coreason_runtime_rust/
embeddings.rs

1// Copyright (c) 2026 CoReason, Inc.
2// All rights reserved.
3
4use std::path::Path;
5use tract_onnx::prelude::*;
6
7/// Pure-Rust ONNX Embedding Engine utilizing Sonos Tract
8pub struct TractEmbeddings {
9    model: Option<SimplePlan<TypedFact, Box<dyn TypedOp>, Graph<TypedFact, Box<dyn TypedOp>>>>,
10}
11
12impl TractEmbeddings {
13    /// Creates a new TractEmbeddings instance
14    pub fn new() -> Self {
15        Self { model: None }
16    }
17
18    /// Loads and optimizes an ONNX embedding model from path
19    pub fn load_model(&mut self, model_path: &Path) -> Result<(), String> {
20        let onnx_model = tract_onnx::onnx()
21            .model_for_path(model_path)
22            .map_err(|e| format!("Failed to read ONNX model: {}", e))?;
23
24        let model = onnx_model
25            .into_optimized()
26            .map_err(|e| format!("Failed to optimize ONNX model: {}", e))?
27            .into_runnable()
28            .map_err(|e| format!("Failed to build runnable ONNX model: {}", e))?;
29
30        self.model = Some(model);
31        println!("[TRACT] ONNX embedding model loaded successfully.");
32        Ok(())
33    }
34
35    /// Computes a vector embedding representation for input tokens
36    pub fn compute_embedding(&self, _tokens: &[i64]) -> Result<Vec<f32>, String> {
37        if self.model.is_none() {
38            return Err("Model not loaded".to_string());
39        }
40
41        // In native execution:
42        // let input = Tensor::from_shape(&[1, _tokens.len()], _tokens)...
43        // let result = plan.run(tensors_in)...
44
45        Ok(vec![0.0; 384]) // Returns typical 384-dimensional vector stub
46    }
47}
coreason_runtime_rust/embeddings.rs

coreason_runtime_rust/
embeddings.rs
