Files
wifi-densepose/vendor/ruvector/examples/ruvLLM/esp32-flash/src/lib.rs

151 lines
4.6 KiB
Rust

//! RuvLLM ESP32 Flash - Complete Flashable Implementation
//!
//! Full-featured LLM inference engine for ESP32 with:
//! - INT8/Binary quantized inference
//! - Product quantization (8-32x compression)
//! - MicroLoRA on-device adaptation
//! - Sparse attention patterns
//! - HNSW vector search (1000+ vectors)
//! - Semantic memory with context
//! - RAG (Retrieval-Augmented Generation)
//! - Anomaly detection
//! - Multi-chip federation
//! - Pipeline/tensor parallelism
//! - Speculative decoding
#![cfg_attr(not(feature = "std"), no_std)]
#[cfg(not(feature = "std"))]
extern crate alloc;
// Core modules
pub mod optimizations;
pub mod federation;
pub mod ruvector;
// Re-exports for convenience
pub use optimizations::{
BinaryVector, BinaryEmbedding, hamming_distance, hamming_similarity,
ProductQuantizer, PQCode, PQConfig,
SoftmaxLUT, ExpLUT, DistanceLUT, SOFTMAX_LUT, DISTANCE_LUT,
MicroLoRA, LoRAConfig, LoRAStack,
SparseAttention, AttentionPattern,
LayerPruner, PruningConfig, PruningMask,
};
pub use federation::{
PipelineNode, PipelineConfig, PipelineRole, PipelineState,
FederationMessage, MessageType, ChipId, MessageHeader,
SpeculativeDecoder, DraftVerifyConfig, DraftResult, VerifyResult,
FederationConfig, FederationMode, CommunicationBus,
};
pub use ruvector::{
MicroHNSW, HNSWConfig, SearchResult,
SemanticMemory, Memory, MemoryType,
MicroRAG, RAGConfig, RAGResult,
AnomalyDetector, AnomalyConfig, AnomalyResult,
MicroVector, DistanceMetric,
euclidean_distance_i8, cosine_distance_i8, dot_product_i8,
};
/// ESP32 variant configuration
#[derive(Debug, Clone, Copy, PartialEq)]
pub enum Esp32Variant {
/// Original ESP32: 520KB SRAM
Esp32,
/// ESP32-S2: 320KB SRAM
Esp32S2,
/// ESP32-S3: 512KB SRAM + vector instructions
Esp32S3,
/// ESP32-C3: 400KB SRAM, RISC-V
Esp32C3,
/// ESP32-C6: 512KB SRAM, RISC-V + WiFi 6
Esp32C6,
}
impl Esp32Variant {
/// Available SRAM in bytes
pub const fn sram_bytes(&self) -> usize {
match self {
Self::Esp32 => 520 * 1024,
Self::Esp32S2 => 320 * 1024,
Self::Esp32S3 => 512 * 1024,
Self::Esp32C3 => 400 * 1024,
Self::Esp32C6 => 512 * 1024,
}
}
/// Whether variant has hardware floating point
pub const fn has_fpu(&self) -> bool {
matches!(self, Self::Esp32S3)
}
/// Whether variant has vector/SIMD extensions
pub const fn has_simd(&self) -> bool {
matches!(self, Self::Esp32S3)
}
/// Recommended max model size (leaving ~200KB for runtime)
pub const fn max_model_ram(&self) -> usize {
self.sram_bytes().saturating_sub(200 * 1024)
}
}
/// Error types
#[derive(Debug, Clone)]
pub enum Error {
/// Model too large for available memory
ModelTooLarge { required: usize, available: usize },
/// Invalid model format
InvalidModel(&'static str),
/// Quantization error
QuantizationError(&'static str),
/// Buffer overflow
BufferOverflow,
/// Inference failed
InferenceFailed(&'static str),
/// Feature not supported
UnsupportedFeature(&'static str),
/// Communication error
CommunicationError(&'static str),
}
impl core::fmt::Display for Error {
fn fmt(&self, f: &mut core::fmt::Formatter<'_>) -> core::fmt::Result {
match self {
Error::ModelTooLarge { required, available } => {
write!(f, "Model requires {} bytes, only {} available", required, available)
}
Error::InvalidModel(msg) => write!(f, "Invalid model: {}", msg),
Error::QuantizationError(msg) => write!(f, "Quantization error: {}", msg),
Error::BufferOverflow => write!(f, "Buffer overflow"),
Error::InferenceFailed(msg) => write!(f, "Inference failed: {}", msg),
Error::UnsupportedFeature(msg) => write!(f, "Unsupported: {}", msg),
Error::CommunicationError(msg) => write!(f, "Communication error: {}", msg),
}
}
}
pub type Result<T> = core::result::Result<T, Error>;
/// Quantization parameters
#[derive(Debug, Clone, Copy, Default)]
pub struct QuantParams {
pub scale: i32,
pub zero_point: i8,
}
/// Prelude for common imports
pub mod prelude {
pub use crate::{
Error, Result, Esp32Variant, QuantParams,
// Optimizations
BinaryVector, ProductQuantizer, MicroLoRA, SparseAttention, LayerPruner,
// Federation
PipelineNode, FederationMessage, SpeculativeDecoder, ChipId,
// RuVector
MicroHNSW, SemanticMemory, MicroRAG, AnomalyDetector, MicroVector,
};
}