Files
sglang/sgl-router/src/protocols/generate.rs

292 lines
9.4 KiB
Rust

use std::collections::HashMap;
use serde::{Deserialize, Serialize};
use serde_json::Value;
use validator::Validate;
use super::{
common::{default_true, GenerationRequest, InputIds},
sampling_params::SamplingParams,
};
use crate::protocols::validated::Normalizable;
// ============================================================================
// SGLang Generate API (native format)
// ============================================================================
#[derive(Clone, Debug, Serialize, Deserialize, Validate)]
#[validate(schema(function = "validate_generate_request"))]
pub struct GenerateRequest {
/// Text input - SGLang native format
#[serde(skip_serializing_if = "Option::is_none")]
pub text: Option<String>,
/// Input IDs for tokenized input
#[serde(skip_serializing_if = "Option::is_none")]
pub input_ids: Option<InputIds>,
/// Input embeddings for direct embedding input
/// Can be a 2D array (single request) or 3D array (batch of requests)
/// Placeholder for future use
#[serde(skip_serializing_if = "Option::is_none")]
pub input_embeds: Option<Value>,
/// Image input data
/// Can be an image instance, file name, URL, or base64 encoded string
/// Supports single images, lists of images, or nested lists for batch processing
/// Placeholder for future use
#[serde(skip_serializing_if = "Option::is_none")]
pub image_data: Option<Value>,
/// Video input data
/// Can be a file name, URL, or base64 encoded string
/// Supports single videos, lists of videos, or nested lists for batch processing
/// Placeholder for future use
#[serde(skip_serializing_if = "Option::is_none")]
pub video_data: Option<Value>,
/// Audio input data
/// Can be a file name, URL, or base64 encoded string
/// Supports single audio files, lists of audio, or nested lists for batch processing
/// Placeholder for future use
#[serde(skip_serializing_if = "Option::is_none")]
pub audio_data: Option<Value>,
/// Sampling parameters (sglang style)
#[serde(skip_serializing_if = "Option::is_none")]
pub sampling_params: Option<SamplingParams>,
/// Whether to return logprobs
#[serde(skip_serializing_if = "Option::is_none")]
pub return_logprob: Option<bool>,
/// If return logprobs, the start location in the prompt for returning logprobs.
#[serde(skip_serializing_if = "Option::is_none")]
pub logprob_start_len: Option<i32>,
/// If return logprobs, the number of top logprobs to return at each position.
#[serde(skip_serializing_if = "Option::is_none")]
pub top_logprobs_num: Option<i32>,
/// If return logprobs, the token ids to return logprob for.
#[serde(skip_serializing_if = "Option::is_none")]
pub token_ids_logprob: Option<Vec<u32>>,
/// Whether to detokenize tokens in text in the returned logprobs.
#[serde(default)]
pub return_text_in_logprobs: bool,
/// Whether to stream the response
#[serde(default)]
pub stream: bool,
/// Whether to log metrics for this request (e.g. health_generate calls do not log metrics)
#[serde(default = "default_true")]
pub log_metrics: bool,
/// Return model hidden states
#[serde(default)]
pub return_hidden_states: bool,
/// The modalities of the image data [image, multi-images, video]
#[serde(skip_serializing_if = "Option::is_none")]
pub modalities: Option<Vec<String>>,
/// Session parameters for continual prompting
#[serde(skip_serializing_if = "Option::is_none")]
pub session_params: Option<HashMap<String, Value>>,
/// Path to LoRA adapter(s) for model customization
#[serde(skip_serializing_if = "Option::is_none")]
pub lora_path: Option<String>,
/// LoRA adapter ID (if pre-loaded)
#[serde(skip_serializing_if = "Option::is_none")]
pub lora_id: Option<String>,
/// Custom logit processor for advanced sampling control. Must be a serialized instance
/// of `CustomLogitProcessor` in python/sglang/srt/sampling/custom_logit_processor.py
/// Use the processor's `to_str()` method to generate the serialized string.
#[serde(skip_serializing_if = "Option::is_none")]
pub custom_logit_processor: Option<String>,
/// For disaggregated inference
#[serde(skip_serializing_if = "Option::is_none")]
pub bootstrap_host: Option<String>,
/// For disaggregated inference
#[serde(skip_serializing_if = "Option::is_none")]
pub bootstrap_port: Option<i32>,
/// For disaggregated inference
#[serde(skip_serializing_if = "Option::is_none")]
pub bootstrap_room: Option<i32>,
/// For disaggregated inference
#[serde(skip_serializing_if = "Option::is_none")]
pub bootstrap_pair_key: Option<String>,
/// Data parallel rank routing
#[serde(skip_serializing_if = "Option::is_none")]
pub data_parallel_rank: Option<i32>,
/// Background response
#[serde(default)]
pub background: bool,
/// Conversation ID for tracking
#[serde(skip_serializing_if = "Option::is_none")]
pub conversation_id: Option<String>,
/// Priority for the request
#[serde(skip_serializing_if = "Option::is_none")]
pub priority: Option<i32>,
/// Extra key for classifying the request (e.g. cache_salt)
#[serde(skip_serializing_if = "Option::is_none")]
pub extra_key: Option<String>,
/// Whether to disallow logging for this request (e.g. due to ZDR)
#[serde(default)]
pub no_logs: bool,
/// Custom metric labels
#[serde(skip_serializing_if = "Option::is_none")]
pub custom_labels: Option<HashMap<String, String>>,
/// Whether to return bytes for image generation
#[serde(default)]
pub return_bytes: bool,
/// Whether to return entropy
#[serde(default)]
pub return_entropy: bool,
/// Request ID for tracking (inherited from BaseReq in Python)
#[serde(skip_serializing_if = "Option::is_none")]
pub rid: Option<String>,
}
impl Normalizable for GenerateRequest {
// Use default no-op implementation - no normalization needed for GenerateRequest
}
/// Validation function for GenerateRequest - ensure exactly one input type is provided
fn validate_generate_request(req: &GenerateRequest) -> Result<(), validator::ValidationError> {
// Exactly one of text or input_ids must be provided
// Note: input_embeds not yet supported in Rust implementation
let has_text = req.text.is_some();
let has_input_ids = req.input_ids.is_some();
let count = [has_text, has_input_ids].iter().filter(|&&x| x).count();
if count == 0 {
return Err(validator::ValidationError::new(
"Either text or input_ids should be provided.",
));
}
if count > 1 {
return Err(validator::ValidationError::new(
"Either text or input_ids should be provided.",
));
}
Ok(())
}
impl GenerationRequest for GenerateRequest {
fn is_stream(&self) -> bool {
self.stream
}
fn get_model(&self) -> Option<&str> {
// Generate requests typically don't have a model field
None
}
fn extract_text_for_routing(&self) -> String {
// Check fields in priority order: text, input_ids
if let Some(ref text) = self.text {
return text.clone();
}
if let Some(ref input_ids) = self.input_ids {
return match input_ids {
InputIds::Single(ids) => ids
.iter()
.map(|&id| id.to_string())
.collect::<Vec<String>>()
.join(" "),
InputIds::Batch(batches) => batches
.iter()
.flat_map(|batch| batch.iter().map(|&id| id.to_string()))
.collect::<Vec<String>>()
.join(" "),
};
}
// No text input found
String::new()
}
}
// ============================================================================
// SGLang Generate Response Types
// ============================================================================
/// SGLang generate response (single completion or array for n>1)
///
/// Format for n=1:
/// ```json
/// {
/// "text": "...",
/// "output_ids": [...],
/// "meta_info": { ... }
/// }
/// ```
///
/// Format for n>1:
/// ```json
/// [
/// {"text": "...", "output_ids": [...], "meta_info": {...}},
/// {"text": "...", "output_ids": [...], "meta_info": {...}}
/// ]
/// ```
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct GenerateResponse {
pub text: String,
pub output_ids: Vec<u32>,
pub meta_info: GenerateMetaInfo,
}
/// Metadata for a single generate completion
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct GenerateMetaInfo {
pub id: String,
pub finish_reason: GenerateFinishReason,
pub prompt_tokens: u32,
pub weight_version: String,
#[serde(skip_serializing_if = "Option::is_none")]
pub input_token_logprobs: Option<Vec<Vec<Option<f64>>>>,
#[serde(skip_serializing_if = "Option::is_none")]
pub output_token_logprobs: Option<Vec<Vec<Option<f64>>>>,
pub completion_tokens: u32,
pub cached_tokens: u32,
pub e2e_latency: f64,
#[serde(skip_serializing_if = "Option::is_none")]
pub matched_stop: Option<Value>,
}
/// Finish reason for generate endpoint
#[derive(Debug, Clone, Serialize, Deserialize)]
#[serde(tag = "type", rename_all = "lowercase")]
pub enum GenerateFinishReason {
Length {
length: u32,
},
Stop,
#[serde(untagged)]
Other(Value),
}