Maharshi Gor
Enhance model provider detection and add repository management script. Added support for multi step agent.
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import datasets
import gradio as gr
from apscheduler.schedulers.background import BackgroundScheduler
from huggingface_hub import snapshot_download
from components.quizbowl.bonus import BonusInterface
from components.quizbowl.tossup import TossupInterface
from display.custom_css import css_pipeline, css_tossup
# Constants
from src.envs import (
API,
AVAILABLE_MODELS,
DEFAULT_SELECTIONS,
EVAL_REQUESTS_PATH,
EVAL_RESULTS_PATH,
PLAYGROUND_DATASET_NAMES,
QUEUE_REPO,
REPO_ID,
RESULTS_REPO,
THEME,
TOKEN,
)
from workflows import factory
def restart_space():
API.restart_space(repo_id=REPO_ID)
### Space initialisation
try:
print(EVAL_REQUESTS_PATH)
snapshot_download(
repo_id=QUEUE_REPO,
local_dir=EVAL_REQUESTS_PATH,
repo_type="dataset",
tqdm_class=None,
etag_timeout=30,
token=TOKEN,
)
except Exception:
restart_space()
try:
print(EVAL_RESULTS_PATH)
snapshot_download(
repo_id=RESULTS_REPO,
local_dir=EVAL_RESULTS_PATH,
repo_type="dataset",
tqdm_class=None,
etag_timeout=30,
token=TOKEN,
)
except Exception:
restart_space()
js_preamble = """
<link href="https://fonts.cdnfonts.com/css/roboto-mono" rel="stylesheet">
<script>
const gradioApp = document.getElementsByTagName('gradio-app')[0];
console.log("Gradio app:", gradioApp);
console.log(gradioApp.querySelectorAll('.token'));
console.log(document.querySelectorAll('.token'));
// Function to trigger Python callback
const setHiddenIndex = (index) => {
console.log("Setting hidden index to:", index);
const hiddenIndex = gradioApp.querySelector("#hidden-index textarea");
if (hiddenIndex) {
hiddenIndex.value = index;
let event = new Event("input", { bubbles: true});
Object.defineProperty(event, "target", { value: hiddenIndex});
hiddenIndex.dispatchEvent(event);
}
};
// Add event listeners to all tokens
function setupTokenListeners() {
const tokens = gradioApp.querySelectorAll('.token');
console.log("Tokens:", tokens);
tokens.forEach(token => {
token.addEventListener('mouseover', function() {
const index = parseInt(this.getAttribute('data-index'));
console.log("Mouseover token index:", index);
// Reset all tokens
gradioApp.querySelectorAll('.token').forEach(el => {
el.classList.remove('highlighted');
});
// Highlight this token
this.classList.add('highlighted');
// Update the hidden index to trigger the Python callback
setHiddenIndex(index);
});
});
}
console.log("Preamble complete");
document.addEventListener("DOMContentLoaded", function() {
// Setup initial listeners
console.log("DOM fully loaded and parsed");
setupTokenListeners();
// Setup a mutation observer to handle dynamically added tokens
const observer = new MutationObserver(function(mutations) {
mutations.forEach(function(mutation) {
if (mutation.addedNodes.length) {
setupTokenListeners();
}
});
});
// Start observing the token container for changes
const tokenContainer = gradioApp.querySelector('.token-container');
console.log("Token container:", tokenContainer);
if (tokenContainer) {
observer.observe(tokenContainer.parentNode, { childList: true, subtree: true });
}
console.log("Listener setup complete");
});
</script>
"""
def load_dataset(mode: str):
if mode == "tossup":
ds = datasets.load_dataset(PLAYGROUND_DATASET_NAMES["tossup"], split="eval")
ds = ds.filter(lambda x: x["qid"].split("-")[2] == "1" and int(x["qid"].split("-")[3]) <= 10)
elif mode == "bonus":
ds = datasets.load_dataset(PLAYGROUND_DATASET_NAMES["bonus"], split="eval")
ds = ds.filter(lambda x: x["qid"].split("-")[2] == "1" and int(x["qid"].split("-")[3]) <= 10)
else:
raise ValueError(f"Invalid mode: {mode}")
return ds
def main():
tossup_ds = load_dataset("tossup")
bonus_ds = load_dataset("bonus")
app = gr.Blocks(
css=css_pipeline + css_tossup,
head=js_preamble,
theme=THEME,
title="Quizbowl Bot",
)
with app:
with gr.Tabs():
with gr.Tab("Tossup Agents"):
defaults = DEFAULT_SELECTIONS["tossup"] | {
"init_workflow": factory.create_quizbowl_simple_workflow(),
"simple_workflow": False,
}
tossup_interface = TossupInterface(app, tossup_ds, AVAILABLE_MODELS, defaults)
# ModelStepComponent(value=factory.create_quizbowl_simple_step())
with gr.Tab("Bonus Round Agents"):
defaults = DEFAULT_SELECTIONS["bonus"] | {
"init_workflow": factory.create_quizbowl_bonus_simple_workflow(),
"simple_workflow": True,
}
bonus_interface = BonusInterface(app, bonus_ds, AVAILABLE_MODELS, defaults)
app.queue(default_concurrency_limit=40).launch()
if __name__ == "__main__":
scheduler = BackgroundScheduler()
scheduler.add_job(restart_space, "interval", seconds=1800)
scheduler.start()
main()