Data Analysis
Lit un jeu de données CSV/JSON et le découpe en train/validation/test avec échantillonnage stratifié par la colonne cible (70/15/15 par défaut, graine reproductible), ou k-fold stratifié ; rapport de distribution des classes par split avec barres d'écart, contrôle des fuites par lignes dupliquées, aperçu SMOTE (interpolation des plus proches voisins sur le train) et export des CSV en ZIP.
Appelez cet outil depuis votre code en trois langages.
# 1) Request a presigned URL → returns { uploadUrl, storageKey }
curl -X POST 'http://127.0.0.1:3003/api/upload/presign/train-test-split-with-stratification' \
-H 'Content-Type: application/json' \
-d '{"filename":"dataFile.ext","contentType":"application/octet-stream","size":12345}'
# 2) PUT the file bytes directly to the presigned uploadUrl
curl -X PUT '<presigned uploadUrl>' \
--data-binary @/path/to/file.ext
# 3) Call the tool, passing the returned storageKey for each file field
curl -X POST 'http://127.0.0.1:3003/fr/api/tools/train-test-split-with-stratification' \
-F 'dataFile=uploads/2026/01/01/your-tool-1700000000000-abc123.ext' \
-F 'datasetText=text,length,label
The movie was wonderful and I loved every minute,42,positive
Absolutely terrible waste of time,31,negative
Pretty good overall would recommend,31,positive
Bad acting and a worse plot,25,negative
I enjoyed it a lot,16,positive
Not great not terrible just fine,30,neutral
Loved the soundtrack and visuals,28,positive
The pacing was boring and slow,28,negative
It was okay nothing special,24,neutral
Fantastic acting by the whole cast,30,positive
Weak ending ruined it for me,24,negative
Fine for a rainy afternoon,24,neutral
Brilliant and moving film,23,positive
Disappointing sequel,19,negative
Mediocre but watchable,21,neutral
Gorgeous cinematography throughout,29,positive
Painfully dull script,19,negative
A masterpiece of the genre,24,positive
Cliched and forgettable,20,negative
Charming and genuinely funny,25,positive
Skip it you will thank me,21,negative
Delightful from start to finish,27,positive
Two hours I will never get back,29,negative
Watchable if nothing else is on,26,neutral' \
-F 'targetColumn=label' \
-F 'splitMode=standard' \
-F 'trainPercent=70' \
-F 'valPercent=15' \
-F 'kFolds=5' \
-F 'randomSeed=42' \
-F 'stratify=true' \
-F 'shuffle=true' \
-F 'smotePreview=false' \
-F 'exportZip=true'Envoyez une requête POST avec vos entrées en JSON. Les paramètres de type fichier nécessitent un upload préalable.
POST http://127.0.0.1:3003/fr/api/tools/train-test-split-with-stratification| Nom | Type | Requis | Description |
|---|---|---|---|
| dataFile | fileupload requis | Non | — |
| datasetText | textarea | Non | — |
| targetColumn | text | Oui | — |
| splitMode | select | Non | — |
| trainPercent | number | Non | — |
| valPercent | number | Non | — |
| kFolds | number | Non | — |
| randomSeed | number | Non | — |
| stratify | checkbox | Non | — |
| shuffle | checkbox | Non | — |
| smotePreview | checkbox | Non | — |
| exportZip | checkbox | Non | — |
Résultat HTML
{
"result": "<div>Processed HTML content</div>",
"error": "Error message (optional)",
"message": "Notification message (optional)",
"metadata": {
"key": "value"
}
}Ajoutez cet outil à votre serveur Model Context Protocol pour que les agents IA puissent le lister et l'appeler.
Ajoutez ce bloc à la configuration de votre client MCP :
{
"mcpServers": {
"elysiatools-train-test-split-with-stratification": {
"name": "train-test-split-with-stratification",
"description": "Lit un jeu de données CSV/JSON et le découpe en train/validation/test avec échantillonnage stratifié par la colonne cible (70/15/15 par défaut, graine reproductible), ou k-fold stratifié ; rapport de distribution des classes par split avec barres d'écart, contrôle des fuites par lignes dupliquées, aperçu SMOTE (interpolation des plus proches voisins sur le train) et export des CSV en ZIP.",
"baseUrl": "http://127.0.0.1:3003/mcp/sse?toolId=train-test-split-with-stratification",
"command": "",
"args": [],
"env": {},
"isActive": true,
"type": "sse"
}
}
}Après connexion au point d'accès SSE, listez les outils exposés :
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/list"
}Appelez l'outil par son id ; les arguments sont construits à partir de ses paramètres :
{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/call",
"params": {
"name": "train-test-split-with-stratification",
"arguments": {
"dataFile": "https://example.com/file.ext",
"datasetText": "text,length,label\nThe movie was wonderful and I loved every minute,42,positive\nAbsolutely terrible waste of time,31,negative\nPretty good overall would recommend,31,positive\nBad acting and a worse plot,25,negative\nI enjoyed it a lot,16,positive\nNot great not terrible just fine,30,neutral\nLoved the soundtrack and visuals,28,positive\nThe pacing was boring and slow,28,negative\nIt was okay nothing special,24,neutral\nFantastic acting by the whole cast,30,positive\nWeak ending ruined it for me,24,negative\nFine for a rainy afternoon,24,neutral\nBrilliant and moving film,23,positive\nDisappointing sequel,19,negative\nMediocre but watchable,21,neutral\nGorgeous cinematography throughout,29,positive\nPainfully dull script,19,negative\nA masterpiece of the genre,24,positive\nCliched and forgettable,20,negative\nCharming and genuinely funny,25,positive\nSkip it you will thank me,21,negative\nDelightful from start to finish,27,positive\nTwo hours I will never get back,29,negative\nWatchable if nothing else is on,26,neutral",
"targetColumn": "label",
"splitMode": "standard",
"trainPercent": 70,
"valPercent": 15,
"kFolds": 5,
"randomSeed": 42,
"stratify": true,
"shuffle": true,
"smotePreview": false,
"exportZip": true
}
}
}Des questions ou un problème ? Contactez [email protected]