test more strategies

app.py

@@ -8,9 +8,25 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name)
 
 with gr.Blocks() as demo:
-    chatbot = gr.Chatbot()
-    msg = gr.Textbox()
-    clear = gr.ClearButton([msg, chatbot])
+    gr.Markdown("# LLM Evaluator With Linguistic Scrutiny")
+
+    with gr.Tab("POS"):
+        gr.Markdown(" Description ")
+
+        msg = gr.Textbox(show_label=False, placeholder="Write a prompt and press enter")
+
+        gr.Markdown("Strategy 1 QA")
+        with gr.Row():
+            vicuna_S1_chatbot_POS = gr.Chatbot(label="vicuna-7b")
+            clear = gr.ClearButton([msg, vicuna_S1_chatbot_POS])
+        gr.Markdown("Strategy 2 Instruction")
+        with gr.Row():
+            vicuna_S2_chatbot_POS = gr.Chatbot(label="vicuna-7b")
+            clear = gr.ClearButton([msg, vicuna_S2_chatbot_POS])
+        gr.Markdown("Strategy 1 Structured Prompting")
+        with gr.Row():
+            vicuna_S3_chatbot_POS = gr.Chatbot(label="vicuna-7b")
+            clear = gr.ClearButton([msg, vicuna_S3_chatbot_POS])
 
     def respond(message, chat_history):
         input_ids = tokenizer.encode(message, return_tensors="pt")
@@ -21,6 +37,8 @@ with gr.Blocks() as demo:
         time.sleep(2)
         return "", chat_history
 
-    msg.submit(respond, [msg, chatbot], [msg, chatbot])
+    msg.submit(respond, [msg, vicuna_S1_chatbot_POS], [msg, vicuna_S1_chatbot_POS])
+    msg.submit(respond, [msg, vicuna_S2_chatbot_POS], [msg, vicuna_S2_chatbot_POS])
+    msg.submit(respond, [msg, vicuna_S3_chatbot_POS], [msg, vicuna_S3_chatbot_POS])
 
 demo.launch()