, MAX_ITER, float(input_reading_score), model_type)
+    output_text, similarity, reading_level, message = generate_similar_sentence(input_text, min_level, max_level, MIN_ENTAILMENT, SYSTEM_PROMPT, MAX_ITER, float(input_reading_score), is_fre)
     return output_text, similarity, reading_level, message
 
 with gr.Blocks(css='styles.css') as app:
@@ -40,7 +37,7 @@ with gr.Blocks(css='styles.css') as app:
 
         fetch_score_and_lvl_btn.click(
             fn=user_input_readability_level,
-            inputs=[input_text, "FRE"],
+            inputs=[input_text, True],
             outputs=[output_input_reading_score, output_input_reading_level]
         )
         
@@ -59,7 +56,7 @@ with gr.Blocks(css='styles.css') as app:
 
         convert_button.click(
             fn=convert_text,
-            inputs=[input_text, grade_level_fre, output_input_reading_score, "FRE"],
+            inputs=[input_text, grade_level_fre, output_input_reading_score, True],
             outputs=[output_converted_text, output_similarity, output_reading_level, output_message]
         )
     #with gr.Tab("SBERT"):

text_converter.py

@@ -61,9 +61,9 @@ def set_reading_levels(level_type):
     inverse_reading_levels = {v: k for k, v in reading_levels.items()}
     return level_type
 
-def user_input_readability_level(input_text, model_type):
-    current_score = ping_api(input_text, model_type)
-    print(f'Reading score for user input is: {current_score} for model type: {model_type}')
+def user_input_readability_level(input_text, is_fre):
+    current_score = ping_api(input_text, model_types[0] if is_fre else model_types[1])
+    print(f'Reading score for user input is: {current_score} for model type: {model_types[0] if is_fre else model_types[1]}')
     current_level = ''
     for (min, max), level in inverse_reading_levels.items():
         if min <= current_score <= max:
@@ -72,7 +72,7 @@ def user_input_readability_level(input_text, model_type):
             break
     return current_score, current_level
 
-def generate_similar_sentence(input_text, min_reading_level, max_reading_level, min_entailment, system_prompt, max_iter, curr_reading_level, model_type):
+def generate_similar_sentence(input_text, min_reading_level, max_reading_level, min_entailment, system_prompt, max_iter, curr_reading_level, is_fre):
     i = 0
     completed = False
     user_prompt = ""
@@ -109,7 +109,7 @@ def generate_similar_sentence(input_text, min_reading_level, max_reading_level,
             generated_texts.append(response)
 
             similarity = get_similarity(response, input_text)
-            reading_level = ping_api(response, model_type) #flesch_reading_ease(response)
+            reading_level = ping_api(response, model_types[0] if is_fre else model_types[1]) #flesch_reading_ease(response)
 
             # We add the generated text's reading level to the list.
             generated_text_scores.append((similarity, reading_level))
@@ -132,7 +132,7 @@ def generate_similar_sentence(input_text, min_reading_level, max_reading_level,
             i += 1
 
         # Printing all generated texts to the console.
-        print(f"=============== Model Type: {model_type} ===============\n")
+        print(f"=============== Model Type: {model_types[0] if is_fre else model_types[1]} ===============\n")
         for index, text in enumerate(generated_texts):
             print(f"=============== Iteration {index} ===============")
             print(f"Generated text: {text}\nSimilarity: {generated_text_scores[index][0]}\nReadability Score: {generated_text_scores[index][1]}\n")