dynamo/lib/bindings/python/rust/llm/local_model.rs

163 lines
4.6 KiB
Rust

// SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
// SPDX-License-Identifier: Apache-2.0
use super::*;
use llm_rs::local_model::runtime_config::DisaggregatedEndpoint as RsDisaggregatedEndpoint;
use llm_rs::local_model::runtime_config::ModelRuntimeConfig as RsModelRuntimeConfig;
#[pyclass]
#[derive(Clone, Debug, Default)]
pub struct ModelRuntimeConfig {
pub(crate) inner: RsModelRuntimeConfig,
}
#[pymethods]
impl ModelRuntimeConfig {
#[new]
fn new() -> Self {
Self {
inner: RsModelRuntimeConfig::new(),
}
}
#[setter]
fn set_total_kv_blocks(&mut self, total_kv_blocks: u64) {
self.inner.total_kv_blocks = Some(total_kv_blocks);
}
#[setter]
fn set_max_num_seqs(&mut self, max_num_seqs: u64) {
self.inner.max_num_seqs = Some(max_num_seqs);
}
#[setter]
fn set_max_num_batched_tokens(&mut self, max_num_batched_tokens: u64) {
self.inner.max_num_batched_tokens = Some(max_num_batched_tokens);
}
#[setter]
fn set_tool_call_parser(&mut self, tool_call_parser: Option<String>) {
self.inner.tool_call_parser = tool_call_parser;
}
#[setter]
fn set_reasoning_parser(&mut self, reasoning_parser: Option<String>) {
self.inner.reasoning_parser = reasoning_parser;
}
#[setter]
fn set_data_parallel_start_rank(&mut self, data_parallel_start_rank: u32) {
self.inner.data_parallel_start_rank = data_parallel_start_rank;
}
#[setter]
fn set_data_parallel_size(&mut self, data_parallel_size: u32) {
self.inner.data_parallel_size = data_parallel_size;
}
#[setter]
fn set_enable_local_indexer(&mut self, enable_local_indexer: bool) {
self.inner.enable_local_indexer = enable_local_indexer;
}
fn set_engine_specific(&mut self, key: &str, value: String) -> PyResult<()> {
let value: serde_json::Value = serde_json::from_str(&value).map_err(to_pyerr)?;
self.inner
.set_engine_specific(key, value)
.map_err(to_pyerr)?;
Ok(())
}
fn set_tensor_model_config(
&mut self,
_py: Python<'_>,
tensor_model_config: &Bound<'_, PyDict>,
) -> PyResult<()> {
let tensor_model_config = pythonize::depythonize(tensor_model_config).map_err(|err| {
PyErr::new::<PyException, _>(format!("Failed to convert tensor_model_config: {}", err))
})?;
self.inner.tensor_model_config = Some(tensor_model_config);
Ok(())
}
fn get_tensor_model_config(&self, _py: Python<'_>) -> PyResult<Option<PyObject>> {
if let Some(tensor_model_config) = &self.inner.tensor_model_config {
let py_obj = pythonize::pythonize(_py, tensor_model_config).map_err(to_pyerr)?;
Ok(Some(py_obj.unbind()))
} else {
Ok(None)
}
}
#[getter]
fn total_kv_blocks(&self) -> Option<u64> {
self.inner.total_kv_blocks
}
#[getter]
fn max_num_seqs(&self) -> Option<u64> {
self.inner.max_num_seqs
}
#[getter]
fn max_num_batched_tokens(&self) -> Option<u64> {
self.inner.max_num_batched_tokens
}
#[getter]
fn tool_call_parser(&self) -> Option<String> {
self.inner.tool_call_parser.clone()
}
#[getter]
fn reasoning_parser(&self) -> Option<String> {
self.inner.reasoning_parser.clone()
}
#[getter]
fn enable_local_indexer(&self) -> bool {
self.inner.enable_local_indexer
}
#[getter]
fn runtime_data(&self, py: Python<'_>) -> PyResult<PyObject> {
let dict = PyDict::new(py);
for (key, value) in self.inner.runtime_data.clone() {
dict.set_item(key, value.to_string())?;
}
Ok(dict.into())
}
fn get_engine_specific(&self, key: &str) -> PyResult<Option<String>> {
self.inner.get_engine_specific(key).map_err(to_pyerr)
}
#[pyo3(signature = (bootstrap_host=None, bootstrap_port=None))]
fn set_disaggregated_endpoint(
&mut self,
bootstrap_host: Option<String>,
bootstrap_port: Option<u16>,
) {
self.inner.disaggregated_endpoint = Some(RsDisaggregatedEndpoint {
bootstrap_host,
bootstrap_port,
});
}
#[getter]
fn bootstrap_host(&self) -> Option<String> {
self.inner
.disaggregated_endpoint
.as_ref()
.and_then(|e| e.bootstrap_host.clone())
}
#[getter]
fn bootstrap_port(&self) -> Option<u16> {
self.inner
.disaggregated_endpoint
.as_ref()
.and_then(|e| e.bootstrap_port)
}
}