Update app.py

app.py

@@ -1,35 +1,27 @@
 import random
+import os
 import datetime
 import sys
 from txagent import TxAgent
 import spaces
 import gradio as gr
-import os
-import os
 
-# Determine the directory where the current file is located
+# Set environment variables
 current_dir = os.path.dirname(os.path.abspath(__file__))
 os.environ["MKL_THREADING_LAYER"] = "GNU"
-
-# Set an environment variable
+os.environ["TOKENIZERS_PARALLELISM"] = "false"
 HF_TOKEN = os.environ.get("HF_TOKEN", None)
 
-
 DESCRIPTION = '''
 <div>
 <h1 style="text-align: center;">TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools </h1>
 </div>
 '''
 INTRO = """
-Precision therapeutics require multimodal adaptive models that provide personalized treatment recommendations. We introduce TxAgent, an AI agent that leverages multi-step reasoning and real-time biomedical knowledge retrieval across a toolbox of 211 expert-curated tools to navigate complex drug interactions, contraindications, and patient-specific treatment strategies, delivering evidence-grounded therapeutic decisions. TxAgent executes goal-oriented tool selection and iterative function calls to solve therapeutic tasks that require deep clinical understanding and cross-source validation. The ToolUniverse consolidates 211 tools linked to trusted sources, including all US FDA-approved drugs since 1939 and validated clinical insights from Open Targets.
+Precision therapeutics require multimodal adaptive models that provide personalized treatment recommendations...
 """
-
 LICENSE = """
-We welcome your feedback and suggestions to enhance your experience with TxAgent, and if you're interested in collaboration, please email Marinka Zitnik and Shanghua Gao.
-
-### Medical Advice Disclaimer
-DISCLAIMER: THIS WEBSITE DOES NOT PROVIDE MEDICAL ADVICE
-The information, including but not limited to, text, graphics, images and other material contained on this website are for informational purposes only. No material on this site is intended to be a substitute for professional medical advice, diagnosis or treatment. Always seek the advice of your physician or other qualified health care provider with any questions you may have regarding a medical condition or treatment and before undertaking a new health care regimen, and never disregard professional medical advice or delay in seeking it because of something you have read on this website.
+DISCLAIMER: THIS WEBSITE DOES NOT PROVIDE MEDICAL ADVICE...
 """
 
 PLACEHOLDER = """
@@ -37,8 +29,8 @@ PLACEHOLDER = """
    <h1 style="font-size: 28px; margin-bottom: 2px; opacity: 0.55;">TxAgent</h1>
    <p style="font-size: 18px; margin-bottom: 2px; opacity: 0.65;">Tips before using TxAgent:</p>
    <p style="font-size: 18px; margin-bottom: 2px; opacity: 0.55;">Please click clear🗑️
- (top-right) to remove previous context before sumbmitting a new question.</p>
-   <p style="font-size: 18px; margin-bottom: 2px; opacity: 0.55;">Click retry🔄 (below message)  to get multiple versions of the answer.</p>
+ (top-right) to remove previous context before submitting a new question.</p>
+   <p style="font-size: 18px; margin-bottom: 2px; opacity: 0.55;">Click retry🔄 (below message) to get multiple versions of the answer.</p>
 </div>
 """
 
@@ -47,7 +39,6 @@ h1 {
   text-align: center;
   display: block;
 }
-
 #duplicate-button {
   margin: auto;
   color: white;
@@ -67,17 +58,13 @@ h1 {
 """
 
 chat_css = """
-.gr-button { font-size: 20px !important; }  /* Enlarges button icons */
-.gr-button svg { width: 32px !important; height: 32px !important; } /* Enlarges SVG icons */
+.gr-button { font-size: 20px !important; }
+.gr-button svg { width: 32px !important; height: 32px !important; }
 """
 
-# model_name = '/n/holylfs06/LABS/mzitnik_lab/Lab/shgao/bioagent/bio/alignment-handbook/data_new/L8-qlora-biov49v9v7v16_32k_chat01_merged'
 model_name = 'mims-harvard/TxAgent-T1-Llama-3.1-8B'
 rag_model_name = 'mims-harvard/ToolRAG-T1-GTE-Qwen2-1.5B'
 
-os.environ["TOKENIZERS_PARALLELISM"] = "false"
-
-
 question_examples = [
     ['Given a 50-year-old patient experiencing severe acute pain and considering the use of the newly approved medication, Journavx, how should the dosage be adjusted considering the presence of moderate hepatic impairment?'],
     ['Given a 50-year-old patient experiencing severe acute pain and considering the use of the newly approved medication, Journavx, how should the dosage be adjusted considering the presence of severe hepatic impairment?'],
@@ -98,12 +85,10 @@ agent = TxAgent(model_name,
                 additional_default_tools=['DirectResponse', 'RequireClarification'])
 agent.init_model()
 
-
 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):
-    # Update model instance parameters dynamically
-    updated_params = agent.update_parameters(
+    return agent.update_parameters(
         enable_finish=enable_finish,
         enable_rag=enable_rag,
         enable_summary=enable_summary,
@@ -117,33 +102,18 @@ def update_model_parameters(enable_finish, enable_rag, enable_summary,
         seed=seed,
     )
 
-    return updated_params
-
-
 def update_seed():
-    # Update model instance parameters dynamically
     seed = random.randint(0, 10000)
-    updated_params = agent.update_parameters(
-        seed=seed,
-    )
-    return updated_params
-
+    return agent.update_parameters(seed=seed)
 
 def handle_retry(history, retry_data: gr.RetryData, temperature, max_new_tokens, max_tokens, multi_agent, conversation, max_round):
-    print("Updated seed:", update_seed())
+    update_seed()
     new_history = history[:retry_data.index]
     previous_prompt = history[retry_data.index]['content']
-
-    print("previous_prompt", previous_prompt)
-
     yield from agent.run_gradio_chat(new_history + [{"role": "user", "content": previous_prompt}], temperature, max_new_tokens, max_tokens, multi_agent, conversation, max_round)
 
-
 PASSWORD = "mypassword"
 
-# Function to check if the password is correct
-
-
 def check_password(input_password):
     if input_password == PASSWORD:
         return gr.update(visible=True), ""
@@ -151,143 +121,108 @@ def check_password(input_password):
         return gr.update(visible=False), "Incorrect password, try again!"
 
 
-conversation_state = gr.State([])
-
-# Gradio block
-chatbot = gr.Chatbot(height=800, placeholder=PLACEHOLDER,
-                     label='TxAgent', type="messages",  show_copy_button=True)
-
-with gr.Blocks(css=css) as demo:
-    gr.Markdown(DESCRIPTION)
-    gr.Markdown(INTRO)
-    default_temperature = 0.3
-    default_max_new_tokens = 1024
-    default_max_tokens = 81920
-    default_max_round = 30
-    temperature_state = gr.State(value=default_temperature)
-    max_new_tokens_state = gr.State(value=default_max_new_tokens)
-    max_tokens_state = gr.State(value=default_max_tokens)
-    max_round_state = gr.State(value=default_max_round)
-    chatbot.retry(handle_retry, chatbot, chatbot, temperature_state, max_new_tokens_state,
-                  max_tokens_state, gr.Checkbox(value=False, render=False), conversation_state, max_round_state)
+if __name__ == "__main__":
+    conversation_state = gr.State([])
 
-    gr.ChatInterface(
-        fn=agent.run_gradio_chat,
-        chatbot=chatbot,
-        fill_height=True, fill_width=True, stop_btn=True,
-        additional_inputs_accordion=gr.Accordion(
-            label="⚙️ Inference Parameters", open=False, render=False),
-        additional_inputs=[
-            temperature_state, max_new_tokens_state, max_tokens_state,
-            gr.Checkbox(
-                label="Activate multi-agent reasoning mode (it requires additional time but offers a more comprehensive analysis).", value=False, render=False),
-            conversation_state,
-            max_round_state,
-            gr.Number(label="Seed", value=100, render=False)
-        ],
-        examples=question_examples,
-        cache_examples=False,
-        css=chat_css,
+    chatbot = gr.Chatbot(
+        height=800, placeholder=PLACEHOLDER, label='TxAgent',
+        type="messages", show_copy_button=True
     )
 
-    with gr.Accordion("Settings", open=False):
-
-        # Define the sliders
-        temperature_slider = gr.Slider(
-            minimum=0,
-            maximum=1,
-            step=0.1,
-            value=default_temperature,
-            label="Temperature"
-        )
-        max_new_tokens_slider = gr.Slider(
-            minimum=128,
-            maximum=4096,
-            step=1,
-            value=default_max_new_tokens,
-            label="Max new tokens"
-        )
-        max_tokens_slider = gr.Slider(
-            minimum=128,
-            maximum=32000,
-            step=1,
-            value=default_max_tokens,
-            label="Max tokens"
+    with gr.Blocks(css=css) as demo:
+        gr.Markdown(DESCRIPTION)
+        gr.Markdown(INTRO)
+
+        default_temperature = 0.3
+        default_max_new_tokens = 1024
+        default_max_tokens = 81920
+        default_max_round = 30
+
+        temperature_state = gr.State(value=default_temperature)
+        max_new_tokens_state = gr.State(value=default_max_new_tokens)
+        max_tokens_state = gr.State(value=default_max_tokens)
+        max_round_state = gr.State(value=default_max_round)
+
+        chatbot.retry(
+            handle_retry,
+            chatbot, chatbot,
+            temperature_state, max_new_tokens_state,
+            max_tokens_state,
+            gr.Checkbox(value=False, render=False),
+            conversation_state,
+            max_round_state
         )
-        max_round_slider = gr.Slider(
-            minimum=0,
-            maximum=50,
-            step=1,
-            value=default_max_round,
-            label="Max round")
-
-        # Automatically update states when slider values change
-        temperature_slider.change(
-            lambda x: x, inputs=temperature_slider, outputs=temperature_state)
-        max_new_tokens_slider.change(
-            lambda x: x, inputs=max_new_tokens_slider, outputs=max_new_tokens_state)
-        max_tokens_slider.change(
-            lambda x: x, inputs=max_tokens_slider, outputs=max_tokens_state)
-        max_round_slider.change(
-            lambda x: x, inputs=max_round_slider, outputs=max_round_state)
 
-        password_input = gr.Textbox(
-            label="Enter Password for More Settings", type="password")
-        incorrect_message = gr.Textbox(visible=False, interactive=False)
-        with gr.Accordion("⚙️ Settings", open=False, visible=False) as protected_accordion:
-            with gr.Row():
-                with gr.Column(scale=1):
-                    with gr.Accordion("⚙️ Model Loading", open=False):
-                        model_name_input = gr.Textbox(
-                            label="Enter model path", value=model_name)
-                        load_model_btn = gr.Button(value="Load Model")
-                        load_model_btn.click(
-                            agent.load_models, inputs=model_name_input, outputs=gr.Textbox(label="Status"))
-                with gr.Column(scale=1):
-                    with gr.Accordion("⚙️ Functional Parameters", open=False):
-                        # Create Gradio components for parameter inputs
-                        enable_finish = gr.Checkbox(
-                            label="Enable Finish", value=True)
-                        enable_rag = gr.Checkbox(
-                            label="Enable RAG", value=True)
-                        enable_summary = gr.Checkbox(
-                            label="Enable Summary", value=False)
-                        init_rag_num = gr.Number(
-                            label="Initial RAG Num", value=0)
-                        step_rag_num = gr.Number(
-                            label="Step RAG Num", value=10)
-                        skip_last_k = gr.Number(label="Skip Last K", value=0)
-                        summary_mode = gr.Textbox(
-                            label="Summary Mode", value='step')
-                        summary_skip_last_k = gr.Number(
-                            label="Summary Skip Last K", value=0)
-                        summary_context_length = gr.Number(
-                            label="Summary Context Length", value=None)
-                        force_finish = gr.Checkbox(
-                            label="Force FinalAnswer", value=True)
-                        seed = gr.Number(label="Seed", value=100)
-                        # Button to submit and update parameters
-                        submit_btn = gr.Button("Update Parameters")
-
-                        # Display the updated parameters
-                        updated_parameters_output = gr.JSON()
-
-                        # When button is clicked, update parameters
-                        submit_btn.click(fn=update_model_parameters,
-                                         inputs=[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],
-                                         outputs=updated_parameters_output)
-        # Button to submit the password
-        submit_button = gr.Button("Submit")
-
-        # When the button is clicked, check if the password is correct
-        submit_button.click(
-            check_password,
-            inputs=password_input,
-            outputs=[protected_accordion, incorrect_message]
+        gr.ChatInterface(
+            fn=agent.run_gradio_chat,
+            chatbot=chatbot,
+            fill_height=True, fill_width=True, stop_btn=True,
+            additional_inputs_accordion=gr.Accordion(label="⚙️ Inference Parameters", open=False, render=False),
+            additional_inputs=[
+                temperature_state, max_new_tokens_state, max_tokens_state,
+                gr.Checkbox(label="Activate multi-agent reasoning mode", value=False, render=False),
+                conversation_state,
+                max_round_state,
+                gr.Number(label="Seed", value=100, render=False)
+            ],
+            examples=question_examples,
+            cache_examples=False,
+            css=chat_css,
         )
-    gr.Markdown(LICENSE)
 
+        with gr.Accordion("Settings", open=False):
+            temperature_slider = gr.Slider(0, 1, step=0.1, value=default_temperature, label="Temperature")
+            max_new_tokens_slider = gr.Slider(128, 4096, step=1, value=default_max_new_tokens, label="Max new tokens")
+            max_tokens_slider = gr.Slider(128, 32000, step=1, value=default_max_tokens, label="Max tokens")
+            max_round_slider = gr.Slider(0, 50, step=1, value=default_max_round, label="Max round")
+
+            temperature_slider.change(lambda x: x, inputs=temperature_slider, outputs=temperature_state)
+            max_new_tokens_slider.change(lambda x: x, inputs=max_new_tokens_slider, outputs=max_new_tokens_state)
+            max_tokens_slider.change(lambda x: x, inputs=max_tokens_slider, outputs=max_tokens_state)
+            max_round_slider.change(lambda x: x, inputs=max_round_slider, outputs=max_round_state)
+
+            password_input = gr.Textbox(label="Enter Password for More Settings", type="password")
+            incorrect_message = gr.Textbox(visible=False, interactive=False)
+
+            with gr.Accordion("⚙️ Settings", open=False, visible=False) as protected_accordion:
+                with gr.Row():
+                    with gr.Column(scale=1):
+                        with gr.Accordion("⚙️ Model Loading", open=False):
+                            model_name_input = gr.Textbox(label="Enter model path", value=model_name)
+                            load_model_btn = gr.Button(value="Load Model")
+                            load_model_btn.click(agent.load_models, inputs=model_name_input, outputs=gr.Textbox(label="Status"))
+                    with gr.Column(scale=1):
+                        with gr.Accordion("⚙️ Functional Parameters", open=False):
+                            enable_finish = gr.Checkbox(label="Enable Finish", value=True)
+                            enable_rag = gr.Checkbox(label="Enable RAG", value=True)
+                            enable_summary = gr.Checkbox(label="Enable Summary", value=False)
+                            init_rag_num = gr.Number(label="Initial RAG Num", value=0)
+                            step_rag_num = gr.Number(label="Step RAG Num", value=10)
+                            skip_last_k = gr.Number(label="Skip Last K", value=0)
+                            summary_mode = gr.Textbox(label="Summary Mode", value='step')
+                            summary_skip_last_k = gr.Number(label="Summary Skip Last K", value=0)
+                            summary_context_length = gr.Number(label="Summary Context Length", value=None)
+                            force_finish = gr.Checkbox(label="Force FinalAnswer", value=True)
+                            seed = gr.Number(label="Seed", value=100)
+
+                            submit_btn = gr.Button("Update Parameters")
+                            updated_parameters_output = gr.JSON()
+                            submit_btn.click(
+                                fn=update_model_parameters,
+                                inputs=[
+                                    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
+                                ],
+                                outputs=updated_parameters_output
+                            )
+
+            submit_button = gr.Button("Submit")
+            submit_button.click(
+                check_password,
+                inputs=password_input,
+                outputs=[protected_accordion, incorrect_message]
+            )
+
+        gr.Markdown(LICENSE)
 
-if __name__ == "__main__":
     demo.launch(share=True)