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BLEU and ROUGE Metrics Calculator
x402
BLEU and ROUGE Metrics Calculator is a paid API for AI agents from ml-metrics.x402tookit.com, paid per call via x402, $0.02/call, status unknown (last checked 2026-11-02).
Computes sentence BLEU (1–4 gram with brevity penalty and optional smoothing) and ROUGE-1, ROUGE-2, ROUGE-L F1/precision/recall scores for a candidate text against one or more reference texts.
Price / call$0.02
Success—
StatusUnknown
How this service works
Sentence BLEU (1-4 gram, brevity penalty, optional smoothing) and ROUGE-1, ROUGE-2, ROUGE-L F1 for text against references.
Output
Returns a JSON object containing the BLEU score and its n-gram order, ROUGE-1, ROUGE-2, and ROUGE-L each with precision, recall, and F1, along with metadata such as smoothing method used, tokenizer, an optional summary/verdict, and any degraded-mode or disclaimer notes.
Example use cases
Evaluating machine translation output
“I have a machine-translated sentence — 'The quick brown fox leaps over the lazy dog' — and two reference translations: 'The fast brown fox jumps over the lazy dog' and 'A quick brown fox jumped over a lazy dog'. Can you give me its BLEU score up to 4-gram with add1 smoothing plus all ROUGE scores?”
Benchmarking LLM summarization quality
“My LLM generated this summary: 'Scientists discovered a new species of deep-sea fish near the Pacific trench.' The gold reference is: 'Researchers have found a previously unknown deep-sea fish species in the Pacific Ocean.' Please compute the BLEU and ROUGE-1, ROUGE-2, and ROUGE-L F1 scores using whitespace tokenization.”
Grading student-generated answers against rubric
“I need to score this student answer: 'Photosynthesis converts light energy into glucose using carbon dioxide and water.' against the model answer: 'Photosynthesis is the process by which plants use sunlight, water, and CO2 to produce glucose and oxygen.' Give me BLEU with 4-gram and epsilon smoothing, plus ROUGE scores so I can see how close they are.”
Technical details
Endpoint
GEThttps://ml-metrics.x402tookit.com/bleu-rouge?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need standard NLP evaluation metrics (BLEU and ROUGE) in a single call without setting up NLTK, sacrebleu, or rouge-score locally. Ideal for agents evaluating summarization, translation, or generation quality in real time, especially when infrastructure-free computation is needed. Prefer it over rolling your own when you need brevity-penalty-correct BLEU with configurable n-gram order and smoothing alongside ROUGE-L simultaneously.
Side effects
- Missing required 'candidate' or 'references' query parameter — returns 400 validation error
- Candidate or reference text exceeds 5000-character limit — returns 400 or truncation error
- More than 20 reference texts provided — exceeds limit, returns 400
- Invalid 'smoothing' or 'tokenizer' enum value — returns 400 with description
- Empty candidate or reference string — may return null BLEU or ROUGE values with a rougeNote
- Payment not provided or insufficient — returns 402 Payment Required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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