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)?  // fails only if the TLS backend won't init
    .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, invisible format controls removed (zero-width joiners, bidi marks, BOM), Arabic-Indic and Persian digits → ASCII (١٢٫٥ becomes 12.5, one number) — so downstream matching gets a stable form. normalize_ar is public and idempotent; you can run it on either side of a comparison.

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 audio is streamed from the file handle rather than read into memory, so peak memory doesn't scale with the length of the recording. Transcriber is Send + Sync and holds a pooled client — share one across threads rather than building one per file.

MSRV 1.86.

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 0.3.0

raqeem-core