raqeem-core

The library behind raqeem (رقيم) — a lightweight client for CohereLabs/cohere-transcribe-arabic-07-2026, the most accurate open-source Arabic speech-recognition model (dialects + Arabic/English code-switching), Apache-2.0.

Inference is always delegated to an endpoint you choose — Cohere's hosted API or your own vLLM. This crate loads no model weights: it POSTs the audio to an OpenAI-compatible /audio/transcriptions endpoint and folds the result. That is what keeps it small, and what lets the same core drive the CLI, the Python wheel, and any future binding.

use raqeem_core::{Endpoint, Transcriber};
use std::path::Path;

let endpoint = Endpoint::cohere(std::env::var("COHERE_API_KEY")?, None);
let transcript = Transcriber::new(endpoint)
    .language("ar")                           // the default; shown for clarity
    .transcribe(Path::new("voice_note.ogg"))?;

println!("{}", transcript.text);              // verbatim, for humans
println!("{}", transcript.text_normalized);   // Arabic-folded, for parsing

Self-hosted instead — same Transcriber, different endpoint:

let endpoint = Endpoint::openai_compatible(
    "http://localhost:8000/v1/audio/transcriptions",
    "cohere-transcribe-arabic-07-2026",
    None,                                     // no key needed
);

text_normalized runs the output through normalize_ar — alef/hamza folding, taa-marbuta → haa, tatweel and diacritics stripped, Arabic-Indic and Persian digits → ASCII (١٢٫٥ becomes 12.5, one number) — so downstream matching gets a stable form.

Two things Cohere's API requires, both handled here: the model and language form fields must precede the file part, and the model id must be dated (undated aliases 404).

The CLI over this crate is raqeem; the Python wheel is pip install raqeem.

Full docs, the CLI, and the Python bindings: github.com/SufficientDaikon/raqeem.

Apache-2.0 — same as the model. All accuracy credit belongs to Cohere Labs.

raqeem-core 0.2.2

raqeem-core