protocols.rs

// SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
// SPDX-License-Identifier: Apache-2.0

use derive_builder::Builder;
use serde::{Deserialize, Serialize};
use std::collections::{HashMap, HashSet};
use std::path::{Path, PathBuf};
use std::sync::Arc;
use uuid::Uuid;
use validator::Validate;

use crate::common::perf_model::PerfModel;
use dynamo_kv_router::protocols::KvCacheEvent;
use dynamo_tokens::blocks::UniqueBlock;
use dynamo_tokens::{BlockHash, SequenceHash, Token};

/// Trait for publishing KV cache events.
/// This abstracts the runtime dependency so mocker components can remain generic.
pub trait KvCacheEventSink: Send + Sync {
    fn publish(
        &self,
        event: KvCacheEvent,
        block_token_ids: Option<&[Vec<u32>]>,
    ) -> anyhow::Result<()>;
}

pub type NumBlocks = usize;

/// Represents different block movement operations in the cache
/// For Use and Promote variants, block hashes are included for KV event publishing
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub enum MoveBlock {
    Use(
        Vec<UniqueBlock>,
        Vec<BlockHash>,
        Option<Vec<Vec<u32>>>,
        Option<UniqueBlock>,
    ),
    Destroy(Vec<UniqueBlock>),
    Deref(Vec<UniqueBlock>),
    Promote(Uuid, SequenceHash, Option<u64>, BlockHash, Option<Vec<u32>>),
}

#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub enum MoveBlockResponse {
    Store(Vec<SequenceHash>, Option<u64>),
    Remove(Vec<SequenceHash>),
}

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct DirectRequest {
    pub tokens: Vec<Token>,
    pub max_output_tokens: usize,
    pub uuid: Option<Uuid>,
    pub dp_rank: u32,
    pub arrival_timestamp_ms: Option<f64>,
}

/// Represents the cost of prefilling content in the cache
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct PrefillCost {
    pub new_blocks: usize,
    pub new_tokens: usize,
    /// Number of tokens already cached (prefix hit).
    /// isl = cached_tokens + new_tokens
    pub cached_tokens: usize,
}

impl PrefillCost {
    pub fn predict_prefill_compute(
        &self,
        new_tokens: Option<usize>,
        perf_model: &PerfModel,
    ) -> f64 {
        let tokens = new_tokens.unwrap_or(self.new_tokens);
        let isl = self.cached_tokens + tokens;
        perf_model.predict_prefill_time(1, isl, self.cached_tokens)
    }
}

/// Signal for output token generation with completion status
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct OutputSignal {
    pub uuid: Uuid,
    pub completed: bool,
}

/// Preemption policy for evicting decode requests under memory pressure
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize, Default)]
pub enum PreemptionMode {
    /// Evict the newest request (matches vLLM v1 default)
    #[default]
    Lifo,
    /// Evict the oldest request
    Fifo,
}

/// Engine type for selecting scheduling and KV cache simulation behavior
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize, Default)]
pub enum EngineType {
    /// vLLM-style scheduling with hash-based block KV cache
    #[default]
    Vllm,
    /// SGLang-style scheduling with radix-tree KV cache
    Sglang,
}

/// Worker type for disaggregated serving configurations
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize, Default)]
pub enum WorkerType {
    /// Standard aggregated worker handling both prefill and decode
    #[default]
    Aggregated,
    /// Dedicated prefill worker in disaggregated mode
    Prefill,
    /// Dedicated decode worker in disaggregated mode
    Decode,
}

/// Configuration for reasoning/thinking token output in the mocker.
///
/// When set, the mocker wraps the first portion of each response in thinking
/// boundary tokens: `[start_token, random..., end_token, random...]`.
#[derive(Debug, Clone, Serialize, Deserialize, Validate)]
pub struct ReasoningConfig {
    pub start_thinking_token_id: u32,
    pub end_thinking_token_id: u32,
    #[validate(range(min = 0.0, max = 1.0))]
    pub thinking_ratio: f64,
}

impl ReasoningConfig {
    /// Number of thinking tokens (including start/end boundaries) for a given osl.
    /// Returns 0 if osl < 2 (thinking disabled). Otherwise clamps to [2, osl].
    pub fn num_thinking_tokens(&self, max_output_tokens: usize) -> usize {
        if max_output_tokens < 2 {
            return 0;
        }
        let raw = (max_output_tokens as f64 * self.thinking_ratio).floor() as usize;
        if raw == 0 {
            return 0;
        }
        raw.max(2).min(max_output_tokens)
    }

    /// Number of response tokens after the thinking block.
    pub fn num_response_tokens(&self, max_output_tokens: usize) -> usize {
        max_output_tokens.saturating_sub(self.num_thinking_tokens(max_output_tokens))
    }
}

/// SGLang-specific configuration parameters.
///
/// Grouped into a nested struct to keep the `MockEngineArgs` namespace clean,
/// following the same pattern as [`ReasoningConfig`].
#[derive(Debug, Clone, Serialize, Deserialize, Validate, Default)]
pub struct SglangArgs {
    /// Scheduling policy: "fifo"/"fcfs" or "lpm". Default: "fifo".
    pub schedule_policy: Option<String>,
    /// Radix cache page size in tokens. Default: 1.
    #[validate(range(min = 1))]
    pub page_size: Option<usize>,
    /// Maximum prefill tokens budget per batch. Default: 16384.
    #[validate(range(min = 1))]
    pub max_prefill_tokens: Option<usize>,
    /// Chunked prefill size (max tokens per chunk). Default: 8192.
    #[validate(range(min = 1))]
    pub chunked_prefill_size: Option<usize>,
    /// Clip max new tokens for admission budget. Default: 4096.
    #[validate(range(min = 1))]
    pub clip_max_new_tokens: Option<usize>,
    /// Schedule conservativeness factor (0.0–1.0). Default: 1.0.
    #[validate(range(min = 0.0, max = 1.0))]
    pub schedule_conservativeness: Option<f64>,
}

/// Configuration arguments for MockEngine
#[derive(Debug, Clone, Serialize, Deserialize, Builder, Validate)]
#[builder(pattern = "owned", build_fn(public))]
pub struct MockEngineArgs {
    /// Engine type: vLLM or SGLang simulation
    #[builder(default = "EngineType::Vllm")]
    pub engine_type: EngineType,

    #[builder(default = "16384")]
    #[validate(range(min = 1))]
    pub num_gpu_blocks: usize,

    #[builder(default = "64")]
    #[validate(range(min = 2))]
    pub block_size: usize,

    // This was 1024 in the past but reverted back to 256
    #[builder(default = Some(256))]
    #[validate(range(min = 1))]
    pub max_num_seqs: Option<usize>,

    // default for open api server, for llm class it's 16384
    #[builder(default = Some(8192))]
    #[validate(range(min = 1))]
    pub max_num_batched_tokens: Option<usize>,

    #[builder(default = true)]
    pub enable_prefix_caching: bool,

    #[builder(default = true)]
    pub enable_chunked_prefill: bool,

    #[builder(default = "1.0")]
    #[validate(range(min = 0.0))]
    pub speedup_ratio: f64,

    /// Additional speedup multiplier applied only to decode steps.
    /// Models speculative decoding (e.g. Eagle) where decode throughput improves
    /// without affecting prefill latency. The effective decode speedup is
    /// `speedup_ratio * decode_speedup_ratio`.
    #[builder(default = "1.0")]
    #[validate(range(min = 0.0))]
    pub decode_speedup_ratio: f64,

    #[builder(default = "1")]
    #[validate(range(min = 1))]
    pub dp_size: u32,

    /// Optional startup time in seconds to simulate engine initialization delay
    #[builder(default = "None")]
    #[validate(range(min = 0.0))]
    pub startup_time: Option<f64>,

    /// Worker type for disaggregated serving (Aggregated, Prefill, or Decode)
    #[builder(default = "WorkerType::Aggregated")]
    pub worker_type: WorkerType,

    /// Performance model for timing predictions (not serialized, loaded from planner_profile_data)
    #[serde(skip)]
    #[builder(default = "Arc::new(PerfModel::default())")]
    pub perf_model: Arc<PerfModel>,

    /// If set, indicates direct AIC SDK calls should be used.
    /// The value is the backend name (e.g., "sglang", "vllm").
    /// The Python layer reads this and overrides perf_model with an Aiconfigurator callback.
    #[serde(skip)]
    #[builder(default = "None")]
    pub aic_backend: Option<String>,

    /// AIC GPU system name (e.g., "h200_sxm"). Required when aic_backend is set.
    #[serde(skip)]
    #[builder(default = "None")]
    pub aic_system: Option<String>,

    /// AIC backend engine version (e.g., "0.12.0" for vLLM, "0.5.6.post2" for SGLang).
    /// If None, uses the default version for the backend.
    #[serde(skip)]
    #[builder(default = "None")]
    pub aic_backend_version: Option<String>,

    /// Tensor parallel size for AIC latency prediction.
    /// Only affects AIC performance model lookups, not mocker scheduling.
    #[serde(skip)]
    #[builder(default = "None")]
    pub aic_tp_size: Option<usize>,

    /// HuggingFace model path for AIC latency prediction (e.g., "nvidia/Llama-3.1-8B-Instruct-FP8").
    #[serde(skip)]
    #[builder(default = "None")]
    pub aic_model_path: Option<String>,

    /// Enable worker-local KV indexer for tracking this worker's own KV cache state
    #[builder(default = "false")]
    pub enable_local_indexer: bool,

    /// Bootstrap port for disaggregated serving rendezvous.
    /// Prefill workers listen on this port; decode workers connect to it.
    /// If None, bootstrap rendezvous is disabled.
    #[builder(default = "None")]
    pub bootstrap_port: Option<u16>,

    /// KV cache bytes per token, auto-computed from model config by Python CLI.
    /// Formula: num_layers * 2 * num_kv_heads * head_dim * dtype_bytes
    #[builder(default = "None")]
    pub kv_bytes_per_token: Option<usize>,

    /// KV cache transfer bandwidth in GB/s for disaggregated serving latency simulation.
    /// Default: 64.0 (inter-node InfiniBand). Set to 0 to disable KV transfer delay.
    /// For intra-node NVLink, typical value is ~450.
    #[builder(default = "None")]
    #[validate(range(min = 0.0))]
    pub kv_transfer_bandwidth: Option<f64>,

    /// Reasoning/thinking token configuration.
    /// When set, the mocker wraps output in thinking boundary tokens.
    #[builder(default = "None")]
    pub reasoning: Option<ReasoningConfig>,

    /// ZMQ port for publishing KV events in vLLM's native wire format.
    /// When set, the scheduler publishes to a ZMQ PUB socket instead of directly to NATS.
    /// A KvEventPublisher relay subscribes to this socket and forwards events to NATS.
    #[builder(default = "None")]
    pub zmq_kv_events_port: Option<u16>,

    /// ZMQ ROUTER port for replay of buffered KV event batches.
    /// When set alongside `zmq_kv_events_port`, the mocker binds a ROUTER socket
    /// that streams back buffered batches by sequence number on request.
    /// Port is offset by dp_rank (replay_port + dp_rank).
    #[builder(default = "None")]
    pub zmq_replay_port: Option<u16>,

    /// Preemption mode for decode eviction under memory pressure.
    /// Lifo (default) evicts the newest request; Fifo evicts the oldest.
    #[builder(default)]
    pub preemption_mode: PreemptionMode,

    /// SGLang-specific configuration. Only used when `engine_type == Sglang`.
    #[builder(default = "None")]
    pub sglang: Option<SglangArgs>,
}

impl Default for MockEngineArgs {
    fn default() -> MockEngineArgs {
        MockEngineArgsBuilder::default()
            .build()
            .expect("Failed to build default MockEngineArgs")
    }
}

impl MockEngineArgs {
    pub fn builder() -> MockEngineArgsBuilder {
        MockEngineArgsBuilder::default()
    }

    pub fn is_prefill(&self) -> bool {
        self.worker_type == WorkerType::Prefill
    }

    pub fn is_decode(&self) -> bool {
        self.worker_type == WorkerType::Decode
    }

    pub fn needs_kv_publisher(&self) -> bool {
        self.enable_prefix_caching && !self.is_decode()
    }

    /// Create MockEngineArgs from a JSON file containing extra engine arguments
    pub fn from_json_file(path: &Path) -> anyhow::Result<Self> {
        let mut builder = Self::builder();

        // Load and parse the JSON file
        let file_content = std::fs::read_to_string(path)?;
        let extra_args: HashMap<String, serde_json::Value> = serde_json::from_str(&file_content)?;

        // Define valid field names
        let valid_fields: HashSet<&str> = [
            "engine_type",
            "num_gpu_blocks",
            "block_size",
            "max_num_seqs",
            "max_num_batched_tokens",
            "enable_prefix_caching",
            "enable_chunked_prefill",
            "speedup_ratio",
            "decode_speedup_ratio",
            "dp_size",
            "startup_time",
            "is_prefill",
            "is_decode",
            "planner_profile_data",
            "aic_backend",
            "aic_system",
            "aic_backend_version",
            "aic_tp_size",
            "aic_model_path",
            "enable_local_indexer",
            "bootstrap_port",
            "kv_bytes_per_token",
            "kv_transfer_bandwidth",
            "reasoning",
            "zmq_kv_events_port",
            "zmq_replay_port",
            "preemption_mode",
            "sglang",
        ]
        .iter()
        .cloned()
        .collect();

        // Check for invalid arguments
        let invalid_args: Vec<String> = extra_args
            .keys()
            .filter(|key| !valid_fields.contains(key.as_str()))
            .cloned()
            .collect();

        if !invalid_args.is_empty() {
            return Err(anyhow::anyhow!(
                "Invalid arguments found in JSON file: {}. Valid arguments are: {:?}",
                invalid_args.join(", "),
                valid_fields
            ));
        }

        // Apply each extra argument to the builder
        if let Some(value) = extra_args.get("engine_type")
            && let Some(s) = value.as_str()
        {
            let engine_type = match s {
                "vllm" => EngineType::Vllm,
                "sglang" => EngineType::Sglang,
                other => {
                    return Err(anyhow::anyhow!(
                        "Invalid engine_type '{}'. Must be 'vllm' or 'sglang'.",
                        other
                    ));
                }
            };
            builder = builder.engine_type(engine_type);
        }

        if let Some(value) = extra_args.get("num_gpu_blocks")
            && let Some(num) = value.as_u64()
        {
            builder = builder.num_gpu_blocks(num as usize);
        }

        if let Some(value) = extra_args.get("block_size")
            && let Some(num) = value.as_u64()
        {
            builder = builder.block_size(num as usize);
        }

        if let Some(value) = extra_args.get("max_num_seqs")
            && let Some(num) = value.as_u64()
        {
            builder = builder.max_num_seqs(Some(num as usize));
        }

        if let Some(value) = extra_args.get("max_num_batched_tokens")
            && let Some(num) = value.as_u64()
        {
            builder = builder.max_num_batched_tokens(Some(num as usize));
        }

        if let Some(value) = extra_args.get("enable_prefix_caching")
            && let Some(enabled) = value.as_bool()
        {
            builder = builder.enable_prefix_caching(enabled);
        }

        if let Some(value) = extra_args.get("enable_chunked_prefill")
            && let Some(enabled) = value.as_bool()
        {
            builder = builder.enable_chunked_prefill(enabled);
        }

        if let Some(value) = extra_args.get("speedup_ratio")
            && let Some(num) = value.as_f64()
        {
            builder = builder.speedup_ratio(num);
        }

        if let Some(value) = extra_args.get("decode_speedup_ratio")
            && let Some(num) = value.as_f64()
        {
            builder = builder.decode_speedup_ratio(num);
        }

        if let Some(value) = extra_args.get("dp_size")
            && let Some(num) = value.as_u64()
        {
            builder = builder.dp_size(num as u32);
        }

        if let Some(value) = extra_args.get("startup_time")
            && let Some(num) = value.as_f64()
        {
            builder = builder.startup_time(Some(num));
        }

        if let Some(value) = extra_args.get("enable_local_indexer")
            && let Some(enabled) = value.as_bool()
        {
            builder = builder.enable_local_indexer(enabled);
        }

        if let Some(value) = extra_args.get("bootstrap_port")
            && let Some(port) = value.as_u64()
        {
            builder = builder.bootstrap_port(Some(port as u16));
        }

        if let Some(value) = extra_args.get("kv_bytes_per_token")
            && let Some(num) = value.as_u64()
        {
            builder = builder.kv_bytes_per_token(Some(num as usize));
        }

        if let Some(value) = extra_args.get("kv_transfer_bandwidth")
            && let Some(num) = value.as_f64()
        {
            builder = builder.kv_transfer_bandwidth(Some(num));
        }

        if let Some(value) = extra_args.get("reasoning") {
            let cfg: ReasoningConfig = serde_json::from_value(value.clone())
                .map_err(|e| anyhow::anyhow!("Failed to parse reasoning config: {}", e))?;
            builder = builder.reasoning(Some(cfg));
        }

        if let Some(value) = extra_args.get("zmq_kv_events_port")
            && let Some(port) = value.as_u64()
        {
            builder = builder.zmq_kv_events_port(Some(port as u16));
        }

        if let Some(value) = extra_args.get("zmq_replay_port")
            && let Some(port) = value.as_u64()
        {
            builder = builder.zmq_replay_port(Some(port as u16));
        }

        if let Some(value) = extra_args.get("preemption_mode")
            && let Some(mode_str) = value.as_str()
        {
            let mode = match mode_str {
                "lifo" => PreemptionMode::Lifo,
                "fifo" => PreemptionMode::Fifo,
                _ => {
                    return Err(anyhow::anyhow!(
                        "Invalid preemption_mode: '{}'. Must be 'lifo' or 'fifo'.",
                        mode_str
                    ));
                }
            };
            builder = builder.preemption_mode(mode);
        }

        if let Some(value) = extra_args.get("sglang") {
            let cfg: SglangArgs = serde_json::from_value(value.clone())
                .map_err(|e| anyhow::anyhow!("Failed to parse sglang config: {}", e))?;
            builder = builder.sglang(Some(cfg));
        }

        // Parse worker type from is_prefill and is_decode flags
        let is_prefill = extra_args
            .get("is_prefill")
            .and_then(|v| v.as_bool())
            .unwrap_or(false);
        let is_decode = extra_args
            .get("is_decode")
            .and_then(|v| v.as_bool())
            .unwrap_or(false);

        // Determine worker type based on flags
        let worker_type = match (is_prefill, is_decode) {
            (false, false) => WorkerType::Aggregated,
            (true, false) => WorkerType::Prefill,
            (false, true) => WorkerType::Decode,
            (true, true) => panic!(
                "Invalid worker configuration: is_prefill and is_decode cannot both be true. \
                 Worker must be either Aggregated (both false), Prefill (is_prefill=true), or Decode (is_decode=true)."
            ),
        };
        builder = builder.worker_type(worker_type);

        // Load performance model from NPZ file if provided.
        let perf_model = if let Some(path_str) = extra_args.get("planner_profile_data")
            && let Some(path_str) = path_str.as_str()
        {
            let npz_path = PathBuf::from(path_str);
            match PerfModel::from_npz(&npz_path) {
                Ok(model) => {
                    tracing::info!("Successfully loaded performance model from: {:?}", npz_path);
                    Arc::new(model)
                }
                Err(e) => {
                    tracing::error!(
                        "Failed to load performance model from {:?}: {}. Falling back to polynomial model.",
                        npz_path,
                        e
                    );
                    Arc::new(PerfModel::default())
                }
            }
        } else {
            Arc::new(PerfModel::default())
        };
        builder = builder.perf_model(perf_model);

        // Check for AIC direct mode fields
        if let Some(backend) = extra_args.get("aic_backend")
            && let Some(backend_str) = backend.as_str()
        {
            builder = builder.aic_backend(Some(backend_str.to_string()));
        }
        if let Some(system) = extra_args.get("aic_system")
            && let Some(s) = system.as_str()
        {
            builder = builder.aic_system(Some(s.to_string()));
        }
        if let Some(version) = extra_args.get("aic_backend_version")
            && let Some(s) = version.as_str()
        {
            builder = builder.aic_backend_version(Some(s.to_string()));
        }
        if let Some(tp) = extra_args.get("aic_tp_size")
            && let Some(n) = tp.as_u64()
        {
            builder = builder.aic_tp_size(Some(n as usize));
        }
        if let Some(mp) = extra_args.get("aic_model_path")
            && let Some(s) = mp.as_str()
        {
            builder = builder.aic_model_path(Some(s.to_string()));
        }
        // Build the MockEngineArgs with either defaults or overridden values
        builder
            .build()
            .map_err(|e| anyhow::anyhow!("Failed to build MockEngineArgs: {}", e))
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_unique_block_default_uniqueness() {
        // Create 10 default UniqueBlock instances
        let blocks: Vec<UniqueBlock> = (0..10).map(|_| UniqueBlock::default()).collect();

        // Extract UUIDs from each block
        let mut uuids = Vec::new();
        for block in blocks {
            match block {
                UniqueBlock::PartialBlock(uuid) => uuids.push(uuid),
                _ => panic!("Expected UuidIdentifier variant"),
            }
        }

        // Check that all UUIDs are unique by comparing each with every other
        for i in 0..uuids.len() {
            for j in i + 1..uuids.len() {
                assert_ne!(
                    uuids[i], uuids[j],
                    "UUID at index {} and {} are identical",
                    i, j
                );
            }
        }
    }
}