// _opt/responses.js
// Simplified OpenAI Responses module with clear flow and context management
import fs from 'fs/promises';
import path from 'path';
import { OpenAI } from 'openai';
import axios from 'axios';
import { AttachmentBuilder } from 'discord.js';

// Discord message max length
const MAX_DISCORD_MSG_LENGTH = 2000;

/**
 * Split a long message into chunks <= maxLength, preserving code fences by closing and reopening.
 * @param {string} text
 * @param {number} maxLength
 * @returns {string[]}
 */
function splitMessage(text, maxLength = MAX_DISCORD_MSG_LENGTH) {
  const lines = text.split(/\n/);
  const chunks = [];
  let chunk = '';
  let codeBlockOpen = false;
  let codeBlockFence = '```';
  for (let line of lines) {
    const trimmed = line.trim();
    const isFenceLine = trimmed.startsWith('```');
    if (isFenceLine) {
      if (!codeBlockOpen) {
        codeBlockOpen = true;
        codeBlockFence = trimmed;
      } else if (trimmed === '```') {
        // closing fence
        codeBlockOpen = false;
      }
    }
    // include the newline that was removed by split
    const segment = line + '\n';
    // if adding segment exceeds limit
    if (chunk.length + segment.length > maxLength) {
      if (chunk.length > 0) {
        // close open code block if needed
        if (codeBlockOpen) chunk += '\n```';
        chunks.push(chunk);
        // start new chunk, reopen code block if needed
        chunk = codeBlockOpen ? (codeBlockFence + '\n' + segment) : segment;
        continue;
      }
      // single segment too long, split it directly
      let rest = segment;
      while (rest.length > maxLength) {
        let part = rest.slice(0, maxLength);
        if (codeBlockOpen) part += '\n```';
        chunks.push(part);
        rest = codeBlockOpen ? (codeBlockFence + '\n' + rest.slice(maxLength)) : rest.slice(maxLength);
      }
      chunk = rest;
      continue;
    }
    chunk += segment;
  }
  if (chunk) {
    // close any unclosed code block
    if (codeBlockOpen) chunk += '\n```';
    chunks.push(chunk);
  }
  // remove trailing newline from each chunk
  return chunks.map(c => c.endsWith('\n') ? c.slice(0, -1) : c);
}

/**
 * Load the system prompt from disk.
 */
async function loadSystemPrompt(filePath, logger) {
  try {
    const prompt = await fs.readFile(path.resolve(filePath), 'utf8');
    logger.info(`Loaded system prompt: ${filePath}`);
    return prompt;
  } catch (err) {
    logger.error(`Failed to load system prompt: ${err.message}`);
    return '';
  }
}

/**
 * Determine if the bot should respond:
 * - Mentioned
 * - Direct reply
 */
async function shouldRespond(message, botId, logger) {
  if (message.author.bot || !botId) return false;
  const isMention = message.mentions.users.has(botId);
  let isReply = false;
  if (message.reference?.messageId) {
    try {
      const ref = await message.channel.messages.fetch(message.reference.messageId);
      isReply = ref.author.id === botId;
    } catch {}
  }
  logger.debug(`Trigger? mention=${isMention} reply=${isReply}`);
  return isMention || isReply;
}

/**
 * Cache the last response ID for context continuity.
 */
function cacheResponse(client, key, id, ttlSeconds) {
  client.pb?.cache?.set(key, id, ttlSeconds);
}

/**
 * Award output tokens via the scorekeeper module.
 */
function awardOutput(client, guildId, userId, amount) {
  if (client.scorekeeper && amount > 0) {
    client.scorekeeper.addOutput(guildId, userId, amount)
      .catch(err => client.logger.error(`Scorekeeper error: ${err.message}`));
  }
}

/**
 * Handle image generation function calls.
 * Returns true if an image was handled and replied.
 */
async function handleImage(client, message, resp, cfg) {
  const calls = Array.isArray(resp.output) ? resp.output : [];
  const fn = calls.find(o => o.type === 'function_call' && o.name === 'generate_image');
  if (!fn?.arguments) return false;
  client.logger.debug(`Image function args: ${fn.arguments}`);
  let args;
  try { args = JSON.parse(fn.arguments); } catch { return false; }
  if (!args.prompt?.trim()) {
    await message.reply('Cannot generate image: empty prompt.');
    return true;
  }
  // Determine image size based on aspect: square, landscape, or portrait
  // Square will always use 1024x1024
  let size;
  switch (args.aspect) {
    case 'landscape':
      size = '1792x1024';
      break;
    case 'portrait':
      size = '1024x1792';
      break;
    case 'square':
      size = '1024x1024';
      break;
    default:
      size = '1024x1024';
  }
  // Determine image quality, defaulting to cfg.imageGeneration.defaultQuality
  const quality = ['standard', 'hd'].includes(args.quality)
    ? args.quality
    : cfg.imageGeneration.defaultQuality;
  try {
    // Generate image via OpenAI
    const imgRes = await client.openai.images.generate({ model: 'dall-e-3', prompt: args.prompt, quality: quality, size: size, n: 1 });
    const url = imgRes.data?.[0]?.url;
    if (!url) throw new Error('No image URL');
    // Download and save locally
    const dl = await axios.get(url, { responseType: 'arraybuffer' });
    const buf = Buffer.from(dl.data);
    const filename = `${message.author.id}-${Date.now()}.png`;
    const dir = cfg.imageGeneration.imageSavePath || './images';
    await fs.mkdir(dir, { recursive: true });
    const filePath = path.join(dir, filename);
    await fs.writeFile(filePath, buf);
    client.logger.info(`Saved image: ${filePath}`);
    // Reply with attachment
    const attachment = new AttachmentBuilder(buf, { name: filename });
    await message.reply({ content: args.prompt, files: [attachment] });
    // Follow-up recap to preserve conversation context (submit function tool output)
    try {
      const convKey = message.thread?.id || message.channel.id;
      // Build a function_call_output input item for the Responses API
      const toolOutputItem = {
        type: 'function_call_output',
        call_id: fn.call_id,
        output: JSON.stringify({ url }),
      };
      const recapBody = {
        model: cfg.defaultModel,
        // re-use original system/developer instructions
        instructions: client.responsesSystemPrompt,
        previous_response_id: resp.id,
        input: [toolOutputItem],
        max_output_tokens: Math.min(100, cfg.defaultMaxTokens),
        temperature: cfg.defaultTemperature,
      };
      const recapResp = await client.openai.responses.create(recapBody);
      cacheResponse(client, convKey, recapResp.id, Math.floor(cfg.conversationExpiry / 1000));
      // Award tokens for the recap chat response
      const recapTokens = recapResp.usage?.total_tokens ?? recapResp.usage?.completion_tokens ?? 0;
      awardOutput(client, message.guild.id, message.author.id, recapTokens);
    } catch (err) {
      client.logger.error(`Recap failed: ${err.message}`);
    }
  } catch (err) {
    client.logger.error(`Image error: ${err.message}`);
    await message.reply(`Image generation error: ${err.message}`);
  }
  return true;
}

/**
 * Main message handler:
 * 1. Determine if bot should respond
 * 2. Build and send AI request
 * 3. Cache response ID
 * 4. Handle image or text reply
 * 5. Award output points
 */
async function onMessage(client, cfg, message) {
  const logger = client.logger;
  const botId = client.user?.id;
  if (!(await shouldRespond(message, botId, logger))) return;
  await message.channel.sendTyping();

  // Determine channel/thread key for context
  const key = message.thread?.id || message.channel.id;
  // Initialize per-channel lock map
  const lockMap = client._responseLockMap || (client._responseLockMap = new Map());
  // Get last pending promise for this key
  const last = lockMap.get(key) || Promise.resolve();
  // Handler to run in sequence
  const handler = async () => {
    try {
      // Previous response ID for context continuity
      const prev = client.pb?.cache?.get(key);
      // Enforce minimum score to use AI responses
      try {
        const scoreData = await client.scorekeeper.getScore(message.guild.id, message.author.id);
        if (scoreData.totalScore < cfg.minScore) {
          await message.reply(
            `You need a score of at least ${cfg.minScore} to use AI responses. Your current score is ${scoreData.totalScore.toFixed(2)}.`
          );
          return;
        }
      } catch (err) {
        client.logger.error(`Error checking score: ${err.message}`);
      }
      // Build request body, prefixing with a mention of who spoke
      const speakerMention = `<@${message.author.id}>`;
      const body = {
        model: cfg.defaultModel,
        instructions: client.responsesSystemPrompt,
        input: `${speakerMention} said to you: ${message.content}`,
        previous_response_id: prev,
        max_output_tokens: cfg.defaultMaxTokens,
        temperature: cfg.defaultTemperature,
      };
      // Assemble any enabled tools
      const tools = [];
      if (cfg.tools?.imageGeneration) {
        tools.push({
          type: 'function',
          name: 'generate_image',
          description: 'Generate an image with a given prompt, aspect, and quality.',
          parameters: {
            type: 'object',
            properties: {
              prompt: { type: 'string' },
              aspect: { type: 'string', enum: ['square','portrait','landscape'] },
              quality: { type: 'string', enum: ['standard', 'hd'] },
            },
            required: ['prompt','aspect','quality'],
            additionalProperties: false,
          },
          strict: true
        });
      }
      if (cfg.tools?.webSearch) {
        tools.push({ type: 'web_search_preview' });
      }
      if (tools.length) {
        body.tools = tools;
      }

      // Call OpenAI Responses
      logger.debug(`Calling AI with body: ${JSON.stringify(body)}`);
      const resp = await client.openai.responses.create(body);
      logger.info(`AI response id=${resp.id}`);
      // Award tokens for the AI chat response
      const chatTokens = resp.usage?.total_tokens ?? resp.usage?.completion_tokens ?? 0;
      awardOutput(client, message.guild.id, message.author.id, chatTokens);

      // Cache response ID if not a function call
      const isFuncCall = Array.isArray(resp.output) && resp.output.some(o => o.type === 'function_call');
      if (!isFuncCall && resp.id && cfg.conversationExpiry) {
        cacheResponse(client, key, resp.id, Math.floor(cfg.conversationExpiry / 1000));
      }

      // Handle image function call if present
      if (await handleImage(client, message, resp, cfg)) return;

      // Otherwise reply with text
      const text = resp.output_text?.trim();
      if (text) {
        const parts = splitMessage(text, MAX_DISCORD_MSG_LENGTH);
        for (const part of parts) {
          await message.reply(part);
        }
      }
    } catch (err) {
      logger.error(`Queued onMessage error for ${key}: ${err.message}`);
    }
  };
  // Chain the handler to the last promise
  const next = last.then(handler).catch(err => logger.error(err));
  lockMap.set(key, next);
  // Queue enqueued; handler will send response when its turn arrives
  return;

  // Call OpenAI Responses
  let resp;
  try {
    logger.debug(`Calling AI with body: ${JSON.stringify(body)}`);
    resp = await client.openai.responses.create(body);
    logger.info(`AI response id=${resp.id}`);
    // Award tokens for the AI chat response immediately (captures token usage even if image follows)
    const chatTokens = resp.usage?.total_tokens ?? resp.usage?.completion_tokens ?? 0;
    awardOutput(client, message.guild.id, message.author.id, chatTokens);
  } catch (err) {
    logger.error(`AI error: ${err.message}`);
    return message.reply('Error generating response.');
  }

  // Cache for next turn only if this was a text response
  const isFuncCall = Array.isArray(resp.output) && resp.output.some(o => o.type === 'function_call');
  if (!isFuncCall && resp.id && cfg.conversationExpiry) {
    cacheResponse(client, key, resp.id, Math.floor(cfg.conversationExpiry / 1000));
  }

  // Handle image function call if present
  if (await handleImage(client, message, resp, cfg)) return;

  // Otherwise reply with text (split if over Discord limit)
  const text = resp.output_text?.trim();
  if (text) {
    const parts = splitMessage(text, MAX_DISCORD_MSG_LENGTH);
    for (const part of parts) {
      await message.reply(part);
    }
  }

}

/**
 * Send a narrative response to a specific Discord channel or thread.
 * @param {import('discord.js').Client} client - Discord client instance.
 * @param {Object} cfg - Responses module configuration.
 * @param {string} channelId - ID of the Discord channel or thread.
 * @param {string} text - Narrative input text to process.
 */
export async function sendNarrative(client, cfg, channelId, text) {
  const logger = client.logger;
  try {
    // Build the narrative instructions
    const instructions = `${client.responsesSystemPrompt}\n\nGenerate the following as an engaging narrative:`;
    const body = {
      model: cfg.defaultModel,
      instructions,
      input: text,
      max_output_tokens: cfg.defaultMaxTokens,
      temperature: cfg.defaultTemperature,
    };
    logger.debug('sendNarrative: calling AI with body', body);
    const resp = await client.openai.responses.create(body);
    logger.info(`sendNarrative AI response id=${resp.id}`);
    // Fetch the target channel or thread
    const channel = await client.channels.fetch(channelId);
    if (!channel || typeof channel.send !== 'function') {
      logger.error(`sendNarrative: cannot send to channel ID ${channelId}`);
      return;
    }
    // Split the output and send
    const content = resp.output_text?.trim();
    if (content) {
      const parts = splitMessage(content, MAX_DISCORD_MSG_LENGTH);
      for (const part of parts) {
        await channel.send(part);
      }
    }
  } catch (err) {
    client.logger.error(`sendNarrative error: ${err.message}`);
  }
}

/**
 * Initialize the Responses module
 */
export async function init(client, clientConfig) {
  const cfg = clientConfig.responses;
  client.logger.info('Initializing Responses module');
  client.responsesSystemPrompt = await loadSystemPrompt(cfg.systemPromptPath, client.logger);
  client.openai = new OpenAI({ apiKey: cfg.apiKey });
  client.on('messageCreate', m => onMessage(client, cfg, m));
  client.logger.info('Responses module ready');
}