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codemath_app.py
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224 lines (199 loc) · 8.54 KB
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import os
import time
import pandas as pd
import streamlit as st
from codemath_solver.crawl.core import CodeMathCrawler
from codemath_solver.utils.select_problems import get_filtered_problems
from conf import codemath_settings
class CodeMathSolverApp:
def __init__(self):
self.CSV_FILE = codemath_settings.CODEMATH_CSV_FILE
self.crawler = CodeMathCrawler()
self.agent = None # Initialize agent lazily when needed
self.init_session_state()
# Title is set by the main app
def init_session_state(self):
if "selected_problems" not in st.session_state:
st.session_state.selected_problems = []
if "data_loaded" not in st.session_state:
st.session_state.data_loaded = os.path.exists(self.CSV_FILE)
if "df" not in st.session_state:
st.session_state.df = None
def crawl_section(self):
st.header("1. Crawl Problems")
if st.button("Start Crawling"):
with st.spinner("🏃♂️ Crawling problems... Please wait."):
self.crawler.run()
st.session_state.data_loaded = True
st.session_state.df = None
st.rerun()
def load_data(self):
try:
df = pd.read_csv(self.CSV_FILE, skipinitialspace=True)
df.columns = df.columns.str.strip()
if "ac-rate" in df.columns:
df["ac-rate"] = (
df["ac-rate"]
.astype(str)
.str.strip()
.str.replace(",", ".")
.str.rstrip("%")
)
df["ac-rate"] = pd.to_numeric(df["ac-rate"], errors="coerce")
if "category" in df.columns:
df["category"] = df["category"].str.strip()
if "problem-code" in df.columns:
df["problem-code"] = df["problem-code"].str.strip()
if "solved" not in df.columns:
st.warning(
"Column 'solved' not found in CSV. Filtering by solved status disabled."
)
df["solved"] = -1
if "users" not in df.columns:
st.warning(
"Column 'users' not found in CSV. Sorting by users disabled."
)
df["users"] = 0
st.session_state.df = df
except Exception as e:
st.error(f"Error loading or processing {self.CSV_FILE}: {e}")
st.session_state.data_loaded = False
def selection_section(self):
st.header("2. Select Problems")
if not st.session_state.data_loaded:
st.warning(
f"'{self.CSV_FILE}' not found. Please run the crawling step first."
)
return
if st.session_state.df is None:
self.load_data()
if st.session_state.df is not None:
df = st.session_state.df
st.dataframe(df.head())
categories = ["Any", "Cơ bản", "Nâng cao", "Vận dụng linh hoạt"]
sort_options = ["ac-rate", "users"]
if "ac-rate" not in df.columns or df["ac-rate"].isnull().all():
if "ac-rate" in sort_options:
sort_options.remove("ac-rate")
if "users" not in df.columns:
if "users" in sort_options:
sort_options.remove("users")
if not sort_options:
st.warning("No valid columns available for sorting.")
col1, col2, col3, col4 = st.columns(4)
with col1:
solved_options = {"Unsolved": -1, "Unfinished": 0, "Solved": 1}
if "solved" in df.columns and set(df["solved"].unique()).issubset(
{0, 1, -1, None}
):
selected_solved_label = st.radio(
"Solved Status:", list(solved_options.keys()), index=0
)
filter_solved = solved_options[selected_solved_label]
else:
filter_solved = -1
with col2:
selected_category = st.selectbox("Category:", categories)
filter_category = (
None if selected_category == "Any" else selected_category
)
with col3:
if sort_options:
selected_sort = st.selectbox("Sort by:", sort_options)
sort_ascending = st.checkbox("Ascending", value=True)
else:
selected_sort = "ac-rate"
sort_ascending = True
with col4:
limit = st.number_input("Limit (0 for all):", min_value=0, value=10)
if st.button("Apply Filters"):
problems, filtered_df = get_filtered_problems(
self.CSV_FILE,
solved=filter_solved,
category=filter_category,
sort_by=selected_sort,
ascending=sort_ascending,
limit=limit,
)
st.session_state.selected_problems = problems
st.success(f"Found {len(problems)} problems matching your criteria.")
st.dataframe(filtered_df)
# Clear selection button
if st.session_state.selected_problems:
if st.button("Clear Selection"):
st.session_state.selected_problems = []
st.rerun()
def processing_section(self):
st.header("3. Process Selected Problems")
if not st.session_state.selected_problems:
st.info("No problems selected yet. Please use the selection step above.")
return
st.write(
f"Ready to process {len(st.session_state.selected_problems)} selected problems:"
)
st.dataframe(
pd.DataFrame(st.session_state.selected_problems, columns=["Problem Code"])
)
# Parallel processing options
col1, col2 = st.columns(2)
with col1:
use_parallel = st.checkbox(
"Use Parallel Processing",
value=st.session_state.get("parallel_processing", False),
help="Enable multi-processing for faster execution",
)
with col2:
if use_parallel:
max_workers = st.slider(
"Number of Workers",
min_value=1,
max_value=4,
value=st.session_state.get("max_workers", 2),
help="Number of parallel processes",
)
else:
max_workers = 1
if st.button("Start Processing"):
with st.spinner("Processing selected problems... This may take a while."):
try:
if use_parallel and max_workers > 1:
# Use parallel processing
from codemath_solver.agent.tools import run_parallel_processing
st.info(
f"🚀 Starting parallel processing with {max_workers} workers..."
)
start_time = time.time()
run_parallel_processing(
st.session_state.selected_problems, max_workers
)
end_time = time.time()
st.success(
f"✅ Parallel processing completed in {end_time - start_time:.2f} seconds!"
)
else:
# Use sequential processing
if self.agent is None:
from codemath_solver.agent.tools import CodeMathAgent
self.agent = CodeMathAgent()
if self.agent.process_problems(
st.session_state.selected_problems
):
st.success("Processing script finished.")
else:
st.error("Processing script failed.")
except Exception as e:
st.error(f"Error during processing: {e}")
st.exception(e)
def cleanup(self):
if self.agent and hasattr(self.agent, "driver"):
self.agent.driver.quit()
def run(self):
try:
self.crawl_section()
self.selection_section()
self.processing_section()
finally:
self.cleanup()
if __name__ == "__main__":
app = CodeMathSolverApp()
app.run()