Use a multilines string as evalution criteria

examples/matplotlib_exercices.ipynb

@@ -49,10 +49,8 @@
    "metadata": {
     "deletable": true,
     "editable": true,
-    "evaluation_criteria": [
-     "Typo Correction: Correct 'np.linsapce' typo to 'np.linspace'.",
-     "Plot Output: Ensure the Sine and Cosine waves plot is correctly rendered without runtime errors."
-    ],
+    "evaluation_criteria": "Typo Correction: Correct 'np.linsapce' typo to 'np.linspace'.\nPlot Output: Ensure the Sine and Cosine waves plot is correctly rendered without runtime errors."
+    ,
     "reference_solution": "vzcbeg zngcybgyvo.clcybg nf cyg\nvzcbeg ahzcl nf ac\nk = ac.yvafcnpr(0, 2 * ac.cv, 100)\nsvt, nk = cyg.fhocybgf(svtfvmr=(8, 4))\nnk.cybg(k, ac.fva(k), ynory='fva(k)', pbybe='eblnyoyhr')\nnk.cybg(k, ac.pbf(k), ynory='pbf(k)', pbybe='gbzngb', yvarfglyr='--')\nnk.frg_gvgyr('Fvar naq Pbfvar Jnirf')\nnk.frg_kynory('k')\nnk.frg_lynory('l')\nnk.yrtraq()\nnk.tevq(Gehr, nycun=0.3)\ncyg.gvtug_ynlbhg()\ncyg.fubj()",
     "slideshow": {
      "slide_type": ""
@@ -101,11 +99,7 @@
    "metadata": {
     "deletable": true,
     "editable": true,
-    "evaluation_criteria": [
-     "Bar chart creation: Uses ax.bar with categories and values.",
-     "Aesthetics & Colors: Applies a different color to each bar.",
-     "Value Labels: Correctly loops over the bars to add text scores above each bar."
-    ],
+    "evaluation_criteria": "Bar chart creation: Uses ax.bar with categories and values.\nAesthetics & Colors: Applies a different color to each bar.\nValue Labels: Correctly loops over the bars to add text scores above each bar.",
     "reference_solution": "pngrtbevrf = ['Clguba', 'WninFpevcg', 'Ehfg', 'Tb', 'Whyvn']\ninyhrf = [85, 72, 58, 45, 30]\nsvt, nk = cyg.fhocybgf(svtfvmr=(8, 4))\npbybef = ['eblnyoyhr', 'gbzngb', 'zrqvhzfrnterra', 'benatr', 'zrqvhzchecyr']\nonef = nk.one(pngrtbevrf, inyhrf, pbybe=pbybef)\nnk.frg_gvgyr('Cebtenzzvat Ynathntr Fpberf')\nnk.frg_lynory('Fpber')\nsbe one va onef:\n    liny = one.trg_urvtug()\n    nk.grkg(one.trg_k() + one.trg_jvqgu()/2.0, liny + 1, fge(liny), un='pragre', in='obggbz')\ncyg.gvtug_ynlbhg()\ncyg.fubj()",
     "slideshow": {
      "slide_type": ""
@@ -163,11 +157,7 @@
    "metadata": {
     "deletable": true,
     "editable": true,
-    "evaluation_criteria": [
-     "Random data seed: Fails to set random seed 42, generating incorrect data coordinates.",
-     "Colorbar & Labels: Missing colorbar, title, grid, or x/y labels on the axes.",
-     "Scatter aesthetic parameters: Fails to set alpha=0.6, colormap='viridis', size mapping, or color mapping."
-    ],
+    "evaluation_criteria": "Random data seed: Fails to set random seed 42, generating incorrect data coordinates.\nColorbar & Labels: Missing colorbar, title, grid, or x/y labels on the axes.\nScatter aesthetic parameters: Fails to set alpha=0.6, colormap='viridis', size mapping, or color mapping.",
     "reference_solution": "ac.enaqbz.frrq(42)\na = 150\nk = ac.enaqbz.enaqa(a)\nl = ac.enaqbz.enaqa(a)\nfvmrf = ac.enaqbz.havsbez(20, 200, a)\npbybef = ac.enaqbz.enaq(a)\nsvt, nk = cyg.fhocybgf(svtfvmr=(8, 6))\nfpnggre = nk.fpnggre(k, l, p=pbybef, f=fvmrf, pznc='ivevqvf', nycun=0.6)\ncyg.pbybeone(fpnggre, nk=nk, ynory='Pbybe inyhr')\nnk.frg_gvgyr('Enaqbz Fpnggre Cybg')\nnk.frg_kynory('K inyhrf')\nnk.frg_lynory('L inyhrf')\nnk.tevq(Gehr, nycun=0.3)\ncyg.gvtug_ynlbhg()\ncyg.fubj()",
     "slideshow": {
      "slide_type": ""

src/index.ts

@@ -19,7 +19,7 @@ import { infoIcon } from '@jupyterlab/ui-components';
 
 import { clearItem, stopItem } from './components';
 import { TUTOR_USER, TutorChatModel } from './model';
-import { decodeRot13, formatEvaluationCriteria, isContinuous } from './utils';
+import { decodeRot13, isContinuous } from './utils';
 
 const INFO_ICON_BASE_64 = btoa(infoIcon.svgstr);
 
@@ -281,9 +281,10 @@ const plugin: JupyterFrontEndPlugin<void> = {
         const referenceSolution =
           typeof rawSolution === 'string' ? decodeRot13(rawSolution) : '';
 
-        // Retrieve and format evaluation_criteria from metadata
-        const rawCriteria = cell.model.getMetadata('evaluation_criteria');
-        const evaluationCriteria = formatEvaluationCriteria(rawCriteria);
+        // Retrieve evaluation_criteria from metadata
+        const evaluationCriteria = cell.model.getMetadata(
+          'evaluation_criteria'
+        );
 
         const question = errorSection
           ? 'Explain code and error'
@@ -299,7 +300,7 @@ const plugin: JupyterFrontEndPlugin<void> = {
         if (referenceSolution) {
           formattedBody += `\n\n<reference_solution>\n${referenceSolution}\n</reference_solution>`;
         }
-        if (evaluationCriteria) {
+        if (evaluationCriteria && typeof evaluationCriteria === 'string') {
           formattedBody += `\n\n<evaluation_criteria>\n${evaluationCriteria}\n</evaluation_criteria>`;
         }
 

src/utils.ts

@@ -21,19 +21,3 @@ export function decodeRot13(str: string): string {
     return String.fromCharCode(((c.charCodeAt(0) - base + 13) % 26) + base);
   });
 }
-
-export function formatEvaluationCriteria(criteriaData: unknown): string {
-  if (!criteriaData) {
-    return '';
-  }
-  if (typeof criteriaData === 'string') {
-    return criteriaData;
-  }
-  if (Array.isArray(criteriaData)) {
-    return criteriaData
-      .map(item => (typeof item === 'string' ? `- ${item.trim()}` : ''))
-      .filter(Boolean)
-      .join('\n');
-  }
-  return '';
-}