import os
import sys
import random
import gradio as gr
from multiprocessing import freeze_support
import importlib
import inspect
# === Path fix
sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), "src"))
# === Reload to avoid stale module
import txagent.txagent
importlib.reload(txagent.txagent)
from txagent.txagent import TxAgent
from gradio import ChatMessage
# === Debug
print(">>> TxAgent loaded from:", inspect.getfile(TxAgent))
print(">>> TxAgent has run_gradio_chat:", hasattr(TxAgent, "run_gradio_chat"))
# === Env vars
current_dir = os.path.dirname(os.path.abspath(__file__))
os.environ["MKL_THREADING_LAYER"] = "GNU"
os.environ["TOKENIZERS_PARALLELISM"] = "false"
# === UI text
DESCRIPTION = '''
TxAgent: AI for Therapeutic Reasoning
'''
INTRO = "Ask biomedical or therapeutic questions. Results are powered by tools and reasoning."
LICENSE = "DISCLAIMER: THIS WEBSITE DOES NOT PROVIDE MEDICAL ADVICE."
# === Model & tool 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")
}
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?"]
]
# === Gradio UI
def create_ui(agent):
with gr.Blocks() as demo:
gr.Markdown(DESCRIPTION)
gr.Markdown(INTRO)
temperature = gr.Slider(0, 1, step=0.1, value=0.3, label="Temperature")
max_new_tokens = gr.Slider(128, 4096, step=1, value=1024, label="Max New Tokens")
max_tokens = gr.Slider(128, 32000, step=1, value=8192, label="Max Total Tokens")
max_round = gr.Slider(1, 50, step=1, value=30, label="Max Rounds")
multi_agent = gr.Checkbox(label="Enable Multi-agent Reasoning", value=False)
conversation_state = gr.State([])
chatbot = gr.Chatbot(label="TxAgent", height=600, type="messages")
message_input = gr.Textbox(placeholder="Ask a biomedical question...", show_label=False)
send_btn = gr.Button("Send", variant="primary")
def handle_chat(message, history, temperature, max_new_tokens, max_tokens, multi_agent, conversation, max_round):
# Ensure response is a generator that yields list of {role, content} dictionaries
return agent.run_gradio_chat(
message=message,
history=history,
temperature=temperature,
max_new_tokens=max_new_tokens,
max_token=max_tokens,
call_agent=multi_agent,
conversation=conversation,
max_round=max_round
)
send_btn.click(
fn=handle_chat,
inputs=[message_input, chatbot, temperature, max_new_tokens, max_tokens, multi_agent, conversation_state, max_round],
outputs=chatbot
)
message_input.submit(
fn=handle_chat,
inputs=[message_input, chatbot, temperature, max_new_tokens, max_tokens, multi_agent, conversation_state, max_round],
outputs=chatbot
)
gr.Examples(
examples=question_examples,
inputs=message_input
)
gr.Markdown(LICENSE)
return demo
# === App startup
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=["DirectResponse", "RequireClarification"]
)
agent.init_model()
if not hasattr(agent, "run_gradio_chat"):
raise AttributeError("❌ TxAgent is missing `run_gradio_chat`.")
demo = create_ui(agent)
demo.launch(show_error=True)
except Exception as e:
print(f"🚨 Startup error: {e}")
raise