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AGISHub Text Classifier
x402
AGISHub Text Classifier is a paid API for AI agents from api.agishub.com, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-15).
Classifies a given text into exactly one of a set of caller-supplied candidate labels (e.g. sentiment, topic, intent).
Price / call$0.02
Success—
StatusUnknown
How this service works
Classify a text into exactly one of the candidate labels you provide (e.g. sentiment, topic, intent).
Output
A JSON object containing a 'result' field with the single label from the provided candidates that best fits the input text. No confidence scores are returned — just the winning label string.
Example use cases
Sentiment tagging for product reviews
“Take this product review and classify it as positive, negative, or neutral: 'The battery life is amazing but the screen scratches way too easily.'”
Support ticket routing by topic
“Classify this support message into one of these departments — billing, technical, shipping, returns — so I know where to send it: 'I was charged twice for my last order.'”
Intent detection for chatbot
“I need to know whether this user message is a greeting, a question, a complaint, or a farewell so my chatbot can respond correctly: 'Hey, can you help me figure out why my account is locked?'”
Technical details
Endpoint
GEThttps://api.agishub.com/v1/classifyWhen to prefer
Choose this endpoint when you need zero-shot text classification against a custom set of labels you define at call time, without training a model. Ideal for routing, sentiment tagging, intent detection, or any scenario where you can enumerate 2–20 meaningful categories. Prefer this over general LLM prompting when you want a deterministic single-label output enforced by the API schema rather than free-form text.
Side effects
- Fewer than 2 labels provided — returns validation error
- Text is empty or missing — returns 400 bad request
- More than 20 candidate labels supplied — exceeds maxItems limit
- Payment not provided or insufficient — returns 402 Payment Required
- Ambiguous text with equally matching labels may return an arbitrary winner with no confidence signal
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| outputrequired | object |
Output
Schema · Response
{
"type": "json",
"example": {
"result": "Classify a text into exactly one of the candidate labels you provide (e.g. sentiment, topic, intent)."
}
}Tags
x402
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