make bash venv compilation script with all this data Goals:

    Create an AI-powered writing tool: The script aims to build a desktop application that uses the Groq API (which is similar to OpenAI's API) for text generation. This tool will assist users in writing creative content like novels, screenplays, or short stories.

    Multi-generation output: The application should be able to generate multiple outputs (multiple generations of text) from a single user prompt.

    Sophisticated context management: The tool should maintain a history of the conversation between the user and the AI, using it for context in subsequent generations. It should also include features like:

        Summarization: To handle long conversations, the app should summarize past interactions to stay within the API's token limits.

        Story Elements: Allow the user to manage key story elements (characters, settings, plot points), which can be fed to the AI to improve the coherence of the generated text.

    User-friendly interface: The application will use tkinter, a standard Python library for creating graphical user interfaces.

    Cross-platform compatibility: While the script focuses on macOS, the goal is to create an application that can be easily adapted for other platforms.

Methods:

    Bash scripting: The primary build process uses a bash script for automation.

    Virtual environments (venv): The script uses Python virtual environments to isolate the project's dependencies. This ensures a clean and controlled development and build environment.

    Package management (pip): The script uses pip, the standard Python package installer, to install the necessary libraries.

    GUI framework (tkinter): The application's user interface is built using tkinter.

    AI library (groq): The groq Python library is used to interact with the Groq API for text generation.

    Application packaging (PyInstaller): The script uses PyInstaller to package the Python code, libraries, and other resources into a standalone executable application.

    macOS distribution (DMG): For macOS, the script creates a DMG file, a standard format for distributing applications on the platform.

Key Challenges Addressed:

    API key management: The script avoids hardcoding the API key and instead reads it from an environment variable (GROQ_API_KEY). This improves security and makes the code more portable.

    PyInstaller compatibility: The script uses the --hidden-import flag to ensure that PyInstaller correctly includes all necessary tkinter modules.

    Conversation history and context: The Python code implements a system for managing the conversation history and feeding it to the Groq API, enabling the AI to generate more coherent outputs.

    Summarization: The application includes logic for summarizing long conversations to manage token limits and maintain context.

For Further Improvement:

    Platform-specific packaging: The current script creates a DMG file, which is specific to macOS. For other platforms, you would need to adapt the packaging process (e.g., creating an executable for Windows).

    Error handling: The script includes basic error handling, but it could be more robust.

    User Interface: The tkinter UI can be made more polished and user-friendly. Improve this to be a much more robust app designed for generation of long documents like scripts and novels

Implement a sophisticated mechanism to keep track of all data so the new generations understand what was generated before and that they must continue. But you must do this through clever summarization mechanisms and tagging so that you don't overload the context window of the ai - as you generate more simply copying prior generations will quickly overload token limits - and rudimentary nonspecfic summarization prompting systems will fail to capture nuance - must design much more sophisticated system

Understand api limits and rate calling and also prevent app from getting stuck - it is important that you implement this without wasting the user's time by making them wait for no reason too - a detailed balanced and speed oriented system is preferred

Progress of generations and content of generations should be visually displayed to user in real time - display in gui text window

Ability to export entire generations or a set of generations or single generations as txts during and after running through gui buttons and text windows is preferred.

Implement other useful suggestions to app

#!/bin/bash

set -e

BUILD_DIR="$HOME/Desktop/CustomAIToolBuild"
DESKTOP_DIR="$HOME/Desktop"
APP_NAME="CustomAITool"

mkdir -p "$BUILD_DIR"
python3 -m venv "$BUILD_DIR/venv"
source "$BUILD_DIR/venv/bin/activate"

pip install --upgrade pip
pip install groq PyQt5 pyinstaller markdown

cat << 'EOF' > "$BUILD_DIR/custom_ai_tool_gui.py"
import os, sys, json
from groq import Groq
from PyQt5.QtWidgets import *
from PyQt5.QtCore import
from PyQt5.QtGui import
import markdown

DEFAULT_MODEL = "llama-3.1-70b-versatile"
DEFAULT_API_KEY = "your key here"

class AIThread(QThread):
response_ready = pyqtSignal(str)
error_occurred = pyqtSignal(str)

def init(self, api_key, messages, model):
super().init()
self.api_key, self.messages, self.model = api_key, messages, model

def run(self):
try:
client = Groq(api_key=self.api_key)
chat_completion = client.chat.completions.create(messages=self.messages, model=self.model)
self.response_ready.emit(chat_completion.choices[0].message.content)
except Exception as e:
self.error_occurred.emit(str(e))

class OptionsDialog(QDialog):
def init(self, current_api_key, current_model, current_font_size, current_copy_raw, parent=None):
super().init(parent)
self.setWindowTitle("Options")
layout = QVBoxLayout(self)

self.api_key_input = QLineEdit(current_api_key)
self.api_key_input.setEchoMode(QLineEdit.Password)
layout.addWidget(QLabel("API Key:"))
layout.addWidget(self.api_key_input)

self.model_combo = QComboBox()
self.model_combo.addItems(["llama-3.1-70b-versatile", "llama-3.1-405b-reasoning", "llama-3.1-8b-instant", "Custom"])
self.model_combo.setCurrentText(current_model)
layout.addWidget(QLabel("Select Model:"))
layout.addWidget(self.model_combo)

self.custom_model_input = QLineEdit()
self.custom_model_input.setPlaceholderText("Enter custom model name")
self.custom_model_input.setEnabled(False)
layout.addWidget(self.custom_model_input)

self.model_combo.currentTextChanged.connect(lambda text: self.custom_model_input.setEnabled(text == "Custom"))

self.font_size_spinner = QSpinBox()
self.font_size_spinner.setRange(8, 24)
self.font_size_spinner.setValue(current_font_size)
layout.addWidget(QLabel("Font Size:"))
layout.addWidget(self.font_size_spinner)

self.copy_raw_checkbox = QCheckBox("Copy Raw Text (Disable Formatting)")
self.copy_raw_checkbox.setChecked(current_copy_raw)
layout.addWidget(self.copy_raw_checkbox)

buttons = QDialogButtonBox(QDialogButtonBox.Ok | QDialogButtonBox.Cancel)
buttons.accepted.connect(self.accept)
buttons.rejected.connect(self.reject)
layout.addWidget(buttons)

def get_values(self):
model = self.custom_model_input.text() if self.model_combo.currentText() == "Custom" else self.model_combo.currentText()
return (self.api_key_input.text(), model, self.font_size_spinner.value(), self.copy_raw_checkbox.isChecked())

class CustomAITool(QWidget):
def init(self):
super().init()
self.config_file = os.path.join(os.path.dirname(sys.executable), "config.json")
self.prompt_file = os.path.join(os.path.dirname(sys.executable), "saved_prompt.json")
self.create_default_files()
self.load_config()
self.prompt = self.load_prompt()
self.conversation_history = []
self.initUI()

def create_default_files(self):
if not os.path.exists(self.config_file):
with open(self.config_file, 'w') as f:
json.dump({"api_key": DEFAULT_API_KEY, "model": DEFAULT_MODEL, "font_size": 12, "copy_raw": False}, f)
if not os.path.exists(self.prompt_file):
with open(self.prompt_file, 'w') as f:
json.dump({"prompt": "You are a helpful AI assistant."}, f)

def load_config(self):
try:
with open(self.config_file, 'r') as f:
config = json.load(f)
self.api_key = config.get("api_key", DEFAULT_API_KEY)
self.model = config.get("model", DEFAULT_MODEL)
self.font_size = config.get("font_size", 12)
self.copy_raw = config.get("copy_raw", False)
except Exception as e:
self.show_error("Error loading config", str(e))
self.api_key, self.model, self.font_size, self.copy_raw = DEFAULT_API_KEY, DEFAULT_MODEL, 12, False

def save_config(self):
try:
with open(self.config_file, 'w') as f:
json.dump({"api_key": self.api_key, "model": self.model, "font_size": self.font_size, "copy_raw": self.copy_raw}, f)
except Exception as e:
self.show_error("Error saving config", str(e))

def show_options_dialog(self):
dialog = OptionsDialog(self.api_key, self.model, self.font_size, self.copy_raw, self)
if dialog.exec_() == QDialog.Accepted:
self.api_key, self.model, self.font_size, self.copy_raw = dialog.get_values()
self.save_config()
self.update_font_size()
self.show_notification("Settings Updated", "Your settings have been updated successfully.")

def update_font_size(self):
font = self.conversation_display.font()
font.setPointSize(self.font_size)
self.conversation_display.setFont(font)

def initUI(self):
layout = QVBoxLayout(self)

toolbar = QHBoxLayout()
for button_text, func in [('Options', self.show_options_dialog), ('New Prompt', self.new_prompt), ('Clear History', self.clear_history)]:
button = QPushButton(button_text)
button.clicked.connect(func)
toolbar.addWidget(button)
layout.addLayout(toolbar)

self.conversation_display = QTextEdit()
self.conversation_display.setReadOnly(True)
self.update_font_size()
layout.addWidget(self.conversation_display)

copy_buttons = QHBoxLayout()
for button_text, func in [('Copy Last Message', self.copy_last_message), ('Copy Conversation', self.copy_conversation)]:
button = QPushButton(button_text)
button.clicked.connect(func)
copy_buttons.addWidget(button)
layout.addLayout(copy_buttons)

input_layout = QHBoxLayout()
self.input_edit = QLineEdit()
self.input_edit.setPlaceholderText("Enter your message here and press Enter or click Send")
self.input_edit.returnPressed.connect(self.send_message)
self.send_button = QPushButton('Send')
self.send_button.clicked.connect(self.send_message)
input_layout.addWidget(self.input_edit)
input_layout.addWidget(self.send_button)
layout.addLayout(input_layout)

self.setWindowTitle('Custom AI Tool')
self.resize(800, 600)

def load_prompt(self):
try:
with open(self.prompt_file, 'r') as f:
return json.load(f).get("prompt", "You are a helpful AI assistant.")
except Exception as e:
self.show_error("Error loading prompt", str(e))
return "You are a helpful AI assistant."

def save_prompt(self, prompt):
try:
with open(self.prompt_file, 'w') as f:
json.dump({"prompt": prompt}, f)
except Exception as e:
self.show_error("Error saving prompt", str(e))

def new_prompt(self):
prompt, ok = QInputDialog.getMultiLineText(self, 'New Prompt', 'Enter your new prompt:', self.prompt)
if ok:
self.prompt = prompt
self.save_prompt(prompt)
self.clear_history()
self.show_notification("Success", "New prompt saved and conversation history cleared.")

def clear_history(self):
self.conversation_history = []
self.conversation_display.clear()
self.conversation_display.append("Conversation history cleared. Start a new conversation!")

def copy_last_message(self):
if self.conversation_history:
self.copy_to_clipboard(self.conversation_history[-1]['content'])

def copy_conversation(self):
if self.conversation_history:
conversation = "\n\n".join([f"{msg['role'].capitalize()}: {msg['content']}" for msg in self.conversation_history])
self.copy_to_clipboard(conversation)

def copy_to_clipboard(self, text):
try:
clipboard = QApplication.clipboard()
if self.copy_raw:
clipboard.setText(text)
else:
html = markdown.markdown(text)
mime_data = QMimeData()
mime_data.setHtml(html)
mime_data.setText(text)
clipboard.setMimeData(mime_data)
except Exception as e:
self.show_error("Error copying to clipboard", str(e))

def show_notification(self, title, message):
QMessageBox.information(self, title, message)

def show_error(self, title, message):
QMessageBox.critical(self, title, message)

def send_message(self):
user_input = self.input_edit.text().strip()
if not user_input or not self.api_key:
return
self.conversation_history.append({"role": "user", "content": user_input})
self.conversation_display.append(f"<b>You:</b> {user_input}")
self.input_edit.clear()
full_conversation = [{"role": "system", "content": self.prompt}] + self.conversation_history
self.send_button.setEnabled(False)
self.input_edit.setEnabled(False)
self.ai_thread = AIThread(self.api_key, full_conversation, self.model)
self.ai_thread.response_ready.connect(self.handle_ai_response)
self.ai_thread.error_occurred.connect(self.handle_error)
self.ai_thread.start()

def handle_ai_response(self, ai_response):
try:
self.conversation_history.append({"role": "assistant", "content": ai_response})
formatted_response = markdown.markdown(ai_response)
self.conversation_display.append(f"<b>AI:</b> {formatted_response}")
self.conversation_display.verticalScrollBar().setValue(self.conversation_display.verticalScrollBar().maximum())
except Exception as e:
self.show_error("Error handling AI response", str(e))
finally:
self.send_button.setEnabled(True)
self.input_edit.setEnabled(True)
self.input_edit.setFocus()

def handle_error(self, error_message):
self.show_error("AI Error", f"An error occurred: {error_message}")
self.send_button.setEnabled(True)
self.input_edit.setEnabled(True)
self.input_edit.setFocus()

if name == 'main':
app = QApplication(sys.argv)
ex = CustomAITool()
ex.show()
sys.exit(app.exec_())
EOF

cat << EOF > "$BUILD_DIR/custom_ai_tool.spec"
# -- mode: python ; coding: utf-8 --

block_cipher = None

a = Analysis(['custom_ai_tool_gui.py'],
pathex=['$BUILD_DIR'],
binaries=[],
datas=[],
hiddenimports=[],
hookspath=[],
runtime_hooks=[],
excludes=[],
win_no_prefer_redirects=False,
win_private_assemblies=False,
cipher=block_cipher,
noarchive=False)
pyz = PYZ(a.pure, a.zipped_data,
cipher=block_cipher)
exe = EXE(pyz,
a.scripts,
[],
exclude_binaries=True,
name='CustomAITool',
debug=False,
bootloader_ignore_signals=False,
strip=False,
upx=True,
console=False )
coll = COLLECT(exe,
a.binaries,
a.zipfiles,
a.datas,
strip=False,
upx=True,
upx_exclude=[],
name='CustomAITool')
app = BUNDLE(coll,
name='CustomAITool.app',
icon=None,
bundle_identifier=None)
EOF

echo '{
"api_key": "your key here",
"model": "llama-3.1-70b-versatile",
"font_size": 12,
"copy_raw": false
}' > "$BUILD_DIR/config.json"

echo '{
"prompt": "You are a helpful AI assistant."
}' > "$BUILD_DIR/saved_prompt.json"

pyinstaller "$BUILD_DIR/custom_ai_tool.spec"

mkdir -p "$BUILD_DIR/dist/CustomAITool.app/Contents/MacOS"
cp "$BUILD_DIR/config.json" "$BUILD_DIR/dist/CustomAITool.app/Contents/MacOS/"
cp "$BUILD_DIR/saved_prompt.json" "$BUILD_DIR/dist/CustomAITool.app/Contents/MacOS/"

mv "$BUILD_DIR/dist/CustomAITool.app" "$DESKTOP_DIR/"

deactivate

echo "CustomAITool.app has been created on your Desktop at $DESKTOP_DIR/CustomAITool.app"
echo "The app includes default config.json and saved_prompt.json files."
echo "You can now manually remove the build directo"

To enhance your application for generating long documents like scripts and novels, while efficiently managing the AI's context window and ensuring responsiveness, you can implement the following improvements:

1. Sophisticated Data Tracking and Summarization Mechanism
2. API Rate Limit Management and Error Handling
3. Real-Time Visual Display of Generation Progress
4. Exporting Generations Functionality
5. Additional Useful Features
# Configuration
APP_NAME="FlatFolderExtractor"
VENV_NAME="venv_$APP_NAME"
DESKTOP_PATH="$HOME/Desktop"
WORK_DIR="$DESKTOP_PATH/${APP_NAME}_Build"
DMG_FILE="$DESKTOP_PATH/${APP_NAME}.dmg"

# Error handling function
handle_error() {
echo "Error: $1"
exit 1
}

# Create and set up working directory
mkdir -p "$WORK_DIR" || handle_error "Failed to create working directory"
cd "$WORK_DIR" || handle_error "Failed to change to working directory"

# Create and activate virtual environment
python3 -m venv "$VENV_NAME" || handle_error "Failed to create virtual environment"
source "$VENV_NAME/bin/activate" || handle_error "Failed to activate virtual environment"

# Upgrade pip and install required packages
pip install --upgrade pip || handle_error "Failed to upgrade pip"
pip install PyQt5 pyinstaller || handle_error "Failed to install required packages"

# Create the main Python script
cat << 'EOF' > flat_folder_extractor.py
import sys
import os
import shutil
import random
import string
import traceback
from PyQt5.QtWidgets import (QApplication, QMainWindow, QWidget, QVBoxLayout, QHBoxLayout,
QPushButton, QLabel, QFileDialog, QCheckBox, QMessageBox,
QProgressBar, QPlainTextEdit)
from PyQt5.QtCore import Qt, QThread, pyqtSignal

class ExtractionThread(QThread):
progress = pyqtSignal(int)
status = pyqtSignal(str)
error = pyqtSignal(str)
finished = pyqtSignal()

def init(self, input_folder, output_folder, restrictions):
super().init()
self.input_folder = input_folder
self.output_folder = output_folder
self.restrictions = restrictions
self.total_files = 0
self.processed_files = 0

def run(self):
try:
self.total_files = sum([len(files) for _, , files in os.walk(self.input_folder)])
self.extract_files(self.input_folder)
self.finished.emit()
except Exception as e:
self.error.emit(str(e))

def extract_files(self, src):
for root, , files in os.walk(src):
for file in files:
src_path = os.path.join(root, file)
if self.should_copy_file(file):
try:
dst_path = os.path.join(self.output_folder, file)
# Handle filename conflicts
counter = 1
while os.path.exists(dst_path):
name, ext = os.path.splitext(file)
dst_path = os.path.join(self.output_folder, f"{name}{counter}{ext}")
counter += 1
shutil.copy2(src_path, dst_path)
self.processed_files += 1
self.progress.emit(int(self.processed_files / self.total_files * 100))
self.status.emit(f"Copied: {file}")
except Exception as e:
self.error.emit(f"Failed to copy {file}: {str(e)}")

def should_copy_file(self, filename):
if not self.restrictions:
return True
ext = os.path.splitext(filename)[1].lower()
return ext in self.restrictions

class FlatFolderExtractorGUI(QMainWindow):
def init(self):
super().init()
self.initUI()

def initUI(self):
self.setWindowTitle("Flat Folder Extractor")
self.setGeometry(100, 100, 600, 400)

central_widget = QWidget()
self.setCentralWidget(central_widget)
layout = QVBoxLayout(central_widget)

self.input_button = QPushButton("Select Input Folder", self)
self.input_button.clicked.connect(self.select_input_folder)
layout.addWidget(self.input_button)

self.input_label = QLabel("No folder selected", self)
layout.addWidget(self.input_label)

checkbox_layout = QHBoxLayout()
self.pdf_checkbox = QCheckBox("Restrict to PDF", self)
self.docx_checkbox = QCheckBox("Restrict to DOCX", self)
self.xlsx_checkbox = QCheckBox("Restrict to XLSX", self)
self.image_checkbox = QCheckBox("Restrict to images", self)
checkbox_layout.addWidget(self.pdf_checkbox)
checkbox_layout.addWidget(self.docx_checkbox)
checkbox_layout.addWidget(self.xlsx_checkbox)
checkbox_layout.addWidget(self.image_checkbox)
layout.addLayout(checkbox_layout)

self.extract_button = QPushButton("Extract", self)
self.extract_button.clicked.connect(self.extract_folders)
layout.addWidget(self.extract_button)

self.progress_bar = QProgressBar(self)
layout.addWidget(self.progress_bar)

self.status_text = QPlainTextEdit(self)
self.status_text.setReadOnly(True)
layout.addWidget(self.status_text)

self.input_folder = ""
self.output_folder = ""

def select_input_folder(self):
self.input_folder = QFileDialog.getExistingDirectory(self, "Select Input Folder")
if self.input_folder:
self.input_label.setText(self.input_folder)
else:
self.input_label.setText("No folder selected")

def extract_folders(self):
if not self.input_folder:
QMessageBox.warning(self, "Error", "Please select an input folder first.")
return

restrictions = []
if self.pdf_checkbox.isChecked(): restrictions.append('.pdf')
if self.docx_checkbox.isChecked(): restrictions.append('.docx')
if self.xlsx_checkbox.isChecked(): restrictions.append('.xlsx')
if self.image_checkbox.isChecked(): restrictions.extend(['.png', '.jpg', '.jpeg'])

random_string = ''.join(random.choices(string.digits, k=5))
self.output_folder = os.path.join(os.path.expanduser("~/Desktop"), random_string)
try:
os.makedirs(self.output_folder, exist_ok=True)
except Exception as e:
QMessageBox.critical(self, "Error", f"Failed to create output folder: {str(e)}")
return

self.extraction_thread = ExtractionThread(self.input_folder, self.output_folder, restrictions)
self.extraction_thread.progress.connect(self.update_progress)
self.extraction_thread.status.connect(self.update_status)
self.extraction_thread.error.connect(self.show_error)
self.extraction_thread.finished.connect(self.extraction_finished)
self.extraction_thread.start()

self.extract_button.setEnabled(False)
self.status_text.clear()
self.status_text.appendPlainText("Extraction started...")

def update_progress(self, value):
self.progress_bar.setValue(value)

def update_status(self, message):
self.status_text.appendPlainText(message)

def show_error(self, error_message):
self.status_text.appendPlainText(f"Error: {error_message}")

def extraction_finished(self):
self.extract_button.setEnabled(True)
self.status_text.appendPlainText("Extraction complete!")
QMessageBox.information(self, "Extraction Complete", f"Files have been extracted to the folder '{self.output_folder}' on your desktop.")

def closeEvent(self, event):
if hasattr(self, 'extraction_thread') and self.extraction_thread.isRunning():
reply = QMessageBox.question(self, 'Exit', "Extraction is still in progress. Are you sure you want to quit?",
QMessageBox.Yes | QMessageBox.No, QMessageBox.No)
if reply == QMessageBox.Yes:
self.extraction_thread.terminate()
self.extraction_thread.wait()
else:
event.ignore()
return
event.accept()

if name == 'main':
app = QApplication(sys.argv)
ex = FlatFolderExtractorGUI()
ex.show()
sys.exit(app.exec())
EOF

# Create the PyInstaller spec file
cat << EOF > flat_folder_extractor.spec
# -- mode: python ; coding: utf-8 --

block_cipher = None

a = Analysis(['flat_folder_extractor.py'],
pathex=['$WORK_DIR'],
binaries=[],
datas=[],
hiddenimports=[],
hookspath=[],
hooksconfig={},
runtime_hooks=[],
excludes=[],
win_no_prefer_redirects=False,
win_private_assemblies=False,
cipher=block_cipher,
noarchive=False)

pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher)

exe = EXE(pyz,
a.scripts,
[],
exclude_binaries=True,
name='FlatFolderExtractor',
debug=False,
bootloader_ignore_signals=False,
strip=False,
upx=True,
console=False,
disable_windowed_traceback=False,
target_arch=None,
codesign_identity=None,
entitlements_file=None )

coll = COLLECT(exe,
a.binaries,
a.zipfiles,
a.datas,
strip=False,
upx=True,
upx_exclude=[],
name='FlatFolderExtractor')

app = BUNDLE(coll,
name='Flat Folder Extractor.app',
icon=None,
bundle_identifier=None)
EOF

# Build the application using PyInstaller
pyinstaller flat_folder_extractor.spec || handle_error "Failed to build the application"

# Create a temporary DMG
TEMP_DMG="$WORK_DIR/temp.dmg"
hdiutil create -volname "Flat Folder Extractor" -srcfolder "dist/Flat Folder Extractor.app" -ov -format UDRW "$TEMP_DMG" || handle_error "Failed to create temporary DMG"

# Mount the temporary DMG
MOUNT_DIR="/Volumes/Flat Folder Extractor"
hdiutil attach -readwrite -noverify -noautoopen "$TEMP_DMG" || handle_error "Failed to mount temporary DMG"

# Wait for the mount to complete
sleep 5

# Create a symbolic link to the Applications folder
ln -s /Applications "$MOUNT_DIR/Applications" || handle_error "Failed to create Applications symlink"

# Unmount the temporary DMG
hdiutil detach "$MOUNT_DIR" || handle_error "Failed to unmount temporary DMG"

# Convert the temporary DMG to the final compressed DMG
hdiutil convert "$TEMP_DMG" -format UDZO -o "$DMG_FILE" || handle_error "Failed to create final DMG"

# Remove the temporary DMG
rm "$TEMP_DMG" || handle_error "Failed to remove temporary DMG"

# Clean up
cd "$DESKTOP_PATH" || handle_error "Failed to change to desktop directory"
rm -rf "$WORK_DIR" || handle_error "Failed to remove working directory"

echo "Flat Folder Extractor application has been created successfully!"
echo "You can find the DMG file at: $DMG_FILE"

# Deactivate virtual environment
deactivate