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from shiny import ui, reactive, render, App | |
from chemcrow.agents import ChemCrow | |
import asyncio | |
import shinyswatch | |
chem_model = ChemCrow(model="gpt-4-0613", temp=0.1, verbose=True) | |
app_ui = ui.page_fluid( | |
shinyswatch.theme.slate(), | |
ui.panel_title("ChemCrow UI"), | |
ui.p("An experiment with Shiny for Python and ChemCrow"), | |
ui.br(), | |
ui.row( | |
ui.column(9, ui.input_text("prompt", label=None, placeholder="E.g., What is the molecular weight of tylenol?", width="100%")), | |
ui.column(3, ui.input_action_button("chat", "Chat", class_="btn btn-primary btn-lg btn-block", width="100%"),) | |
), | |
ui.output_text("txt"), | |
ui.output_ui("prompt_ui"), | |
ui.output_ui("result"), | |
ui.hr(), | |
ui.div( | |
{"style": "align-items: center; display: flex; flex-direction: column; justify-content: center;"}, | |
ui.img(src="https://github.com/ur-whitelab/chemcrow-public/raw/main/assets/chemcrow_dark_thin.png", width="400px") | |
), | |
ui.br(), | |
ui.markdown(f'ChemCrow was [introduced](https://arxiv.org/abs/2304.05376) by Bran, Andres M., et al. "ChemCrow: Augmenting large-language models with chemistry tools." arXiv preprint arXiv:2304.05376 (2023). This tool is an extension of that work that puts the code into an interactive web app created by [James Wade](https://jameshwade.com) using [Shiny for Python](https://shiny.posit.co/py/). Find the code for the app [here](https://github.com/jameshwade/chemcrow) and the original code [here](https://github.com/ur-whitelab/chemcrow-public).') | |
) | |
def server(input, output, session): | |
def _(): | |
if input.chat(): | |
ui.update_text("prompt", value="") | |
def prompt_ui(): | |
list_ui = [ui.strong("Prompt"), | |
ui.markdown(input.prompt())] | |
return list_ui | |
# triggered when the "Chat" button is clicked | |
async def result(): | |
ui.notification_show("Chatting with ChemCrow...", type="message") | |
try: | |
response = await asyncio.to_thread(chem_model.run, input.prompt()) | |
list_ui = [ui.strong("Thoughts"), | |
ui.markdown(response[0]), | |
ui.strong("Reasoning"), | |
ui.markdown(response[1]), | |
ui.strong("Answer"), | |
ui.markdown(response[2])] | |
return list_ui | |
except TypeError: | |
async def error_coro(): | |
return "An error occurred while processing your request." | |
return await error_coro() | |
app = App(app_ui, server, debug=True) |