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app.py

@@ -22,16 +22,6 @@ with gr.Blocks(css='styles.css') as app:
     gr.Markdown(APP_DESCRIPTION)
 
     with gr.Tab("FRE"):
-        """with gr.Row():
-            readability_model = gr.Radio(choices=model_types, label="Readability Model", value = model_types[0], interactive=True, scale = 2)
-            readability_model_btn = gr.Button("Set Readability Model", scale = 1)
-        
-        readability_model_btn.click(
-            fn=set_reading_levels,
-            inputs=[readability_model],
-            outputs=[readability_model]
-        )"""
-
         with gr.Row():
             input_text = gr.Textbox(label="Input Text", placeholder="Type here...", lines=4, scale = 2)
             fetch_score_and_lvl_btn = gr.Button("Fetch Score and Level", scale = 1)
@@ -45,10 +35,7 @@ with gr.Blocks(css='styles.css') as app:
             outputs=[output_input_reading_score, output_input_reading_level]
         )
         
-        
         grade_level_fre = gr.Radio(choices=list(fre_levels.keys()), label="Target Reading Level", interactive=True)
-        #grade_level_sbert = gr.Radio(choices=list(sbert_levels.keys()), label="Target Reading Level", interactive=True, visible=(readability_model == model_types[1]))
-        #grade_level = gr.Radio(choices=list(fre_levels.keys()) if readability_model == model_types[0] else list(sbert_levels.keys()), label="Target Reading Level", interactive=True)
         
         output_reading_level = gr.Textbox(label="Output Reading Level", placeholder="Output Reading Level...", lines=1)
         output_similarity = gr.Textbox(label="Similarity", placeholder="Similarity Score...", lines=1)
@@ -63,8 +50,35 @@ with gr.Blocks(css='styles.css') as app:
             inputs=[input_text, grade_level_fre, output_input_reading_score],
             outputs=[output_converted_text, output_similarity, output_reading_level, output_message]
         )
-    #with gr.Tab("SBERT"):
+    with gr.Tab("SBERT"):
+        with gr.Row():
+            input_text = gr.Textbox(label="Input Text", placeholder="Type here...", lines=4, scale = 2)
+            fetch_score_and_lvl_btn = gr.Button("Fetch Score and Level", scale = 1)
+
+        output_input_reading_score = gr.Textbox(label="Input Text Reading Score", placeholder="Input Text Reading Score...", lines=1, interactive=False)
+        output_input_reading_level = gr.Textbox(label="Input Text Reading Level", placeholder="Input Text Reading Level...", lines=1, interactive=False)
 
+        fetch_score_and_lvl_btn.click(
+            fn=fetch_readability_score_sbert,
+            inputs=[input_text],
+            outputs=[output_input_reading_score, output_input_reading_level]
+        )
+        
+        grade_level_sbert = gr.Radio(choices=list(sbert_levels.keys()), label="Target Reading Level", interactive=True)
+        
+        output_reading_level = gr.Textbox(label="Output Reading Level", placeholder="Output Reading Level...", lines=1)
+        output_similarity = gr.Textbox(label="Similarity", placeholder="Similarity Score...", lines=1)
+        output_converted_text = gr.Textbox(label="Converted Text", placeholder="Results will appear here...", lines=4)
+                    
+        output_message = gr.Textbox(label="Message", placeholder="System Message...", lines=2)
+        
+        convert_button = gr.Button("Convert Text")
+
+        convert_button.click(
+            fn=convert_text_sbert,
+            inputs=[input_text, grade_level_fre, output_input_reading_score],
+            outputs=[output_converted_text, output_similarity, output_reading_level, output_message]
+        )
 
 if __name__ == '__main__':
     app.launch()

text_converter.py

@@ -1,7 +1,6 @@
 from bert_similarity import get_similarity
 from text_generator import get_gpt_response
 from arte_score import ping_api
-from textstat import flesch_reading_ease
 
 def generate_user_prompt(prompt_type, base_text):
     prompts = {
@@ -25,7 +24,7 @@ def generate_user_prompt(prompt_type, base_text):
 
     return prompts[prompt_type].format(base_text=base_text)
 
-model_types = ["FRE", "SBERT"]
+__model_types = ["FRE", "SBERT"]
 
 fre_levels = {
     "5th Grade (90-100)": (90, 100),
@@ -46,32 +45,34 @@ sbert_levels = {
     "Easy (> -0.04)": (-0.04, 100)
     }
 
-# Setting SBert to be default to avoid any issues.
-reading_levels = sbert_levels
+# Setting FRE to be default.
+__reading_levels = fre_levels
 
-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 set_reading_levels(level_type):
-    global reading_levels
-    global inverse_reading_levels
+def __set_reading_levels(level_type):
+    global __reading_levels
+    global __inverse_reading_levels
     if level_type == "FRE":
-        reading_levels = fre_levels
+        __reading_levels = fre_levels
     elif level_type == "SBERT":
-        reading_levels = sbert_levels
-    inverse_reading_levels = {v: k for k, v in reading_levels.items()}
+        __reading_levels = sbert_levels
+    __inverse_reading_levels = {v: k for k, v in __reading_levels.items()}
     return level_type
 
 def fetch_readability_score_fre(input_text):
-    return user_input_readability_level(input_text, True)
+    __set_reading_levels(__model_types[0])
+    return __user_input_readability_level(input_text, True)
 
 def fetch_readability_score_sbert(input_text):
-    return user_input_readability_level(input_text, False)
+    __set_reading_levels(__model_types[1])
+    return __user_input_readability_level(input_text, False)
 
-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]}')
+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():
+    for (min, max), level in __inverse_reading_levels.items():
         if min <= current_score <= max:
             print(f'Reading level for user input is: {level}')
             current_level = level
@@ -79,12 +80,12 @@ def user_input_readability_level(input_text, is_fre):
     return current_score, current_level
 
 def generate_sim_fre(input_text, min_reading_level, max_reading_level, min_entailment, system_prompt, max_iter, curr_reading_level):
-    return generate_similar_sentence(input_text, min_reading_level, max_reading_level, min_entailment, system_prompt, max_iter, curr_reading_level, True)
+    return __generate_similar_sentence(input_text, min_reading_level, max_reading_level, min_entailment, system_prompt, max_iter, curr_reading_level, True)
 
 def generate_sim_sbert(input_text, min_reading_level, max_reading_level, min_entailment, system_prompt, max_iter, curr_reading_level):
-    return generate_similar_sentence(input_text, min_reading_level, max_reading_level, min_entailment, system_prompt, max_iter, curr_reading_level, False)
+    return __generate_similar_sentence(input_text, min_reading_level, max_reading_level, min_entailment, system_prompt, max_iter, curr_reading_level, False)
 
-def generate_similar_sentence(input_text, min_reading_level, max_reading_level, min_entailment, system_prompt, max_iter, curr_reading_level, is_fre):
+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 = ""
@@ -121,7 +122,7 @@ 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_types[0] if is_fre else model_types[1]) #flesch_reading_ease(response)
+            reading_level = ping_api(response, __model_types[0] if is_fre else __model_types[1])
 
             # We add the generated text's reading level to the list.
             generated_text_scores.append((similarity, reading_level))
@@ -144,7 +145,7 @@ 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_types[0] if is_fre else model_types[1]} ===============\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")