use crate::models::common::MultiModalData; use crate::models::common::generate::{ GenerationContext, generate_generic, generate_stream_generic, }; use crate::params::chat::{ChatCompletionParameters, ChatCompletionResponse}; use crate::{ chat_template::ChatTemplate, models::{ GenerateModel, lfm2::{ config::{Lfm2Config, Lfm2GenerateConfig}, model::Lfm2Model, }, }, tokenizer::TokenizerModel, utils::{find_type_files, get_device, get_dtype}, }; use anyhow::Result; use candle_core::{DType, Device}; use candle_nn::VarBuilder; pub struct Lfm2GenerateModel<'a> { chat_template: ChatTemplate<'a>, tokenizer: TokenizerModel, device: Device, model: Lfm2Model, model_name: String, } impl<'a> Lfm2GenerateModel<'a> { pub fn init(path: &str, device: Option<&Device>, dtype: Option) -> Result { let chat_template = ChatTemplate::init(path)?; let tokenizer = TokenizerModel::init(path)?; let device = get_device(device); let gen_cfg_path = path.to_string() + "/generation_config.json"; let gen_cfg: Lfm2GenerateConfig = serde_json::from_slice(&std::fs::read(gen_cfg_path)?)?; let cfg_path = path.to_string() + "/config.json"; let cfg: Lfm2Config = serde_json::from_slice(&std::fs::read(cfg_path)?)?; let model_path = find_type_files(path, "safetensors")?; let cfg_dtype = if let Some(dtype) = &cfg.dtype { dtype.clone() } else if let Some(dtype) = &cfg.torch_dtype { dtype.clone() } else { "bfloat16".to_string() }; let dtype = get_dtype(dtype, &cfg_dtype); let vb = unsafe { VarBuilder::from_mmaped_safetensors(&model_path, dtype, &device)? }; let eos_ids = vec![gen_cfg.eos_token_id]; let model = Lfm2Model::new(vb, &cfg, eos_ids)?; let model_name = std::path::Path::new(path) .file_name() .and_then(|s| s.to_str()) .unwrap_or("lfm2") .to_string(); Ok(Self { chat_template, tokenizer, device, model, model_name, }) } } impl<'a> GenerateModel for Lfm2GenerateModel<'a> { fn generate(&mut self, mes: ChatCompletionParameters) -> Result { let mes_render = self.chat_template.apply_chat_template(&mes)?; let input_ids = self.tokenizer.text_encode(mes_render, &self.device)?; let sample_len = mes.max_tokens.unwrap_or(1024); let seed = mes.seed.unwrap_or(34562) as u64; let mut ctx = GenerationContext::new( mes.temperature, mes.top_p, None, mes.repeat_penalty, mes.repeat_last_n, seed, input_ids.dim(1)?, sample_len, self.device.clone(), ); let data = MultiModalData::new(vec![]); generate_generic( &mut self.model, &self.tokenizer, input_ids, data, &mut ctx, &self.model_name, ) } fn generate_stream( &mut self, mes: ChatCompletionParameters, ) -> Result< Box< dyn rocket::futures::Stream< Item = Result, > + Send + Unpin + '_, >, > { let mes_render = self.chat_template.apply_chat_template(&mes)?; let input_ids = self.tokenizer.text_encode(mes_render, &self.device)?; let sample_len = mes.max_tokens.unwrap_or(1024); let data = MultiModalData::new(vec![]); let seed = mes.seed.unwrap_or(34562) as u64; let stream = generate_stream_generic( &mut self.model, &self.tokenizer, input_ids, data, mes.temperature, mes.top_p, None, mes.repeat_penalty, mes.repeat_last_n, seed, sample_len, false, &self.device, &self.model_name, )?; Ok(Box::new(Box::pin(stream))) } }