Add proper tokenizers for NAI Krake and Clio

public/index.html

@@ -1735,6 +1735,8 @@
                                 <option value="1">GPT-3 (OpenAI)</option>
                                 <option value="2">GPT-3 (Alternative / Classic)</option>
                                 <option value="3">Sentencepiece (LLaMA)</option>
+                                <option value="4">NerdStash (NovelAI Krake)</option>
+                                <option value="5">NerdStash v2 (NovelAI Clio)</option>
                             </select>
                         </div>
                         <div class="range-block">

public/script.js

@@ -481,22 +481,33 @@ function getTokenCount(str, padding = undefined) {
         case tokenizers.CLASSIC:
             return encode(str).length + padding;
         case tokenizers.LLAMA:
-            let tokenCount = 0;
+            return countTokensRemote('/tokenize_llama', str, padding);
-            jQuery.ajax({
+        case tokenizers.NERD:
-                async: false,
+            return countTokensRemote('/tokenize_nerdstash', str, padding);
-                type: 'POST', //
+        case tokenizers.NERD2:
-                url: `/tokenize_llama`,
+            return countTokensRemote('/tokenize_nerdstash_v2', str, padding);
-                data: JSON.stringify({ text: str }),
+        default:
-                dataType: "json",
+            console.warn("Unknown tokenizer type", tokenizerType);
-                contentType: "application/json",
+            return Math.ceil(str.length / CHARACTERS_PER_TOKEN_RATIO) + padding;
-                success: function (data) {
-                    tokenCount = data.count;
-                }
-            });
-            return tokenCount + padding;
     }
 }
 
+function countTokensRemote(endpoint, str, padding) {
+    let tokenCount = 0;
+    jQuery.ajax({
+        async: false,
+        type: 'POST',
+        url: endpoint,
+        data: JSON.stringify({ text: str }),
+        dataType: "json",
+        contentType: "application/json",
+        success: function (data) {
+            tokenCount = data.count;
+        }
+    });
+    return tokenCount + padding;
+}
+
 function reloadMarkdownProcessor(render_formulas = false) {
     if (render_formulas) {
         converter = new showdown.Converter({
@@ -2589,12 +2600,14 @@ function getMaxContextSize() {
         } else {
             this_max_context = Number(max_context);
             if (nai_settings.model_novel == 'krake-v2') {
-                this_max_context -= 160;
+                // Krake has a max context of 2048
+                // Should be used with nerdstash tokenizer for best results
+                this_max_context = Math.min(max_context, 2048);
             }
             if (nai_settings.model_novel == 'clio-v1') {
                 // Clio has a max context of 8192
-                // TODO: Evaluate the relevance of nerdstash-v1 tokenizer, changes quite a bit.
+                // Should be used with nerdstash_v2 tokenizer for best results
-                this_max_context = 8192 - 60 - 160;
+                this_max_context = Math.min(max_context, 8192);
             }
         }
     }

public/scripts/power-user.js

@@ -60,6 +60,8 @@ const tokenizers = {
     GPT3: 1,
     CLASSIC: 2,
     LLAMA: 3,
+    NERD: 4,
+    NERD2: 5,
 }
 
 const send_on_enter_options = {

server.js

@@ -128,23 +128,25 @@ const delay = ms => new Promise(resolve => setTimeout(resolve, ms))
 
 const { SentencePieceProcessor, cleanText } = require("sentencepiece-js");
 
-let spp;
+let spp_llama;
+let spp_nerd;
+let spp_nerd_v2;
 
-async function loadSentencepieceTokenizer() {
+async function loadSentencepieceTokenizer(modelPath) {
     try {
         const spp = new SentencePieceProcessor();
-        await spp.load("src/sentencepiece/tokenizer.model");
+        await spp.load(modelPath);
         return spp;
     } catch (error) {
-        console.error("Sentencepiece tokenizer failed to load.");
+        console.error("Sentencepiece tokenizer failed to load: " + modelPath, error);
         return null;
     }
 };
 
-async function countTokensLlama(text) {
+async function countSentencepieceTokens(spp, text) {
     // Fallback to strlen estimation
     if (!spp) {
-        return Math.ceil(v.length / 3.35);
+        return Math.ceil(text.length / 3.35);
     }
 
     let cleaned = cleanText(text);
@@ -2795,14 +2797,22 @@ app.post("/savepreset_openai", jsonParser, function (request, response) {
     return response.send({ name });
 });
 
-app.post("/tokenize_llama", jsonParser, async function (request, response) {
+function createTokenizationHandler(getTokenizerFn) {
-    if (!request.body) {
+    return async function (request, response) {
-        return response.sendStatus(400);
+        if (!request.body) {
-    }
+            return response.sendStatus(400);
+        }
 
-    const count = await countTokensLlama(request.body.text);
+        const text = request.body.text || '';
-    return response.send({ count });
+        const tokenizer = getTokenizerFn();
-});
+        const count = await countSentencepieceTokens(tokenizer, text);
+        return response.send({ count });
+    };
+}
+
+app.post("/tokenize_llama", jsonParser, createTokenizationHandler(() => spp_llama));
+app.post("/tokenize_nerdstash", jsonParser, createTokenizationHandler(() => spp_nerd));
+app.post("/tokenize_nerdstash_v2", jsonParser, createTokenizationHandler(() => spp_nerd_v2));
 
 // ** REST CLIENT ASYNC WRAPPERS **
 
@@ -2861,7 +2871,11 @@ const setupTasks = async function () {
     // Colab users could run the embedded tool
     if (!is_colab) await convertWebp();
 
-    spp = await loadSentencepieceTokenizer();
+    [spp_llama, spp_nerd, spp_nerd_v2] = await Promise.all([
+        loadSentencepieceTokenizer('src/sentencepiece/tokenizer.model'),
+        loadSentencepieceTokenizer('src/sentencepiece/nerdstash.model'),
+        loadSentencepieceTokenizer('src/sentencepiece/nerdstash_v2.model'),
+    ]);
 
     console.log('Launching...');