Correct paper extraction in demo

agentreview/role_descriptions.py

@@ -30,7 +30,7 @@ SCORE_CALCULATION_v1 = {
     1: "This study is not yet sufficiently thorough to warrant publication or is not relevant to the conference. This paper makes marginal contributions"
 }
 
-# Start to use this rubric from 2024.1.23 as SCORE_CALCULATION_v1 is too harsh
+# Start to use this rubric as SCORE_CALCULATION_v1 is too harsh
 SCORE_CALCULATION = {
     10: "This study is among the top 2% of all papers. It is one of the most thorough I have seen. It changed my "
         "thinking on this topic. I would fight for it to be accepted",
@@ -97,12 +97,14 @@ def get_reviewer_description(is_benign: bool = None, is_knowledgeable: bool = No
     bio = ("You are a reviewer. You write peer review of academic papers by evaluating their technical "
            f"quality, originality, and clarity. ")
 
+    """
     # The reviewer's famous identities are known to the AC
     if knows_authors:
         bio += "\n\n" + INSTRUCTIONS_FOR_FAMOUS_AUTHORS
 
     else:
         bio += f"{SCORE_CONTROL}\n\n"
+    """
 
     bio += "## Review Guidelines\n"
 

app.py

@@ -116,11 +116,11 @@ def get_player_components(name, visible):
             with gr.Row():
                 # Converting the three attributes into dropdowns
                 Intention_config = gr.Dropdown(
-                    choices=["Benign", "Malicious", "Neutral"],
+                    choices=["Benign", "Malicious", "Normal"],
                     interactive=True,
                     label = "Intention",
                     show_label=True,
-                    value="Neutral",
+                    value="Normal",
                 )
                 
                 Knowledge_config = gr.Dropdown(
@@ -425,7 +425,7 @@ Simulate conference reviews on your own papers using LLM agents.
                 
                 upload_file_box = gr.File(
                     visible=True,
-                    height = 100,
+                    height=100,
                 )
                 
                 with gr.Row():
@@ -640,7 +640,7 @@ Simulate conference reviews on your own papers using LLM agents.
         # 更新前端信息
         if timestep:
             all_messages = timestep.observation
-            all_messages[0].content = 'Paper content has been extracted.'
+
             chatbot_output = _convert_to_chatbot_output(all_messages, display_recv=True)
 
             # Initialize update dictionary
@@ -769,4 +769,4 @@ Simulate conference reviews on your own papers using LLM agents.
 
     
 demo.queue()
-demo.launch() 
+demo.launch()