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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):
@reactive.Effect()
def _():
if input.chat():
ui.update_text("prompt", value="")
@output
@render.ui
@reactive.event(input.chat)
def prompt_ui():
list_ui = [ui.strong("Prompt"),
ui.markdown(input.prompt())]
return list_ui
@output
@render.ui
@reactive.event(input.chat) # 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) |