Text → vector embeddings via Cloudflare Workers AI
Text → vector embeddings via Cloudflare Workers AI. Send {text} or {texts[]} (≤20, each ≤4000 chars); returns one float vector per input. Default model @cf/baai/bge-m3 (1024-dim, multilingual). The model is named in the response — embeddings only compare within the same model. Completes the RAG chain: readability → chunk → embed, no OpenAI account. Cosine-compare the vectors yourself. Unavailable model/binding → 503, not billed.
Paid test badge: not yet. The checks above are free: we call the tool without paying and read the payment request it sends back. The Verified badge needs paid calls whose answers match the promised output, and nobody can buy a badge.
Endpoint
POST https://402utils.com/v1/embed
| Category | Everything else |
|---|---|
| Provider host | 402utils.com |
| Networks | eip155:8453 |
| Payment schemes | exact |
| Self-reported calls, 30 days | 1 from 1 payers (the provider's figure, not ours) |
Our checks, last 30 days
We never call tools that send, buy, move money or file anything, not even without paying.
Example input (from the provider)
{
"body": {
"texts": [
"A cat sat on the mat.",
"A feline rested on the rug."
]
},
"bodyType": "json",
"method": "POST",
"type": "http"
}
Promised output schema (from the provider)
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"properties": {
"input": {
"additionalProperties": false,
"properties": {
"body": {
"description": "Provide exactly one of `text` or `texts`.",
"properties": {
"model": {
"default": "@cf/baai/bge-m3",
"description": "Embedding model. Default @cf/baai/bge-m3. en-v1.5 models are English-only, 512-token max.",
"enum": [
"@cf/baai/bge-m3",
"@cf/baai/bge-base-en-v1.5",
"@cf/baai/bge-large-en-v1.5",
"@cf/baai/bge-small-en-v1.5"
],
"type": "string"
},
"text": {
"description": "A single text to embed (\u2264 4000 chars).",
"type": "string"
},
"texts": {
"description": "Up to 20 texts to embed in one call (each \u2264 4000 chars).",
"items": {
"type": "string"
},
"maxItems": 20,
"type": "array"
}
},
"type": "object"
},
"bodyType": {
"enum": [
"json",
"form-data",
"text"
],
"type": "string"
},
"method": {
"enum": [
"POST"
],
"type": "string"
},
"type": {
"const": "http",
"type": "string"
}
},
"required": [
"type",
"method",
"bodyType",
"body"
],
"type": "object"
},
"output": {
"properties": {
"example": {
"additionalProperties": false,
"properties": {
"dimensions": {
"description": "Length of each vector (bge-m3 \u2192 1024).",
"type": "integer"
},
"embeddings": {
"description": "One vector per input text, in request order.",
"items": {
"items": {
"type": "number"
},
"type": "array"
},
"type": "array"
},
"model": {
"description": "The model used (compare embeddings only within one model).",
"type": "string"
},
"usage": {
"properties": {
"inputs": {
"description": "Number of texts embedded in this call.",
"type": "integer"
}
},
"required": [
"inputs"
],
"type": "object"
}
},
"required": [
"embeddings",
"model",
"dimensions",
"usage"
],
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"type"
],
"type": "object"
}
},
"required": [
"input"
],
"type": "object"
}