Bolt C++ ML — AI-Powered C++ IDE

Description

--- name: bolt-cppml description: Build and optimize the Bolt C++ ML IDE with neural network module architecture. Use for C++ IDE development with GGML integration, RWKV neural networks, AI code completion, GPU acceleration, and modular component composition following nn patterns. source_chain: function-creator( c++( nn( bolt-new ) ) ) --- # Bolt C++ ML — AI-Powered C++ IDE Bolt C++ ML is a modular C++ IDE with integrated machine learning capabilities, combining GGML-based inference, RWKV neural networks, and a full-featured editor with split views, multi-cursor editing, code folding, theming, keyboard shortcuts, plugin system, LSP integration, and collaborative editing. ## Architecture Overview The project follows a **neural network module composition pattern** where each IDE component is treated as a composable module (analogous to `nn.Module` in Torch7), connected through a sequential pipeline. ### Core Module Hierarchy | Module Layer | Component | Source Path | |---|---|---| | **AI / Inference** | GGML Wrapper, RWKV Wrapper, Direct GGUF Inference | `src/bolt/ai/` | | **Editor** | Split View, Multi-Cursor, Code Folding, Keyboard Shortcuts | `src/bolt/editor/` | | **Core** | Chat Store, Editor Store, File Store, Workbench Store | `src/bolt/core/` | | **GUI** | ImGui Integration, Theme System, Tab Bar, Minimap | `src/bolt/gui/` | | **Git** | Repository Management, Diff, Staging | `src/bolt/git/` | | **Network** | Collaboration, Network Optimizations | `src/bolt/network/` | | **System** | Logging, Debugger, Memory Leak Detector, Profiler | `src/bolt/system/` | | **Plugin** | Plugin System, Extension API | `src/bolt/plugin/` | | **LSP** | Language Server Protocol Client | `src/bolt/lsp/` | ### Key Files | File | Purpose | |---|---| | `CMakeLists.txt` | Top-level build configuration | | `test/CMakeLists.txt` | Test framework with CTest integration | | `src/bolt/ai/ggml_wrapper.cpp` | GGML backend for tensor operations | | `src/bolt/ai/rwkv_wrapper.cpp` | RWKV time-mixing and channel-mixing layers | | `src/bolt/ai/direct_gguf_inference.cpp` | Direct GGUF model loading and inference | | `include/bolt/ai/*.hpp` | AI module headers | | `include/bolt/editor/*.hpp` | Editor component headers | | `include/bolt/core/*.hpp` | Core store headers | ## Quick Start ### Prerequisites - C++20 compatible compiler (GCC 11+, Clang 14+) - CMake 3.15+ - GGML library (bundled as submodule) ### Build ```bash git clone https://github.com/cogpy/bolt-cppml.git cd bolt-cppml mkdir build && cd build cmake .. -DCMAKE_BUILD_TYPE=Release make -j$(nproc) ``` ### Test ```bash cd build ctest --output-on-failure ``` All 97 tests should pass with 0 warnings. The CTest configuration automatically sets `LD_LIBRARY_PATH` for shared library resolution. ## Neural Network Module Pattern Each component follows the nn module pattern: ### Forward Pass (Data Flow) ``` Input → [Tokenizer] → [RWKV TimeMixing] → [RWKV ChannelMixing] → [LayerNorm] → [Output Projection] → Completion ``` ### RWKV Time-Mixing (WKV Attention) The RWKV wrapper implements the full WKV attention mechanism: ``` xk = last_x + (x - last_x) * time_mix_k xv = last_x + (x - last_x) * time_mix_v xr = last_x + (x - last_x) * time_mix_r k = Wk @ xk, v = Wv @ xv, r = Wr @ xr wkv = (last_num + exp(bonus + k) * v) / (last_den + exp(bonus + k)) output = Wout @ (sigmoid(r) * wkv) ``` ### RWKV Channel-Mixing (Feed-Forward with Memory) ``` xk = last_x + (x - last_x) * time_mix_k xr = last_x + (x - last_x) * time_mix_r k = Wk @ xk, r = Wr @ xr vk = Wv @ (relu(k))^2 output = sigmoid(r) * vk ``` ## Test Framework The project uses a custom lightweight test framework with CTest integration: | Test Suite | Tests | Description | |---|---|---| | Core | 7 | Chat, Memory, Store, String, FileTree, Minimap | | Editor | 5 | SplitView, MultiCursor, KeyboardShortcuts, Theme, CodeFolding | | ErrorHandling | 7 | Error recovery, boundary conditions | | AI | 15 | GGML wrapper, AI models, KoboldCpp provider (13 suites) | | Comprehensive E2E | 27 | Cross-module, DrawKern VM, Styx, Git, Benchmark, Plugin | | Extended E2E | 11 | DataProcessor, MathUtils, FileSystem, LineNumbers, VectorDB, OT edge cases | | Integration | 2 | Full integration tests | | System | 4 | Debugger, Logging, MemoryLeak, Sanitizer | ### Running Specific Test Labels ```bash ctest -L Unit # All unit tests ctest -L Editor # Editor component tests ctest -L AI # AI/ML tests ctest -L Integration # Integration tests ``` ## Extending the IDE ### Adding New Modules 1. Create header in `include/bolt/<category>/` 2. Create implementation in `src/bolt/<category>/` 3. Add source to `CMakeLists.txt` bolt_lib target 4. Add test in `test/` 5. Register test in `test/CMakeLists.txt` ### Plugin System Plugins follow the module pattern with lifecycle hooks: ```cpp class MyPlugin : public bolt::Plugin { void onActivate() override; void onDeactivate() override; std::string getName() const override; }; ``` ## Build Status - **Errors**: 0 - **Warnings**: 0 - **Tests**: 97/97 passing (100%) - **CTest**: Fully configured with LD_LIBRARY_PATH and labels - **Labels**: Unit, Core, Editor, ErrorHandling, AI, KoboldCpp, Extended, Integration

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