Update app.py

app.py

@@ -8,8 +8,9 @@ import google.generativeai as genai
 # api
 genai.configure(api_key="AIzaSyCmdsQeYMapI6l3maUpAkrE_GkT348w5UA")
 
+# model_1 = genai.GenerativeModel('gemini-pro')
+# model_2 = genai.GenerativeModel('gemini-pro')
 
-# gemini model initialization
 model = genai.GenerativeModel('gemini-pro')
 
 # assign score function
@@ -28,11 +29,9 @@ def assign_score(response):
         score = 0
     return score
 
-# funtion: prompt to model, parse the response to the judger, and enable user editing judgment
 def model_prompt_response(prompt):
-# using the Gemini model
-
-    # pompting the model for response
+# using the gemini model
+  
     prompt_response_1 = model.generate_content(prompt + "in 3 sentences or less")
     prompt_response_2 = model.generate_content(prompt + "in 3 sentences or less")
     response1_model = prompt_response_1.text
@@ -43,14 +42,12 @@ def model_prompt_response(prompt):
   
     prompt_to_judge_2 = f'Given the question, {prompt} and answer {response2_model}, decide whether: score = 1 when answer is strongly irrelevant to the question, score = 2 when the answer is slitely relevant, score = 3 when the answer is relevant, score = 4 when it is slitely relevant and score = 5 for strongly relevant answer. Give reason for your answer and start with scores and write the score as [score=1], [score=2], [score=3], [score=4], or [score=5]. '
 
-    # prompting the judger for judgment
     judge_1_response_1 = model.generate_content(prompt_to_judge_1)
     judge_2_response_2 = model.generate_content(prompt_to_judge_2)
     judge_1 = judge_1_response_1.text
     judge_2 = judge_2_response_2.text
 
 
-    # assigning scores
     score1_judger = assign_score(judge_1)
     score2_judger = assign_score(judge_2) 
 
@@ -59,9 +56,10 @@ def model_prompt_response(prompt):
 
     return response1_model, judge_1, score1_judger, response2_model, judge_2, score2_judger
 
+
+
 # anonators judgement
 def judge_response(score1_judger, score2_judger, judge_1, judge_2):
-    # user judgemnet
   score1_anonator = score1_judger
   score2_anonator = score2_judger
   response1_judger = judge_1
@@ -71,14 +69,17 @@ def judge_response(score1_judger, score2_judger, judge_1, judge_2):
 
 demo = gr.Blocks(theme=gr.themes.Monochrome(), title='Group1_Subtask2')
 
+
+
+
 with demo:
 
   gr.Markdown(
       """
       # Group1_Subtask2
       ## The Model takes a request from the user and returns a response.
-      #### A judger is assigned the response from the model and outputs the corresponding judgment.
-      #### The user asses the judgment and alters the response to correspond to their views or objective truth
+      #### A judger is asigned the response from the model and outputs corresponding judgement.
+      #### The user asses the judgement and alters the responds to correspond to their views or objective truth
       """
   )
   prompt = gr.Textbox(label='Question to the model')
@@ -97,6 +98,9 @@ with demo:
   response_model = gr.Button("Model response")
 
 
+
+
+
 # user/judger edited response
   with gr.Row():
     response1_judger = gr.Textbox(label='Corrected Response 1')