import { NextRequest, NextResponse } from 'next/server';
import Anthropic from '@anthropic-ai/sdk';
import {
  buildTaskGenerationPrompt,
  buildCodeReviewPrompt,
  buildChatPrompt,
  buildLessonPrompt,
  buildClassroomChatPrompt,
} from '@/lib/prompts';
import { PROVIDER_MAP } from '@/lib/providers';
import type { AIRequestBody, ProviderConfig } from '@/types';

// ─── Anthropic streaming ────────────────────────────────────────────────────

async function streamAnthropic(
  config: ProviderConfig,
  systemPrompt: string,
  messages: Anthropic.MessageParam[],
  controller: ReadableStreamDefaultController
) {
  const client = config.apiKey
    ? new Anthropic({ apiKey: config.apiKey })
    : new Anthropic(); // falls back to ANTHROPIC_API_KEY env var

  const stream = await client.messages.stream({
    model: config.model,
    max_tokens: 2048,
    system: systemPrompt,
    messages,
  });

  for await (const chunk of stream) {
    if (chunk.type === 'content_block_delta' && chunk.delta.type === 'text_delta') {
      controller.enqueue(new TextEncoder().encode(chunk.delta.text));
    }
  }
}

// ─── OpenAI-compatible streaming (OpenRouter, LM Studio, Ollama) ────────────

async function streamOpenAICompatible(
  config: ProviderConfig,
  systemPrompt: string,
  messages: Array<{ role: 'user' | 'assistant'; content: string }>,
  controller: ReadableStreamDefaultController
) {
  const providerDef = PROVIDER_MAP[config.provider];
  const baseUrl = config.baseUrl ?? providerDef.defaultBaseUrl;
  const apiKey = config.apiKey || 'none'; // LM Studio / Ollama accept any value

  const headers: Record<string, string> = {
    'Content-Type': 'application/json',
    Authorization: `Bearer ${apiKey}`,
  };

  // OpenRouter requires attribution headers
  if (config.provider === 'openrouter') {
    headers['HTTP-Referer'] = 'http://localhost:3000';
    headers['X-Title'] = 'Professor';
  }

  const res = await fetch(`${baseUrl}/chat/completions`, {
    method: 'POST',
    headers,
    body: JSON.stringify({
      model: config.model,
      messages: [{ role: 'system', content: systemPrompt }, ...messages],
      stream: true,
    }),
  });

  if (!res.ok || !res.body) {
    const text = await res.text().catch(() => res.statusText);
    throw new Error(`${providerDef.label} error ${res.status}: ${text}`);
  }

  // Parse SSE stream
  const reader = res.body.getReader();
  const decoder = new TextDecoder();
  let buffer = '';

  while (true) {
    const { done, value } = await reader.read();
    if (done) break;

    buffer += decoder.decode(value, { stream: true });
    const lines = buffer.split('\n');
    buffer = lines.pop() ?? '';

    for (const line of lines) {
      const trimmed = line.trim();
      if (!trimmed.startsWith('data: ')) continue;
      const data = trimmed.slice(6);
      if (data === '[DONE]') return;
      try {
        const json = JSON.parse(data);
        const content = json.choices?.[0]?.delta?.content;
        if (content) controller.enqueue(new TextEncoder().encode(content));
      } catch {
        // ignore malformed SSE lines
      }
    }
  }
}

// ─── Route handler ──────────────────────────────────────────────────────────

export async function POST(req: NextRequest) {
  let body: AIRequestBody;
  try {
    body = await req.json();
  } catch {
    return NextResponse.json({ error: 'Invalid JSON' }, { status: 400 });
  }

  const { mode, topic, code, executionResult, messages, userMessage, providerConfig, responseMode } = body;

  if (!mode || !topic || !providerConfig) {
    return NextResponse.json({ error: 'Missing required fields' }, { status: 400 });
  }

  // Build system prompt
  let systemPrompt: string;
  switch (mode) {
    case 'generate_task':
      systemPrompt = buildTaskGenerationPrompt(topic);
      break;
    case 'review_code':
      systemPrompt = buildCodeReviewPrompt(topic, code, executionResult, responseMode);
      break;
    case 'chat':
      systemPrompt = buildChatPrompt(topic, code, responseMode);
      break;
    case 'generate_lesson':
      systemPrompt = buildLessonPrompt(topic);
      break;
    case 'classroom_chat':
      systemPrompt = buildClassroomChatPrompt(topic);
      break;
    default:
      return NextResponse.json({ error: 'Invalid mode' }, { status: 400 });
  }

  // Build message list
  const chatMessages: Array<{ role: 'user' | 'assistant'; content: string }> =
    mode === 'generate_task'
      ? [{ role: 'user', content: 'Generate a task for this topic.' }]
      : mode === 'review_code'
      ? [{ role: 'user', content: 'Please review my code and give me feedback.' }]
      : mode === 'generate_lesson'
      ? [{ role: 'user', content: 'Write the lesson.' }]
      : [
          ...(messages ?? []).map((m) => ({
            role: m.role as 'user' | 'assistant',
            content: m.content,
          })),
          ...(userMessage ? [{ role: 'user' as const, content: userMessage }] : []),
        ];

  const stream = new ReadableStream({
    async start(controller) {
      try {
        if (providerConfig.provider === 'anthropic') {
          await streamAnthropic(providerConfig, systemPrompt, chatMessages, controller);
        } else {
          await streamOpenAICompatible(providerConfig, systemPrompt, chatMessages, controller);
        }
        controller.close();
      } catch (err) {
        const message = err instanceof Error ? err.message : 'AI error';
        controller.enqueue(new TextEncoder().encode(`\n\n[Error: ${message}]`));
        controller.close();
      }
    },
  });

  return new Response(stream, {
    headers: {
      'Content-Type': 'text/plain; charset=utf-8',
      'Transfer-Encoding': 'chunked',
      'Cache-Control': 'no-cache',
    },
  });
}