77 lines
2.2 KiB
Rust
77 lines
2.2 KiB
Rust
use serde::{Deserialize, Serialize};
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use serde_json::Value;
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use super::common::{GenerationRequest, UsageInfo};
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// ============================================================================
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// Embedding API
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// ============================================================================
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#[derive(Debug, Clone, Deserialize, Serialize)]
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pub struct EmbeddingRequest {
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/// ID of the model to use
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pub model: String,
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/// Input can be a string, array of strings, tokens, or batch inputs
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pub input: Value,
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/// Optional encoding format (e.g., "float", "base64")
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#[serde(skip_serializing_if = "Option::is_none")]
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pub encoding_format: Option<String>,
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/// Optional user identifier
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#[serde(skip_serializing_if = "Option::is_none")]
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pub user: Option<String>,
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/// Optional number of dimensions for the embedding
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#[serde(skip_serializing_if = "Option::is_none")]
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pub dimensions: Option<u32>,
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/// SGLang extension: request id for tracking
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#[serde(skip_serializing_if = "Option::is_none")]
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pub rid: Option<String>,
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/// SGLang extension: enable/disable logging of metrics for this request
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#[serde(skip_serializing_if = "Option::is_none")]
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pub log_metrics: Option<bool>,
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}
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impl GenerationRequest for EmbeddingRequest {
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fn is_stream(&self) -> bool {
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// Embeddings are non-streaming
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false
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}
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fn get_model(&self) -> Option<&str> {
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Some(&self.model)
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}
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fn extract_text_for_routing(&self) -> String {
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// Best effort: extract text content for routing decisions
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match &self.input {
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Value::String(s) => s.clone(),
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Value::Array(arr) => arr
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.iter()
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.filter_map(|v| v.as_str())
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.collect::<Vec<_>>()
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.join(" "),
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_ => String::new(),
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}
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}
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}
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct EmbeddingObject {
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pub object: String, // "embedding"
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pub embedding: Vec<f32>,
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pub index: u32,
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}
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct EmbeddingResponse {
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pub object: String, // "list"
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pub data: Vec<EmbeddingObject>,
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pub model: String,
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pub usage: UsageInfo,
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}
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