reflex-cache 0.2.2

Episodic memory and high-speed semantic cache for LLM responses
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66

use std::path::PathBuf;
use thiserror::Error;

#[derive(Debug, Error)]
/// Errors returned by embedding generation and model loading.
pub enum EmbeddingError {
    /// Model files were not found.
    #[error("embedding model not found at path: {path}")]
    ModelNotFound {
        /// Missing model path.
        path: PathBuf,
    },

    /// Model load failed.
    #[error("failed to load embedding model: {reason}")]
    ModelLoadFailed {
        /// Error message.
        reason: String,
    },

    /// Requested compute device is unavailable.
    #[error("{device} device unavailable: {reason}")]
    DeviceUnavailable {
        /// Device name (e.g. "cuda", "metal").
        device: String,
        /// Error message.
        reason: String,
    },

    /// Inference failed.
    #[error("embedding inference failed: {reason}")]
    InferenceFailed {
        /// Error message.
        reason: String,
    },

    /// Tokenization failed.
    #[error("tokenization failed: {reason}")]
    TokenizationFailed {
        /// Error message.
        reason: String,
    },

    /// Configuration is invalid.
    #[error("invalid model configuration: {reason}")]
    InvalidConfig {
        /// Error message.
        reason: String,
    },
}

impl From<candle_core::Error> for EmbeddingError {
    fn from(err: candle_core::Error) -> Self {
        EmbeddingError::InferenceFailed {
            reason: err.to_string(),
        }
    }
}

impl From<std::io::Error> for EmbeddingError {
    fn from(err: std::io::Error) -> Self {
        EmbeddingError::ModelLoadFailed {
            reason: err.to_string(),
        }
    }
}