Update app.py

app.py

@@ -1,15 +1,19 @@
 import os
+import sys
 import random
 import gradio as gr
 from datetime import datetime
 
-from txagent import TxAgent
+# Add `src` directory to Python path to import your custom agent
+sys.path.append(os.path.join(os.path.dirname(__file__), "src"))
+
+# Import your TxAgent class from src/txagent/TxAgent.py
+from txagent.TxAgent import TxAgent
 
 # ==== Environment Setup ====
 current_dir = os.path.dirname(os.path.abspath(__file__))
 os.environ["MKL_THREADING_LAYER"] = "GNU"
 os.environ["TOKENIZERS_PARALLELISM"] = "false"
-HF_TOKEN = os.environ.get("HF_TOKEN", None)
 
 # ==== UI Content ====
 DESCRIPTION = '''
@@ -78,24 +82,6 @@ if __name__ == "__main__":
     def handle_chat(message, history, temperature, max_new_tokens, max_tokens, multi_agent, conversation, max_round):
         return agent.run_gradio_chat(message, history, temperature, max_new_tokens, max_tokens, multi_agent, conversation, max_round)
 
-    def update_model_parameters(enable_finish, enable_rag, enable_summary,
-                                init_rag_num, step_rag_num, skip_last_k,
-                                summary_mode, summary_skip_last_k, summary_context_length,
-                                force_finish, seed):
-        return agent.update_parameters(
-            enable_finish=enable_finish,
-            enable_rag=enable_rag,
-            enable_summary=enable_summary,
-            init_rag_num=init_rag_num,
-            step_rag_num=step_rag_num,
-            skip_last_k=skip_last_k,
-            summary_mode=summary_mode,
-            summary_skip_last_k=summary_skip_last_k,
-            summary_context_length=summary_context_length,
-            force_finish=force_finish,
-            seed=seed
-        )
-
     def update_seed():
         seed = random.randint(0, 10000)
         return agent.update_parameters(seed=seed)