working baseline
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261
simple_generate.py
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261
simple_generate.py
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#!/usr/bin/env python3
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"""
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Simple Daily Journal Prompt Generator
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A lightweight version without rich dependency.
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"""
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import os
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import json
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import sys
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import argparse
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from datetime import datetime
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from typing import List, Dict, Any
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from openai import OpenAI
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from dotenv import load_dotenv
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class SimplePromptGenerator:
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"""Simple version without rich dependency."""
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def __init__(self, config_path: str = ".env"):
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"""Initialize the generator with configuration."""
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self.config_path = config_path
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self.client = None
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self.historic_prompts = []
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self.prompt_template = ""
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# Load configuration
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self._load_config()
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# Load data files
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self._load_prompt_template()
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self._load_historic_prompts()
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def _load_config(self):
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"""Load configuration from environment file."""
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load_dotenv(self.config_path)
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# Get API key
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self.api_key = os.getenv("DEEPSEEK_API_KEY") or os.getenv("OPENAI_API_KEY")
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if not self.api_key:
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print("Error: No API key found in .env file")
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print("Please add DEEPSEEK_API_KEY or OPENAI_API_KEY to your .env file")
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sys.exit(1)
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# Get API base URL (default to DeepSeek)
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self.base_url = os.getenv("API_BASE_URL", "https://api.deepseek.com")
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# Get model (default to deepseek-chat)
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self.model = os.getenv("MODEL", "deepseek-chat")
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# Initialize OpenAI client
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self.client = OpenAI(
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api_key=self.api_key,
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base_url=self.base_url
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)
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def _load_prompt_template(self):
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"""Load the prompt template from ds_prompt.txt."""
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try:
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with open("ds_prompt.txt", "r") as f:
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self.prompt_template = f.read()
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except FileNotFoundError:
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print("Error: ds_prompt.txt not found")
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sys.exit(1)
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def _load_historic_prompts(self):
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"""Load historic prompts from JSON file."""
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try:
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with open("historic_prompts.json", "r") as f:
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self.historic_prompts = json.load(f)
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except (FileNotFoundError, json.JSONDecodeError):
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print("Warning: Starting with empty prompt history")
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self.historic_prompts = []
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def _save_historic_prompts(self):
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"""Save historic prompts to JSON file (keeping only last 60)."""
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# Keep only the last 60 prompts
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if len(self.historic_prompts) > 60:
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self.historic_prompts = self.historic_prompts[-60:]
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with open("historic_prompts.json", "w") as f:
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json.dump(self.historic_prompts, f, indent=2)
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def _prepare_prompt(self) -> str:
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"""Prepare the full prompt with historic context."""
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if self.historic_prompts:
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historic_context = json.dumps(self.historic_prompts, indent=2)
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full_prompt = f"{self.prompt_template}\n\nPrevious prompts:\n{historic_context}"
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else:
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full_prompt = self.prompt_template
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return full_prompt
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def _parse_ai_response(self, response_content: str) -> List[Dict[str, str]]:
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"""Parse the AI response to extract new prompts."""
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try:
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# Try to parse as JSON
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data = json.loads(response_content)
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# Convert to list of prompt dictionaries
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new_prompts = []
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for i in range(6):
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key = f"newprompt{i}"
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if key in data:
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prompt_text = data[key]
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prompt_obj = {
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f"prompt{len(self.historic_prompts) + i:02d}": prompt_text
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}
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new_prompts.append(prompt_obj)
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return new_prompts
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except json.JSONDecodeError:
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# If not valid JSON, try to extract prompts from text
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print("Warning: AI response is not valid JSON, attempting to extract prompts...")
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# Look for patterns in the text
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lines = response_content.strip().split('\n')
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new_prompts = []
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for i, line in enumerate(lines[:6]):
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line = line.strip()
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if line and len(line) > 50:
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prompt_obj = {
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f"prompt{len(self.historic_prompts) + i:02d}": line
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}
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new_prompts.append(prompt_obj)
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return new_prompts
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def generate_prompts(self) -> List[Dict[str, str]]:
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"""Generate new journal prompts using AI."""
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print("\nGenerating new journal prompts...")
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# Prepare the prompt
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full_prompt = self._prepare_prompt()
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try:
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# Call the AI API
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print("Calling AI API...")
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response = self.client.chat.completions.create(
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model=self.model,
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messages=[
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{"role": "system", "content": "You are a creative writing assistant that generates journal prompts. Always respond with valid JSON."},
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{"role": "user", "content": full_prompt}
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],
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temperature=0.7,
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max_tokens=2000
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)
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response_content = response.choices[0].message.content
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except Exception as e:
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print(f"Error calling AI API: {e}")
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return []
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# Parse the response
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new_prompts = self._parse_ai_response(response_content)
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if not new_prompts:
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print("Error: Could not parse any prompts from AI response")
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return []
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# Add to historic prompts
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self.historic_prompts.extend(new_prompts)
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# Save updated history
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self._save_historic_prompts()
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return new_prompts
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def display_prompts(self, prompts: List[Dict[str, str]]):
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"""Display generated prompts in a simple format."""
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print("\n" + "="*60)
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print("✨ NEW JOURNAL PROMPTS GENERATED ✨")
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print("="*60 + "\n")
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for i, prompt_dict in enumerate(prompts, 1):
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# Extract prompt text
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prompt_key = list(prompt_dict.keys())[0]
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prompt_text = prompt_dict[prompt_key]
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print(f"Prompt #{i}:")
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print("-" * 40)
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print(prompt_text)
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print("-" * 40 + "\n")
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def show_history_stats(self):
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"""Show statistics about prompt history."""
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total_prompts = len(self.historic_prompts)
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print("\nPrompt History Statistics:")
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print("-" * 30)
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print(f"Total prompts in history: {total_prompts}")
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print(f"History capacity: 60 prompts")
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print(f"Available slots: {max(0, 60 - total_prompts)}")
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def save_prompt_to_file(self, prompt_dict: Dict[str, str], filename: str = None):
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"""Save a prompt to a text file."""
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prompt_key = list(prompt_dict.keys())[0]
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prompt_text = prompt_dict[prompt_key]
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if not filename:
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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filename = f"journal_prompt_{timestamp}.txt"
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with open(filename, "w") as f:
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f.write(f"Journal Prompt - {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n")
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f.write("="*50 + "\n\n")
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f.write(prompt_text)
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f.write("\n\n" + "="*50 + "\n")
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f.write("Happy writing! ✍️\n")
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print(f"Prompt saved to {filename}")
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def main():
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"""Main entry point for the simple script."""
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parser = argparse.ArgumentParser(description="Generate journal prompts using AI (simple version)")
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parser.add_argument(
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"--stats", "-s",
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action="store_true",
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help="Show history statistics"
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)
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parser.add_argument(
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"--save", "-S",
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type=int,
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help="Save a specific prompt number to file (1-6)"
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)
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parser.add_argument(
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"--config", "-c",
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default=".env",
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help="Path to configuration file (default: .env)"
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)
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args = parser.parse_args()
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# Initialize generator
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generator = SimplePromptGenerator(config_path=args.config)
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if args.stats:
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generator.show_history_stats()
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else:
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# Generate prompts
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new_prompts = generator.generate_prompts()
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if new_prompts:
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generator.display_prompts(new_prompts)
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# Save specific prompt if requested
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if args.save:
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prompt_num = args.save
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if 1 <= prompt_num <= len(new_prompts):
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generator.save_prompt_to_file(new_prompts[prompt_num - 1])
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else:
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print(f"Error: Prompt number must be between 1 and {len(new_prompts)}")
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if __name__ == "__main__":
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main()
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