coreason-runtime 0.1.0

Kinetic Plane execution engine for the CoReason Tripartite Cybernetic Manifold
Documentation 
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// Copyright (c) 2026 CoReason, Inc.
// All rights reserved.

use std::path::Path;
use tract_onnx::prelude::*;

/// Pure-Rust ONNX Embedding Engine utilizing Sonos Tract
pub struct TractEmbeddings {
    model: Option<SimplePlan<TypedFact, Box<dyn TypedOp>, Graph<TypedFact, Box<dyn TypedOp>>>>,
}

impl TractEmbeddings {
    /// Creates a new TractEmbeddings instance
    pub fn new() -> Self {
        Self { model: None }
    }

    /// Loads and optimizes an ONNX embedding model from path
    pub fn load_model(&mut self, model_path: &Path) -> Result<(), String> {
        let onnx_model = tract_onnx::onnx()
            .model_for_path(model_path)
            .map_err(|e| format!("Failed to read ONNX model: {}", e))?;

        let model = onnx_model
            .into_optimized()
            .map_err(|e| format!("Failed to optimize ONNX model: {}", e))?
            .into_runnable()
            .map_err(|e| format!("Failed to build runnable ONNX model: {}", e))?;

        self.model = Some(model);
        println!("[TRACT] ONNX embedding model loaded successfully.");
        Ok(())
    }

    /// Computes a vector embedding representation for input tokens
    pub fn compute_embedding(&self, _tokens: &[i64]) -> Result<Vec<f32>, String> {
        if self.model.is_none() {
            return Err("Model not loaded".to_string());
        }

        // In native execution:
        // let input = Tensor::from_shape(&[1, _tokens.len()], _tokens)...
        // let result = plan.run(tensors_in)...

        Ok(vec![0.0; 384]) // Returns typical 384-dimensional vector stub
    }
}