Dramlog-Prod/src/services/analyze-bottle.ts

'use server';

import { geminiModel, SYSTEM_INSTRUCTION } from '@/lib/gemini';
import { BottleMetadataSchema, AnalysisResponse } from '@/types/whisky';
import { createServerActionClient } from '@supabase/auth-helpers-nextjs';
import { cookies } from 'next/headers';
import { createHash } from 'crypto';
import { trackApiUsage } from './track-api-usage';
import { checkCreditBalance, deductCredits } from './credit-service';

export async function analyzeBottle(base64Image: string, tags?: string[], locale: string = 'de'): Promise<AnalysisResponse> {
    const supabase = createServerActionClient({ cookies });

    if (!process.env.GEMINI_API_KEY) {
        return { success: false, error: 'GEMINI_API_KEY is not configured.' };
    }

    try {
        // ... (auth and credit check remain same) ...
        const { data: { session } } = await supabase.auth.getSession();
        if (!session || !session.user) {
            return { success: false, error: 'Nicht autorisiert oder Session abgelaufen.' };
        }

        const userId = session.user.id;

        const creditCheck = await checkCreditBalance(userId, 'gemini_ai');
        if (!creditCheck.allowed) {
            return {
                success: false,
                error: `Nicht genügend Credits. Du benötigst ${creditCheck.cost} Credits, hast aber nur ${creditCheck.balance}.`
            };
        }

        const base64Data = base64Image.split(',')[1] || base64Image;
        const imageHash = createHash('sha256').update(base64Data).digest('hex');

        const { data: cachedResult } = await supabase
            .from('vision_cache')
            .select('result')
            .eq('hash', imageHash)
            .maybeSingle();

        if (cachedResult) {
            return {
                success: true,
                data: cachedResult.result as any,
            };
        }

        const instruction = SYSTEM_INSTRUCTION
            .replace('{AVAILABLE_TAGS}', tags ? tags.join(', ') : 'No tags available')
            .replace('{LANGUAGE}', locale === 'en' ? 'English' : 'German');

        const result = await geminiModel.generateContent([
            {
                inlineData: {
                    data: base64Data,
                    mimeType: 'image/jpeg',
                },
            },
            { text: instruction },
        ]);

        const responseText = result.response.text();
        let jsonData = JSON.parse(responseText);

        if (Array.isArray(jsonData)) {
            jsonData = jsonData[0];
        }

        if (!jsonData) {
            throw new Error('Keine Daten in der KI-Antwort gefunden.');
        }

        const validatedData = BottleMetadataSchema.parse(jsonData);

        // Track successful API call
        await trackApiUsage({
            userId: userId,
            apiType: 'gemini_ai',
            endpoint: 'generateContent',
            success: true
        });

        // Deduct credits after successful API call
        const creditDeduction = await deductCredits(userId, 'gemini_ai', 'Bottle analysis');
        if (!creditDeduction.success) {
            console.error('Failed to deduct credits:', creditDeduction.error);
            // Don't fail the analysis if credit deduction fails
        }

        // 4. Store in Cache
        const { error: storeError } = await supabase
            .from('vision_cache')
            .insert({ hash: imageHash, result: validatedData });

        if (storeError) {
            console.warn(`[AI Cache] Storage failed: ${storeError.message}`);
        } else {
            console.log(`[AI Cache] Stored new result for hash: ${imageHash}`);
        }

        return {
            success: true,
            data: validatedData,
        };
    } catch (error) {
        console.error('Gemini Analysis Error:', error);

        // Track failed API call
        try {
            const { data: { session } } = await supabase.auth.getSession();
            if (session?.user) {
                await trackApiUsage({
                    userId: session.user.id,
                    apiType: 'gemini_ai',
                    endpoint: 'generateContent',
                    success: false,
                    errorMessage: error instanceof Error ? error.message : 'Unknown error'
                });
            }
        } catch (trackError) {
            console.error('Failed to track error:', trackError);
        }

        return {
            success: false,
            error: error instanceof Error ? error.message : 'An unknown error occurred during analysis.',
        };
    }
}