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text-keywords
x402
text-keywords is a paid API for AI agents from intel.rallylive.ca, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-14).
Extracts the top keywords and bigrams from a block of text by frequency with stopwords removed, for tagging, routing, or indexing content.
Price / call$0.01
Success—
StatusUnknown
How this service works
Keyword extraction from text: the top terms and bigrams by frequency with stopwords removed. Tag, route or index agent-generated content. $0.01 per call.
Output
Returns the top keywords (single terms) and bigrams (two-word phrases) ranked by frequency after stopword removal, enabling downstream tagging, content routing, or search indexing of the input text.
Example use cases
Auto-tagging agent-generated blog posts
“Extract the top keywords and bigrams from this blog post so I can automatically assign tags before publishing: 'Cloud computing adoption continues to surge among enterprise firms, with multi-cloud strategies becoming the dominant approach for resilience and cost control.'”
Routing customer support tickets by topic
“Get me the key terms from this support message so I can route it to the right team: 'My payment failed twice and I still see a charge on my credit card — I need a refund urgently.'”
Indexing research summaries for search
“Extract the most frequent keywords and two-word phrases from this research abstract so I can index it properly in our knowledge base: 'Quantum entanglement enables instantaneous correlation between particles regardless of distance, forming the basis for quantum cryptography and secure communication protocols.'”
Technical details
Endpoint
GEThttps://intel.rallylive.ca/data/keywords-textWhen to prefer
Choose this endpoint when you need lightweight, fast keyword and bigram extraction from free-form text for tagging, routing, or indexing purposes, especially in agentic pipelines where content must be classified or indexed on the fly. It is ideal for English-language text analysis where full NLP pipelines are overkill and stopword-filtered frequency counts are sufficient. Prefer alternatives when you need sentiment analysis, entity recognition, semantic embeddings, or multi-language support.
Side effects
- Empty or missing input text returns an error or empty keyword list
- Very short input (1-2 words) may yield no meaningful bigrams
- Non-English text may produce poor results if stopwords are English-only
- Highly repetitive or boilerplate text may surface low-value terms
- Network or payment authorization failure returns a 402 or 5xx error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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