Added options on ai and plagiarisim checker.

app.py

@@ -34,6 +34,7 @@ np.set_printoptions(suppress=True)
 
 
 def plagiarism_check(
+    plag_option,
     input,
     year_from,
     month_from,
@@ -58,8 +59,10 @@ def plagiarism_check(
     date_from = build_date(year_from, month_from, day_from)
     date_to = build_date(year_to, month_to, day_to)
     sort_date = f"date:r:{date_from}:{date_to}"
+
     # get list of URLS to check
     urlCount, ScoreArray = googleSearch(
+        plag_option,
         sentences,
         urlCount,
         ScoreArray,
@@ -210,7 +213,7 @@ def predict_mc(model, tokenizer, text):
         mc_score[label.upper()] = score.item()
     return mc_score
 
-def ai_generated_test(input):
+def ai_generated_test(ai_option, input):
 
     cleaned_text = remove_special_characters(input)
     bc_score = predict_bc(text_bc_model, text_bc_tokenizer, cleaned_text)
@@ -220,7 +223,10 @@ def ai_generated_test(input):
     for key, value in mc_score.items():
         mc_score[key] = value * sum_prob
     
-    if sum_prob < 0.1  :
+    if ai_option == "Human vs AI":
+        mc_score = {}
+
+    if sum_prob < 0.01  :
         mc_score = {}
         return bc_score, mc_score
     else:
@@ -228,6 +234,8 @@ def ai_generated_test(input):
 
 # COMBINED
 def main(
+    ai_option,
+    plag_option,
     input,
     # models,
     year_from,
@@ -240,6 +248,7 @@ def main(
 ):
 
     formatted_tokens = plagiarism_check(
+        plag_option,
         input,
         year_from,
         month_from,
@@ -250,7 +259,7 @@ def main(
         domains_to_skip,
     )
     depth_analysis_plot = depth_analysis(input)
-    bc_score, mc_score = ai_generated_test(input)
+    bc_score, mc_score = ai_generated_test(ai_option,input)
     
     return (
     bc_score,
@@ -402,13 +411,24 @@ with gr.Blocks() as demo:
 
     with gr.Row():
         with gr.Column():
-            only_ai_btn = gr.Button("AI Check")
+            ai_option = gr.Radio(["Human vs AI", "Human vs AI Source Models"], label="Choose an option please.")
         with gr.Column():
-            only_plagiarism_btn = gr.Button("Plagiarism Check")
+            plag_option = gr.Radio(["Standard", "Advanced"], label="Choose an option please.")
+
+    with gr.Row():
         with gr.Column():
-            depth_analysis_btn = gr.Button("Depth Analysis")
+            only_ai_btn = gr.Button("AI Check")
+
         with gr.Column():
-            full_check_btn = gr.Button("Full Check")
+            only_plagiarism_btn = gr.Button("Plagiarism Check")
+    with gr.Row():
+
+    with gr.Row():
+        depth_analysis_btn = gr.Button("Detailed Writing Analysis")
+
+    with gr.Row():
+        full_check_btn = gr.Button("Full Check")
+
     gr.Markdown(
         """
         ## Output
@@ -479,6 +499,8 @@ with gr.Blocks() as demo:
     full_check_btn.click(
         fn=main,
         inputs=[
+            ai_option,
+            plag_option,
             input_text,
             # models,
             year_from,
@@ -500,7 +522,7 @@ with gr.Blocks() as demo:
 
     only_ai_btn.click(
         fn=ai_generated_test,
-        inputs=[input_text],
+        inputs=[ai_option, input_text],
         outputs=[
             bcLabel,
             mcLabel,
@@ -511,6 +533,7 @@ with gr.Blocks() as demo:
     only_plagiarism_btn.click(
         fn=plagiarism_check,
         inputs=[
+            plag_option,
             input_text,
             year_from,
             month_from,

utils.py

@@ -96,6 +96,7 @@ def getSentences(text):
 
 
 def googleSearch(
+    plag_option,
     sentences,
     urlCount,
     scoreArray,
@@ -139,8 +140,12 @@ def googleSearch(
                     urlList.append(url)
                     scoreArray.append([0] * len(sentences))
                 urlCount[url] = urlCount[url] + 1 if url in urlCount else 1
-                scoreArray[urlList.index(url)][i] = sentence_similarity(
-                    sentence, snippet
+                if plag_option == 'Standard':
+                    scoreArray[urlList.index(url)][i] = cosineSim(
+                        sentence, snippet)
+                else :     
+                    scoreArray[urlList.index(url)][i] = sentence_similarity(
+                        sentence, snippet
                 )
         else:
             print("Google Search failed")