Architecture review: Analysis, documentation, and foundational improvements

[Copilot]

Comprehensive architecture review of the LLM inference system with prioritized improvement recommendations and foundational module implementations.

Analysis & Documentation

ARCHITECTURE_ANALYSIS.md (447 lines)

• Module structure evaluation with scoring (current: 7.6/10, potential: 9.0/10)
• Prioritized improvements: error handling, code modularization, performance optimization
• Concrete refactoring proposals for self-attention and inference loops
• Memory optimization strategies and extensibility patterns

API_IMPROVEMENTS.md (418 lines)

• Error propagation patterns replacing unwrap() chains
• Configuration consolidation (5 params → 1 struct)
• Builder pattern implementations for model initialization
• Type-safe tensor operations with compile-time shape checking

IMPROVEMENTS_SUMMARY.md (486 lines)

• 4-phase implementation roadmap (1-2 weeks → ongoing)
• Before/after code comparisons for key improvements
• Testing strategy expansion (unit → integration → benchmarks)

DOCS_README.md + REVIEW_COMPLETION.md

• Navigation guide and completion metrics

Foundational Modules

src/error.rs

pub enum LlamaError {
    TensorShapeMismatch { expected, actual, context },
    ModelLoadError(String),
    InferenceError(String),
    // ... with From impls for std errors
}

src/sampling.rs

pub struct SamplingConfig {
    pub max_len: usize,
    pub top_p: f32,
    pub top_k: u32, 
    pub temperature: f32,
}
// Presets: default(), greedy(), creative()

These enable cleaner APIs:

// Before: 5 parameters repeated across functions
generate(tokens, max_len, top_p, top_k, temp)

// After: single config object
generate(tokens, &SamplingConfig::creative())

Key Findings

Strengths: Clear separation of concerns, good test coverage, teaching-friendly
Priority improvements: Error handling (✓ provided), config management (✓ provided), self-attention refactoring, memory pooling
Performance opportunities: 220-line self-attention function, temporary allocations in hot paths, SIMD-eligible operations

Original prompt

请你审视一下我的项目架构，提出建议

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