/**
 * POST /v1/messages — Anthropic Messages API compatibility layer.
 *
 * Translates Anthropic request/response format to/from the internal OpenAI
 * format so Claude Code and any Anthropic SDK client can connect directly.
 *
 * Streaming path is a real-time translator: it pipes the OpenAI SSE stream
 * from handleChatCompletions through a response shim that parses each
 * chat.completion.chunk and emits the equivalent Anthropic message_start /
 * content_block_* / message_delta / message_stop events as bytes arrive.
 * No buffering, so first-token latency matches the upstream Cascade stream.
 */

import { randomUUID } from 'crypto';
import { handleChatCompletions } from './chat.js';
import { log } from '../config.js';

function genMsgId() {
  return 'msg_' + randomUUID().replace(/-/g, '').slice(0, 24);
}

// ─── Anthropic → OpenAI request translation ──────────────────

function anthropicToOpenAI(body) {
  const messages = [];
  if (body.system) {
    const sysText = typeof body.system === 'string'
      ? body.system
      : Array.isArray(body.system)
        ? body.system.map(b => b.text || '').join('\n')
        : '';
    if (sysText) messages.push({ role: 'system', content: sysText });
  }
  for (const m of (body.messages || [])) {
    const role = m.role === 'assistant' ? 'assistant' : 'user';
    if (typeof m.content === 'string') {
      messages.push({ role, content: m.content });
    } else if (Array.isArray(m.content)) {
      const textParts = [];
      const toolCalls = [];
      const toolResults = [];
      for (const block of m.content) {
        if (block.type === 'text') {
          textParts.push(block.text || '');
        } else if (block.type === 'thinking') {
          // Thinking blocks from assistant history — skip; the model will regenerate
        } else if (block.type === 'tool_use' && role === 'assistant') {
          toolCalls.push({
            id: block.id || `call_${randomUUID().slice(0, 8)}`,
            type: 'function',
            function: { name: block.name, arguments: JSON.stringify(block.input || {}) },
          });
        } else if (block.type === 'tool_result') {
          const content = typeof block.content === 'string'
            ? block.content
            : Array.isArray(block.content)
              ? block.content.map(b => b.text || '').join('\n')
              : JSON.stringify(block.content);
          toolResults.push({ role: 'tool', tool_call_id: block.tool_use_id, content });
        }
      }
      if (toolCalls.length) {
        messages.push({
          role: 'assistant',
          content: textParts.length ? textParts.join('\n') : null,
          tool_calls: toolCalls,
        });
      } else if (textParts.length) {
        messages.push({ role, content: textParts.join('\n') });
      }
      for (const tr of toolResults) messages.push(tr);
    }
  }
  const tools = (body.tools || []).map(t => ({
    type: 'function',
    function: {
      name: t.name,
      description: t.description || '',
      parameters: t.input_schema || {},
    },
  }));
  return {
    model: body.model || 'claude-sonnet-4.6',
    messages,
    max_tokens: body.max_tokens || 8192,
    stream: !!body.stream,
    ...(tools.length ? { tools } : {}),
    ...(body.temperature != null ? { temperature: body.temperature } : {}),
    ...(body.top_p != null ? { top_p: body.top_p } : {}),
    ...(body.stop_sequences ? { stop: body.stop_sequences } : {}),
  };
}

// ─── OpenAI → Anthropic non-stream response translation ──────

function openAIToAnthropic(result, model, msgId) {
  const choice = result.choices?.[0];
  const usage = result.usage || {};
  const content = [];
  if (choice?.message?.reasoning_content) {
    content.push({ type: 'thinking', thinking: choice.message.reasoning_content });
  }
  if (choice?.message?.tool_calls?.length) {
    if (choice.message.content) content.push({ type: 'text', text: choice.message.content });
    for (const tc of choice.message.tool_calls) {
      let input = {};
      try { input = JSON.parse(tc.function?.arguments || '{}'); } catch {}
      content.push({
        type: 'tool_use',
        id: tc.id,
        name: tc.function?.name || 'unknown',
        input,
      });
    }
  } else {
    content.push({ type: 'text', text: choice?.message?.content || '' });
  }
  const stopMap = { stop: 'end_turn', length: 'max_tokens', tool_calls: 'tool_use' };
  return {
    id: msgId,
    type: 'message',
    role: 'assistant',
    content,
    model: model || result.model,
    stop_reason: stopMap[choice?.finish_reason] || 'end_turn',
    stop_sequence: null,
    usage: {
      input_tokens: usage.prompt_tokens || usage.input_tokens || 0,
      output_tokens: usage.completion_tokens || usage.output_tokens || 0,
      cache_creation_input_tokens: usage.cache_creation_input_tokens || 0,
      cache_read_input_tokens: usage.prompt_tokens_details?.cached_tokens || 0,
    },
  };
}

// ─── Streaming translator: intercepts OpenAI SSE, emits Anthropic SSE ──

class AnthropicStreamTranslator {
  constructor(res, msgId, model) {
    this.res = res;
    this.msgId = msgId;
    this.model = model;
    // Current content block: null | { type, index }
    // type: 'text' | 'thinking' | 'tool_use'
    this.current = null;
    this.blockIndex = 0;
    this.toolCallBufs = new Map();   // index → { id, name, argsBuffered }
    this.finalUsage = null;
    this.stopReason = 'end_turn';
    this.messageStarted = false;
    this.messageStopped = false;
    this.pendingSseBuf = '';
  }

  send(event, data) {
    if (!this.res.writableEnded) {
      this.res.write(`event: ${event}\ndata: ${JSON.stringify(data)}\n\n`);
    }
  }

  startMessage() {
    if (this.messageStarted) return;
    this.messageStarted = true;
    this.send('message_start', {
      type: 'message_start',
      message: {
        id: this.msgId,
        type: 'message',
        role: 'assistant',
        content: [],
        model: this.model,
        stop_reason: null,
        stop_sequence: null,
        usage: { input_tokens: 0, output_tokens: 0, cache_creation_input_tokens: 0, cache_read_input_tokens: 0 },
      },
    });
  }

  startBlock(type, extra = {}) {
    this.closeCurrentBlock();
    this.current = { type, index: this.blockIndex };
    let content_block;
    if (type === 'text') content_block = { type: 'text', text: '' };
    else if (type === 'thinking') content_block = { type: 'thinking', thinking: '' };
    else if (type === 'tool_use') content_block = { type: 'tool_use', id: extra.id, name: extra.name, input: {} };
    this.send('content_block_start', {
      type: 'content_block_start',
      index: this.blockIndex,
      content_block,
    });
  }

  closeCurrentBlock() {
    if (!this.current) return;
    this.send('content_block_stop', { type: 'content_block_stop', index: this.current.index });
    this.blockIndex++;
    this.current = null;
  }

  emitTextDelta(text) {
    if (!text) return;
    if (this.current?.type !== 'text') this.startBlock('text');
    this.send('content_block_delta', {
      type: 'content_block_delta',
      index: this.current.index,
      delta: { type: 'text_delta', text },
    });
  }

  emitThinkingDelta(text) {
    if (!text) return;
    if (this.current?.type !== 'thinking') this.startBlock('thinking');
    this.send('content_block_delta', {
      type: 'content_block_delta',
      index: this.current.index,
      delta: { type: 'thinking_delta', thinking: text },
    });
  }

  emitToolCallDelta(toolCall) {
    const idx = toolCall.index ?? 0;
    const existing = this.toolCallBufs.get(idx);
    const id = toolCall.id || existing?.id;
    const name = toolCall.function?.name || existing?.name;
    const argsChunk = toolCall.function?.arguments || '';

    if (!existing) {
      // New tool call — start a new tool_use content block
      this.startBlock('tool_use', { id, name });
      this.toolCallBufs.set(idx, { id, name, blockIndex: this.current.index, argsBuffered: '' });
    }
    const buf = this.toolCallBufs.get(idx);
    if (argsChunk) {
      buf.argsBuffered += argsChunk;
      this.send('content_block_delta', {
        type: 'content_block_delta',
        index: buf.blockIndex,
        delta: { type: 'input_json_delta', partial_json: argsChunk },
      });
    }
  }

  processChunk(chunk) {
    this.startMessage();
    const choice = chunk.choices?.[0];
    if (choice) {
      const delta = choice.delta || {};
      if (delta.reasoning_content) this.emitThinkingDelta(delta.reasoning_content);
      if (delta.content) this.emitTextDelta(delta.content);
      if (Array.isArray(delta.tool_calls)) {
        for (const tc of delta.tool_calls) this.emitToolCallDelta(tc);
      }
      if (choice.finish_reason) {
        const stopMap = { stop: 'end_turn', length: 'max_tokens', tool_calls: 'tool_use' };
        this.stopReason = stopMap[choice.finish_reason] || 'end_turn';
      }
    }
    if (chunk.usage) this.finalUsage = chunk.usage;
  }

  finish() {
    if (this.messageStopped) return;
    this.messageStopped = true;
    this.closeCurrentBlock();
    const u = this.finalUsage || {};
    this.send('message_delta', {
      type: 'message_delta',
      delta: { stop_reason: this.stopReason, stop_sequence: null },
      usage: {
        input_tokens: u.prompt_tokens || u.input_tokens || 0,
        output_tokens: u.completion_tokens || u.output_tokens || 0,
        cache_creation_input_tokens: u.cache_creation_input_tokens || 0,
        cache_read_input_tokens: u.prompt_tokens_details?.cached_tokens || 0,
      },
    });
    this.send('message_stop', { type: 'message_stop' });
  }

  // SSE parser — handleChatCompletions writes `data: {...}\n\n` frames;
  // accumulate and flush each complete frame as a translated event.
  feed(rawChunk) {
    this.pendingSseBuf += typeof rawChunk === 'string' ? rawChunk : rawChunk.toString('utf8');
    let idx;
    while ((idx = this.pendingSseBuf.indexOf('\n\n')) !== -1) {
      const frame = this.pendingSseBuf.slice(0, idx);
      this.pendingSseBuf = this.pendingSseBuf.slice(idx + 2);
      const lines = frame.split('\n');
      for (const line of lines) {
        if (!line.startsWith('data: ')) continue;
        const payload = line.slice(6);
        if (payload === '[DONE]') continue;
        try {
          this.processChunk(JSON.parse(payload));
        } catch (e) {
          log.warn(`Messages SSE parse error: ${e.message}`);
        }
      }
    }
  }
}

// ─── Fake ServerResponse that pipes writes into the translator ──

function createCaptureRes(translator) {
  const listeners = new Map();
  const fire = (event) => {
    const cbs = listeners.get(event) || [];
    for (const cb of cbs) { try { cb(); } catch {} }
  };
  return {
    writableEnded: false,
    headersSent: false,
    writeHead() { this.headersSent = true; },
    write(chunk) {
      translator.feed(chunk);
      return true;
    },
    end(chunk) {
      if (this.writableEnded) return;
      if (chunk) translator.feed(chunk);
      translator.finish();
      this.writableEnded = true;
      fire('close');
    },
    // Fire 'close' without marking writableEnded=true so chat.js's
    // close handler sees an un-ended stream and triggers its abort path.
    _clientDisconnected() { fire('close'); },
    on(event, cb) {
      if (!listeners.has(event)) listeners.set(event, []);
      listeners.get(event).push(cb);
      return this;
    },
    once(event, cb) {
      const self = this;
      const wrapped = function onceWrapper() {
        self.off(event, wrapped);
        cb.apply(self, arguments);
      };
      return self.on(event, wrapped);
    },
    off(event, cb) {
      const arr = listeners.get(event);
      if (arr) {
        const idx = arr.indexOf(cb);
        if (idx !== -1) arr.splice(idx, 1);
      }
      return this;
    },
    removeListener(event, cb) { return this.off(event, cb); },
    emit() { return true; },
  };
}

// ─── Main entry ───────────────────────────────────────────────

export async function handleMessages(body) {
  const msgId = genMsgId();
  const requestedModel = body.model || 'claude-sonnet-4.6';
  const wantStream = !!body.stream;
  const openaiBody = anthropicToOpenAI(body);

  if (!wantStream) {
    const result = await handleChatCompletions({ ...openaiBody, stream: false });
    if (result.status !== 200) {
      return {
        status: result.status,
        body: {
          type: 'error',
          error: {
            type: result.body?.error?.type || 'api_error',
            message: result.body?.error?.message || 'Unknown error',
          },
        },
      };
    }
    return { status: 200, body: openAIToAnthropic(result.body, requestedModel, msgId) };
  }

  // Streaming path — ask handleChatCompletions for its streaming handler and
  // point its writes at our translator shim. This lets the upstream Cascade
  // poll loop drive the downstream SSE in real time — no buffer-then-replay.
  const streamResult = await handleChatCompletions({ ...openaiBody, stream: true });

  if (!streamResult.stream) {
    // The OpenAI path returned a non-stream error (e.g. 403 model_not_entitled)
    return {
      status: streamResult.status || 502,
      body: {
        type: 'error',
        error: {
          type: streamResult.body?.error?.type || 'api_error',
          message: streamResult.body?.error?.message || 'Upstream error',
        },
      },
    };
  }

  return {
    status: 200,
    stream: true,
    headers: {
      'Content-Type': 'text/event-stream',
      'Cache-Control': 'no-cache',
      'Connection': 'keep-alive',
      'X-Accel-Buffering': 'no',
    },
    async handler(realRes) {
      const translator = new AnthropicStreamTranslator(realRes, msgId, requestedModel);
      const captureRes = createCaptureRes(translator);

      // Forward client disconnect so the upstream cascade is cancelled.
      // We don't call captureRes.end() here — that would set writableEnded=true
      // and suppress the abort path inside chat.js's stream handler.
      realRes.on('close', () => {
        if (!captureRes.writableEnded) captureRes._clientDisconnected();
      });

      try {
        await streamResult.handler(captureRes);
      } catch (e) {
        log.error(`Messages stream error: ${e.message}`);
        if (!translator.messageStarted) {
          translator.startMessage();
        }
        translator.finish();
      }

      if (!realRes.writableEnded) realRes.end();
    },
  };
}