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Oblique Markets Text Classifier
x402
Oblique Markets Text Classifier is a paid API for AI agents from api.oblique.markets, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-14).
Classifies a piece of text into one of 2–20 caller-supplied labels using an LLM, returning only a validated canonical label (never a hallucinated one) or a 502 error.
Price / call$0.005
Success—
StatusUnknown
How this service works
Use when an agent needs classify. Returns Single-label text classification against 2-20 caller-supplied labels — reply validated against the label set, canonical label returned, 502 instead of hallucinated labels. $0.005.
Output
A single canonical label drawn exactly from the caller-supplied label set. The response is validated against that set — if the LLM would otherwise produce something outside the list, the endpoint returns a 502 rather than a hallucinated label. Agents receive a clean, machine-readable string with no extra explanation.
Example use cases
Support ticket routing by category
“I have an incoming support message: 'The app keeps crashing when I try to log in.' Can you classify it into one of these categories: account, billing, bug, feature-request, general? I only want back one of those exact labels.”
Content moderation label assignment
“Classify this user-submitted comment — 'Go buy followers, this is trash' — into one of these labels: spam, harassment, misinformation, safe. Only return one of those exact labels, nothing else.”
Expense transaction categorization
“I have a bank transaction description: 'UBER EATS ORDER 8843'. Classify it into one of these expense categories: food, transport, accommodation, entertainment, utilities. Give me just the matching label.”
Technical details
Endpoint
POSThttps://api.oblique.markets/api/v1/paid/classifyWhen to prefer
Choose this endpoint when you need guaranteed label fidelity — i.e., you cannot tolerate an LLM returning a label outside your predefined set. It is ideal for deterministic routing pipelines, compliance-sensitive categorization, or any workflow where a hallucinated label would cause a downstream error. Prefer it over a raw LLM call when you need a strict enum-like output with no free-text drift. It pays per call at $0.005 USDC, making it cost-effective for high-volume classification tasks that don't need a full generative response.
Side effects
- 502 returned when the LLM cannot confidently map the text to any of the supplied labels — prevents hallucinated or out-of-set labels
- Input text is ambiguous or too short for any label to be meaningful — 502 or unexpected label
- Fewer than 2 or more than 20 labels supplied — likely a 4xx validation error
- Payment failure via x402 — endpoint refuses request before classification is attempted
- Latency spike if underlying LLM is under load — retries may be needed
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string | Text to classify; truncated to 8,000 characters |
| labels | array | Candidate labels; exactly one is returned |
Output
Schema · Response
{
"type": "json",
"example": {
"label": "billing_issue",
"model": "inclusionai/ling-3.0-flash"
}
}Tags
x402
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