apix/app/api/meta-chat/route.ts

import { NextRequest, NextResponse } from 'next/server';
import { MetaAIClient } from '@/lib/providers/meta-client';

/**
 * Meta AI Chat API
 * Uses MetaAIClient directly (GraphQL-based) for Llama 3 chat
 * No external Crawl4AI service needed
 */
export async function POST(req: NextRequest) {
    try {
        const body = await req.json();
        const { message, history, metaCookies } = body;

        if (!message) {
            return NextResponse.json({ error: "Message is required" }, { status: 400 });
        }

        if (!metaCookies) {
            return NextResponse.json(
                { error: "Meta AI cookies required. Configure in Settings." },
                { status: 401 }
            );
        }

        console.log(`[Meta Chat] Message: "${message.substring(0, 50)}..."`);

        // Use MetaAIClient to send chat message
        // The Meta AI API is primarily designed for image generation,
        // but we can use it for text chat by not prefixing with "Imagine"
        const client = new MetaAIClient({ cookies: metaCookies });

        // For chat, we need to initialize session and send via GraphQL
        // Since MetaAIClient.generate() adds "Imagine" prefix for images,
        // we'll create a direct chat method or adapt the prompt

        // Send message directly - the response will contain text, not images
        const chatPrompt = message; // Don't add "Imagine" prefix for chat

        try {
            // Use the internal sendPrompt mechanism via generate
            // But we'll extract the text response instead of images
            const response = await sendMetaChatMessage(client, chatPrompt, metaCookies);
            return NextResponse.json({ response });
        } catch (chatError: any) {
            // If the direct approach fails, provide helpful error
            throw new Error(chatError.message || "Failed to get response from Meta AI");
        }

    } catch (error: any) {
        console.error('[Meta Chat] Error:', error);

        const msg = error.message || "";
        const isAuthError = msg.includes("401") || msg.includes("cookies") ||
            msg.includes("expired") || msg.includes("Login");

        return NextResponse.json(
            { error: error.message || 'Internal Server Error' },
            { status: isAuthError ? 401 : 500 }
        );
    }
}

/**
 * Send a chat message to Meta AI and extract text response
 */
async function sendMetaChatMessage(client: MetaAIClient, message: string, cookies: string): Promise<string> {
    const META_AI_BASE = "https://www.meta.ai";
    const GRAPHQL_ENDPOINT = `${META_AI_BASE}/api/graphql/`;

    // Normalize cookies from JSON array to string format
    const normalizedCookies = normalizeCookies(cookies);

    // First we need to get session tokens
    const sessionResponse = await fetch(META_AI_BASE, {
        headers: {
            "Cookie": normalizedCookies,
            "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36",
        }
    });
    const html = await sessionResponse.text();

    // Extract LSD token
    const lsdMatch = html.match(/\"LSD\",\[\],\{\"token\":\"([^\"]+)\"/) ||
        html.match(/\"lsd\":\"([^\"]+)\"/) ||
        html.match(/name=\"lsd\" value=\"([^\"]+)\"/);
    const lsd = lsdMatch?.[1] || '';

    // Extract access token
    const tokenMatch = html.match(/\"accessToken\":\"([^\"]+)\"/);
    const accessToken = tokenMatch?.[1];

    if (html.includes('login_form') || html.includes('login_page')) {
        throw new Error("Meta AI: Cookies expired. Please update in Settings.");
    }

    // Send chat message
    const variables = {
        message: {
            text: message,
            content_type: "TEXT"
        },
        source: "PDT_CHAT_INPUT",
        external_message_id: Math.random().toString(36).substring(2) + Date.now().toString(36)
    };

    const body = new URLSearchParams({
        fb_api_caller_class: "RelayModern",
        fb_api_req_friendly_name: "useAbraSendMessageMutation",
        variables: JSON.stringify(variables),
        doc_id: "7783822248314888",
        ...(lsd && { lsd }),
    });

    const response = await fetch(GRAPHQL_ENDPOINT, {
        method: "POST",
        headers: {
            "Content-Type": "application/x-www-form-urlencoded",
            "Cookie": normalizedCookies,
            "Origin": META_AI_BASE,
            "Referer": `${META_AI_BASE}/`,
            "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/122.0.0.0 Safari/537.36",
            "Sec-Fetch-Site": "same-origin",
            "Sec-Fetch-Mode": "cors",
            "Sec-Fetch-Dest": "empty",
            "Accept": "application/json",
            "Accept-Language": "en-US,en;q=0.9",
            ...(accessToken && { "Authorization": `OAuth ${accessToken}` })
        },
        body: body.toString()
    });

    // Get response text first
    const responseText = await response.text();

    // Check if response is HTML (error page)
    if (responseText.trim().startsWith('<') || responseText.includes('<!DOCTYPE')) {
        console.error('[Meta Chat] Received HTML instead of JSON:', responseText.substring(0, 200));
        if (responseText.includes('login') || responseText.includes('checkpoint')) {
            throw new Error("Meta AI: Cookies expired or account requires verification. Please update cookies in Settings.");
        }
        throw new Error("Meta AI: Service returned an error page. Please try again later.");
    }

    if (!response.ok) {
        console.error('[Meta Chat] Response not OK:', response.status, responseText.substring(0, 200));
        throw new Error(`Meta AI Error: ${response.status}`);
    }

    // Parse JSON response
    let data;
    try {
        data = JSON.parse(responseText);
    } catch (e) {
        console.error('[Meta Chat] Failed to parse JSON:', responseText.substring(0, 200));
        throw new Error("Meta AI: Invalid response format. Please try again.");
    }

    // Extract text response from the GraphQL response
    const messageData = data?.data?.node?.bot_response_message ||
        data?.data?.xabraAIPreviewMessageSendMutation?.message;

    // Check for GraphQL errors
    if (data?.errors) {
        console.error('[Meta Chat] GraphQL errors:', JSON.stringify(data.errors));
        throw new Error("Meta AI: Request failed. " + (data.errors[0]?.message || "Unknown error"));
    }

    const textResponse = messageData?.text ||
        messageData?.snippet ||
        messageData?.message_text ||
        "I'm sorry, I couldn't generate a response.";

    return textResponse;
}

/**
 * Normalize cookies from JSON array format to header string format
 * Handles: [{name: "foo", value: "bar"}, ...] -> "foo=bar; ..."
 */
function normalizeCookies(cookies: string): string {
    if (!cookies) return '';

    try {
        const trimmed = cookies.trim();
        // Check if it's JSON array
        if (trimmed.startsWith('[')) {
            const parsed = JSON.parse(trimmed);
            if (Array.isArray(parsed)) {
                return parsed
                    .map((c: any) => `${c.name}=${c.value}`)
                    .join('; ');
            }
        }
        // Check if it's JSON object with multiple arrays (merged cookies)
        if (trimmed.startsWith('{')) {
            const parsed = JSON.parse(trimmed);
            // If it's an object, iterate values
            const entries = Object.entries(parsed)
                .map(([k, v]) => `${k}=${v}`)
                .join('; ');
            return entries;
        }
    } catch (e) {
        // Not JSON, assume it's already a string format
    }

    return cookies;
}