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| # src/utils.py | |
| import os | |
| import uuid | |
| import re | |
| import logging | |
| import pandas as pd | |
| import matplotlib.pyplot as plt | |
| import streamlit as st | |
| import time | |
| import json | |
| # Generate a unique image path for saving plots | |
| def generate_unique_image_path(): | |
| figs_dir = os.path.join('tmp', 'figs') | |
| os.makedirs(figs_dir, exist_ok=True) | |
| unique_filename = f'fig_{uuid.uuid4()}.png' | |
| unique_path = os.path.join(figs_dir, unique_filename) | |
| logging.debug(f"Generated unique image path: {unique_path}") | |
| return unique_path | |
| # Function to sanitize input | |
| def sanitize_input(query: str) -> str: | |
| return query.strip() | |
| # Define the function to extract the last Python REPL command | |
| def get_last_python_repl_command(): | |
| import streamlit as st # Ensure Streamlit is imported | |
| if 'intermediate_steps' not in st.session_state: | |
| logging.warning("No intermediate steps found in session state.") | |
| return None | |
| intermediate_steps = st.session_state['intermediate_steps'] | |
| python_repl_commands = [] | |
| for step in intermediate_steps: | |
| action = step[0] | |
| observation = step[1] | |
| if action.get('tool') == 'Python_REPL': | |
| python_repl_commands.append(action) | |
| if python_repl_commands: | |
| last_command_action = python_repl_commands[-1] | |
| command = last_command_action.get('tool_input', '') | |
| logging.debug(f"Extracted last Python REPL command: {command}") | |
| return command | |
| else: | |
| logging.warning("No Python_REPL commands found in intermediate steps.") | |
| return None | |
| def log_history_event(session_data: dict, event_type: str, details: dict): | |
| if "execution_history" not in session_data: | |
| session_data["execution_history"] = [] # fallback | |
| timestamp = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()) | |
| event = { | |
| "type": event_type, | |
| "timestamp": timestamp | |
| } | |
| event.update(details) # merges in content from details | |
| session_data["execution_history"].append(event) | |