use crate::models::common::generate::{GenerationDataProvider, PrepareData};
use crate::{
chat_template::ChatTemplate,
models::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<DType>) -> Result<Self> {
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> GenerationDataProvider for Lfm2GenerateModel<'a> {
fn get_data(&self, mes: &crate::params::chat::ChatCompletionParameters) -> Result<PrepareData> {
let mes_render = self.chat_template.apply_chat_template(mes)?;
let in_reasoning = self.is_in_reasoning(&mes_render);
let input_ids = self.tokenizer.text_encode(mes_render, &self.device)?;
let multi_model_data = self.get_multi_model_data();
Ok(PrepareData {
in_reasoning,
input_ids,
multi_model_data,
})
}
}
crate::impl_generate_model!(Lfm2GenerateModel<'a>);