llm.rs

// SPDX-FileCopyrightText: Copyright (c) 2024-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
// SPDX-License-Identifier: Apache-2.0
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
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/// This module provides a high-performance interface that bridges Python
/// applications with the Rust-powered Dynamo LLM runtime.
///
/// It is organized into several specialized sub-modules, each responsible for a particular aspect of the system:
///
/// - `backend`:
///   Wraps low-level interfaces for LLM inference, manages resource allocation,
///   and integrates with specialized hardware for optimized execution.
/// - `disagg_route`:
///   Implements distributed routing of inference requests with dynamic
///   load balancing and efficient resource allocation across clusters.
/// - `kv`:
///   Implements a high-performance key-value caching system that stores
///   intermediate computations and maintains model state for rapid data access.
/// - `model_card`:
///   Manages model deployment cards containing detailed metadata, configuration
///   settings, and versioning information to ensure consistent deployments.
/// - `preprocessor`:
///   Provides utilities for transforming raw LLM requests—including tokenization,
///   prompt formatting, and validation—into a format required by the Dynamo runtime.
///
/// Each sub-module is designed to encapsulate its functionality for clean
/// integration between Python tools and the Dynamo runtime.
use super::*;

pub mod backend;
pub mod disagg_router;
pub mod kv;
pub mod model_card;
pub mod nats;
pub mod preprocessor;