Principle:Groq Groq python Embedding Input Preparation
| Knowledge Sources | |
|---|---|
| Domains | NLP, Embeddings |
| Last Updated | 2026-02-15 16:00 GMT |
Overview
The process of preparing text input for embedding vector generation, including single strings and batched arrays.
Description
Embedding Input Preparation involves formatting text data for submission to an embedding API. The input can be a single string or a list of strings for batch embedding. Each input string is tokenized by the model, and the total tokens must not exceed the model's maximum context window. Arrays must be 2048 dimensions or less, and inputs cannot be empty strings.
This is a user-side preparation step with no corresponding library API — users construct the input directly as Python strings or lists.
Usage
Use this principle before calling the embedding API. Prepare your text data as a single string for one embedding or a list of strings for batch embedding. Ensure no empty strings are included.
Theoretical Basis
# Abstract input preparation
# Single text
input_single = "Hello world"
# Batch of texts
input_batch = [
"First document to embed",
"Second document to embed",
"Third document to embed",
]
# Pass to embedding API