Add consent-gated media exchange library

src/ai/openrouter.ts

@@ -1,4 +1,5 @@
 import OpenAI from 'openai';
+import { z } from 'zod';
 import type { Config } from '../config/index.js';
 import type { Logger } from '../utils/logger.js';
 import type { AiUsageRecordInput, AiUsageOutcome } from '../database/ai-usage-repository.js';
@@ -10,6 +11,10 @@ import {
   type ConversationState,
 } from '../services/conversation-state.js';
 import { isSafeOutboundMessage } from '../services/outbound-message-safety.js';
+import {
+  MEDIA_LIBRARY_TAGS,
+  type MediaLibraryClassification,
+} from '../services/media-library-types.js';
 
 export type DetectedGender = 'male' | 'female' | 'other' | 'unknown';
 
@@ -142,6 +147,61 @@ export class OpenRouterClient {
     throw new Error('AI_REFUSAL: All models refused to analyze image');
   }
 
+  async classifyLibraryImage(imageBase64: string, mimeType: string): Promise<MediaLibraryClassification> {
+    const models = [
+      this.config.openrouter.imageAnalysisModel,
+      ...this.config.openrouter.imageAnalysisFallbackModels,
+    ];
+    let lastError: unknown = null;
+    for (const model of models) {
+      const startedAt = Date.now();
+      try {
+        const response = await this.client.chat.completions.create({
+          model,
+          messages: [{
+            role: 'user',
+            content: [
+              {
+                type: 'text',
+                text: `Classify this operator-owned adult image for a private media library. Return JSON only with this exact shape:
+{"tags":["selfie"],"safety":"sfw","description":"short neutral description","confidence":0.95}
+
+Allowed tags: ${MEDIA_LIBRARY_TAGS.join(', ')}.
+- selfie: a face-led or self-portrait style image
+- chest: a clothed chest or upper torso
+- topless: a bare chest or bare upper torso
+- penis: a visible penis
+- feet: feet are a material focus
+
+Use every applicable tag; tags may overlap. Set safety to "nsfw" when nudity, exposed genitals, or clearly sexual presentation is visible, otherwise "sfw". Confidence must be between 0 and 1. Do not identify the person, infer age, or add attributes outside this taxonomy.`,
+              },
+              {
+                type: 'image_url',
+                image_url: { url: `data:${mimeType};base64,${imageBase64}` },
+              },
+            ],
+          }],
+          max_tokens: 180,
+          temperature: 0,
+        });
+        const content = response.choices[0]?.message?.content ?? '';
+        const parsed = MediaLibraryClassificationSchema.parse(parseJsonObject(content));
+        this.recordUsage('classifyLibraryImage', model, startedAt, response, 'success');
+        return {
+          tags: [...new Set(parsed.tags)],
+          safety: parsed.safety,
+          description: parsed.description.trim().slice(0, 300),
+          confidence: parsed.confidence,
+        };
+      } catch (error) {
+        lastError = error;
+        this.recordError('classifyLibraryImage', model, startedAt, error);
+        this.logger.warn(`[AI] classifyLibraryImage: ${model} failed${model !== models.at(-1) ? ', trying fallback...' : ''}`);
+      }
+    }
+    throw lastError ?? new Error('Library image classification failed');
+  }
+
   private async tryAnalyzeWithModel(model: string, imageBase64: string, mimeType: string): Promise<ImageAnalysisResult | null> {
     const startedAt = Date.now();
     const genderPrompt = `First, identify the gender of the person in this image. Respond with EXACTLY one of these on the first line: GENDER:male, GENDER:female, GENDER:other, or GENDER:unknown
@@ -684,3 +744,18 @@ Just write the message, nothing else.`;
 function numericUsage(value: unknown): number {
   return typeof value === 'number' && Number.isFinite(value) ? Math.max(0, Math.trunc(value)) : 0;
 }
+
+const MediaLibraryClassificationSchema = z.strictObject({
+  tags: z.array(z.enum(MEDIA_LIBRARY_TAGS)).min(1),
+  safety: z.enum(['sfw', 'nsfw']),
+  description: z.string().min(1).max(500),
+  confidence: z.number().min(0).max(1),
+});
+
+function parseJsonObject(text: string): unknown {
+  const cleaned = text.trim().replace(/^```(?:json)?\s*/i, '').replace(/\s*```$/, '');
+  const start = cleaned.indexOf('{');
+  const end = cleaned.lastIndexOf('}');
+  if (start < 0 || end < start) throw new Error('Classifier returned no JSON object');
+  return JSON.parse(cleaned.slice(start, end + 1));
+}