Update app.py

app.py

@@ -4,6 +4,13 @@ import gradio as gr
 from openai import OpenAI
 
 from optillm.cot_reflection import cot_reflection
+from optillm.rto import round_trip_optimization
+from optillm.z3_solver import Z3SolverSystem
+from optillm.self_consistency import advanced_self_consistency_approach
+from optillm.rstar import RStar
+from optillm.plansearch import plansearch
+from optillm.leap import leap
+
 
 API_KEY = os.environ.get("OPENROUTER_API_KEY")
 
@@ -29,9 +36,23 @@ def respond(
 
     messages.append({"role": "user", "content": message})
 
-    # response = ""
-
-    final_response = cot_reflection(system_message, message, client, model)
+    if approach == 'rto':
+        final_response = round_trip_optimization(system_prompt, initial_query, client, model)
+    elif approach == 'z3':
+        z3_solver = Z3SolverSystem(system_prompt, client, model)
+        final_response = z3_solver.process_query(initial_query)
+    elif approach == "self_consistency":
+        final_response = advanced_self_consistency_approach(system_prompt, initial_query, client, model)
+    elif approach == "rstar":
+        rstar = RStar(system_prompt, client, model)
+        final_response = rstar.solve(initial_query)
+    elif approach == "cot_reflection":
+        final_response = cot_reflection(system_prompt, initial_query, client, model)
+    elif approach == 'plansearch':
+        final_response = plansearch(system_prompt, initial_query, client, model)
+    elif approach == 'leap':
+        final_response = leap(system_prompt, initial_query, client, model)
+        
     return final_response
 
     # for message in client.chat_completion(
@@ -58,7 +79,7 @@ demo = gr.ChatInterface(
             value="nousresearch/hermes-3-llama-3.1-405b:free", label="Model", info="Choose the base model"
         ),
         gr.Dropdown(
-            ["leap", "plansearch", "rstar", "cot_reflection"], value="cot_reflection", label="Approach", info="Choose the approach"
+            ["leap", "plansearch", "rstar", "cot_reflection", "rto", "self_consistency", "z3"], value="cot_reflection", label="Approach", info="Choose the approach"
         ),
         gr.Textbox(value="", label="System message"),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
@@ -73,6 +94,5 @@ demo = gr.ChatInterface(
     ],
 )
 
-
 if __name__ == "__main__":
     demo.launch()