Increase meme funniness requirements

README.md

@@ -20,6 +20,7 @@ The server listens on `http://localhost:8080` by default.
 - `ADMIN_TOKEN`: secret review URL token. If omitted, one is generated at boot and printed in server logs.
 - `OPENAI_API_KEY`: enables AI upload moderation. Without it, uploads are queued for admin review.
 - `OPENAI_MODERATION_MODEL`: moderation vision model, default `gpt-4o-mini`
+- `AUTO_APPROVE_MIN_SCORE`: minimum `MEME_CONSENSUS_SCORE` for immediate AI approval, default `80`
 - `TRUST_PROXY`: set to `true` when running behind a trusted reverse proxy so upload limits use `X-Forwarded-For`
 
 Uploads accept PNG and JPEG images. The server rejects files over 5 MB, any image edge over `6000px`, and images over 20 million pixels. Accepted uploads are decoded, metadata-stripped, resized so the longest edge is at most `1600px`, and stored as WebP.

docker-compose.yaml

@@ -15,6 +15,7 @@ services:
       ADMIN_TOKEN: ${ADMIN_TOKEN}
       OPENAI_API_KEY: ${OPENAI_API_KEY}
       OPENAI_MODERATION_MODEL: ${OPENAI_MODERATION_MODEL:-gpt-4o-mini}
+      AUTO_APPROVE_MIN_SCORE: ${AUTO_APPROVE_MIN_SCORE:-80}
       MAX_IMAGE_DIMENSION: ${MAX_IMAGE_DIMENSION:-1600}
       WEBP_QUALITY: ${WEBP_QUALITY:-85}
     volumes:

src/moderation.js

@@ -1,5 +1,5 @@
 const DEFAULT_MODEL = process.env.OPENAI_MODERATION_MODEL || 'gpt-4o-mini';
-const AUTO_APPROVE_MIN_SCORE = 80;
+const DEFAULT_AUTO_APPROVE_MIN_SCORE = 80;
 
 export async function moderateImage({ buffer, mime }) {
   if (!process.env.OPENAI_API_KEY) {
@@ -59,6 +59,7 @@ export async function moderateImage({ buffer, mime }) {
 }
 
 function moderationPrompt() {
+  const autoApproveMinScore = autoApproveMinScoreValue();
   return [
     'You are moderating image uploads for THE_MEME_PROTOCOL, a meme gallery.',
     'This is a meme site. Images may be sarcastic, roasting, edgy, political, profane, absurd, or not PG-13.',
@@ -72,7 +73,7 @@ function moderationPrompt() {
     'Assign MEME_CONSENSUS_SCORE from 0-100: higher means it is legal, clearly a meme/reaction/roast/remix, visually meaningful, has a real punchline, and is suitable for this site; lower means random photo, spam, ad, QR scam, screenshot dump, unclear, generic template caption, text-only joke, weak payoff, or AI-slop.',
     'Return only compact JSON with keys: decision, score, reason.',
     'decision must be one of: approved, pending, rejected.',
-    `Use approved only when it appears legal and score is at least ${AUTO_APPROVE_MIN_SCORE}.`,
+    `Use approved only when it appears legal and score is at least ${autoApproveMinScore}.`,
     'Use pending for ambiguity, uncertainty, low meme relevance, weak quality, generic/slop memes, or anything that needs human review.',
     'Use rejected only for likely illegal content.'
   ].join('\n');
@@ -100,12 +101,19 @@ function normalizeDecision(raw) {
     ? raw.reason.trim().slice(0, 300)
     : 'No moderation reason supplied.';
 
-  if (decision === 'approved' && score < AUTO_APPROVE_MIN_SCORE) {
+  const autoApproveMinScore = autoApproveMinScoreValue();
+  if (decision === 'approved' && score < autoApproveMinScore) {
     return { status: 'pending', score, reason: `${reason} Low MEME_CONSENSUS_SCORE queued for review.` };
   }
   return { status: decision, score, reason };
 }
 
+function autoApproveMinScoreValue() {
+  const value = Number.parseInt(process.env.AUTO_APPROVE_MIN_SCORE || '', 10);
+  if (!Number.isFinite(value)) return DEFAULT_AUTO_APPROVE_MIN_SCORE;
+  return Math.max(0, Math.min(100, value));
+}
+
 function extractOutputText(payload) {
   const parts = [];
   for (const item of payload.output || []) {

tests/moderation.test.js

@@ -27,22 +27,24 @@ test('queues uploads when AI moderation is not configured', async () => {
 
 test('queues model approvals below the auto-publish quality threshold', async () => {
   const originalApiKey = process.env.OPENAI_API_KEY;
+  const originalThreshold = process.env.AUTO_APPROVE_MIN_SCORE;
   const originalFetch = globalThis.fetch;
   process.env.OPENAI_API_KEY = 'test-key';
+  process.env.AUTO_APPROVE_MIN_SCORE = '90';
 
   globalThis.fetch = async (_url, options) => {
     const body = JSON.parse(options.body);
     const prompt = body.input[0].content.find((item) => item.type === 'input_text').text;
 
     assert.match(prompt, /could the exact same caption work on 50 unrelated images/);
-    assert.match(prompt, /Use approved only when it appears legal and score is at least 80/);
+    assert.match(prompt, /Use approved only when it appears legal and score is at least 90/);
 
     return {
       ok: true,
       json: async () => ({
         output_text: JSON.stringify({
           decision: 'approved',
-          score: 79,
+          score: 89,
           reason: 'Specific joke, but not strong enough.'
         })
       })
@@ -56,7 +58,7 @@ test('queues model approvals below the auto-publish quality threshold', async ()
     });
 
     assert.equal(moderation.status, 'pending');
-    assert.equal(moderation.score, 79);
+    assert.equal(moderation.score, 89);
     assert.match(moderation.reason, /Low MEME_CONSENSUS_SCORE queued for review/);
   } finally {
     globalThis.fetch = originalFetch;
@@ -65,5 +67,10 @@ test('queues model approvals below the auto-publish quality threshold', async ()
     } else {
       process.env.OPENAI_API_KEY = originalApiKey;
     }
+    if (originalThreshold === undefined) {
+      delete process.env.AUTO_APPROVE_MIN_SCORE;
+    } else {
+      process.env.AUTO_APPROVE_MIN_SCORE = originalThreshold;
+    }
   }
 });