Upload 2 files

app.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from text_converter import reading_levels, model_types, generate_similar_sentence, user_input_readability_level, set_reading_levels
+from text_converter import fre_levels, sbert_levels, model_types, generate_similar_sentence, user_input_readability_level
 
 APP_DESCRIPTION = '''# Reading Level Converter
 <div id="content_align">Convert any text to a specified reading level while retaining the core text meaning</div>'''
@@ -8,39 +8,63 @@ 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):
+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
     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))
+    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)
     return output_text, similarity, reading_level, message
 
 with gr.Blocks(css='styles.css') as app:
     gr.Markdown(APP_DESCRIPTION)
 
-    with gr.Tab("Reading Level Calculator"):
+    with gr.Tab("FRE"):
         with gr.Row():
-            model_select = gr.Radio(choices=model_types, label="Readability Score Model", value=model_types[1], interactive=True, scale=2)
-            model_select_btn = gr.Button("Select Readability Score Model", scale=1)
-
-        input_text = gr.Textbox(label="Input Text", placeholder="Type here...", lines=4)
-
-        fetch_score_and_lvl_btn = gr.Button("Fetch Score and Level")
+            input_text = gr.Textbox(label="Input Text", placeholder="Type here...", lines=4, sclae = 2.5)
+            fetch_score_and_lvl_btn = gr.Button("Fetch Score and Level", scale = 0.5)
 
         output_input_reading_score = gr.Textbox(label="Input Text Reading Score", placeholder="Input Text Reading Score...", lines=1)
         output_input_reading_level = gr.Textbox(label="Input Text Reading Level", placeholder="Input Text Reading Level...", lines=1)
 
         fetch_score_and_lvl_btn.click(
             fn=user_input_readability_level,
-            inputs=[input_text],
+            inputs=[input_text, model_types[0]],
             outputs=[output_input_reading_score, output_input_reading_level]
         )
         
-        grade_level = gr.Radio(label="Target Reading Level", interactive=True)
+        grade_level = gr.Radio(choices=list(fre_levels.keys()), label="Target Reading Level", value = list(fre_levels.keys())[0], 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")
 
-        model_select_btn.click(
-            fn=set_reading_levels,
-            inputs=[model_select],
-            outputs=[grade_level]
+        convert_button.click(
+            fn=convert_text,
+            inputs=[input_text, grade_level, output_input_reading_score, model_types[0]],
+            outputs=[output_converted_text, output_similarity, output_reading_level, output_message]
         )
+
+    with gr.Tab("SBERT"):
+        with gr.Row():
+            input_text = gr.Textbox(label="Input Text", placeholder="Type here...", lines=4, sclae = 2.5)
+            fetch_score_and_lvl_btn = gr.Button("Fetch Score and Level", scale = 0.5)
+
+        output_input_reading_score = gr.Textbox(label="Input Text Reading Score", placeholder="Input Text Reading Score...", lines=1)
+        output_input_reading_level = gr.Textbox(label="Input Text Reading Level", placeholder="Input Text Reading Level...", lines=1)
+
+        fetch_score_and_lvl_btn.click(
+            fn=user_input_readability_level,
+            inputs=[input_text, model_types[1]],
+            outputs=[output_input_reading_score, output_input_reading_level]
+        )
+        
+        grade_level = gr.Radio(choices=list(sbert_levels.keys()), label="Target Reading Level", value = list(sbert_levels.keys())[0], 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)
@@ -52,10 +76,9 @@ with gr.Blocks(css='styles.css') as app:
 
         convert_button.click(
             fn=convert_text,
-            inputs=[input_text, grade_level, output_input_reading_score],
+            inputs=[input_text, grade_level, output_input_reading_score, model_types[1]],
             outputs=[output_converted_text, output_similarity, output_reading_level, output_message]
         )
 
-
 if __name__ == '__main__':
     app.launch()

text_converter.py

@@ -26,7 +26,6 @@ def generate_user_prompt(prompt_type, base_text):
     return prompts[prompt_type].format(base_text=base_text)
 
 model_types = ["FRE", "SBERT"]
-model_type = model_types[1]
 
 fre_levels = {
     "5th Grade (90-100)": (90, 100),
@@ -55,17 +54,15 @@ 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
-    global model_type
     if level_type == "FRE":
         reading_levels = fre_levels
     elif level_type == "SBERT":
         reading_levels = sbert_levels
     inverse_reading_levels = {v: k for k, v in reading_levels.items()}
-    model_type = level_type
-    return reading_levels.keys()
 
-def user_input_readability_level(input_text):
-    current_score = ping_api(input_text, model_type) #flesch_reading_ease(input_text)
+def user_input_readability_level(input_text, model_type):
+    set_reading_levels(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}')
     current_level = ''
     for (min, max), level in inverse_reading_levels.items():
@@ -75,7 +72,7 @@ def user_input_readability_level(input_text):
             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):
+def generate_similar_sentence(input_text, min_reading_level, max_reading_level, min_entailment, system_prompt, max_iter, curr_reading_level, model_type):
     i = 0
     completed = False
     user_prompt = ""