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pagos.andreax.dev Vision (LLaVA)
x402
pagos.andreax.dev Vision (LLaVA) is a paid API for AI agents from pagos.andreax.dev, paid per call via x402, $0.008/call, status unknown (last checked 2026-09-14).
Analyzes or describes the content of an image using a local multimodal LLM (LLaVA), answering a user-specified question about the image
Price / call$0.008
Success—
StatusUnknown
How this service works
Visión por computador: describe o analiza el contenido de una imagen con un modelo multimodal LOCAL (llava). Para agentes que necesitan 'ver' (describir escenas, leer diagramas, clasificar imágenes). Sube la imagen por multipart o como 'archivo_b64'; 'input' = la pregunta o instrucción sobre la imagen.
Output
A natural language response generated by the LLaVA multimodal model answering the user's question about the image — this may include scene descriptions, object identification, text transcription from the image, classification labels, or any other visual analysis the model infers from the image content.
Example use cases
Describe a photo for accessibility
“I have a base64-encoded image of a street scene — can you describe everything visible in it in plain language, including any text or signs you can see?”
Read a technical diagram
“Here's a base64 image of a network architecture diagram. Can you explain what components are shown and how they connect to each other?”
Classify uploaded product image
“I've got a base64-encoded product photo — can you tell me what category of item this is and describe its main visual features?”
Technical details
Endpoint
GEThttps://pagos.andreax.dev/api/taller/peaje/visionWhen to prefer
Choose this endpoint when you need a locally-run, privacy-respecting multimodal image analysis that does not send data to cloud vision APIs. It is ideal for agents that need to 'see' — describing scenes, reading diagrams, classifying images — at a low per-call cost of $0.008 USDC. Prefer this over text-only endpoints when the input is an image rather than text, and over cloud vision APIs when cost, latency, or data-residency concerns apply.
Side effects
- Missing 'archivo_b64' parameter returns an error — the base64 image is required
- Malformed or non-image base64 data causes model failure or garbage output
- Very large images may exceed payload limits or cause slow response
- Ambiguous or missing 'input' question may yield a generic description rather than targeted analysis
- Local model (LLaVA) may produce hallucinations or inaccurate readings on complex diagrams
- Payment (x402) not provided or insufficient USDC balance causes 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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