Update app.py

app.py

@@ -1,141 +1,18 @@
+# app.py (Gradio UI)
 import os
 import sys
 import gradio as gr
 from multiprocessing import freeze_support
-import importlib
-import inspect
-import json
-import logging
 
-# === Fix path to include src/txagent
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "src"))
+from ui.ui_core import create_ui
+from backend.agent_instance import init_agent
 
-# === Import and reload to ensure correct file
-import txagent.txagent
-importlib.reload(txagent.txagent)
-from txagent.txagent import TxAgent
-
-# === Debug info
-print(">>> TxAgent loaded from:", inspect.getfile(TxAgent))
-print(">>> TxAgent has run_gradio_chat:", hasattr(TxAgent, "run_gradio_chat"))
-
-# === Logging
-logging.basicConfig(level=logging.INFO)
-
-# === Environment
-current_dir = os.path.abspath(os.path.dirname(__file__))
-os.environ["MKL_THREADING_LAYER"] = "GNU"
-os.environ["TOKENIZERS_PARALLELISM"] = "false"
-
-# === Model config
-model_name = "mims-harvard/TxAgent-T1-Llama-3.1-8B"
-rag_model_name = "mims-harvard/ToolRAG-T1-GTE-Qwen2-1.5B"
-new_tool_files = {
-    "new_tool": os.path.join(current_dir, "data", "new_tool.json")
-}
-
-# === Example prompts
-question_examples = [
-    ["Given a patient with WHIM syndrome on prophylactic antibiotics, is it advisable to co-administer Xolremdi with fluconazole?"],
-    ["What treatment options exist for HER2+ breast cancer resistant to trastuzumab?"]
-]
-
-# === Extract tool name and format output
-def extract_tool_name_and_clean_content(msg):
-    tool_name = "Tool Result"
-    content = msg.get("content") if isinstance(msg, dict) else getattr(msg, "content", "")
-
-    # Attempt to load JSON from tool response
-    try:
-        parsed = json.loads(content)
-        if isinstance(parsed, dict):
-            tool_name = parsed.get("tool_name", tool_name)
-            content = parsed.get("content", content)
-    except Exception as e:
-        # fallback if content is not JSON
-        pass
-
-    if isinstance(content, (dict, list)):
-        content = json.dumps(content, indent=2)
-
-    return f"Tool: {tool_name}", content
-
-# === Format answer in collapsible box
-def format_collapsible(content, title="Answer"):
-    return (
-        f"<details style='border: 1px solid #ccc; border-radius: 8px; padding: 10px; margin-top: 10px;'>"
-        f"<summary style='font-size: 16px; font-weight: bold; color: #3B82F6;'>{title}</summary>"
-        f"<div style='margin-top: 8px; font-size: 15px; line-height: 1.6; white-space: pre-wrap;'>{content}</div></details>"
-    )
-
-# === Build UI
-def create_ui(agent):
-    with gr.Blocks(theme=gr.themes.Soft()) as demo:
-        gr.Markdown("<h1 style='text-align: center;'>💊 TxAgent: Therapeutic Reasoning</h1>")
-        gr.Markdown("Ask biomedical or therapeutic questions. Powered by tool-augmented reasoning.")
-
-        chatbot = gr.Chatbot(label="TxAgent", height=600, type="messages")
-        message_input = gr.Textbox(placeholder="Ask a biomedical question...", show_label=False)
-        send_button = gr.Button("Send", variant="primary")
-        conversation_state = gr.State([])
-
-        def handle_chat(message, history, conversation):
-            generator = agent.run_gradio_chat(
-                message=message,
-                history=history,
-                temperature=0.3,
-                max_new_tokens=1024,
-                max_token=8192,
-                call_agent=False,
-                conversation=conversation,
-                max_round=30
-            )
-            for update in generator:
-                formatted = []
-                for m in update:
-                    role = m.get("role") if isinstance(m, dict) else getattr(m, "role", "assistant")
-                    if role == "assistant":
-                        title, clean = extract_tool_name_and_clean_content(m)
-                        content = format_collapsible(clean, title)
-                    else:
-                        content = m.get("content") if isinstance(m, dict) else getattr(m, "content", "")
-                    formatted.append({"role": role, "content": content})
-                yield formatted
-
-        inputs = [message_input, chatbot, conversation_state]
-        send_button.click(fn=handle_chat, inputs=inputs, outputs=chatbot)
-        message_input.submit(fn=handle_chat, inputs=inputs, outputs=chatbot)
-
-        gr.Examples(examples=question_examples, inputs=message_input)
-        gr.Markdown("<small style='color: gray;'>DISCLAIMER: This demo is for research purposes only and does not provide medical advice.</small>")
-
-    return demo
-
-# === Main
 if __name__ == "__main__":
     freeze_support()
-    try:
-        agent = TxAgent(
-            model_name=model_name,
-            rag_model_name=rag_model_name,
-            tool_files_dict=new_tool_files,
-            force_finish=True,
-            enable_checker=True,
-            step_rag_num=10,
-            seed=100,
-            additional_default_tools=[]
-        )
-        agent.init_model()
-
-        if not hasattr(agent, "run_gradio_chat"):
-            raise AttributeError("❌ TxAgent is missing `run_gradio_chat`.")
-
-        demo = create_ui(agent)
-        demo.queue().launch(
-            server_name="0.0.0.0",
-            server_port=7860,
-            show_error=True
-        )
-    except Exception as e:
-        print(f"❌ App failed to start: {e}")
-        raise
+    agent = init_agent()
+    demo = create_ui(agent)
+    demo.queue().launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        show_error=True
+    )