Update inspiration FAQ to reference waxwing's Primal post and the Meteor paper

www/js/stego.mjs

@@ -0,0 +1,345 @@
+/**
+ * LLM-based steganography — JavaScript port of stego.py.
+ *
+ * Half-splitting entropy coding on top of GPT-2's next-token distribution.
+ * Both encoder and decoder run the same JS code with the same PRNG seed,
+ * so they stay synchronized regardless of cross-language PRNG differences.
+ */
+
+import { Tensor } from "https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.0.0";
+
+// ---------------------------------------------------------------------------
+// PRNG — mulberry32 (deterministic given seed)
+// ---------------------------------------------------------------------------
+export function mulberry32(seed) {
+    let a = seed >>> 0;
+    return function random() {
+        a = (a + 0x6D2B79F5) >>> 0;
+        let t = Math.imul(a ^ (a >>> 15), 1 | a);
+        t = (t + Math.imul(t ^ (t >>> 7), 61 | t)) ^ t;
+        return ((t ^ (t >>> 14)) >>> 0) / 4294967296;
+    };
+}
+
+// ---------------------------------------------------------------------------
+// Bit <-> string conversion (UTF-8)
+// ---------------------------------------------------------------------------
+export function strToBits(s) {
+    const data = new TextEncoder().encode(s);
+    const bits = [];
+    for (const byte of data) {
+        for (let i = 7; i >= 0; i--) {
+            bits.push((byte >> i) & 1);
+        }
+    }
+    return bits;
+}
+
+export function bitsToStr(bits) {
+    // Pad to a multiple of 8 (should already be).
+    const padded = bits.slice();
+    while (padded.length % 8 !== 0) padded.push(0);
+    const bytes = new Uint8Array(Math.floor(padded.length / 8));
+    for (let i = 0; i < padded.length; i += 8) {
+        let byte = 0;
+        for (let j = 0; j < 8; j++) {
+            byte = (byte << 1) | padded[i + j];
+        }
+        bytes[i / 8] = byte;
+    }
+    return new TextDecoder("utf-8", { fatal: false }).decode(bytes);
+}
+
+// ---------------------------------------------------------------------------
+// Softmax over a TypedArray / Array of logits (numerically stable)
+// ---------------------------------------------------------------------------
+function softmax(logits) {
+    let max = -Infinity;
+    for (let i = 0; i < logits.length; i++) {
+        if (logits[i] > max) max = logits[i];
+    }
+    const probs = new Float32Array(logits.length);
+    let sum = 0;
+    for (let i = 0; i < logits.length; i++) {
+        const e = Math.exp(logits[i] - max);
+        probs[i] = e;
+        sum += e;
+    }
+    if (sum <= 0) sum = 1;
+    for (let i = 0; i < logits.length; i++) {
+        probs[i] /= sum;
+    }
+    return probs;
+}
+
+// ---------------------------------------------------------------------------
+// Next-token probability distribution from the model.
+// Returns a Float32Array of length vocab_size.
+// ---------------------------------------------------------------------------
+async function nextTokenProbs(model, tokenizer, tokenIds) {
+    // Build the model inputs directly from the token-id array. We must NOT
+    // pass the id array through tokenizer(): in Transformers.js v3 the
+    // tokenizer call expects a string and will fail with
+    // "e.split is not a function" when given numbers. Instead we construct
+    // int64 tensors ourselves and feed them straight to the model.
+    const seqLength = tokenIds.length;
+    const idData = BigInt64Array.from(tokenIds, (x) => BigInt(x));
+    const maskData = BigInt64Array.from({ length: seqLength }, () => 1n);
+    const inputs = {
+        input_ids: new Tensor("int64", idData, [1, seqLength]),
+        attention_mask: new Tensor("int64", maskData, [1, seqLength]),
+    };
+    const output = await model(inputs);
+    const logits = output.logits;
+
+    // logits.dims = [batch, seq_len, vocab_size]
+    const dims = logits.dims;
+    const seqLen = dims[1];
+    const vocabSize = dims[2];
+    const data = logits.data;
+
+    // Extract the last token's logits: row = (batch=0, last token, :)
+    const offset = (seqLen - 1) * vocabSize;
+    const lastLogits = new Float32Array(vocabSize);
+    for (let i = 0; i < vocabSize; i++) {
+        lastLogits[i] = data[offset + i];
+    }
+    return softmax(lastLogits);
+}
+
+// ---------------------------------------------------------------------------
+// Split the sorted vocabulary into two halves at cumulative prob 0.50.
+// Returns { firstIds, firstProbs, secondIds, secondProbs }.
+// ---------------------------------------------------------------------------
+export function splitHalves(probs) {
+    const vocabSize = probs.length;
+
+    // Build an index array covering EVERY token id [0 .. vocabSize-1] and
+    // sort it by probability descending. Sorting indices (rather than
+    // dropping any) guarantees that all token ids are retained and that the
+    // two slices below form a complete, disjoint partition of the vocabulary.
+    // Ties are broken by ascending token id so the ordering is fully
+    // deterministic — important under int8 quantization where many logits can
+    // be exactly equal (an unstable sort could otherwise diverge between the
+    // encoder and decoder passes).
+    const sortedIds = new Array(vocabSize);
+    for (let i = 0; i < vocabSize; i++) sortedIds[i] = i;
+    sortedIds.sort((a, b) => {
+        const diff = probs[b] - probs[a];
+        if (diff !== 0) return diff;
+        return a - b; // stable tie-break by token id
+    });
+
+    // Find the split point: the first index at which the cumulative
+    // probability mass reaches/exceeds 0.50. Everything up to and including
+    // that token forms the first half; the remainder forms the second half.
+    let cum = 0.0;
+    let splitIdx = vocabSize; // default: all mass in first half (edge case)
+    for (let i = 0; i < vocabSize; i++) {
+        cum += probs[sortedIds[i]];
+        if (cum >= 0.50) {
+            splitIdx = i + 1; // include this token in the first half
+            break;
+        }
+    }
+
+    // Clamp so BOTH halves are guaranteed non-empty. The split index must be
+    // at least 1 (first half non-empty) and at most vocabSize-1 (second half
+    // non-empty). This handles degenerate distributions where a single token
+    // already holds >= 0.50 of the mass, or where the mass never reaches 0.50.
+    if (splitIdx < 1) splitIdx = 1;
+    if (splitIdx > vocabSize - 1) splitIdx = vocabSize - 1;
+
+    // slice(0, splitIdx) + slice(splitIdx) ALWAYS covers the entire sorted
+    // array, so every token id appears in exactly one half — none missing,
+    // none duplicated. Ids are plain Numbers (0..vocabSize-1).
+    const firstIds = sortedIds.slice(0, splitIdx);
+    const secondIds = sortedIds.slice(splitIdx);
+    const firstProbs = firstIds.map(id => probs[id]);
+    const secondProbs = secondIds.map(id => probs[id]);
+
+    return { firstIds, firstProbs, secondIds, secondProbs };
+}
+
+// ---------------------------------------------------------------------------
+// Sample a token id from the given half using renormalized probabilities.
+// Advances the PRNG exactly once (one call to rng()).
+// ---------------------------------------------------------------------------
+export function sampleWithinHalf(ids, probs, rng) {
+    let total = 0;
+    for (let i = 0; i < probs.length; i++) total += probs[i];
+    if (total <= 0) total = 1;
+    const r = rng();
+    let cum = 0.0;
+    let chosen = ids[ids.length - 1];
+    for (let i = 0; i < ids.length; i++) {
+        cum += probs[i] / total;
+        if (r < cum) {
+            chosen = ids[i];
+            break;
+        }
+    }
+    return chosen;
+}
+
+// ---------------------------------------------------------------------------
+// Encoder
+// ---------------------------------------------------------------------------
+export async function encode(model, tokenizer, secretMessage, context, key, padTokens = 3, onToken = null) {
+    const rng = mulberry32(key >>> 0);
+    const bits = strToBits(secretMessage);
+    const numBits = bits.length;
+    const totalBits = numBits;
+    const totalChars = secretMessage.length;
+
+    // Tokenize the context. Transformers.js tokenizer() returns an object
+    // with input_ids; we extract the raw id array.
+    const tokenIds = tokenizeToIds(tokenizer, context);
+
+    for (let bitIndex = 0; bitIndex < bits.length; bitIndex++) {
+        const bit = bits[bitIndex];
+        const probs = await nextTokenProbs(model, tokenizer, tokenIds);
+        const { firstIds, firstProbs, secondIds, secondProbs } = splitHalves(probs);
+        let chosen;
+        if (bit === 0) {
+            chosen = sampleWithinHalf(firstIds, firstProbs, rng);
+        } else {
+            chosen = sampleWithinHalf(secondIds, secondProbs, rng);
+        }
+        tokenIds.push(chosen);
+
+        // Stream the partial cover text back to the caller and yield to the
+        // browser so the UI can repaint between (slow) forward passes.
+        if (onToken) {
+            const textSoFar = tokenizer.decode(tokenIds, { skip_special_tokens: true });
+            const charIndex = Math.floor(bitIndex / 8) + 1;
+            const currentChar = secretMessage[charIndex - 1] ?? "";
+            onToken(textSoFar, bitIndex + 1, totalBits, currentChar, charIndex, totalChars);
+        }
+        await new Promise(resolve => setTimeout(resolve, 0));
+    }
+
+    // Padding tokens: sample from the full distribution using the same PRNG.
+    for (let p = 0; p < padTokens; p++) {
+        const probs = await nextTokenProbs(model, tokenizer, tokenIds);
+        // Sort descending.
+        const pairs = [];
+        for (let i = 0; i < probs.length; i++) pairs.push([probs[i], i]);
+        pairs.sort((a, b) => b[0] - a[0]);
+        const sp = pairs.map(x => x[0]);
+        const si = pairs.map(x => x[1]);
+        let total = 0;
+        for (let i = 0; i < sp.length; i++) total += sp[i];
+        if (total <= 0) total = 1;
+        const r = rng();
+        let cum = 0.0;
+        let chosen = si[0];
+        for (let i = 0; i < si.length; i++) {
+            cum += sp[i] / total;
+            if (r < cum) {
+                chosen = si[i];
+                break;
+            }
+        }
+        tokenIds.push(chosen);
+    }
+
+    const coverText = tokenizer.decode(tokenIds, { skip_special_tokens: true });
+    return { coverText, numBits, tokenCount: tokenIds.length };
+}
+
+// ---------------------------------------------------------------------------
+// Decoder
+// ---------------------------------------------------------------------------
+export async function decode(model, tokenizer, coverText, context, key, numBits, padTokens = 3, onProgress = null) {
+    const rng = mulberry32(key >>> 0);
+    const totalBits = numBits;
+
+    const contextIds = tokenizeToIds(tokenizer, context);
+    const coverIds = tokenizeToIds(tokenizer, coverText);
+
+    // Generated tokens are everything after the context prefix.
+    const genIds = coverIds.slice(contextIds.length);
+
+    const tokenIds = contextIds.slice();
+    const bits = [];
+
+    for (const genToken of genIds) {
+        if (bits.length >= numBits) break;
+        const probs = await nextTokenProbs(model, tokenizer, tokenIds);
+        const { firstIds, firstProbs, secondIds, secondProbs } = splitHalves(probs);
+
+        // splitHalves yields plain Number ids and partitions the entire
+        // vocabulary, so a normalized (Number) genToken is guaranteed to be in
+        // exactly one half. tokenizeToIds normalizes ids to Number, but coerce
+        // defensively here too in case a BigInt slips through.
+        const token = typeof genToken === "bigint" ? Number(genToken) : genToken;
+        const firstSet = new Set(firstIds);
+        const secondSet = new Set(secondIds);
+
+        let recoveredBit;
+        if (firstSet.has(token)) {
+            recoveredBit = 0;
+            bits.push(0);
+            // Advance PRNG identically to the encoder.
+            sampleWithinHalf(firstIds, firstProbs, rng);
+        } else if (secondSet.has(token)) {
+            recoveredBit = 1;
+            bits.push(1);
+            sampleWithinHalf(secondIds, secondProbs, rng);
+        } else {
+            throw new Error(`Generated token ${token} not found in either half.`);
+        }
+        tokenIds.push(token);
+
+        // Report progress and yield so the UI can repaint between passes.
+        if (onProgress) {
+            const currentToken = tokenizer.decode([token], { skip_special_tokens: true });
+            const completedBytes = Math.floor(bits.length / 8);
+            const recoveredChars = bitsToStr(bits.slice(0, completedBytes * 8));
+            onProgress(
+                bits.length,
+                totalBits,
+                recoveredChars,
+                currentToken,
+                recoveredBit,
+            );
+        }
+        await new Promise(resolve => setTimeout(resolve, 0));
+    }
+
+    return bitsToStr(bits.slice(0, numBits));
+}
+
+// ---------------------------------------------------------------------------
+// Helper: tokenize a string to a plain array of token ids.
+// Handles the various shapes Transformers.js may return.
+// ---------------------------------------------------------------------------
+function tokenizeToIds(tokenizer, text) {
+    const inputs = tokenizer(text, { add_special_tokens: false });
+    let ids;
+    if (inputs && inputs.input_ids) {
+        ids = inputs.input_ids;
+    } else if (Array.isArray(inputs)) {
+        ids = inputs;
+    } else {
+        ids = inputs;
+    }
+    // ids may be a Tensor or a nested array like [[1,2,3]].
+    let arr;
+    if (ids && typeof ids.data !== "undefined" && ids.dims) {
+        arr = Array.from(ids.data);
+    } else if (Array.isArray(ids)) {
+        // Flatten one level if nested: [[...]] -> [...]
+        arr = (ids.length > 0 && Array.isArray(ids[0])) ? ids[0].slice() : ids.slice();
+    } else {
+        // Fallback: try to iterate.
+        arr = Array.from(ids);
+    }
+    // CRITICAL: token tensors are int64, so ids.data is a BigInt64Array and
+    // Array.from() yields BigInts (e.g. 351n). splitHalves produces plain
+    // Number ids, and `new Set([...Numbers]).has(351n)` is false — which is
+    // exactly what caused "Generated token 351 not found in either half".
+    // Normalize every id to a plain Number so membership checks line up.
+    return arr.map(v => (typeof v === "bigint" ? Number(v) : Number(v)));
+}

www/js/version.json

@@ -1,5 +1,5 @@
 {
-  "VERSION": "v0.7.51",
-  "VERSION_NUMBER": "0.7.51",
-  "BUILD_DATE": "2026-06-26T17:29:49.389Z"
+  "VERSION": "v0.7.62",
+  "VERSION_NUMBER": "0.7.62",
+  "BUILD_DATE": "2026-06-29T00:30:26.801Z"
 }

www/ndk-worker.js

@@ -6443,73 +6443,200 @@ async function handleSetRelayEventLogging(requestId, enabled, port) {
 // from followed authors who write to relays the user does not subscribe to.
 // For each discovered relay we also report which followed pubkeys it serves,
 // by inverting ndk.outboxTracker.data (pubkey -> OutboxItem{writeRelays}).
+function shortHexPubkey(hex) {
+    if (!hex || hex.length < 16) return hex || '-';
+    return `${hex.slice(0, 8)}…${hex.slice(-4)}`;
+}
+
+// Cache for discovered relays — rebuilt only when the contact list changes.
+// The version suffix forces a rebuild when the handler code changes (e.g.
+// adding servingNames).
+let discoveredRelaysCache = null;
+let discoveredRelaysCacheKey = '';
+const DISCOVERED_RELAYS_CACHE_VERSION = 'v3-names-k0';
+
 async function handleGetDiscoveredRelays(requestId, port) {
     try {
-        if (!ndk?.pool?.relays) {
-            port.postMessage({
-                type: 'getDiscoveredRelaysResult',
-                requestId,
-                relays: []
-            });
+        if (!ndk) {
+            port.postMessage({ type: 'getDiscoveredRelaysResult', requestId, relays: [] });
             return;
         }
 
         // Build the set of the user's own relay URLs (normalized) from
-        // relayTypes (kind 10002). These are the "configured" relays; anything
-        // else in the pool is a discovered/temporary outbox relay.
+        // relayTypes (kind 10002). These are the "configured" relays.
         const ownRelays = new Set();
         for (const url of relayTypes.keys()) {
             const normalized = normalizeRelayUrl(url);
             if (normalized) ownRelays.add(normalized);
         }
 
-        // Build relayUrl -> [pubkeys] map by inverting the outbox tracker.
-        // The typescript-lru-cache iteration API is broken (it yields millions
-        // of phantom keys from only a handful of real entries), so instead of
-        // iterating the LRU cache we query the NDK cache for the user's kind 3
-        // contact list and then look up each followed pubkey by key.
-        const relayServesPubkeys = new Map(); // normalizedUrl -> Set<pubkey>
-        try {
-            const kind3Events = await ndk.fetchEvents(
-                { kinds: [3], authors: [currentPubkey], limit: 1 },
-                { cacheUsage: 'ONLY_CACHE' }
-            );
-            const latestKind3 = kind3Events && kind3Events.size > 0
-                ? Array.from(kind3Events).sort((a, b) => (b.created_at || 0) - (a.created_at || 0))[0]
-                : null;
-            const followedPubkeys = latestKind3 ? extractFollowedPubkeysFromKind3(latestKind3) : [];
+        // Get the user's kind 3 contact list from the Dexie cache to
+        // determine the followed pubkeys. Use the contact list's created_at
+        // as a cache key so we only rebuild when it changes.
+        const kind3Events = await ndk.fetchEvents(
+            { kinds: [3], authors: [currentPubkey], limit: 1 },
+            { cacheUsage: 'ONLY_CACHE' }
+        );
+        const latestKind3 = kind3Events && kind3Events.size > 0
+            ? Array.from(kind3Events).sort((a, b) => (b.created_at || 0) - (a.created_at || 0))[0]
+            : null;
+        const followedPubkeys = latestKind3 ? extractFollowedPubkeysFromKind3(latestKind3) : [];
+        const cacheKey = `${DISCOVERED_RELAYS_CACHE_VERSION}_${latestKind3?.id || 'none'}_${latestKind3?.created_at || 0}`;
 
-            for (const pubkey of followedPubkeys) {
-                try {
-                    const outboxItem = ndk?.outboxTracker?.data?.get(pubkey);
-                    if (!outboxItem?.writeRelays) continue;
-                    for (const relayUrl of outboxItem.writeRelays) {
-                        const normalized = normalizeRelayUrl(relayUrl);
-                        if (!normalized) continue;
-                        if (!relayServesPubkeys.has(normalized)) {
-                            relayServesPubkeys.set(normalized, new Set());
+        // Rebuild the relay→[pubkeys] mapping from follows' kind 10002 events
+        // in the Dexie cache if the contact list has changed.
+        if (discoveredRelaysCacheKey !== cacheKey) {
+            discoveredRelaysCacheKey = cacheKey;
+            discoveredRelaysCache = null; // invalidate
+
+            if (followedPubkeys.length > 0) {
+                // Query all follows' kind 10002 events from the Dexie cache.
+                // This is the persistent data source — no 2-minute TTL like
+                // the outbox tracker.
+                const relayServesPubkeys = new Map(); // normalizedUrl -> Set<pubkey>
+
+                // Process in batches of 400 to avoid filter size limits.
+                for (let i = 0; i < followedPubkeys.length; i += 400) {
+                    const batch = followedPubkeys.slice(i, i + 400);
+                    try {
+                        const k10002Events = await ndk.fetchEvents(
+                            { kinds: [10002], authors: batch },
+                            { cacheUsage: 'ONLY_CACHE' }
+                        );
+                        if (k10002Events && k10002Events.size > 0) {
+                            // For each author, keep only the latest kind 10002.
+                            const latestByAuthor = new Map();
+                            for (const evt of k10002Events) {
+                                const existing = latestByAuthor.get(evt.pubkey);
+                                if (!existing || (evt.created_at || 0) > (existing.created_at || 0)) {
+                                    latestByAuthor.set(evt.pubkey, evt);
+                                }
+                            }
+                            // Parse 'r' tags from each author's latest kind 10002.
+                            for (const [pubkey, evt] of latestByAuthor) {
+                                if (!Array.isArray(evt.tags)) continue;
+                                for (const tag of evt.tags) {
+                                    if (tag[0] === 'r' && tag[1]) {
+                                        const relayType = tag[2] || 'both';
+                                        // Include 'write' and 'both' relays — these are
+                                        // where the follow posts content.
+                                        if (relayType === 'write' || relayType === 'both') {
+                                            const normalized = normalizeRelayUrl(tag[1]);
+                                            if (!normalized) continue;
+                                            if (!relayServesPubkeys.has(normalized)) {
+                                                relayServesPubkeys.set(normalized, new Set());
+                                            }
+                                            relayServesPubkeys.get(normalized).add(pubkey);
+                                        }
+                                    }
+                                }
+                            }
+                        }
+                    } catch (_) {}
+                }
+
+                // Look up profile names for all serving pubkeys from the Dexie
+                // profiles table so we can display usernames instead of pubkeys.
+                // Look up profile names for all serving pubkeys.
+                const pubkeyToName = new Map();
+                const allServingPubkeys = new Set();
+                for (const servingSet of relayServesPubkeys.values()) {
+                    for (const pk of servingSet) allServingPubkeys.add(pk);
+                }
+
+                // Strategy 1: Try Dexie profiles table.
+                try {
+                    const adapter = ndk?.cacheAdapter?.adapter;
+                    if (adapter?.db?.profiles) {
+                        for (const pk of allServingPubkeys) {
+                            try {
+                                const row = await adapter.db.profiles.get(pk);
+                                if (row) {
+                                    const name = row.displayName || row.name || '';
+                                    if (name) pubkeyToName.set(pk, name);
+                                }
+                            } catch (_) {}
                         }
-                        relayServesPubkeys.get(normalized).add(pubkey);
                     }
                 } catch (_) {}
+
+                // Strategy 2: If Dexie profiles didn't have names for everyone,
+                // query kind 0 events from the NDK cache for the missing pubkeys.
+                const missingPubkeys = Array.from(allServingPubkeys).filter(pk => !pubkeyToName.has(pk));
+                if (missingPubkeys.length > 0) {
+                    try {
+                        // Query in batches of 400.
+                        for (let i = 0; i < missingPubkeys.length; i += 400) {
+                            const batch = missingPubkeys.slice(i, i + 400);
+                            const k0Events = await ndk.fetchEvents(
+                                { kinds: [0], authors: batch },
+                                { cacheUsage: 'ONLY_CACHE' }
+                            );
+                            if (k0Events && k0Events.size > 0) {
+                                // For each author, keep only the latest kind 0.
+                                const latestByAuthor = new Map();
+                                for (const evt of k0Events) {
+                                    const existing = latestByAuthor.get(evt.pubkey);
+                                    if (!existing || (evt.created_at || 0) > (existing.created_at || 0)) {
+                                        latestByAuthor.set(evt.pubkey, evt);
+                                    }
+                                }
+                                for (const [pubkey, evt] of latestByAuthor) {
+                                    try {
+                                        const profile = typeof evt.content === 'string'
+                                            ? JSON.parse(evt.content) : evt.content;
+                                        const name = profile?.display_name || profile?.name || '';
+                                        if (name) pubkeyToName.set(pubkey, name);
+                                    } catch (_) {}
+                                }
+                            }
+                        }
+                    } catch (_) {}
+                }
+
+                console.log('[Worker] getDiscoveredRelays: profile names resolved for', pubkeyToName.size, 'of', allServingPubkeys.size, 'pubkeys');
+
+                // Build the discovered relays list: relays that are NOT in the
+                // user's own kind 10002 but ARE in follows' kind 10002.
+                const relays = [];
+                for (const [relayUrl, servingSet] of relayServesPubkeys) {
+                    if (ownRelays.has(relayUrl)) continue; // skip user's own relays
+                    // Check live connection status from the pool.
+                    const poolRelay = ndk.pool?.relays?.get(relayUrl);
+                    const pubkeys = Array.from(servingSet);
+                    // Map pubkeys to names, falling back to truncated pubkey.
+                    const names = pubkeys.map(pk =>
+                        pubkeyToName.get(pk) || shortHexPubkey(pk)
+                    );
+                    relays.push({
+                        url: relayUrl,
+                        status: poolRelay?.status || 0,
+                        connected: poolRelay ? poolRelay.status >= 5 : false,
+                        servingPubkeys: pubkeys,
+                        servingNames: names
+                    });
+                }
+                // Sort by serving count (most follows first), then by URL.
+                relays.sort((a, b) => {
+                    const countDiff = b.servingPubkeys.length - a.servingPubkeys.length;
+                    if (countDiff !== 0) return countDiff;
+                    return a.url.localeCompare(b.url);
+                });
+                discoveredRelaysCache = relays;
             }
-        } catch (err) {
-            console.warn('[Worker] getDiscoveredRelays: outbox tracker inversion failed:', err?.message || err);
         }
 
-        const relays = [];
-        for (const relay of ndk.pool.relays.values()) {
-            const normalized = normalizeRelayUrl(relay?.url);
-            if (!normalized) continue;
-            // Skip relays that are part of the user's own kind 10002 list.
-            if (ownRelays.has(normalized)) continue;
-
-            const servingSet = relayServesPubkeys.get(normalized);
-            relays.push({
-                url: relay.url,
-                status: relay.status,
-                connected: relay.status >= 5,
-                servingPubkeys: servingSet ? Array.from(servingSet) : []
+        // If we have cached data, update the live connection status from the
+        // pool without rebuilding the entire mapping.
+        let relays = discoveredRelaysCache || [];
+        if (relays.length > 0 && ndk.pool?.relays) {
+            relays = relays.map(r => {
+                const poolRelay = ndk.pool.relays.get(r.url);
+                return {
+                    ...r,
+                    status: poolRelay?.status || r.status || 0,
+                    connected: poolRelay ? poolRelay.status >= 5 : r.connected
+                };
             });
         }
 

www/relays.html

@@ -1383,9 +1383,9 @@ const versionInfo = await getVersion();
       for (const relay of relaysWithFollows) {
         const connected = relay.connected ? SVG_CHECKED : SVG_UNCHECKED;
         const servingCount = Array.isArray(relay.servingPubkeys) ? relay.servingPubkeys.length : 0;
-        const followsList = Array.isArray(relay.servingPubkeys)
-          ? relay.servingPubkeys.map(shortNpub).join(', ')
-          : '-';
+        const followsList = Array.isArray(relay.servingNames) && relay.servingNames.length > 0
+          ? relay.servingNames.join(', ')
+          : (Array.isArray(relay.servingPubkeys) ? relay.servingPubkeys.map(shortNpub).join(', ') : '-');
         const rowClass = relay.connected ? 'tblRowConnected' : '';
 
         html += `<tr class="${rowClass}">`;