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import streamlit as st
from task_operations import TaskManager
from task_visualization import TaskVisualizer
from llm_part import get_task_advice # Import the LLM advice function
import pandas as pd
from datetime import datetime
def main():
st.title("Daily Task Tracker")
task_manager = TaskManager()
visualizer = TaskVisualizer()
# Ensure tasks are loaded from the database into session state
if 'tasks' not in st.session_state:
st.session_state.tasks = task_manager.load_tasks()
# Task input fields
task_name = st.text_input("Task Name")
task_time = st.time_input("Task Time")
task_duration_hours = st.number_input("Task Duration (Hours)", min_value=0, step=1, format="%d")
task_duration_minutes = st.number_input("Task Duration (Minutes)", min_value=0, max_value=59, step=1, format="%d")
task_category = st.selectbox("Task Category", TaskManager.CATEGORIES)
# Create a button to add the task
if st.button("Add Task"):
# Add the task to the task manager
task_manager.add_task(task_name, task_time, task_duration_hours, task_duration_minutes, task_category)
st.success(f"Task '{task_name}' added!")
# Get advice from both LLMs
advice_gemini, advice_llama = get_task_advice(task_name, task_category, task_duration_hours, task_duration_minutes)
# Store the responses in session state
st.session_state.advice_gemini = advice_gemini
st.session_state.advice_llama = advice_llama
# Create tabs for LLM advice display
tab1, tab2 = st.tabs(["Gemini LLM", "Llama LLM"])
with tab1:
st.header("Gemini LLM")
st.write("**Gemini Advice:**")
st.write(st.session_state.advice_gemini)
with tab2:
st.header("Llama LLM")
st.write("**Llama Advice:**")
st.write(st.session_state.advice_llama)
# Display tasks for today only
if st.session_state.tasks:
st.write("Today's Tasks:")
# Convert session tasks to DataFrame and filter tasks for today
df = pd.DataFrame(st.session_state.tasks)
df['Task Time'] = pd.to_datetime(df['Task Time'])
today_tasks = df[df['Task Time'].dt.date == datetime.today().date()]
if not today_tasks.empty:
st.table(today_tasks[['Task ID', 'Task Name', 'Task Time', 'Task Duration (hours)',
'Task Duration (minutes)', 'Category']])
else:
st.write("No tasks for today.")
# Task deletion option by ID
task_id_to_delete = st.number_input("Enter Task ID to Delete", min_value=0, step=1)
if st.button("Delete Task by ID"):
if task_manager.delete_task_by_id(task_id_to_delete):
st.success(f"Task with ID '{task_id_to_delete}' deleted!")
else:
st.error(f"Task with ID '{task_id_to_delete}' not found.")
# Report options and other visualizations remain unchanged
if st.button("Daily Report"):
report = task_manager.generate_report('daily')
if not report.empty:
st.write("Daily Report:")
st.dataframe(report)
visualizer.plot_category_performance('daily', task_manager)
else:
st.warning("No tasks for today.")
if st.button("Weekly Report"):
report = task_manager.generate_report('weekly')
if not report.empty:
st.write("Weekly Report:")
st.dataframe(report)
visualizer.plot_category_performance('weekly', task_manager)
else:
st.warning("No tasks for this week.")
if st.button("Monthly Report"):
report = task_manager.generate_report('monthly')
if not report.empty:
st.write("Monthly Report:")
st.dataframe(report)
visualizer.plot_category_performance('monthly', task_manager)
else:
st.warning("No tasks for this month.")
if st.button("Yearly Report"):
report = task_manager.generate_report('yearly')
if not report.empty:
st.write("Yearly Report:")
st.dataframe(report)
visualizer.plot_category_performance('yearly', task_manager)
else:
st.warning("No tasks for this year.")
# Performance visualizations
visualizer.plot_performance()
visualizer.plot_overall_category_performance()
# Option to download the report
visualizer.download_report()
if __name__ == "__main__":
main() |