st/proxy/
candle.rs

1//! 🤖 Candle Local LLM Provider Implementation
2//!
3//! "Bringing AI home with Rust-native local models!" - The Cheet 😺
4
5use crate::proxy::{LlmProvider, LlmRequest, LlmResponse};
6use anyhow::Result;
7use async_trait::async_trait;
8
9#[cfg(feature = "candle")]
10use crate::proxy::LlmUsage;
11#[cfg(feature = "candle")]
12use candle_core::{Device, Tensor};
13#[cfg(feature = "candle")]
14use candle_transformers::models::llama;
15
16pub struct CandleProvider {
17    // In a real implementation, we would hold model weights here
18    model_path: Option<String>,
19}
20
21impl CandleProvider {
22    pub fn new(model_path: Option<String>) -> Self {
23        Self { model_path }
24    }
25}
26
27impl Default for CandleProvider {
28    fn default() -> Self {
29        Self::new(None)
30    }
31}
32
33#[async_trait]
34impl LlmProvider for CandleProvider {
35    async fn complete(&self, _request: LlmRequest) -> Result<LlmResponse> {
36        #[cfg(not(feature = "candle"))]
37        {
38            return Err(anyhow::anyhow!(
39                "Candle support is not enabled. Recompile with --features candle"
40            ));
41        }
42
43        #[cfg(feature = "candle")]
44        {
45            // Suppress unused import warnings - these will be used when implementation is complete
46            let _suppress_warnings = (
47                std::marker::PhantomData::<LlmUsage>,
48                std::marker::PhantomData::<Device>,
49                std::marker::PhantomData::<Tensor>,
50                std::marker::PhantomData::<llama::Config>,
51            );
52
53            // This is a placeholder for the actual Candle implementation.
54            // In a real scenario, we would:
55            // 1. Load the model (if not already loaded)
56            // 2. Tokenize the input
57            // 3. Run inference
58            // 4. Decode the output
59
60            println!(
61                "🕯️ Running local inference with Candle (model: {})...",
62                _request.model
63            );
64
65            // For now, return a helpful message
66            Ok(LlmResponse {
67                content: format!("Local inference with Candle is configured but requires model weights. (Requested model: {})", _request.model),
68                model: _request.model,
69                usage: None,
70            })
71        }
72    }
73
74    fn name(&self) -> &'static str {
75        "Candle"
76    }
77}
st/proxy/candle.rs

st/proxy/
candle.rs
