#!/usr/bin/env python3
"""
Daily Journal Prompt Generator
A tool that uses AI to generate creative writing prompts for daily journaling.
"""

import os
import json
import sys
import argparse
import configparser
from datetime import datetime
from typing import List, Dict, Any, Optional
from pathlib import Path

from openai import OpenAI
from dotenv import load_dotenv
from rich.console import Console
from rich.panel import Panel
from rich.table import Table
from rich.prompt import Prompt, Confirm
from rich.progress import Progress, SpinnerColumn, TextColumn


class JournalPromptGenerator:
    """Main class for generating journal prompts using AI."""

    def __init__(self, config_path: str = ".env"):
        """Initialize the generator with configuration."""
        self.console = Console()
        self.config_path = config_path
        self.client = None
        self.historic_prompts = []
        self.prompt_template = ""
        self.settings = {}

        # Load configuration
        self._load_config()
        self._load_settings()

        # Load data files
        self._load_prompt_template()
        self._load_historic_prompts()

    def _load_config(self):
        """Load configuration from environment file."""
        load_dotenv(self.config_path)

        # Get API key
        self.api_key = os.getenv("DEEPSEEK_API_KEY") or os.getenv("OPENAI_API_KEY")
        if not self.api_key:
            self.console.print("[red]Error: No API key found in .env file[/red]")
            self.console.print("Please add DEEPSEEK_API_KEY or OPENAI_API_KEY to your .env file")
            sys.exit(1)

        # Get API base URL (default to DeepSeek)
        self.base_url = os.getenv("API_BASE_URL", "https://api.deepseek.com")

        # Get model (default to deepseek-chat)
        self.model = os.getenv("MODEL", "deepseek-chat")

        # Initialize OpenAI client
        self.client = OpenAI(
            api_key=self.api_key,
            base_url=self.base_url
        )

    def _load_settings(self):
        """Load settings from settings.cfg configuration file."""
        config = configparser.ConfigParser()

        # Set default values
        self.settings = {
            'min_length': 500,
            'max_length': 1000,
            'num_prompts': 6
        }

        try:
            config.read('settings.cfg')

            if 'prompts' in config:
                prompts_section = config['prompts']

                # Load min_length
                if 'min_length' in prompts_section:
                    self.settings['min_length'] = int(prompts_section['min_length'])

                # Load max_length
                if 'max_length' in prompts_section:
                    self.settings['max_length'] = int(prompts_section['max_length'])

                # Load num_prompts
                if 'num_prompts' in prompts_section:
                    self.settings['num_prompts'] = int(prompts_section['num_prompts'])

        except FileNotFoundError:
            self.console.print("[yellow]Warning: settings.cfg not found, using default values[/yellow]")
        except ValueError as e:
            self.console.print(f"[yellow]Warning: Invalid value in settings.cfg: {e}, using default values[/yellow]")
        except Exception as e:
            self.console.print(f"[yellow]Warning: Error reading settings.cfg: {e}, using default values[/yellow]")

    def _load_prompt_template(self):
        """Load the prompt template from ds_prompt.txt and update with config values."""
        try:
            with open("ds_prompt.txt", "r") as f:
                template = f.read()

            # Replace hardcoded values with config values
            template = template.replace(
                "between 500 and 1000 characters",
                f"between {self.settings['min_length']} and {self.settings['max_length']} characters"
            )

            # Replace the number of prompts (6) with config value
            template = template.replace(
                "Please generate 6 writing prompts",
                f"Please generate {self.settings['num_prompts']} writing prompts"
            )

            self.prompt_template = template
        except FileNotFoundError:
            self.console.print("[red]Error: ds_prompt.txt not found[/red]")
            sys.exit(1)

    def _load_historic_prompts(self):
        """Load historic prompts from JSON file."""
        try:
            with open("historic_prompts.json", "r") as f:
                self.historic_prompts = json.load(f)
        except FileNotFoundError:
            self.console.print("[yellow]Warning: historic_prompts.json not found, starting with empty history[/yellow]")
            self.historic_prompts = []
        except json.JSONDecodeError:
            self.console.print("[yellow]Warning: historic_prompts.json is corrupted, starting with empty history[/yellow]")
            self.historic_prompts = []

    def _save_historic_prompts(self):
        """Save historic prompts to JSON file (keeping only first 60)."""
        # Keep only the first 60 prompts (newest are at the beginning)
        if len(self.historic_prompts) > 60:
            self.historic_prompts = self.historic_prompts[:60]

        with open("historic_prompts.json", "w") as f:
            json.dump(self.historic_prompts, f, indent=2)

    def _renumber_prompts(self):
        """Renumber all prompts to maintain prompt00-prompt59 range."""
        renumbered_prompts = []
        for i, prompt_dict in enumerate(self.historic_prompts):
            # Get the prompt text from the first key in the dictionary
            prompt_key = list(prompt_dict.keys())[0]
            prompt_text = prompt_dict[prompt_key]

            # Create new prompt with correct numbering
            new_prompt_key = f"prompt{i:02d}"
            renumbered_prompts.append({
                new_prompt_key: prompt_text
            })

        self.historic_prompts = renumbered_prompts

    def add_prompt_to_history(self, prompt_text: str):
        """
        Add a single prompt to the historic prompts cyclic buffer.
        The new prompt becomes prompt00, all others shift down, and prompt59 is discarded.
        """
        # Create the new prompt object
        new_prompt = {
            "prompt00": prompt_text
        }

        # Shift all existing prompts down by one position
        # We'll create a new list starting with the new prompt
        updated_prompts = [new_prompt]

        # Add all existing prompts, shifting their numbers down by one
        for i, prompt_dict in enumerate(self.historic_prompts):
            if i >= 59:  # We only keep 60 prompts total (00-59)
                break

            # Get the prompt text
            prompt_key = list(prompt_dict.keys())[0]
            prompt_text = prompt_dict[prompt_key]

            # Create prompt with new number (shifted down by one)
            new_prompt_key = f"prompt{i+1:02d}"
            updated_prompts.append({
                new_prompt_key: prompt_text
            })

        self.historic_prompts = updated_prompts
        self._save_historic_prompts()

    def _prepare_prompt(self) -> str:
        """Prepare the full prompt with historic context."""
        # Format historic prompts for the AI
        if self.historic_prompts:
            historic_context = json.dumps(self.historic_prompts, indent=2)
            full_prompt = f"{self.prompt_template}\n\nPrevious prompts:\n{historic_context}"
        else:
            full_prompt = self.prompt_template

        return full_prompt

    def _parse_ai_response(self, response_content: str) -> List[Dict[str, str]]:
        """
        Parse the AI response to extract new prompts.
        Expected format: JSON array with keys "newprompt0" to "newpromptN" where N = num_prompts-1
        """
        try:
            # Try to parse as JSON
            data = json.loads(response_content)

            # Convert to list of prompt dictionaries
            new_prompts = []
            for i in range(self.settings['num_prompts']):
                key = f"newprompt{i}"
                if key in data:
                    prompt_text = data[key]
                    prompt_obj = {
                        f"prompt{len(self.historic_prompts) + i:02d}": prompt_text
                    }
                    new_prompts.append(prompt_obj)

            return new_prompts

        except json.JSONDecodeError:
            # If not valid JSON, try to extract prompts from text
            self.console.print("[yellow]Warning: AI response is not valid JSON, attempting to extract prompts...[/yellow]")
            self.console.print(f"[yellow]Full response content for debugging:[/yellow]")
            self.console.print(f"[yellow]{response_content}[/yellow]")

            # Look for patterns in the text
            lines = response_content.strip().split('\n')
            new_prompts = []

            for i, line in enumerate(lines[:self.settings['num_prompts']]):  # Take first N non-empty lines
                line = line.strip()
                if line and len(line) > 50:  # Reasonable minimum length for a prompt
                    prompt_obj = {
                        f"prompt{len(self.historic_prompts) + i:02d}": line
                    }
                    new_prompts.append(prompt_obj)

            return new_prompts

    def generate_prompts(self) -> List[Dict[str, str]]:
        """Generate new journal prompts using AI."""
        self.console.print("\n[cyan]Generating new journal prompts...[/cyan]")

        # Prepare the prompt
        full_prompt = self._prepare_prompt()

        # Show progress
        with Progress(
            SpinnerColumn(),
            TextColumn("[progress.description]{task.description}"),
            transient=True,
        ) as progress:
            task = progress.add_task("Calling AI API...", total=None)

            try:
                # Call the AI API
                response = self.client.chat.completions.create(
                    model=self.model,
                    messages=[
                        {"role": "system", "content": "You are a creative writing assistant that generates journal prompts. Always respond with valid JSON."},
                        {"role": "user", "content": full_prompt}
                    ],
                    temperature=0.7,
                    max_tokens=2000
                )

                response_content = response.choices[0].message.content

            except Exception as e:
                self.console.print(f"[red]Error calling AI API: {e}[/red]")
                return []

        # Parse the response
        new_prompts = self._parse_ai_response(response_content)

        if not new_prompts:
            self.console.print("[red]Error: Could not parse any prompts from AI response[/red]")
            return []

        # Note: Prompts are NOT added to historic_prompts here
        # They will be added only when the user chooses one in interactive mode
        # via the add_prompt_to_history() method

        return new_prompts

    def display_prompts(self, prompts: List[Dict[str, str]]):
        """Display generated prompts in a nice format."""
        self.console.print("\n" + "="*60)
        self.console.print("[bold green]✨ NEW JOURNAL PROMPTS GENERATED ✨[/bold green]")
        self.console.print("="*60 + "\n")

        for i, prompt_dict in enumerate(prompts, 1):
            # Extract prompt text (key is like "prompt60", "prompt61", etc.)
            prompt_key = list(prompt_dict.keys())[0]
            prompt_text = prompt_dict[prompt_key]

            # Create a panel for each prompt
            panel = Panel(
                f"[cyan]{prompt_text}[/cyan]",
                title=f"[bold]Prompt #{i}[/bold]",
                border_style="blue",
                padding=(1, 2)
            )
            self.console.print(panel)
            self.console.print()  # Empty line between prompts

    def show_history_stats(self):
        """Show statistics about prompt history."""
        total_prompts = len(self.historic_prompts)

        table = Table(title="Prompt History Statistics")
        table.add_column("Metric", style="cyan")
        table.add_column("Value", style="green")

        table.add_row("Total prompts in history", str(total_prompts))
        table.add_row("History capacity", "60 prompts")
        table.add_row("Available slots", str(max(0, 60 - total_prompts)))

        self.console.print(table)

    def interactive_mode(self):
        """Run in interactive mode with user prompts."""
        self.console.print(Panel.fit(
            "[bold]Daily Journal Prompt Generator[/bold]\n"
            "Generate creative writing prompts for your journal practice",
            border_style="green"
        ))

        while True:
            self.console.print("\n[bold]Options:[/bold]")
            self.console.print("1. Generate new prompts")
            self.console.print("2. View history statistics")
            self.console.print("3. Exit")

            choice = Prompt.ask("\nEnter your choice", choices=["1", "2", "3"], default="1")

            if choice == "1":
                new_prompts = self.generate_prompts()
                if new_prompts:
                    self.display_prompts(new_prompts)

                    # Ask if user wants to save a prompt
                    if Confirm.ask("\nWould you like to save one of these prompts to a file?"):
                        prompt_num = Prompt.ask(
                            "Which prompt number would you like to save?",
                            choices=[str(i) for i in range(1, len(new_prompts) + 1)],
                            default="1"
                        )

                        prompt_idx = int(prompt_num) - 1
                        prompt_dict = new_prompts[prompt_idx]
                        prompt_key = list(prompt_dict.keys())[0]
                        prompt_text = prompt_dict[prompt_key]

                        # Save to file
                        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
                        filename = f"journal_prompt_{timestamp}.txt"

                        with open(filename, "w") as f:
                            f.write(f"Journal Prompt - {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n")
                            f.write("="*50 + "\n\n")
                            f.write(prompt_text)
                            f.write("\n\n" + "="*50 + "\n")
                            f.write("Happy writing! ✍️\n")

                        self.console.print(f"[green]Prompt saved to {filename}[/green]")

                        # Add the chosen prompt to historic prompts cyclic buffer
                        self.add_prompt_to_history(prompt_text)
                        self.console.print(f"[green]Prompt added to history as prompt00[/green]")

            elif choice == "2":
                self.show_history_stats()

            elif choice == "3":
                self.console.print("[green]Goodbye! Happy journaling! 📓[/green]")
                break


def main():
    """Main entry point for the script."""
    parser = argparse.ArgumentParser(description="Generate journal prompts using AI")
    parser.add_argument(
        "--interactive", "-i",
        action="store_true",
        help="Run in interactive mode"
    )
    parser.add_argument(
        "--config", "-c",
        default=".env",
        help="Path to configuration file (default: .env)"
    )
    parser.add_argument(
        "--stats", "-s",
        action="store_true",
        help="Show history statistics"
    )

    args = parser.parse_args()

    # Initialize generator
    generator = JournalPromptGenerator(config_path=args.config)

    if args.stats:
        generator.show_history_stats()
    elif args.interactive:
        generator.interactive_mode()
    else:
        # Default: generate and display prompts
        new_prompts = generator.generate_prompts()
        if new_prompts:
            generator.display_prompts(new_prompts)


if __name__ == "__main__":
    main()