run_app.py

import random
import datetime
import sys
from agent.agent import SigSpace
import spaces
import gradio as gr
import os
from PIL import Image

import os

os.environ["VLLM_USE_V1"] = "0" # Disable v1 API for now since it does not support logits processors.

# Determine the directory where the current file is located
current_dir = os.path.dirname(os.path.abspath(__file__))
os.environ["MKL_THREADING_LAYER"] = "GNU"

# Set an environment variable
HF_TOKEN = os.environ.get("HF_TOKEN", None)


# Create the image path - use absolute path for reliability
img_path = os.path.join(current_dir, 'img', 'SigSpace.png')

def display_image(image_path):
    # Load and return the image
    img = Image.open(image_path)
    return img

DESCRIPTION = f'''
<div style="text-align: center;">
  <h1 style="font-size: 32px; margin-bottom: 10px;">SigSpace: An AI Agent for Tahoe-100M</h1>
</div>
'''
INTRO = """
This is the intro that goes here
"""

LICENSE = """
License goes here
"""

PLACEHOLDER = """
<div style="padding: 30px; text-align: center; display: flex; flex-direction: column; align-items: center;">
   <h1 style="font-size: 28px; margin-bottom: 2px; opacity: 0.55;">Agent</h1>
   <p style="font-size: 18px; margin-bottom: 2px; opacity: 0.65;">Tips before using Agent:</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>
</div>
"""

css = """
h1 {
  text-align: center;
  display: block;
}

#duplicate-button {
  margin: auto;
  color: white;
  background: #1565c0;
  border-radius: 100vh;
}
.small-button button {
    font-size: 12px !important;
    padding: 4px 8px !important;
    height: 6px !important;
    width: 4px !important;
}
.gradio-accordion {
    margin-top: 0px !important;
    margin-bottom: 0px !important;
}
"""

chat_css = """
.gr-button { font-size: 20px !important; }  /* Enlarges button icons */
.gr-button svg { width: 32px !important; height: 32px !important; } /* Enlarges SVG icons */
"""

model_name = ''

os.environ["TOKENIZERS_PARALLELISM"] = "false"


question_examples = [
    # ['What is the IC50 values for the drug Abemaciclib in the cell line A549?'],
    ["What's the MoA of the drug Ponatinib on the HCT15 colon cancer cell line? Please synthesize results from the Tahoe-100M dataset, the jump dataset, and the IC50 dataset."],
    ["Natural perturbation: find the disease perturbation that has the similar effect to Glycyrrhizic acid on CVCL_0334? use the result and what you know to explain the mechanism of action."],
    ["Mechanism of action: give me the mechanism of action for drug name Abemaciclib provided by Tahoe."],
    ["Vision scores: what are the top 5 vision scores for cell line A549 and drug name Abemaciclib"]
]

new_tool_files = {
    'new_tool': os.path.join(current_dir, 'data', 'new_tool.json'),
}

config_path = "/home/ubuntu/.lambda_api_config.yaml"
agent = SigSpace(config_path)
# 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(
        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,
    )

    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


def handle_retry(history, retry_data: gr.RetryData, temperature, max_new_tokens, max_tokens, multi_agent, conversation, max_round):
    print("Updated 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), ""
    else:
        return gr.update(visible=False), "Incorrect password, try again!"


conversation_state = gr.State([])

# Gradio block
chatbot = gr.Chatbot(height=400, placeholder=PLACEHOLDER,
                     label='SigSpace', type="messages",  show_copy_button=True)

with gr.Blocks(css=css) as demo:
    gr.Markdown(DESCRIPTION)
    # gr.Markdown(INTRO)
    gr.Image(value=display_image(img_path), label="", show_label=False, height=600, width=600)
    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)

    gr.ChatInterface(
        fn=agent.run_gradio_chat,
        chatbot=chatbot,
        fill_height=False, fill_width=False, 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 X", 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,
    )

    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"
        )
        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.Markdown(LICENSE)


if __name__ == "__main__":
    demo.launch(share=True)