use std::sync::Arc; use async_stream::stream; use async_trait::async_trait; use derive_builder::Builder; use futures::stream::BoxStream; use tabby_inference::{ decoding::{DecodingFactory, IncrementalDecoding}, helpers, TextGeneration, TextGenerationOptions, }; use tokenizers::tokenizer::Tokenizer; use tokio::sync::mpsc::{channel, Sender}; use tokio_util::sync::CancellationToken; #[cxx::bridge(namespace = "tabby")] mod ffi { extern "Rust" { type InferenceContext; } unsafe extern "C++" { include!("ctranslate2-bindings/include/ctranslate2.h"); type TextInferenceEngine; fn create_engine( model_path: &str, model_type: &str, device: &str, device_indices: &[i32], ) -> SharedPtr; fn inference( &self, context: Box, callback: fn( &mut InferenceContext, // step usize, // token_id u32, // token String, ) -> bool, tokens: &[String], max_decoding_length: usize, sampling_temperature: f32, ) -> Vec; } } unsafe impl Send for ffi::TextInferenceEngine {} unsafe impl Sync for ffi::TextInferenceEngine {} #[derive(Builder, Debug)] pub struct CTranslate2EngineOptions { model_path: String, model_type: String, tokenizer_path: String, device: String, device_indices: Vec, } pub struct InferenceContext { sender: Sender, decoding: IncrementalDecoding, cancel: CancellationToken, } impl InferenceContext { fn new( sender: Sender, decoding: IncrementalDecoding, cancel: CancellationToken, ) -> Self { InferenceContext { sender, decoding, cancel, } } } pub struct CTranslate2Engine { engine: cxx::SharedPtr, decoding_factory: DecodingFactory, tokenizer: Arc, } impl CTranslate2Engine { pub fn create(options: CTranslate2EngineOptions) -> Self where { let engine = ffi::create_engine( &options.model_path, &options.model_type, &options.device, &options.device_indices, ); return Self { engine, decoding_factory: DecodingFactory::default(), tokenizer: Arc::new(Tokenizer::from_file(&options.tokenizer_path).unwrap()), }; } } #[async_trait] impl TextGeneration for CTranslate2Engine { async fn generate(&self, prompt: &str, options: TextGenerationOptions) -> String { let s = self.generate_stream(prompt, options).await; helpers::stream_to_string(s).await } async fn generate_stream( &self, prompt: &str, options: TextGenerationOptions, ) -> BoxStream { let encoding = self.tokenizer.encode(prompt, true).unwrap(); let decoding = self.decoding_factory.create_incremental_decoding( self.tokenizer.clone(), truncate_tokens(encoding.get_ids(), options.max_input_length), options.stop_words, ); let cancel = CancellationToken::new(); let engine = self.engine.clone(); let (sender, mut receiver) = channel::(8); let context = InferenceContext::new(sender, decoding, cancel.clone()); tokio::task::spawn_blocking(move || { let context = Box::new(context); engine.inference( context, inference_callback, truncate_tokens(encoding.get_tokens(), options.max_input_length), options.max_decoding_length, options.sampling_temperature, ); }); let s = stream! { let _guard = cancel.drop_guard(); while let Some(text) = receiver.recv().await { yield text; } }; Box::pin(s) } } fn truncate_tokens(tokens: &[T], max_length: usize) -> &[T] { if max_length < tokens.len() { let start = tokens.len() - max_length; &tokens[start..] } else { tokens } } fn inference_callback( context: &mut InferenceContext, _step: usize, token_id: u32, _token: String, ) -> bool { if context.cancel.is_cancelled() { true } else if let Some(new_text) = context.decoding.next_token(token_id) { let _ = context.sender.blocking_send(new_text); false } else { true } }