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AgentUtility.ai · x402.agentutility.ai

Embeds 1 to 100 strings into semantic vectors

Embeds 1 to 100 strings into semantic vectors via Venice. Tier shorthand: 'default' → gemini-embedding-2-preview (newest, recommended), 'fast' → text-embedding-bge-m3, 'openai-compat' → text-embedding-3-small. You can also pass a full Venice embedding model name. Returns a list of vectors aligned with input order. Use it for text embedding, vector embedding, Venice embeddings, Gemini embeddings, or BGE-M3.

Ready now4 calls · 3 buyers in 30 days

Input

Tier shorthand ('default'|'fast'|'openai-compat') or full Venice embedding model name. Default 'default'.
Texts
1 to 100 strings to embed; each up to 30,000 chars.

Sample response

Published by the provider. Your run returns a fresh response.

response7 keys
count2
dimensions1024
embeddings2 items
model"gemini-embedding-2-preview"
source"venice"
tier"default"
usage2 keys
prompt_tokens6
total_tokens6
responseobject, 7 keys
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MCP URL

https://app.aecon.ai/mcp
Terminalbash
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Track record

Paid calls, last 30 days
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