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# Venus Annotation System | |
# Author: Du Mingzhe ([email protected]) | |
# Date: 2024-09-25 | |
import uuid | |
import streamlit as st | |
import streamlit_ext as ste | |
from code_editor import code_editor | |
from datasets import load_dataset, Dataset | |
st.title(":blue[Venus] Annotation System 🪐") | |
# Step 1: Load the problem set | |
my_bar = st.progress(0, text="Loading the problem set...") | |
my_bar.progress(10, text="Loading [Elfsong/Venus] datasets...") | |
if "raw_ds" not in st.session_state.keys(): | |
st.session_state["raw_ds"] = load_dataset("Elfsong/Venus", "python3") | |
raw_ds = st.session_state["raw_ds"] | |
my_bar.progress(55, text="Loading [Elfsong/venus_case] datasets...") | |
if "case_ds" not in st.session_state.keys(): | |
st.session_state["case_ds"] = load_dataset("Elfsong/venus_case", "python3") | |
case_ds = st.session_state["case_ds"] | |
my_bar.progress(90, text="Filtering out the cases that already exist...") | |
if "candidates" not in st.session_state.keys(): | |
case_ds_ids = set(case_ds['train']['question_id']) | |
candidates = [raw_ds['train'][i] for i in range(len(raw_ds['train'])) if raw_ds['train'][i]['question_id'] not in case_ds_ids] | |
st.session_state["candidates"] = candidates | |
candidates = st.session_state["candidates"] | |
my_bar.progress(100, text="System Initialized Successfully 🚀") | |
# Step 2: Select the problem | |
candidates_dict = {} | |
for candidate in candidates: | |
candidate_name = str(candidate['question_id']) + '.' + str(candidate['name']) + ' [' + str(candidate['difficulty']).upper() + ']' | |
candidates_dict[candidate_name] = candidate | |
option = ste.selectbox("Select a problem here", candidates_dict.keys()) | |
example = candidates_dict[option] | |
tab1, tab2, tab3 = st.tabs(["Problem Description", "Canonical Solution", "Test Cases Generator"]) | |
with tab1: | |
st.html(example['content']) | |
with tab2: | |
solutions_displayed = 0 | |
for solution in example['rt_list']: | |
if "Solution" in solution['code']: | |
st.write(f"Canonical Solution {solutions_displayed + 1}") | |
st.code(solution['code']) | |
solutions_displayed += 1 | |
if solutions_displayed >= 3: | |
break | |
with tab3: | |
editor_buttons = [{ | |
"name": "Submit", | |
"feather": "Play", | |
"primary": True, | |
"hasText": True, | |
"showWithIcon": True, | |
"commands": ["submit"], | |
"style": {"bottom": "0.44rem","right": "0.4rem"} | |
}] | |
predefined_code = "def generate_test_cases():\n\tpass\n\ndef serialize_input():\n\tpass\n\ndef deserialize_input():\n\tpass\n\ndef serialize_output():\n\tpass\n\ndef deserialize_output():\n\tpass" | |
response_dict = code_editor(predefined_code, lang="python", height=20, options={"wrap": False}, buttons=editor_buttons) | |
if response_dict['type'] == 'submit': | |
new_ds = Dataset.from_list([{ | |
"question_id": example['question_id'], | |
"test_case_functions": response_dict['text'], | |
}]) | |
ds_name = str(uuid.uuid1()) | |
new_ds.push_to_hub(f"Elfsong/Venus_Anotation", f'python3-{ds_name}') | |
st.write("Thanks for your contribution! 🌟") | |