From 6f37963329e179d1ea246be0d8d7e94bad7942b4 Mon Sep 17 00:00:00 2001
From: ttstudio300 <143816235+ttstudio300@users.noreply.github.com>
Date: Sat, 2 Aug 2025 23:02:17 +0300
Subject: [PATCH 1/7] Add files via upload

---
 extensions/MountainAI-main/Banner.svg         |   1 +
 extensions/MountainAI-main/Logo.svg           |   1 +
 extensions/MountainAI-main/MountainAI.js      | 413 ++++++++++++++++++
 extensions/MountainAI-main/README.md          |  71 +++
 .../MountainAI-main/extension-info.json       |  10 +
 5 files changed, 496 insertions(+)
 create mode 100644 extensions/MountainAI-main/Banner.svg
 create mode 100644 extensions/MountainAI-main/Logo.svg
 create mode 100644 extensions/MountainAI-main/MountainAI.js
 create mode 100644 extensions/MountainAI-main/README.md
 create mode 100644 extensions/MountainAI-main/extension-info.json

diff --git a/extensions/MountainAI-main/Banner.svg b/extensions/MountainAI-main/Banner.svg
new file mode 100644
index 0000000000..a4b6310801
--- /dev/null
+++ b/extensions/MountainAI-main/Banner.svg
@@ -0,0 +1 @@
+<svg version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="600" height="300" viewBox="0,0,600,300"><defs><radialGradient cx="240" cy="180" r="300" gradientUnits="userSpaceOnUse" id="color-1"><stop offset="0" stop-color="#2257f7"/><stop offset="1" stop-color="#001b6c"/></radialGradient><radialGradient cx="240" cy="180" r="286" gradientTransform="translate(92,-233.0875) scale(2,2)" gradientUnits="userSpaceOnUse" id="color-2"><stop offset="0" stop-color="#002eb6" stop-opacity="0.60784"/><stop offset="1" stop-color="#002eb6" stop-opacity="0"/></radialGradient></defs><g transform="translate(60,-30)"><g stroke="none" stroke-miterlimit="10"><path d="M-60,330v-300h600v300z" fill="url(#color-1)" stroke-width="1"/><text transform="translate(-46,116.54375) scale(0.5,0.5)" font-size="40" font-style="normal" xml:space="preserve" fill="url(#color-2)" stroke-width="1" font-family="Sans Serif" font-weight="normal" text-anchor="start" text-decoration="none"><tspan x="0" dy="0">11101001101000110010110000011101111101111111001011</tspan><tspan x="0" dy="46.15px">10011111010010000011000011101001100000110000111001</tspan><tspan x="0" dy="46.15px">00110010011011111101110100000110100110000011010001</tspan><tspan x="0" dy="46.15px">10000111101101100101100000110010111101101100101111</tspan><tspan x="0" dy="46.15px">00101000001110011110010111001011101110101110100000</tspan><tspan x="0" dy="46.15px">11010011000001101101110010111000011101110101110100</tspan><tspan x="0" dy="46.15px">000111001011001011100001110110011011001111001</tspan></text><g fill-opacity="0.60392" fill="#1f005c" stroke-width="0"><path d="M185.57074,238l54.42926,-116l54.42926,116z"/><path d="M294.42926,122l-54.42926,116l-54.42926,-116z"/></g></g></g></svg><!--rotationCenter:300:150-->
\ No newline at end of file
diff --git a/extensions/MountainAI-main/Logo.svg b/extensions/MountainAI-main/Logo.svg
new file mode 100644
index 0000000000..a423ab02db
--- /dev/null
+++ b/extensions/MountainAI-main/Logo.svg
@@ -0,0 +1 @@
+<svg version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="511.53754" height="511.53754" viewBox="0,0,511.53754,511.53754"><defs><radialGradient cx="240" cy="180" r="255.76877" gradientUnits="userSpaceOnUse" id="color-1"><stop offset="0" stop-color="#9366ff"/><stop offset="1" stop-color="#330098"/></radialGradient></defs><g transform="translate(15.76877,75.76877)"><g stroke-width="0" stroke-miterlimit="10"><path d="M-15.76877,435.76877v-511.53754h511.53754v511.53754z" fill="url(#color-1)" stroke="#000000"/><g fill-opacity="0.60392" fill="#1f005c" stroke="none"><path d="M169.85194,254.75l70.14806,-149.5l70.14806,149.5z"/><path d="M310.14806,105.25l-70.14806,149.5l-70.14806,-149.5z"/></g></g></g></svg><!--rotationCenter:255.76877:255.76877000000002-->
\ No newline at end of file
diff --git a/extensions/MountainAI-main/MountainAI.js b/extensions/MountainAI-main/MountainAI.js
new file mode 100644
index 0000000000..2a46cf592e
--- /dev/null
+++ b/extensions/MountainAI-main/MountainAI.js
@@ -0,0 +1,413 @@
+// Name: MountainAI
+// ID: MountainAI
+// Description: Create and run your own GPT like ai models localy!
+// By: RadereDev
+// Original: RadereDev
+// License: MPL-2.0
+
+class MountainAI {
+  //MountainAI Build-15 public beta
+  constructor(numLayers=2, embedDim=16, ffDim=64, seqLen=8) {
+    this.numLayers = numLayers;
+    this.embedDim = embedDim;
+    this.ffDim = ffDim;
+    this.seqLen = seqLen;
+    this.temperature = 1.0;
+
+    this.vocab = [];
+    this.tokenToIdx = {};
+    this.idxToToken = {};
+
+    this.W_embed = null;
+
+    this.W_q = [];
+    this.W_k = [];
+    this.W_v = [];
+    this.W_out = [];
+
+    this.W_ff1 = [];
+    this.W_ff2 = [];
+
+    this.finalOutputWeights = null;
+
+    this.initialized = false;
+    this.learningRate = 0.01;
+  }
+
+  randomMatrix(rows, cols) {
+    const m = [];
+    for(let i=0; i<rows; i++){
+      m[i] = [];
+      for(let j=0; j<cols; j++){
+        m[i][j] = (Math.random()-0.5)*0.1;
+      }
+    }
+    return m;
+  }
+
+  buildVocab(text) {
+    const tokens = text.toLowerCase().split(/\s+/).filter(Boolean);
+    const uniqueTokens = [...new Set(tokens)];
+    this.vocab = uniqueTokens;
+    this.tokenToIdx = {};
+    this.idxToToken = {};
+    this.vocab.forEach((t,i) => {
+      this.tokenToIdx[t] = i;
+      this.idxToToken[i] = t;
+    });
+    const vocabSize = this.vocab.length;
+
+    this.W_embed = this.randomMatrix(vocabSize, this.embedDim);
+
+    this.W_q = [];
+    this.W_k = [];
+    this.W_v = [];
+    this.W_out = [];
+    this.W_ff1 = [];
+    this.W_ff2 = [];
+
+    for(let i=0; i<this.numLayers; i++){
+      this.W_q.push(this.randomMatrix(this.embedDim, this.embedDim));
+      this.W_k.push(this.randomMatrix(this.embedDim, this.embedDim));
+      this.W_v.push(this.randomMatrix(this.embedDim, this.embedDim));
+      this.W_out.push(this.randomMatrix(this.embedDim, this.embedDim));
+      this.W_ff1.push(this.randomMatrix(this.embedDim, this.ffDim));
+      this.W_ff2.push(this.randomMatrix(this.ffDim, this.embedDim));
+    }
+
+    this.finalOutputWeights = this.randomMatrix(this.embedDim, vocabSize);
+    this.initialized = true;
+  }
+
+  tokenize(text) {
+    const tokens = text.toLowerCase().split(/\s+/).filter(Boolean);
+    return tokens.map(t => this.tokenToIdx[t] !== undefined ? this.tokenToIdx[t] : 0);
+  }
+
+  detokenize(indices) {
+    return indices.map(i => this.idxToToken[i]).join(' ');
+  }
+
+  matMulVec(mat, vec) {
+    const res = [];
+    for(let i=0; i<mat.length; i++){
+      let s = 0;
+      for(let j=0; j<vec.length; j++){
+        s += mat[i][j]*vec[j];
+      }
+      res[i] = s;
+    }
+    return res;
+  }
+
+  softmax(arr) {
+    const max = Math.max(...arr);
+    const exps = arr.map(x => Math.exp((x - max)/this.temperature));
+    const sum = exps.reduce((a,b)=>a+b,0);
+    return exps.map(e => e/sum);
+  }
+
+  relu(x) {return x>0 ? x : 0;}
+
+  feedForward(input, layerIndex) {
+    const W1 = this.W_ff1[layerIndex];
+    const W2 = this.W_ff2[layerIndex];
+    const seqLen = input.length;
+    const ffDim = this.ffDim;
+    const embedDim = this.embedDim;
+
+    let hidden = [];
+    for(let i=0; i<seqLen; i++){
+      let row = this.matMulVec(W1, input[i]);
+      row = row.map(x => this.relu(x));
+      hidden.push(row);
+    }
+
+    let output = [];
+    for(let i=0; i<seqLen; i++){
+      output.push(this.matMulVec(W2, hidden[i]));
+    }
+
+    return output;
+  }
+
+  transformerLayer(emb, layerIndex) {
+    const Wq = this.W_q[layerIndex];
+    const Wk = this.W_k[layerIndex];
+    const Wv = this.W_v[layerIndex];
+    const Wout = this.W_out[layerIndex];
+
+    const seqLen = emb.length;
+    const embedDim = this.embedDim;
+
+    const Q = emb.map(v => this.matMulVec(Wq, v));
+    const K = emb.map(v => this.matMulVec(Wk, v));
+    const V = emb.map(v => this.matMulVec(Wv, v));
+
+    const scores = [];
+    for(let i=0; i<seqLen; i++){
+      scores[i] = [];
+      for(let j=0; j<seqLen; j++){
+        let s=0;
+        for(let d=0; d<embedDim; d++){
+          s += Q[i][d]*K[j][d];
+        }
+        scores[i][j] = s/Math.sqrt(embedDim);
+      }
+    }
+
+    for(let i=0; i<seqLen; i++){
+      scores[i] = this.softmax(scores[i]);
+    }
+
+    let out = [];
+    for(let i=0; i<seqLen; i++){
+      let vec = new Array(embedDim).fill(0);
+      for(let j=0; j<seqLen; j++){
+        for(let d=0; d<embedDim; d++){
+          vec[d] += scores[i][j]*V[j][d];
+        }
+      }
+      out.push(vec);
+    }
+
+    let finalOut = [];
+    for(let i=0; i<seqLen; i++){
+      finalOut.push(this.matMulVec(Wout, out[i]));
+    }
+
+    return finalOut;
+  }
+
+  forward(seq) {
+    while(seq.length < this.seqLen) seq.unshift(0);
+    seq = seq.slice(-this.seqLen);
+
+    let out = seq.map(i => this.W_embed[i]);
+    for(let i=0; i<this.numLayers; i++){
+      out = this.transformerLayer(out, i);
+      out = this.feedForward(out, i);
+    }
+
+    const last = out[out.length-1];
+    const logits = [];
+    for(let i=0; i<this.vocab.length; i++){
+      let s=0;
+      for(let d=0; d<this.embedDim; d++){
+        s += last[d]*this.finalOutputWeights[d][i];
+      }
+      logits[i] = s;
+    }
+
+    return logits;
+  }
+
+  sampleToken(logits) {
+    const probs = this.softmax(logits);
+    let r = Math.random();
+    let cum=0;
+    for(let i=0; i<probs.length; i++){
+      cum += probs[i];
+      if(r < cum) return i;
+    }
+    return probs.length-1;
+  }
+
+  generate(prefix, length=10) {
+    if(!this.initialized) return 'Модель не инициализирована';
+
+    let tokens = this.tokenize(prefix);
+    while(tokens.length < this.seqLen){
+      tokens.unshift(0);
+    }
+    tokens = tokens.slice(-this.seqLen);
+
+    const generated = [...tokens];
+
+    for(let i=0; i<length; i++){
+      const logits = this.forward(tokens);
+      const nextToken = this.sampleToken(logits);
+      generated.push(nextToken);
+      tokens.shift();
+      tokens.push(nextToken);
+    }
+
+    return this.detokenize(generated.slice(this.seqLen));
+  }
+
+  async train(text, epochs=10, onEpoch=null) {
+    this.buildVocab(text);
+    const tokens = this.tokenize(text);
+    if(tokens.length < this.seqLen+1) return;
+
+    for(let epoch=1; epoch<=epochs; epoch++){
+      if(onEpoch) onEpoch(epoch);
+      for(let i=0; i < tokens.length - this.seqLen; i++){
+        const inputSeq = tokens.slice(i, i+this.seqLen);
+        const target = tokens[i+this.seqLen];
+
+        const logits = this.forward(inputSeq);
+        const probs = this.softmax(logits);
+
+        const dL_dlogits = probs.slice();
+        dL_dlogits[target] -= 1;
+
+        for(let d=0; d<this.embedDim; d++){
+          for(let v=0; v<this.vocab.length; v++){
+            this.finalOutputWeights[d][v] -= this.learningRate * dL_dlogits[v] * this.W_embed[inputSeq[this.seqLen-1]][d];
+          }
+        }
+
+        for(let d=0; d<this.embedDim; d++){
+          this.W_embed[inputSeq[this.seqLen-1]][d] -= this.learningRate * dL_dlogits[target];
+        }
+      }
+      await new Promise(r => setTimeout(r, 1000)); // Задержка 1 сек
+    }
+  }
+
+  setTemperature(t) {
+    this.temperature = t;
+  }
+
+  resetModel(numLayers, embedDim, ffDim, seqLen) {
+    this.numLayers = numLayers;
+    this.embedDim = embedDim;
+    this.ffDim = ffDim;
+    this.seqLen = seqLen;
+    this.initialized = false;
+    this.vocab = [];
+    this.tokenToIdx = {};
+    this.idxToToken = {};
+    this.W_embed = null;
+    this.W_q = [];
+    this.W_k = [];
+    this.W_v = [];
+    this.W_out = [];
+    this.W_ff1 = [];
+    this.W_ff2 = [];
+    this.finalOutputWeights = null;
+  }
+}
+
+class MountainAIExtension {
+  constructor() {
+    this.model = new MountainAI(2, 16, 64, 8);
+    this.currentEpoch = 0;
+  }
+
+  getInfo() {
+    return {
+      id: 'MountainAI',
+      name: 'MountainAI',
+      blocks: [
+        {
+          opcode: 'train',
+          blockType: Scratch.BlockType.COMMAND,
+          text: 'train on text [TEXT], [EPOCHS] epochs',
+          arguments: {
+            TEXT: {type: Scratch.ArgumentType.STRING, defaultValue: 'any train text here'},
+            EPOCHS: {type: Scratch.ArgumentType.NUMBER, defaultValue: 50},
+          },
+        },
+        {
+          opcode: 'generate',
+          blockType: Scratch.BlockType.REPORTER,
+          text: 'generate from [PROMPT] with length [LENGTH]',
+          arguments: {
+            PROMPT: {type: Scratch.ArgumentType.STRING, defaultValue: 'He look in his eyes and '},
+            LENGTH: {type: Scratch.ArgumentType.NUMBER, defaultValue: 50},
+          },
+        },
+        {
+          opcode: 'setTemperature',
+          blockType: Scratch.BlockType.COMMAND,
+          text: 'set temperature [TEMP]',
+          arguments: {
+            TEMP: {type: Scratch.ArgumentType.NUMBER, defaultValue: 0.3},
+          },
+        },
+        {
+          opcode: 'setNumLayers',
+          blockType: Scratch.BlockType.COMMAND,
+          text: 'Layer Count [NUM]',
+          arguments: {
+            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 2},
+          },
+        },
+        {
+          opcode: 'setEmbedDim',
+          blockType: Scratch.BlockType.COMMAND,
+          text: 'embedding size [NUM]',
+          arguments: {
+            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 16},
+          },
+        },
+        {
+          opcode: 'setFFDim',
+          blockType: Scratch.BlockType.COMMAND,
+          text: 'FFN size [NUM]',
+          arguments: {
+            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 64},
+          },
+        },
+        {
+          opcode: 'setSeqLen',
+          blockType: Scratch.BlockType.COMMAND,
+          text: 'context size [NUM]',
+          arguments: {
+            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 16},
+          },
+        },
+        {
+          opcode: 'getCurrentEpoch',
+          blockType: Scratch.BlockType.REPORTER,
+          text: 'current epoch',
+        },
+      ],
+    };
+  }
+
+  async train({TEXT, EPOCHS}) {
+    this.currentEpoch = 0;
+    const onEpoch = (epoch) => {
+      this.currentEpoch = epoch;
+    };
+    await this.model.train(TEXT, Number(EPOCHS), onEpoch);
+    this.currentEpoch = 0;
+  }
+
+  generate({PROMPT, LENGTH}) {
+    return this.model.generate(PROMPT, Number(LENGTH));
+  }
+
+  setTemperature({TEMP}) {
+    this.model.setTemperature(Number(TEMP));
+  }
+
+  setNumLayers({NUM}) {
+    const n = Math.max(1, Math.floor(NUM));
+    this.model.resetModel(n, this.model.embedDim, this.model.ffDim, this.model.seqLen);
+  }
+
+  setEmbedDim({NUM}) {
+    const n = Math.max(1, Math.floor(NUM));
+    this.model.resetModel(this.model.numLayers, n, this.model.ffDim, this.model.seqLen);
+  }
+
+  setFFDim({NUM}) {
+    const n = Math.max(1, Math.floor(NUM));
+    this.model.resetModel(this.model.numLayers, this.model.embedDim, n, this.model.seqLen);
+  }
+
+  setSeqLen({NUM}) {
+    const n = Math.max(1, Math.floor(NUM));
+    this.model.resetModel(this.model.numLayers, this.model.embedDim, this.model.ffDim, n);
+  }
+
+  getCurrentEpoch() {
+    return this.currentEpoch;
+  }
+}
+
+Scratch.extensions.register(new MountainAIExtension());
diff --git a/extensions/MountainAI-main/README.md b/extensions/MountainAI-main/README.md
new file mode 100644
index 0000000000..e23cf991b6
--- /dev/null
+++ b/extensions/MountainAI-main/README.md
@@ -0,0 +1,71 @@
+## 🧠 MountainAI — GPT-like Neural Network for TurboWarp
+
+**MountainAI** is a simple GPT-style neural network extension for [TurboWarp](https://turbowarp.org), written entirely in JavaScript.
+It allows users to **train** and **use** a text-generation model directly inside Scratch projects — no server or installation required.
+
+---
+
+### ⚠️ Performance Notice
+
+**Training the model may cause the page to temporarily freeze**, especially on slower or older computers.
+This is expected behavior — **the training is still running in the background**, and the browser will resume responsiveness when it's complete.
+If you see a warning like *“This page is unresponsive”* — just wait, and don’t reload.
+
+---
+
+### 🔧 Features
+
+* 🧠 Fully local training and inference
+* 📄 Custom dataset support (text-based)
+* ⚙️ Adjustable hyperparameters:
+
+  * Number of transformer layers
+  * Feed-forward size
+  * Sequence length
+* 📝 Text continuation instead of random generation
+* 🪄 Easy to use through custom blocks
+
+---
+
+### 📦 How to Use
+
+1. Open [TurboWarp Editor](https://turbowarp.org/editor?extension=https://ttstudio300.github.io/MountainAI/MountainAI.js)
+2. Load the extension using this URL:
+   `https://ttstudio300.github.io/MountainAI/MountainAI.js`
+3. Use the blocks from the “MountainAI” category to:
+
+   * Set model parameters
+   * Load or input training data
+   * Train the model
+   * Generate text
+
+---
+
+### 🧱 Example Blocks
+
+* `Set number of layers [3]`
+* `Set sequence length [8]`
+* `Train model`
+* `Generate text from [start phrase] for [length] tokens`
+
+---
+
+### 🔗 Links
+
+* 🌐 Live Extension URL:
+  `https://ttstudio300.github.io/MountainAI/MountainAI.js`
+* 💾 GitHub Repository:
+  [github.com/ttstudio300/MountainAI](https://github.com/ttstudio300/MountainAI)
+* 🧪 Try it instantly:
+  [TurboWarp + Extension](https://turbowarp.org/editor?extension=https://ttstudio300.github.io/MountainAI/MountainAI.js)
+
+---
+
+### ✨ Author
+
+Made with care by **RadereDev**
+Special thanks to GPT and open learning communities.
+
+---
+
+Хочешь добавить ещё секцию о том, как устроена архитектура внутри? Или, например, гифку, показывающую, как оно работает?
diff --git a/extensions/MountainAI-main/extension-info.json b/extensions/MountainAI-main/extension-info.json
new file mode 100644
index 0000000000..adbf814141
--- /dev/null
+++ b/extensions/MountainAI-main/extension-info.json
@@ -0,0 +1,10 @@
+{
+  "name": "MountainAI",
+  "description": "A simple GPT-like neural network that can be trained and used directly in TurboWarp using JavaScript.",
+  "icon": "icon.png",
+  "banner": "banner.png",
+  "tags": ["ai", "gpt", "machine learning", "neural network", "text generation"],
+  "developer": "RadereDev",
+  "extensionUrl": "https://ttstudio300.github.io/MountainAI/MountainAI.js",
+  "github": "https://github.com/ttstudio300/MountainAI"
+}

From 2bc1064ebcc693e0a8b559f1d5ace125f2f2d3cd Mon Sep 17 00:00:00 2001
From: ttstudio300 <143816235+ttstudio300@users.noreply.github.com>
Date: Sat, 2 Aug 2025 23:21:16 +0300
Subject: [PATCH 2/7] Delete extensions/MountainAI-main/MountainAI.js

---
 extensions/MountainAI-main/MountainAI.js | 413 -----------------------
 1 file changed, 413 deletions(-)
 delete mode 100644 extensions/MountainAI-main/MountainAI.js

diff --git a/extensions/MountainAI-main/MountainAI.js b/extensions/MountainAI-main/MountainAI.js
deleted file mode 100644
index 2a46cf592e..0000000000
--- a/extensions/MountainAI-main/MountainAI.js
+++ /dev/null
@@ -1,413 +0,0 @@
-// Name: MountainAI
-// ID: MountainAI
-// Description: Create and run your own GPT like ai models localy!
-// By: RadereDev
-// Original: RadereDev
-// License: MPL-2.0
-
-class MountainAI {
-  //MountainAI Build-15 public beta
-  constructor(numLayers=2, embedDim=16, ffDim=64, seqLen=8) {
-    this.numLayers = numLayers;
-    this.embedDim = embedDim;
-    this.ffDim = ffDim;
-    this.seqLen = seqLen;
-    this.temperature = 1.0;
-
-    this.vocab = [];
-    this.tokenToIdx = {};
-    this.idxToToken = {};
-
-    this.W_embed = null;
-
-    this.W_q = [];
-    this.W_k = [];
-    this.W_v = [];
-    this.W_out = [];
-
-    this.W_ff1 = [];
-    this.W_ff2 = [];
-
-    this.finalOutputWeights = null;
-
-    this.initialized = false;
-    this.learningRate = 0.01;
-  }
-
-  randomMatrix(rows, cols) {
-    const m = [];
-    for(let i=0; i<rows; i++){
-      m[i] = [];
-      for(let j=0; j<cols; j++){
-        m[i][j] = (Math.random()-0.5)*0.1;
-      }
-    }
-    return m;
-  }
-
-  buildVocab(text) {
-    const tokens = text.toLowerCase().split(/\s+/).filter(Boolean);
-    const uniqueTokens = [...new Set(tokens)];
-    this.vocab = uniqueTokens;
-    this.tokenToIdx = {};
-    this.idxToToken = {};
-    this.vocab.forEach((t,i) => {
-      this.tokenToIdx[t] = i;
-      this.idxToToken[i] = t;
-    });
-    const vocabSize = this.vocab.length;
-
-    this.W_embed = this.randomMatrix(vocabSize, this.embedDim);
-
-    this.W_q = [];
-    this.W_k = [];
-    this.W_v = [];
-    this.W_out = [];
-    this.W_ff1 = [];
-    this.W_ff2 = [];
-
-    for(let i=0; i<this.numLayers; i++){
-      this.W_q.push(this.randomMatrix(this.embedDim, this.embedDim));
-      this.W_k.push(this.randomMatrix(this.embedDim, this.embedDim));
-      this.W_v.push(this.randomMatrix(this.embedDim, this.embedDim));
-      this.W_out.push(this.randomMatrix(this.embedDim, this.embedDim));
-      this.W_ff1.push(this.randomMatrix(this.embedDim, this.ffDim));
-      this.W_ff2.push(this.randomMatrix(this.ffDim, this.embedDim));
-    }
-
-    this.finalOutputWeights = this.randomMatrix(this.embedDim, vocabSize);
-    this.initialized = true;
-  }
-
-  tokenize(text) {
-    const tokens = text.toLowerCase().split(/\s+/).filter(Boolean);
-    return tokens.map(t => this.tokenToIdx[t] !== undefined ? this.tokenToIdx[t] : 0);
-  }
-
-  detokenize(indices) {
-    return indices.map(i => this.idxToToken[i]).join(' ');
-  }
-
-  matMulVec(mat, vec) {
-    const res = [];
-    for(let i=0; i<mat.length; i++){
-      let s = 0;
-      for(let j=0; j<vec.length; j++){
-        s += mat[i][j]*vec[j];
-      }
-      res[i] = s;
-    }
-    return res;
-  }
-
-  softmax(arr) {
-    const max = Math.max(...arr);
-    const exps = arr.map(x => Math.exp((x - max)/this.temperature));
-    const sum = exps.reduce((a,b)=>a+b,0);
-    return exps.map(e => e/sum);
-  }
-
-  relu(x) {return x>0 ? x : 0;}
-
-  feedForward(input, layerIndex) {
-    const W1 = this.W_ff1[layerIndex];
-    const W2 = this.W_ff2[layerIndex];
-    const seqLen = input.length;
-    const ffDim = this.ffDim;
-    const embedDim = this.embedDim;
-
-    let hidden = [];
-    for(let i=0; i<seqLen; i++){
-      let row = this.matMulVec(W1, input[i]);
-      row = row.map(x => this.relu(x));
-      hidden.push(row);
-    }
-
-    let output = [];
-    for(let i=0; i<seqLen; i++){
-      output.push(this.matMulVec(W2, hidden[i]));
-    }
-
-    return output;
-  }
-
-  transformerLayer(emb, layerIndex) {
-    const Wq = this.W_q[layerIndex];
-    const Wk = this.W_k[layerIndex];
-    const Wv = this.W_v[layerIndex];
-    const Wout = this.W_out[layerIndex];
-
-    const seqLen = emb.length;
-    const embedDim = this.embedDim;
-
-    const Q = emb.map(v => this.matMulVec(Wq, v));
-    const K = emb.map(v => this.matMulVec(Wk, v));
-    const V = emb.map(v => this.matMulVec(Wv, v));
-
-    const scores = [];
-    for(let i=0; i<seqLen; i++){
-      scores[i] = [];
-      for(let j=0; j<seqLen; j++){
-        let s=0;
-        for(let d=0; d<embedDim; d++){
-          s += Q[i][d]*K[j][d];
-        }
-        scores[i][j] = s/Math.sqrt(embedDim);
-      }
-    }
-
-    for(let i=0; i<seqLen; i++){
-      scores[i] = this.softmax(scores[i]);
-    }
-
-    let out = [];
-    for(let i=0; i<seqLen; i++){
-      let vec = new Array(embedDim).fill(0);
-      for(let j=0; j<seqLen; j++){
-        for(let d=0; d<embedDim; d++){
-          vec[d] += scores[i][j]*V[j][d];
-        }
-      }
-      out.push(vec);
-    }
-
-    let finalOut = [];
-    for(let i=0; i<seqLen; i++){
-      finalOut.push(this.matMulVec(Wout, out[i]));
-    }
-
-    return finalOut;
-  }
-
-  forward(seq) {
-    while(seq.length < this.seqLen) seq.unshift(0);
-    seq = seq.slice(-this.seqLen);
-
-    let out = seq.map(i => this.W_embed[i]);
-    for(let i=0; i<this.numLayers; i++){
-      out = this.transformerLayer(out, i);
-      out = this.feedForward(out, i);
-    }
-
-    const last = out[out.length-1];
-    const logits = [];
-    for(let i=0; i<this.vocab.length; i++){
-      let s=0;
-      for(let d=0; d<this.embedDim; d++){
-        s += last[d]*this.finalOutputWeights[d][i];
-      }
-      logits[i] = s;
-    }
-
-    return logits;
-  }
-
-  sampleToken(logits) {
-    const probs = this.softmax(logits);
-    let r = Math.random();
-    let cum=0;
-    for(let i=0; i<probs.length; i++){
-      cum += probs[i];
-      if(r < cum) return i;
-    }
-    return probs.length-1;
-  }
-
-  generate(prefix, length=10) {
-    if(!this.initialized) return 'Модель не инициализирована';
-
-    let tokens = this.tokenize(prefix);
-    while(tokens.length < this.seqLen){
-      tokens.unshift(0);
-    }
-    tokens = tokens.slice(-this.seqLen);
-
-    const generated = [...tokens];
-
-    for(let i=0; i<length; i++){
-      const logits = this.forward(tokens);
-      const nextToken = this.sampleToken(logits);
-      generated.push(nextToken);
-      tokens.shift();
-      tokens.push(nextToken);
-    }
-
-    return this.detokenize(generated.slice(this.seqLen));
-  }
-
-  async train(text, epochs=10, onEpoch=null) {
-    this.buildVocab(text);
-    const tokens = this.tokenize(text);
-    if(tokens.length < this.seqLen+1) return;
-
-    for(let epoch=1; epoch<=epochs; epoch++){
-      if(onEpoch) onEpoch(epoch);
-      for(let i=0; i < tokens.length - this.seqLen; i++){
-        const inputSeq = tokens.slice(i, i+this.seqLen);
-        const target = tokens[i+this.seqLen];
-
-        const logits = this.forward(inputSeq);
-        const probs = this.softmax(logits);
-
-        const dL_dlogits = probs.slice();
-        dL_dlogits[target] -= 1;
-
-        for(let d=0; d<this.embedDim; d++){
-          for(let v=0; v<this.vocab.length; v++){
-            this.finalOutputWeights[d][v] -= this.learningRate * dL_dlogits[v] * this.W_embed[inputSeq[this.seqLen-1]][d];
-          }
-        }
-
-        for(let d=0; d<this.embedDim; d++){
-          this.W_embed[inputSeq[this.seqLen-1]][d] -= this.learningRate * dL_dlogits[target];
-        }
-      }
-      await new Promise(r => setTimeout(r, 1000)); // Задержка 1 сек
-    }
-  }
-
-  setTemperature(t) {
-    this.temperature = t;
-  }
-
-  resetModel(numLayers, embedDim, ffDim, seqLen) {
-    this.numLayers = numLayers;
-    this.embedDim = embedDim;
-    this.ffDim = ffDim;
-    this.seqLen = seqLen;
-    this.initialized = false;
-    this.vocab = [];
-    this.tokenToIdx = {};
-    this.idxToToken = {};
-    this.W_embed = null;
-    this.W_q = [];
-    this.W_k = [];
-    this.W_v = [];
-    this.W_out = [];
-    this.W_ff1 = [];
-    this.W_ff2 = [];
-    this.finalOutputWeights = null;
-  }
-}
-
-class MountainAIExtension {
-  constructor() {
-    this.model = new MountainAI(2, 16, 64, 8);
-    this.currentEpoch = 0;
-  }
-
-  getInfo() {
-    return {
-      id: 'MountainAI',
-      name: 'MountainAI',
-      blocks: [
-        {
-          opcode: 'train',
-          blockType: Scratch.BlockType.COMMAND,
-          text: 'train on text [TEXT], [EPOCHS] epochs',
-          arguments: {
-            TEXT: {type: Scratch.ArgumentType.STRING, defaultValue: 'any train text here'},
-            EPOCHS: {type: Scratch.ArgumentType.NUMBER, defaultValue: 50},
-          },
-        },
-        {
-          opcode: 'generate',
-          blockType: Scratch.BlockType.REPORTER,
-          text: 'generate from [PROMPT] with length [LENGTH]',
-          arguments: {
-            PROMPT: {type: Scratch.ArgumentType.STRING, defaultValue: 'He look in his eyes and '},
-            LENGTH: {type: Scratch.ArgumentType.NUMBER, defaultValue: 50},
-          },
-        },
-        {
-          opcode: 'setTemperature',
-          blockType: Scratch.BlockType.COMMAND,
-          text: 'set temperature [TEMP]',
-          arguments: {
-            TEMP: {type: Scratch.ArgumentType.NUMBER, defaultValue: 0.3},
-          },
-        },
-        {
-          opcode: 'setNumLayers',
-          blockType: Scratch.BlockType.COMMAND,
-          text: 'Layer Count [NUM]',
-          arguments: {
-            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 2},
-          },
-        },
-        {
-          opcode: 'setEmbedDim',
-          blockType: Scratch.BlockType.COMMAND,
-          text: 'embedding size [NUM]',
-          arguments: {
-            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 16},
-          },
-        },
-        {
-          opcode: 'setFFDim',
-          blockType: Scratch.BlockType.COMMAND,
-          text: 'FFN size [NUM]',
-          arguments: {
-            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 64},
-          },
-        },
-        {
-          opcode: 'setSeqLen',
-          blockType: Scratch.BlockType.COMMAND,
-          text: 'context size [NUM]',
-          arguments: {
-            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 16},
-          },
-        },
-        {
-          opcode: 'getCurrentEpoch',
-          blockType: Scratch.BlockType.REPORTER,
-          text: 'current epoch',
-        },
-      ],
-    };
-  }
-
-  async train({TEXT, EPOCHS}) {
-    this.currentEpoch = 0;
-    const onEpoch = (epoch) => {
-      this.currentEpoch = epoch;
-    };
-    await this.model.train(TEXT, Number(EPOCHS), onEpoch);
-    this.currentEpoch = 0;
-  }
-
-  generate({PROMPT, LENGTH}) {
-    return this.model.generate(PROMPT, Number(LENGTH));
-  }
-
-  setTemperature({TEMP}) {
-    this.model.setTemperature(Number(TEMP));
-  }
-
-  setNumLayers({NUM}) {
-    const n = Math.max(1, Math.floor(NUM));
-    this.model.resetModel(n, this.model.embedDim, this.model.ffDim, this.model.seqLen);
-  }
-
-  setEmbedDim({NUM}) {
-    const n = Math.max(1, Math.floor(NUM));
-    this.model.resetModel(this.model.numLayers, n, this.model.ffDim, this.model.seqLen);
-  }
-
-  setFFDim({NUM}) {
-    const n = Math.max(1, Math.floor(NUM));
-    this.model.resetModel(this.model.numLayers, this.model.embedDim, n, this.model.seqLen);
-  }
-
-  setSeqLen({NUM}) {
-    const n = Math.max(1, Math.floor(NUM));
-    this.model.resetModel(this.model.numLayers, this.model.embedDim, this.model.ffDim, n);
-  }
-
-  getCurrentEpoch() {
-    return this.currentEpoch;
-  }
-}
-
-Scratch.extensions.register(new MountainAIExtension());

From 0f7e097577a9ed57e7e9787cabef81fa779f9771 Mon Sep 17 00:00:00 2001
From: ttstudio300 <143816235+ttstudio300@users.noreply.github.com>
Date: Sat, 2 Aug 2025 23:21:44 +0300
Subject: [PATCH 3/7] add MountainAI extension

---
 extensions/MountainAI-main/Mountain-AI.js | 408 ++++++++++++++++++++++
 1 file changed, 408 insertions(+)
 create mode 100644 extensions/MountainAI-main/Mountain-AI.js

diff --git a/extensions/MountainAI-main/Mountain-AI.js b/extensions/MountainAI-main/Mountain-AI.js
new file mode 100644
index 0000000000..5dbe3b31cd
--- /dev/null
+++ b/extensions/MountainAI-main/Mountain-AI.js
@@ -0,0 +1,408 @@
+(function(Scratch) {
+'use strict';
+
+class MountainAI {
+  // MountainAI Build-15 public beta
+  constructor(numLayers=2, embedDim=16, ffDim=64, seqLen=8) {
+    this.numLayers = numLayers;
+    this.embedDim = embedDim;
+    this.ffDim = ffDim;
+    this.seqLen = seqLen;
+    this.temperature = 1.0;
+
+    this.vocab = [];
+    this.tokenToIdx = {};
+    this.idxToToken = {};
+
+    this.W_embed = null;
+
+    this.W_q = [];
+    this.W_k = [];
+    this.W_v = [];
+    this.W_out = [];
+
+    this.W_ff1 = [];
+    this.W_ff2 = [];
+
+    this.finalOutputWeights = null;
+
+    this.initialized = false;
+    this.learningRate = 0.01;
+  }
+
+  randomMatrix(rows, cols) {
+    const m = [];
+    for(let i=0; i<rows; i++){
+      m[i] = [];
+      for(let j=0; j<cols; j++){
+        m[i][j] = (Math.random()-0.5)*0.1;
+      }
+    }
+    return m;
+  }
+
+  buildVocab(text) {
+    const tokens = text.toLowerCase().split(/\s+/).filter(Boolean);
+    const uniqueTokens = [...new Set(tokens)];
+    this.vocab = uniqueTokens;
+    this.tokenToIdx = {};
+    this.idxToToken = {};
+    this.vocab.forEach((t,i) => {
+      this.tokenToIdx[t] = i;
+      this.idxToToken[i] = t;
+    });
+    const vocabSize = this.vocab.length;
+
+    this.W_embed = this.randomMatrix(vocabSize, this.embedDim);
+
+    this.W_q = [];
+    this.W_k = [];
+    this.W_v = [];
+    this.W_out = [];
+    this.W_ff1 = [];
+    this.W_ff2 = [];
+
+    for(let i=0; i<this.numLayers; i++){
+      this.W_q.push(this.randomMatrix(this.embedDim, this.embedDim));
+      this.W_k.push(this.randomMatrix(this.embedDim, this.embedDim));
+      this.W_v.push(this.randomMatrix(this.embedDim, this.embedDim));
+      this.W_out.push(this.randomMatrix(this.embedDim, this.embedDim));
+      this.W_ff1.push(this.randomMatrix(this.embedDim, this.ffDim));
+      this.W_ff2.push(this.randomMatrix(this.ffDim, this.embedDim));
+    }
+
+    this.finalOutputWeights = this.randomMatrix(this.embedDim, vocabSize);
+    this.initialized = true;
+  }
+
+  tokenize(text) {
+    const tokens = text.toLowerCase().split(/\s+/).filter(Boolean);
+    return tokens.map(t => this.tokenToIdx[t] !== undefined ? this.tokenToIdx[t] : 0);
+  }
+
+  detokenize(indices) {
+    return indices.map(i => this.idxToToken[i]).join(' ');
+  }
+
+  matMulVec(mat, vec) {
+    const res = [];
+    for(let i=0; i<mat.length; i++){
+      let s = 0;
+      for(let j=0; j<vec.length; j++){
+        s += mat[i][j]*vec[j];
+      }
+      res[i] = s;
+    }
+    return res;
+  }
+
+  softmax(arr) {
+    const max = Math.max(...arr);
+    const exps = arr.map(x => Math.exp((x - max)/this.temperature));
+    const sum = exps.reduce((a,b)=>a+b,0);
+    return exps.map(e => e/sum);
+  }
+
+  relu(x) {return x>0 ? x : 0;}
+
+  feedForward(input, layerIndex) {
+    const W1 = this.W_ff1[layerIndex];
+    const W2 = this.W_ff2[layerIndex];
+    const seqLen = input.length;
+
+    let hidden = [];
+    for(let i=0; i<seqLen; i++){
+      let row = this.matMulVec(W1, input[i]);
+      row = row.map(x => this.relu(x));
+      hidden.push(row);
+    }
+
+    let output = [];
+    for(let i=0; i<seqLen; i++){
+      output.push(this.matMulVec(W2, hidden[i]));
+    }
+
+    return output;
+  }
+
+  transformerLayer(emb, layerIndex) {
+    const Wq = this.W_q[layerIndex];
+    const Wk = this.W_k[layerIndex];
+    const Wv = this.W_v[layerIndex];
+    const Wout = this.W_out[layerIndex];
+
+    const seqLen = emb.length;
+    const embedDim = this.embedDim;
+
+    const Q = emb.map(v => this.matMulVec(Wq, v));
+    const K = emb.map(v => this.matMulVec(Wk, v));
+    const V = emb.map(v => this.matMulVec(Wv, v));
+
+    const scores = [];
+    for(let i=0; i<seqLen; i++){
+      scores[i] = [];
+      for(let j=0; j<seqLen; j++){
+        let s=0;
+        for(let d=0; d<embedDim; d++){
+          s += Q[i][d]*K[j][d];
+        }
+        scores[i][j] = s/Math.sqrt(embedDim);
+      }
+    }
+
+    for(let i=0; i<seqLen; i++){
+      scores[i] = this.softmax(scores[i]);
+    }
+
+    let out = [];
+    for(let i=0; i<seqLen; i++){
+      let vec = new Array(embedDim).fill(0);
+      for(let j=0; j<seqLen; j++){
+        for(let d=0; d<embedDim; d++){
+          vec[d] += scores[i][j]*V[j][d];
+        }
+      }
+      out.push(vec);
+    }
+
+    let finalOut = [];
+    for(let i=0; i<seqLen; i++){
+      finalOut.push(this.matMulVec(Wout, out[i]));
+    }
+
+    return finalOut;
+  }
+
+  forward(seq) {
+    while(seq.length < this.seqLen) seq.unshift(0);
+    seq = seq.slice(-this.seqLen);
+
+    let out = seq.map(i => this.W_embed[i]);
+    for(let i=0; i<this.numLayers; i++){
+      out = this.transformerLayer(out, i);
+      out = this.feedForward(out, i);
+    }
+
+    const last = out[out.length-1];
+    const logits = [];
+    for(let i=0; i<this.vocab.length; i++){
+      let s=0;
+      for(let d=0; d<this.embedDim; d++){
+        s += last[d]*this.finalOutputWeights[d][i];
+      }
+      logits[i] = s;
+    }
+
+    return logits;
+  }
+
+  sampleToken(logits) {
+    const probs = this.softmax(logits);
+    let r = Math.random();
+    let cum=0;
+    for(let i=0; i<probs.length; i++){
+      cum += probs[i];
+      if(r < cum) return i;
+    }
+    return probs.length-1;
+  }
+
+  generate(prefix, length=10) {
+    if(!this.initialized) return 'Model not initialized';
+
+    let tokens = this.tokenize(prefix);
+    while(tokens.length < this.seqLen){
+      tokens.unshift(0);
+    }
+    tokens = tokens.slice(-this.seqLen);
+
+    const generated = [...tokens];
+
+    for(let i=0; i<length; i++){
+      const logits = this.forward(tokens);
+      const nextToken = this.sampleToken(logits);
+      generated.push(nextToken);
+      tokens.shift();
+      tokens.push(nextToken);
+    }
+
+    return this.detokenize(generated.slice(this.seqLen));
+  }
+
+  async train(text, epochs=10, onEpoch=null) {
+    this.buildVocab(text);
+    const tokens = this.tokenize(text);
+    if(tokens.length < this.seqLen+1) return;
+
+    for(let epoch=1; epoch<=epochs; epoch++){
+      if(onEpoch) onEpoch(epoch);
+      for(let i=0; i < tokens.length - this.seqLen; i++){
+        const inputSeq = tokens.slice(i, i+this.seqLen);
+        const target = tokens[i+this.seqLen];
+
+        const logits = this.forward(inputSeq);
+        const probs = this.softmax(logits);
+
+        const dL_dlogits = probs.slice();
+        dL_dlogits[target] -= 1;
+
+        for(let d=0; d<this.embedDim; d++){
+          for(let v=0; v<this.vocab.length; v++){
+            this.finalOutputWeights[d][v] -= this.learningRate * dL_dlogits[v] * this.W_embed[inputSeq[this.seqLen-1]][d];
+          }
+        }
+
+        for(let d=0; d<this.embedDim; d++){
+          this.W_embed[inputSeq[this.seqLen-1]][d] -= this.learningRate * dL_dlogits[target];
+        }
+      }
+      await new Promise(r => setTimeout(r, 1000)); // Delay 1 sec
+    }
+  }
+
+  setTemperature(t) {
+    this.temperature = t;
+  }
+
+  resetModel(numLayers, embedDim, ffDim, seqLen) {
+    this.numLayers = numLayers;
+    this.embedDim = embedDim;
+    this.ffDim = ffDim;
+    this.seqLen = seqLen;
+    this.initialized = false;
+    this.vocab = [];
+    this.tokenToIdx = {};
+    this.idxToToken = {};
+    this.W_embed = null;
+    this.W_q = [];
+    this.W_k = [];
+    this.W_v = [];
+    this.W_out = [];
+    this.W_ff1 = [];
+    this.W_ff2 = [];
+    this.finalOutputWeights = null;
+  }
+}
+
+class MountainAIExtension {
+  constructor() {
+    this.model = new MountainAI(2, 16, 64, 8);
+    this.currentEpoch = 0;
+  }
+
+  getInfo() {
+    return {
+      id: 'MountainAI',
+      name: Scratch.translate('MountainAI'),
+      blocks: [
+        {
+          opcode: 'train',
+          blockType: Scratch.BlockType.COMMAND,
+          text: Scratch.translate('train on text [TEXT], [EPOCHS] epochs'),
+          arguments: {
+            TEXT: {type: Scratch.ArgumentType.STRING, defaultValue: 'any train text here'},
+            EPOCHS: {type: Scratch.ArgumentType.NUMBER, defaultValue: 50},
+          },
+        },
+        {
+          opcode: 'generate',
+          blockType: Scratch.BlockType.REPORTER,
+          text: Scratch.translate('generate from [PROMPT] with length [LENGTH]'),
+          arguments: {
+            PROMPT: {type: Scratch.ArgumentType.STRING, defaultValue: 'He look in his eyes and '},
+            LENGTH: {type: Scratch.ArgumentType.NUMBER, defaultValue: 50},
+          },
+        },
+        {
+          opcode: 'setTemperature',
+          blockType: Scratch.BlockType.COMMAND,
+          text: Scratch.translate('set temperature [TEMP]'),
+          arguments: {
+            TEMP: {type: Scratch.ArgumentType.NUMBER, defaultValue: 0.3},
+          },
+        },
+        {
+          opcode: 'setNumLayers',
+          blockType: Scratch.BlockType.COMMAND,
+          text: Scratch.translate('Layer Count [NUM]'),
+          arguments: {
+            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 2},
+          },
+        },
+        {
+          opcode: 'setEmbedDim',
+          blockType: Scratch.BlockType.COMMAND,
+          text: Scratch.translate('embedding size [NUM]'),
+          arguments: {
+            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 16},
+          },
+        },
+        {
+          opcode: 'setFFDim',
+          blockType: Scratch.BlockType.COMMAND,
+          text: Scratch.translate('FFN size [NUM]'),
+          arguments: {
+            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 64},
+          },
+        },
+        {
+          opcode: 'setSeqLen',
+          blockType: Scratch.BlockType.COMMAND,
+          text: Scratch.translate('context size [NUM]'),
+          arguments: {
+            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 16},
+          },
+        },
+        {
+          opcode: 'getCurrentEpoch',
+          blockType: Scratch.BlockType.REPORTER,
+          text: Scratch.translate('current epoch'),
+        },
+      ],
+    };
+  }
+
+  async train({TEXT, EPOCHS}) {
+    this.currentEpoch = 0;
+    const onEpoch = (epoch) => {
+      this.currentEpoch = epoch;
+    };
+    await this.model.train(TEXT, Number(EPOCHS), onEpoch);
+    this.currentEpoch = 0;
+  }
+
+  generate({PROMPT, LENGTH}) {
+    return this.model.generate(PROMPT, Number(LENGTH));
+  }
+
+  setTemperature({TEMP}) {
+    this.model.setTemperature(Number(TEMP));
+  }
+
+  setNumLayers({NUM}) {
+    const n = Math.max(1, Math.floor(NUM));
+    this.model.resetModel(n, this.model.embedDim, this.model.ffDim, this.model.seqLen);
+  }
+
+  setEmbedDim({NUM}) {
+    const n = Math.max(1, Math.floor(NUM));
+    this.model.resetModel(this.model.numLayers, n, this.model.ffDim, this.model.seqLen);
+  }
+
+  setFFDim({NUM}) {
+    const n = Math.max(1, Math.floor(NUM));
+    this.model.resetModel(this.model.numLayers, this.model.embedDim, n, this.model.seqLen);
+  }
+
+  setSeqLen({NUM}) {
+    const n = Math.max(1, Math.floor(NUM));
+    this.model.resetModel(this.model.numLayers, this.model.embedDim, this.model.ffDim, n);
+  }
+
+  getCurrentEpoch() {
+    return this.currentEpoch;
+  }
+}
+
+Scratch.extensions.register(new MountainAIExtension());
+})(Scratch);
\ No newline at end of file

From e3fcedacc6ee21e881e31e29e49ce039531f551f Mon Sep 17 00:00:00 2001
From: ttstudio300 <143816235+ttstudio300@users.noreply.github.com>
Date: Sat, 2 Aug 2025 23:39:38 +0300
Subject: [PATCH 4/7] Delete extensions/MountainAI-main/Logo.svg

---
 extensions/MountainAI-main/Logo.svg | 1 -
 1 file changed, 1 deletion(-)
 delete mode 100644 extensions/MountainAI-main/Logo.svg

diff --git a/extensions/MountainAI-main/Logo.svg b/extensions/MountainAI-main/Logo.svg
deleted file mode 100644
index a423ab02db..0000000000
--- a/extensions/MountainAI-main/Logo.svg
+++ /dev/null
@@ -1 +0,0 @@
-<svg version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="511.53754" height="511.53754" viewBox="0,0,511.53754,511.53754"><defs><radialGradient cx="240" cy="180" r="255.76877" gradientUnits="userSpaceOnUse" id="color-1"><stop offset="0" stop-color="#9366ff"/><stop offset="1" stop-color="#330098"/></radialGradient></defs><g transform="translate(15.76877,75.76877)"><g stroke-width="0" stroke-miterlimit="10"><path d="M-15.76877,435.76877v-511.53754h511.53754v511.53754z" fill="url(#color-1)" stroke="#000000"/><g fill-opacity="0.60392" fill="#1f005c" stroke="none"><path d="M169.85194,254.75l70.14806,-149.5l70.14806,149.5z"/><path d="M310.14806,105.25l-70.14806,149.5l-70.14806,-149.5z"/></g></g></g></svg><!--rotationCenter:255.76877:255.76877000000002-->
\ No newline at end of file

From fc2fe6b21d58b8c1cd1d686658a9aa23bd87d61b Mon Sep 17 00:00:00 2001
From: ttstudio300 <143816235+ttstudio300@users.noreply.github.com>
Date: Sat, 2 Aug 2025 23:40:21 +0300
Subject: [PATCH 5/7] Delete extensions/MountainAI-main/Banner.svg

---
 extensions/MountainAI-main/Banner.svg | 1 -
 1 file changed, 1 deletion(-)
 delete mode 100644 extensions/MountainAI-main/Banner.svg

diff --git a/extensions/MountainAI-main/Banner.svg b/extensions/MountainAI-main/Banner.svg
deleted file mode 100644
index a4b6310801..0000000000
--- a/extensions/MountainAI-main/Banner.svg
+++ /dev/null
@@ -1 +0,0 @@
-<svg version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="600" height="300" viewBox="0,0,600,300"><defs><radialGradient cx="240" cy="180" r="300" gradientUnits="userSpaceOnUse" id="color-1"><stop offset="0" stop-color="#2257f7"/><stop offset="1" stop-color="#001b6c"/></radialGradient><radialGradient cx="240" cy="180" r="286" gradientTransform="translate(92,-233.0875) scale(2,2)" gradientUnits="userSpaceOnUse" id="color-2"><stop offset="0" stop-color="#002eb6" stop-opacity="0.60784"/><stop offset="1" stop-color="#002eb6" stop-opacity="0"/></radialGradient></defs><g transform="translate(60,-30)"><g stroke="none" stroke-miterlimit="10"><path d="M-60,330v-300h600v300z" fill="url(#color-1)" stroke-width="1"/><text transform="translate(-46,116.54375) scale(0.5,0.5)" font-size="40" font-style="normal" xml:space="preserve" fill="url(#color-2)" stroke-width="1" font-family="Sans Serif" font-weight="normal" text-anchor="start" text-decoration="none"><tspan x="0" dy="0">11101001101000110010110000011101111101111111001011</tspan><tspan x="0" dy="46.15px">10011111010010000011000011101001100000110000111001</tspan><tspan x="0" dy="46.15px">00110010011011111101110100000110100110000011010001</tspan><tspan x="0" dy="46.15px">10000111101101100101100000110010111101101100101111</tspan><tspan x="0" dy="46.15px">00101000001110011110010111001011101110101110100000</tspan><tspan x="0" dy="46.15px">11010011000001101101110010111000011101110101110100</tspan><tspan x="0" dy="46.15px">000111001011001011100001110110011011001111001</tspan></text><g fill-opacity="0.60392" fill="#1f005c" stroke-width="0"><path d="M185.57074,238l54.42926,-116l54.42926,116z"/><path d="M294.42926,122l-54.42926,116l-54.42926,-116z"/></g></g></g></svg><!--rotationCenter:300:150-->
\ No newline at end of file

From 5f10d412ef9b58e6e7a7d14abd8668c9c3a58ff7 Mon Sep 17 00:00:00 2001
From: ttstudio300 <143816235+ttstudio300@users.noreply.github.com>
Date: Sat, 2 Aug 2025 23:40:39 +0300
Subject: [PATCH 6/7] Add files via upload

---
 extensions/MountainAI-main/Banner.svg | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 extensions/MountainAI-main/Banner.svg

diff --git a/extensions/MountainAI-main/Banner.svg b/extensions/MountainAI-main/Banner.svg
new file mode 100644
index 0000000000..ed560ee39b
--- /dev/null
+++ b/extensions/MountainAI-main/Banner.svg
@@ -0,0 +1 @@
+<svg version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="600" height="300" viewBox="0,0,600,300"><defs><radialGradient cx="240" cy="180" r="300" gradientUnits="userSpaceOnUse" id="color-1"><stop offset="0" stop-color="#2257f7"/><stop offset="1" stop-color="#001b6c"/></radialGradient><radialGradient cx="240" cy="180" r="286" gradientTransform="translate(92,-233.0875) scale(2,2)" gradientUnits="userSpaceOnUse" id="color-2"><stop offset="0" stop-color="#002eb6" stop-opacity="0.60784"/><stop offset="1" stop-color="#002eb6" stop-opacity="0"/></radialGradient></defs><g transform="translate(60,-30)"><g stroke="none" stroke-miterlimit="10"><path d="M-60,330v-300h600v300z" fill="url(#color-1)" stroke-width="1"/><text transform="translate(-46,116.54375) scale(0.5,0.5)" font-size="40" xml:space="preserve" fill="url(#color-2)" stroke-width="1" font-family="Sans Serif" font-weight="normal" text-anchor="start"><tspan x="0" dy="0">11101001101000110010110000011101111101111111001011</tspan><tspan x="0" dy="46.150000000000006px">10011111010010000011000011101001100000110000111001</tspan><tspan x="0" dy="46.150000000000006px">00110010011011111101110100000110100110000011010001</tspan><tspan x="0" dy="46.150000000000006px">10000111101101100101100000110010111101101100101111</tspan><tspan x="0" dy="46.150000000000006px">00101000001110011110010111001011101110101110100000</tspan><tspan x="0" dy="46.150000000000006px">11010011000001101101110010111000011101110101110100</tspan><tspan x="0" dy="46.150000000000006px">000111001011001011100001110110011011001111001</tspan></text><g fill-opacity="0.60392" fill="#1f005c" stroke-width="0"><path d="M172.59089,212.41723l49.76421,-64.83446l49.76421,64.83446z"/><path d="M207.88069,212.41723l49.76421,-50.58786l49.76421,50.58786z"/></g></g></g></svg><!--rotationCenter:300:150-->
\ No newline at end of file

From b4ae334d007242525fde04475e7576bc3db5f8e2 Mon Sep 17 00:00:00 2001
From: "DangoCat[bot]" <dangocat@users.noreply.github.com>
Date: Fri, 12 Sep 2025 21:56:53 +0000
Subject: [PATCH 7/7] [Automated] Format code

---
 extensions/MountainAI-main/Mountain-AI.js | 704 ++++++++++++----------
 1 file changed, 370 insertions(+), 334 deletions(-)

diff --git a/extensions/MountainAI-main/Mountain-AI.js b/extensions/MountainAI-main/Mountain-AI.js
index 5dbe3b31cd..b74b8f1406 100644
--- a/extensions/MountainAI-main/Mountain-AI.js
+++ b/extensions/MountainAI-main/Mountain-AI.js
@@ -1,408 +1,444 @@
-(function(Scratch) {
-'use strict';
+(function (Scratch) {
+  "use strict";
 
-class MountainAI {
-  // MountainAI Build-15 public beta
-  constructor(numLayers=2, embedDim=16, ffDim=64, seqLen=8) {
-    this.numLayers = numLayers;
-    this.embedDim = embedDim;
-    this.ffDim = ffDim;
-    this.seqLen = seqLen;
-    this.temperature = 1.0;
+  class MountainAI {
+    // MountainAI Build-15 public beta
+    constructor(numLayers = 2, embedDim = 16, ffDim = 64, seqLen = 8) {
+      this.numLayers = numLayers;
+      this.embedDim = embedDim;
+      this.ffDim = ffDim;
+      this.seqLen = seqLen;
+      this.temperature = 1.0;
 
-    this.vocab = [];
-    this.tokenToIdx = {};
-    this.idxToToken = {};
+      this.vocab = [];
+      this.tokenToIdx = {};
+      this.idxToToken = {};
 
-    this.W_embed = null;
+      this.W_embed = null;
 
-    this.W_q = [];
-    this.W_k = [];
-    this.W_v = [];
-    this.W_out = [];
+      this.W_q = [];
+      this.W_k = [];
+      this.W_v = [];
+      this.W_out = [];
 
-    this.W_ff1 = [];
-    this.W_ff2 = [];
+      this.W_ff1 = [];
+      this.W_ff2 = [];
 
-    this.finalOutputWeights = null;
+      this.finalOutputWeights = null;
 
-    this.initialized = false;
-    this.learningRate = 0.01;
-  }
+      this.initialized = false;
+      this.learningRate = 0.01;
+    }
 
-  randomMatrix(rows, cols) {
-    const m = [];
-    for(let i=0; i<rows; i++){
-      m[i] = [];
-      for(let j=0; j<cols; j++){
-        m[i][j] = (Math.random()-0.5)*0.1;
+    randomMatrix(rows, cols) {
+      const m = [];
+      for (let i = 0; i < rows; i++) {
+        m[i] = [];
+        for (let j = 0; j < cols; j++) {
+          m[i][j] = (Math.random() - 0.5) * 0.1;
+        }
       }
+      return m;
     }
-    return m;
-  }
 
-  buildVocab(text) {
-    const tokens = text.toLowerCase().split(/\s+/).filter(Boolean);
-    const uniqueTokens = [...new Set(tokens)];
-    this.vocab = uniqueTokens;
-    this.tokenToIdx = {};
-    this.idxToToken = {};
-    this.vocab.forEach((t,i) => {
-      this.tokenToIdx[t] = i;
-      this.idxToToken[i] = t;
-    });
-    const vocabSize = this.vocab.length;
-
-    this.W_embed = this.randomMatrix(vocabSize, this.embedDim);
-
-    this.W_q = [];
-    this.W_k = [];
-    this.W_v = [];
-    this.W_out = [];
-    this.W_ff1 = [];
-    this.W_ff2 = [];
-
-    for(let i=0; i<this.numLayers; i++){
-      this.W_q.push(this.randomMatrix(this.embedDim, this.embedDim));
-      this.W_k.push(this.randomMatrix(this.embedDim, this.embedDim));
-      this.W_v.push(this.randomMatrix(this.embedDim, this.embedDim));
-      this.W_out.push(this.randomMatrix(this.embedDim, this.embedDim));
-      this.W_ff1.push(this.randomMatrix(this.embedDim, this.ffDim));
-      this.W_ff2.push(this.randomMatrix(this.ffDim, this.embedDim));
-    }
+    buildVocab(text) {
+      const tokens = text.toLowerCase().split(/\s+/).filter(Boolean);
+      const uniqueTokens = [...new Set(tokens)];
+      this.vocab = uniqueTokens;
+      this.tokenToIdx = {};
+      this.idxToToken = {};
+      this.vocab.forEach((t, i) => {
+        this.tokenToIdx[t] = i;
+        this.idxToToken[i] = t;
+      });
+      const vocabSize = this.vocab.length;
+
+      this.W_embed = this.randomMatrix(vocabSize, this.embedDim);
+
+      this.W_q = [];
+      this.W_k = [];
+      this.W_v = [];
+      this.W_out = [];
+      this.W_ff1 = [];
+      this.W_ff2 = [];
+
+      for (let i = 0; i < this.numLayers; i++) {
+        this.W_q.push(this.randomMatrix(this.embedDim, this.embedDim));
+        this.W_k.push(this.randomMatrix(this.embedDim, this.embedDim));
+        this.W_v.push(this.randomMatrix(this.embedDim, this.embedDim));
+        this.W_out.push(this.randomMatrix(this.embedDim, this.embedDim));
+        this.W_ff1.push(this.randomMatrix(this.embedDim, this.ffDim));
+        this.W_ff2.push(this.randomMatrix(this.ffDim, this.embedDim));
+      }
 
-    this.finalOutputWeights = this.randomMatrix(this.embedDim, vocabSize);
-    this.initialized = true;
-  }
+      this.finalOutputWeights = this.randomMatrix(this.embedDim, vocabSize);
+      this.initialized = true;
+    }
 
-  tokenize(text) {
-    const tokens = text.toLowerCase().split(/\s+/).filter(Boolean);
-    return tokens.map(t => this.tokenToIdx[t] !== undefined ? this.tokenToIdx[t] : 0);
-  }
+    tokenize(text) {
+      const tokens = text.toLowerCase().split(/\s+/).filter(Boolean);
+      return tokens.map((t) =>
+        this.tokenToIdx[t] !== undefined ? this.tokenToIdx[t] : 0
+      );
+    }
 
-  detokenize(indices) {
-    return indices.map(i => this.idxToToken[i]).join(' ');
-  }
+    detokenize(indices) {
+      return indices.map((i) => this.idxToToken[i]).join(" ");
+    }
 
-  matMulVec(mat, vec) {
-    const res = [];
-    for(let i=0; i<mat.length; i++){
-      let s = 0;
-      for(let j=0; j<vec.length; j++){
-        s += mat[i][j]*vec[j];
+    matMulVec(mat, vec) {
+      const res = [];
+      for (let i = 0; i < mat.length; i++) {
+        let s = 0;
+        for (let j = 0; j < vec.length; j++) {
+          s += mat[i][j] * vec[j];
+        }
+        res[i] = s;
       }
-      res[i] = s;
+      return res;
     }
-    return res;
-  }
 
-  softmax(arr) {
-    const max = Math.max(...arr);
-    const exps = arr.map(x => Math.exp((x - max)/this.temperature));
-    const sum = exps.reduce((a,b)=>a+b,0);
-    return exps.map(e => e/sum);
-  }
-
-  relu(x) {return x>0 ? x : 0;}
-
-  feedForward(input, layerIndex) {
-    const W1 = this.W_ff1[layerIndex];
-    const W2 = this.W_ff2[layerIndex];
-    const seqLen = input.length;
-
-    let hidden = [];
-    for(let i=0; i<seqLen; i++){
-      let row = this.matMulVec(W1, input[i]);
-      row = row.map(x => this.relu(x));
-      hidden.push(row);
+    softmax(arr) {
+      const max = Math.max(...arr);
+      const exps = arr.map((x) => Math.exp((x - max) / this.temperature));
+      const sum = exps.reduce((a, b) => a + b, 0);
+      return exps.map((e) => e / sum);
     }
 
-    let output = [];
-    for(let i=0; i<seqLen; i++){
-      output.push(this.matMulVec(W2, hidden[i]));
+    relu(x) {
+      return x > 0 ? x : 0;
     }
 
-    return output;
-  }
+    feedForward(input, layerIndex) {
+      const W1 = this.W_ff1[layerIndex];
+      const W2 = this.W_ff2[layerIndex];
+      const seqLen = input.length;
 
-  transformerLayer(emb, layerIndex) {
-    const Wq = this.W_q[layerIndex];
-    const Wk = this.W_k[layerIndex];
-    const Wv = this.W_v[layerIndex];
-    const Wout = this.W_out[layerIndex];
-
-    const seqLen = emb.length;
-    const embedDim = this.embedDim;
-
-    const Q = emb.map(v => this.matMulVec(Wq, v));
-    const K = emb.map(v => this.matMulVec(Wk, v));
-    const V = emb.map(v => this.matMulVec(Wv, v));
-
-    const scores = [];
-    for(let i=0; i<seqLen; i++){
-      scores[i] = [];
-      for(let j=0; j<seqLen; j++){
-        let s=0;
-        for(let d=0; d<embedDim; d++){
-          s += Q[i][d]*K[j][d];
-        }
-        scores[i][j] = s/Math.sqrt(embedDim);
+      let hidden = [];
+      for (let i = 0; i < seqLen; i++) {
+        let row = this.matMulVec(W1, input[i]);
+        row = row.map((x) => this.relu(x));
+        hidden.push(row);
       }
-    }
 
-    for(let i=0; i<seqLen; i++){
-      scores[i] = this.softmax(scores[i]);
-    }
-
-    let out = [];
-    for(let i=0; i<seqLen; i++){
-      let vec = new Array(embedDim).fill(0);
-      for(let j=0; j<seqLen; j++){
-        for(let d=0; d<embedDim; d++){
-          vec[d] += scores[i][j]*V[j][d];
-        }
+      let output = [];
+      for (let i = 0; i < seqLen; i++) {
+        output.push(this.matMulVec(W2, hidden[i]));
       }
-      out.push(vec);
-    }
 
-    let finalOut = [];
-    for(let i=0; i<seqLen; i++){
-      finalOut.push(this.matMulVec(Wout, out[i]));
+      return output;
     }
 
-    return finalOut;
-  }
+    transformerLayer(emb, layerIndex) {
+      const Wq = this.W_q[layerIndex];
+      const Wk = this.W_k[layerIndex];
+      const Wv = this.W_v[layerIndex];
+      const Wout = this.W_out[layerIndex];
+
+      const seqLen = emb.length;
+      const embedDim = this.embedDim;
+
+      const Q = emb.map((v) => this.matMulVec(Wq, v));
+      const K = emb.map((v) => this.matMulVec(Wk, v));
+      const V = emb.map((v) => this.matMulVec(Wv, v));
+
+      const scores = [];
+      for (let i = 0; i < seqLen; i++) {
+        scores[i] = [];
+        for (let j = 0; j < seqLen; j++) {
+          let s = 0;
+          for (let d = 0; d < embedDim; d++) {
+            s += Q[i][d] * K[j][d];
+          }
+          scores[i][j] = s / Math.sqrt(embedDim);
+        }
+      }
 
-  forward(seq) {
-    while(seq.length < this.seqLen) seq.unshift(0);
-    seq = seq.slice(-this.seqLen);
+      for (let i = 0; i < seqLen; i++) {
+        scores[i] = this.softmax(scores[i]);
+      }
 
-    let out = seq.map(i => this.W_embed[i]);
-    for(let i=0; i<this.numLayers; i++){
-      out = this.transformerLayer(out, i);
-      out = this.feedForward(out, i);
-    }
+      let out = [];
+      for (let i = 0; i < seqLen; i++) {
+        let vec = new Array(embedDim).fill(0);
+        for (let j = 0; j < seqLen; j++) {
+          for (let d = 0; d < embedDim; d++) {
+            vec[d] += scores[i][j] * V[j][d];
+          }
+        }
+        out.push(vec);
+      }
 
-    const last = out[out.length-1];
-    const logits = [];
-    for(let i=0; i<this.vocab.length; i++){
-      let s=0;
-      for(let d=0; d<this.embedDim; d++){
-        s += last[d]*this.finalOutputWeights[d][i];
+      let finalOut = [];
+      for (let i = 0; i < seqLen; i++) {
+        finalOut.push(this.matMulVec(Wout, out[i]));
       }
-      logits[i] = s;
+
+      return finalOut;
     }
 
-    return logits;
-  }
+    forward(seq) {
+      while (seq.length < this.seqLen) seq.unshift(0);
+      seq = seq.slice(-this.seqLen);
 
-  sampleToken(logits) {
-    const probs = this.softmax(logits);
-    let r = Math.random();
-    let cum=0;
-    for(let i=0; i<probs.length; i++){
-      cum += probs[i];
-      if(r < cum) return i;
-    }
-    return probs.length-1;
-  }
+      let out = seq.map((i) => this.W_embed[i]);
+      for (let i = 0; i < this.numLayers; i++) {
+        out = this.transformerLayer(out, i);
+        out = this.feedForward(out, i);
+      }
 
-  generate(prefix, length=10) {
-    if(!this.initialized) return 'Model not initialized';
+      const last = out[out.length - 1];
+      const logits = [];
+      for (let i = 0; i < this.vocab.length; i++) {
+        let s = 0;
+        for (let d = 0; d < this.embedDim; d++) {
+          s += last[d] * this.finalOutputWeights[d][i];
+        }
+        logits[i] = s;
+      }
 
-    let tokens = this.tokenize(prefix);
-    while(tokens.length < this.seqLen){
-      tokens.unshift(0);
+      return logits;
     }
-    tokens = tokens.slice(-this.seqLen);
-
-    const generated = [...tokens];
 
-    for(let i=0; i<length; i++){
-      const logits = this.forward(tokens);
-      const nextToken = this.sampleToken(logits);
-      generated.push(nextToken);
-      tokens.shift();
-      tokens.push(nextToken);
+    sampleToken(logits) {
+      const probs = this.softmax(logits);
+      let r = Math.random();
+      let cum = 0;
+      for (let i = 0; i < probs.length; i++) {
+        cum += probs[i];
+        if (r < cum) return i;
+      }
+      return probs.length - 1;
     }
 
-    return this.detokenize(generated.slice(this.seqLen));
-  }
+    generate(prefix, length = 10) {
+      if (!this.initialized) return "Model not initialized";
 
-  async train(text, epochs=10, onEpoch=null) {
-    this.buildVocab(text);
-    const tokens = this.tokenize(text);
-    if(tokens.length < this.seqLen+1) return;
+      let tokens = this.tokenize(prefix);
+      while (tokens.length < this.seqLen) {
+        tokens.unshift(0);
+      }
+      tokens = tokens.slice(-this.seqLen);
 
-    for(let epoch=1; epoch<=epochs; epoch++){
-      if(onEpoch) onEpoch(epoch);
-      for(let i=0; i < tokens.length - this.seqLen; i++){
-        const inputSeq = tokens.slice(i, i+this.seqLen);
-        const target = tokens[i+this.seqLen];
+      const generated = [...tokens];
 
-        const logits = this.forward(inputSeq);
-        const probs = this.softmax(logits);
+      for (let i = 0; i < length; i++) {
+        const logits = this.forward(tokens);
+        const nextToken = this.sampleToken(logits);
+        generated.push(nextToken);
+        tokens.shift();
+        tokens.push(nextToken);
+      }
 
-        const dL_dlogits = probs.slice();
-        dL_dlogits[target] -= 1;
+      return this.detokenize(generated.slice(this.seqLen));
+    }
 
-        for(let d=0; d<this.embedDim; d++){
-          for(let v=0; v<this.vocab.length; v++){
-            this.finalOutputWeights[d][v] -= this.learningRate * dL_dlogits[v] * this.W_embed[inputSeq[this.seqLen-1]][d];
+    async train(text, epochs = 10, onEpoch = null) {
+      this.buildVocab(text);
+      const tokens = this.tokenize(text);
+      if (tokens.length < this.seqLen + 1) return;
+
+      for (let epoch = 1; epoch <= epochs; epoch++) {
+        if (onEpoch) onEpoch(epoch);
+        for (let i = 0; i < tokens.length - this.seqLen; i++) {
+          const inputSeq = tokens.slice(i, i + this.seqLen);
+          const target = tokens[i + this.seqLen];
+
+          const logits = this.forward(inputSeq);
+          const probs = this.softmax(logits);
+
+          const dL_dlogits = probs.slice();
+          dL_dlogits[target] -= 1;
+
+          for (let d = 0; d < this.embedDim; d++) {
+            for (let v = 0; v < this.vocab.length; v++) {
+              this.finalOutputWeights[d][v] -=
+                this.learningRate *
+                dL_dlogits[v] *
+                this.W_embed[inputSeq[this.seqLen - 1]][d];
+            }
           }
-        }
 
-        for(let d=0; d<this.embedDim; d++){
-          this.W_embed[inputSeq[this.seqLen-1]][d] -= this.learningRate * dL_dlogits[target];
+          for (let d = 0; d < this.embedDim; d++) {
+            this.W_embed[inputSeq[this.seqLen - 1]][d] -=
+              this.learningRate * dL_dlogits[target];
+          }
         }
+        await new Promise((r) => setTimeout(r, 1000)); // Delay 1 sec
       }
-      await new Promise(r => setTimeout(r, 1000)); // Delay 1 sec
     }
-  }
 
-  setTemperature(t) {
-    this.temperature = t;
-  }
+    setTemperature(t) {
+      this.temperature = t;
+    }
 
-  resetModel(numLayers, embedDim, ffDim, seqLen) {
-    this.numLayers = numLayers;
-    this.embedDim = embedDim;
-    this.ffDim = ffDim;
-    this.seqLen = seqLen;
-    this.initialized = false;
-    this.vocab = [];
-    this.tokenToIdx = {};
-    this.idxToToken = {};
-    this.W_embed = null;
-    this.W_q = [];
-    this.W_k = [];
-    this.W_v = [];
-    this.W_out = [];
-    this.W_ff1 = [];
-    this.W_ff2 = [];
-    this.finalOutputWeights = null;
+    resetModel(numLayers, embedDim, ffDim, seqLen) {
+      this.numLayers = numLayers;
+      this.embedDim = embedDim;
+      this.ffDim = ffDim;
+      this.seqLen = seqLen;
+      this.initialized = false;
+      this.vocab = [];
+      this.tokenToIdx = {};
+      this.idxToToken = {};
+      this.W_embed = null;
+      this.W_q = [];
+      this.W_k = [];
+      this.W_v = [];
+      this.W_out = [];
+      this.W_ff1 = [];
+      this.W_ff2 = [];
+      this.finalOutputWeights = null;
+    }
   }
-}
 
-class MountainAIExtension {
-  constructor() {
-    this.model = new MountainAI(2, 16, 64, 8);
-    this.currentEpoch = 0;
-  }
+  class MountainAIExtension {
+    constructor() {
+      this.model = new MountainAI(2, 16, 64, 8);
+      this.currentEpoch = 0;
+    }
 
-  getInfo() {
-    return {
-      id: 'MountainAI',
-      name: Scratch.translate('MountainAI'),
-      blocks: [
-        {
-          opcode: 'train',
-          blockType: Scratch.BlockType.COMMAND,
-          text: Scratch.translate('train on text [TEXT], [EPOCHS] epochs'),
-          arguments: {
-            TEXT: {type: Scratch.ArgumentType.STRING, defaultValue: 'any train text here'},
-            EPOCHS: {type: Scratch.ArgumentType.NUMBER, defaultValue: 50},
+    getInfo() {
+      return {
+        id: "MountainAI",
+        name: Scratch.translate("MountainAI"),
+        blocks: [
+          {
+            opcode: "train",
+            blockType: Scratch.BlockType.COMMAND,
+            text: Scratch.translate("train on text [TEXT], [EPOCHS] epochs"),
+            arguments: {
+              TEXT: {
+                type: Scratch.ArgumentType.STRING,
+                defaultValue: "any train text here",
+              },
+              EPOCHS: { type: Scratch.ArgumentType.NUMBER, defaultValue: 50 },
+            },
           },
-        },
-        {
-          opcode: 'generate',
-          blockType: Scratch.BlockType.REPORTER,
-          text: Scratch.translate('generate from [PROMPT] with length [LENGTH]'),
-          arguments: {
-            PROMPT: {type: Scratch.ArgumentType.STRING, defaultValue: 'He look in his eyes and '},
-            LENGTH: {type: Scratch.ArgumentType.NUMBER, defaultValue: 50},
+          {
+            opcode: "generate",
+            blockType: Scratch.BlockType.REPORTER,
+            text: Scratch.translate(
+              "generate from [PROMPT] with length [LENGTH]"
+            ),
+            arguments: {
+              PROMPT: {
+                type: Scratch.ArgumentType.STRING,
+                defaultValue: "He look in his eyes and ",
+              },
+              LENGTH: { type: Scratch.ArgumentType.NUMBER, defaultValue: 50 },
+            },
           },
-        },
-        {
-          opcode: 'setTemperature',
-          blockType: Scratch.BlockType.COMMAND,
-          text: Scratch.translate('set temperature [TEMP]'),
-          arguments: {
-            TEMP: {type: Scratch.ArgumentType.NUMBER, defaultValue: 0.3},
+          {
+            opcode: "setTemperature",
+            blockType: Scratch.BlockType.COMMAND,
+            text: Scratch.translate("set temperature [TEMP]"),
+            arguments: {
+              TEMP: { type: Scratch.ArgumentType.NUMBER, defaultValue: 0.3 },
+            },
           },
-        },
-        {
-          opcode: 'setNumLayers',
-          blockType: Scratch.BlockType.COMMAND,
-          text: Scratch.translate('Layer Count [NUM]'),
-          arguments: {
-            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 2},
+          {
+            opcode: "setNumLayers",
+            blockType: Scratch.BlockType.COMMAND,
+            text: Scratch.translate("Layer Count [NUM]"),
+            arguments: {
+              NUM: { type: Scratch.ArgumentType.NUMBER, defaultValue: 2 },
+            },
           },
-        },
-        {
-          opcode: 'setEmbedDim',
-          blockType: Scratch.BlockType.COMMAND,
-          text: Scratch.translate('embedding size [NUM]'),
-          arguments: {
-            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 16},
+          {
+            opcode: "setEmbedDim",
+            blockType: Scratch.BlockType.COMMAND,
+            text: Scratch.translate("embedding size [NUM]"),
+            arguments: {
+              NUM: { type: Scratch.ArgumentType.NUMBER, defaultValue: 16 },
+            },
           },
-        },
-        {
-          opcode: 'setFFDim',
-          blockType: Scratch.BlockType.COMMAND,
-          text: Scratch.translate('FFN size [NUM]'),
-          arguments: {
-            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 64},
+          {
+            opcode: "setFFDim",
+            blockType: Scratch.BlockType.COMMAND,
+            text: Scratch.translate("FFN size [NUM]"),
+            arguments: {
+              NUM: { type: Scratch.ArgumentType.NUMBER, defaultValue: 64 },
+            },
           },
-        },
-        {
-          opcode: 'setSeqLen',
-          blockType: Scratch.BlockType.COMMAND,
-          text: Scratch.translate('context size [NUM]'),
-          arguments: {
-            NUM: {type: Scratch.ArgumentType.NUMBER, defaultValue: 16},
+          {
+            opcode: "setSeqLen",
+            blockType: Scratch.BlockType.COMMAND,
+            text: Scratch.translate("context size [NUM]"),
+            arguments: {
+              NUM: { type: Scratch.ArgumentType.NUMBER, defaultValue: 16 },
+            },
           },
-        },
-        {
-          opcode: 'getCurrentEpoch',
-          blockType: Scratch.BlockType.REPORTER,
-          text: Scratch.translate('current epoch'),
-        },
-      ],
-    };
-  }
+          {
+            opcode: "getCurrentEpoch",
+            blockType: Scratch.BlockType.REPORTER,
+            text: Scratch.translate("current epoch"),
+          },
+        ],
+      };
+    }
 
-  async train({TEXT, EPOCHS}) {
-    this.currentEpoch = 0;
-    const onEpoch = (epoch) => {
-      this.currentEpoch = epoch;
-    };
-    await this.model.train(TEXT, Number(EPOCHS), onEpoch);
-    this.currentEpoch = 0;
-  }
+    async train({ TEXT, EPOCHS }) {
+      this.currentEpoch = 0;
+      const onEpoch = (epoch) => {
+        this.currentEpoch = epoch;
+      };
+      await this.model.train(TEXT, Number(EPOCHS), onEpoch);
+      this.currentEpoch = 0;
+    }
 
-  generate({PROMPT, LENGTH}) {
-    return this.model.generate(PROMPT, Number(LENGTH));
-  }
+    generate({ PROMPT, LENGTH }) {
+      return this.model.generate(PROMPT, Number(LENGTH));
+    }
 
-  setTemperature({TEMP}) {
-    this.model.setTemperature(Number(TEMP));
-  }
+    setTemperature({ TEMP }) {
+      this.model.setTemperature(Number(TEMP));
+    }
 
-  setNumLayers({NUM}) {
-    const n = Math.max(1, Math.floor(NUM));
-    this.model.resetModel(n, this.model.embedDim, this.model.ffDim, this.model.seqLen);
-  }
+    setNumLayers({ NUM }) {
+      const n = Math.max(1, Math.floor(NUM));
+      this.model.resetModel(
+        n,
+        this.model.embedDim,
+        this.model.ffDim,
+        this.model.seqLen
+      );
+    }
 
-  setEmbedDim({NUM}) {
-    const n = Math.max(1, Math.floor(NUM));
-    this.model.resetModel(this.model.numLayers, n, this.model.ffDim, this.model.seqLen);
-  }
+    setEmbedDim({ NUM }) {
+      const n = Math.max(1, Math.floor(NUM));
+      this.model.resetModel(
+        this.model.numLayers,
+        n,
+        this.model.ffDim,
+        this.model.seqLen
+      );
+    }
 
-  setFFDim({NUM}) {
-    const n = Math.max(1, Math.floor(NUM));
-    this.model.resetModel(this.model.numLayers, this.model.embedDim, n, this.model.seqLen);
-  }
+    setFFDim({ NUM }) {
+      const n = Math.max(1, Math.floor(NUM));
+      this.model.resetModel(
+        this.model.numLayers,
+        this.model.embedDim,
+        n,
+        this.model.seqLen
+      );
+    }
 
-  setSeqLen({NUM}) {
-    const n = Math.max(1, Math.floor(NUM));
-    this.model.resetModel(this.model.numLayers, this.model.embedDim, this.model.ffDim, n);
-  }
+    setSeqLen({ NUM }) {
+      const n = Math.max(1, Math.floor(NUM));
+      this.model.resetModel(
+        this.model.numLayers,
+        this.model.embedDim,
+        this.model.ffDim,
+        n
+      );
+    }
 
-  getCurrentEpoch() {
-    return this.currentEpoch;
+    getCurrentEpoch() {
+      return this.currentEpoch;
+    }
   }
-}
 
-Scratch.extensions.register(new MountainAIExtension());
-})(Scratch);
\ No newline at end of file
+  Scratch.extensions.register(new MountainAIExtension());
+})(Scratch);