import {
  streamText,
  convertToModelMessages,
  stepCountIs,
  pruneMessages,
} from 'ai';
import { createOpenRouter } from '@openrouter/ai-sdk-provider';
import { tools } from '@/chat.config';

const openrouter = createOpenRouter({
  apiKey: process.env.OPENROUTER_API_KEY,
});

export async function POST(request: Request) {
  try {
    const { messages } = await request.json();

    if (!process.env.OPENROUTER_API_KEY) {
      return Response.json(
        { error: 'OPENROUTER_API_KEY is not configured' },
        { status: 503 }
      );
    }

    const model = openrouter(
      process.env.OPENROUTER_MODEL || 'openai/gpt-5.6-luna-pro'
    );

    const webSearchEnabled = Boolean(process.env.FIRECRAWL_API_KEY);

    const instructions = webSearchEnabled
      ? `You are an expert ChatGPT Agent with real-time access to the internet.

Your capabilities:
- Search the web using Firecrawl to find up-to-date information
- Fetch and read full web pages to extract detailed content
- Synthesize information from multiple sources into clear, accurate answers
- Cite your sources inline so the user can verify information

Guidelines:
- Always search the web before answering questions that require current or factual information
- Use multiple searches when needed to get comprehensive answers
- Cross-reference sources for accuracy
- Structure your responses clearly with headings, bullet points, and citations where appropriate
- When fetching pages, extract only the relevant information
- Be transparent about the sources you used
- Today's date is ${new Date().toLocaleDateString('en-US', { weekday: 'long', year: 'numeric', month: 'long', day: 'numeric' })}`
      : `You are a helpful AI research assistant. Answer clearly and accurately. You do not have live web access, so be transparent when a question requires current information. Today's date is ${new Date().toLocaleDateString('en-US', { weekday: 'long', year: 'numeric', month: 'long', day: 'numeric' })}.`;

    const convertedMessages = await convertToModelMessages(messages);

    const prunedMessages = pruneMessages({
      messages: convertedMessages,
      reasoning: 'all',
      toolCalls: 'none',
    });

    const result = await streamText({
      model,
      instructions,
      messages: prunedMessages,
      tools: webSearchEnabled ? tools : {},
      stopWhen: stepCountIs(20),
      providerOptions: {
        openrouter: {
          reasoning: {
            enabled: true,
            effort: 'medium',
          },
        },
      },
    });

    return result.toUIMessageStreamResponse({ sendReasoning: true });
  } catch (error) {
    console.error('Chat API error:', error);
    return new Response(
      JSON.stringify({ error: 'Failed to process chat request' }),
      {
        status: 500,
        headers: { 'Content-Type': 'application/json' },
      }
    );
  }
}