Infinity

ML inferenceinfinity-embeddings

REST server for embedding, rerank and classification models with dynamic batching.

Provider: default
Kind: ML inference
Category: Compute
Official docs: https://github.com/michaelfeil/infinity

Properties · 3 set by this component

property	type	values	required	kind default	this component
accelerator	enum	none \| gpu \| asic	no	none	inherited
acceleratorModel · advanced	enum	nvidia-h100 \| nvidia-h200 \| nvidia-b200 \| nvidia-l4 \| nvidia-a100 \| amd-mi300x \| aws-trainium \| aws-inferentia \| google-tpu \| intel-gaudi \| groq-lpu \| cerebras-wse	no	—	inherited
backend · component property	enum	torch \| optimum \| ctranslate2	no	torch	inherited
embeddingSyncMinutes · advanced	integer	—	no	—	inherited
inputs	enum	live \| historical \| both	no	live	▸ live
instances	integer	—	no	—	inherited
managed	boolean	—	no	false	▸ false
port · component property	integer	—	no	7997	inherited
snapshotToObjectStore · advanced	boolean	—	no	false	inherited
task · component property	enum	embed \| rerank \| classify \| clip	no	embed	inherited
training	enum	batch \| online	no	batch	▸ batch

Rules that apply · 1

Every rule whose selector covers this component's kind or its category. Whether a rule fires depends on the design: its properties, its edges and its groups.

Stateful node without zone redundancyerror

stateful-node-without-zone-redundancy

A stateful compute node pinned to exactly one availability zone disappears with that zone, and its state goes with it. Nodes inside a cell are exempt, because there the cell is deliberately single-zone and redundancy comes from the other cells.

— all of these hold:
— the node's `stateless` is false
— the node sits inside exactly 1 availability-zone group
— this does not hold:
— the node sits inside at least one cell group

Use it in a design

nodes:
  - { id: "infinity-embeddings", component: "infinity-embeddings" }

Other ML inference products · 37

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Source

1# yaml-language-server: $schema=../../schema/component.schema.json
2# Infinity: MIT-licensed REST server for embedding, reranking, classification and CLIP models from Hugging Face, with an
3# API aligned to OpenAI's embeddings spec and dynamic batching. Per the README it listens on port 7997 and runs on
4# the PyTorch, Optimum (ONNX/TensorRT) or CTranslate2 backend.
5schemaVersion: "1"
6type: "component"
7id: "infinity-embeddings"
8kind: "ml-inference"
9provider: "default"
10docs: "https://github.com/michaelfeil/infinity"
11aliases: ["Infinity"]
12defaults:
13  training: "batch"
14  inputs: "live"
15  managed: false
16properties:
17  port:
18    type: "integer"
19    default: 7997
20  backend:
21    type: "enum"
22    values: ["torch", "optimum", "ctranslate2"]
23    default: "torch"
24  task:
25    type: "enum"
26    values: ["embed", "rerank", "classify", "clip"]
27    default: "embed"

The same page as markdown, for an agent: /catalogue/components/infinity-embeddings.md