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import gradio as gr |
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import os |
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import logging |
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from txagent import TxAgent |
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from tooluniverse import ToolUniverse |
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logging.basicConfig(level=logging.INFO) |
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logger = logging.getLogger(__name__) |
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class TxAgentApp: |
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def __init__(self): |
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self.agent = self._initialize_agent() |
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def _initialize_agent(self): |
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"""Initialize the TxAgent with proper parameters""" |
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try: |
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logger.info("Initializing TxAgent...") |
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tool_files = { |
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"opentarget": "opentarget_tools.json", |
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"fda_drug_label": "fda_drug_labeling_tools.json", |
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"special_tools": "special_tools.json", |
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"monarch": "monarch_tools.json" |
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} |
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agent = TxAgent( |
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model_name="mims-harvard/TxAgent-T1-Llama-3.1-8B", |
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rag_model_name="mims-harvard/ToolRAG-T1-GTE-Qwen2-1.5B", |
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tool_files_dict=tool_files, |
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enable_finish=True, |
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enable_rag=True, |
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enable_summary=False, |
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init_rag_num=0, |
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step_rag_num=10, |
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summary_mode='step', |
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summary_skip_last_k=0, |
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summary_context_length=None, |
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force_finish=True, |
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avoid_repeat=True, |
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seed=42, |
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enable_checker=True, |
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enable_chat=False, |
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additional_default_tools=["DirectResponse", "RequireClarification"] |
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) |
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agent.init_model() |
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logger.info("Model loading complete") |
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return agent |
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except Exception as e: |
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logger.error(f"Initialization failed: {str(e)}") |
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raise |
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def respond(self, message, chat_history, temperature, max_new_tokens, max_tokens, multi_agent, conversation_state, max_round): |
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"""Handle streaming responses with Gradio""" |
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try: |
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if not isinstance(message, str) or len(message.strip()) <= 10: |
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return chat_history + [("", "Please provide a valid message longer than 10 characters.")] |
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if chat_history and isinstance(chat_history[0], dict): |
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chat_history = [(h["role"], h["content"]) for h in chat_history if "role" in h and "content" in h] |
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response = "" |
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for chunk in self.agent.run_gradio_chat( |
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message=message.strip(), |
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history=chat_history, |
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temperature=temperature, |
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max_new_tokens=max_new_tokens, |
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max_token=max_tokens, |
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call_agent=multi_agent, |
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conversation=conversation_state, |
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max_round=max_round, |
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seed=42 |
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): |
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if isinstance(chunk, dict): |
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response += chunk.get("content", "") |
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elif isinstance(chunk, str): |
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response += chunk |
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else: |
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response += str(chunk) |
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yield chat_history + [("user", message), ("assistant", response)] |
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except Exception as e: |
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logger.error(f"Error in respond function: {str(e)}") |
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yield chat_history + [("", f"⚠️ Error: {str(e)}")] |
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def create_demo(): |
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"""Create and configure the Gradio interface""" |
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app = TxAgentApp() |
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with gr.Blocks(title="TxAgent Medical AI") as demo: |
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gr.Markdown("# TxAgent Biomedical Assistant") |
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chatbot = gr.Chatbot( |
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label="Conversation", |
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height=600, |
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bubble_full_width=False |
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) |
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msg = gr.Textbox( |
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label="Your medical query", |
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placeholder="Enter your biomedical question...", |
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lines=3 |
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) |
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with gr.Row(): |
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temp = gr.Slider(0, 1, value=0.3, label="Temperature") |
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max_new_tokens = gr.Slider(128, 4096, value=1024, label="Max New Tokens") |
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max_tokens = gr.Slider(128, 81920, value=81920, label="Max Total Tokens") |
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max_rounds = gr.Slider(1, 30, value=10, label="Max Rounds") |
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multi_agent = gr.Checkbox(label="Multi-Agent Mode") |
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submit = gr.Button("Submit") |
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clear = gr.Button("Clear") |
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conversation_state = gr.State([]) |
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submit.click( |
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app.respond, |
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[msg, chatbot, temp, max_new_tokens, max_tokens, multi_agent, conversation_state, max_rounds], |
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chatbot |
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) |
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clear.click(lambda: [], None, chatbot) |
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msg.submit( |
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app.respond, |
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[msg, chatbot, temp, max_new_tokens, max_tokens, multi_agent, conversation_state, max_rounds], |
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chatbot |
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) |
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return demo |
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def main(): |
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"""Main entry point for the application""" |
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try: |
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logger.info("Starting TxAgent application...") |
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demo = create_demo() |
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logger.info("Launching Gradio interface...") |
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demo.launch( |
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server_name="0.0.0.0", |
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server_port=7860, |
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share=False |
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) |
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except Exception as e: |
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logger.error(f"Application failed to start: {str(e)}") |
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raise |
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if __name__ == "__main__": |
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main() |