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.github/workflows/pr-auto-describe.yml

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name: PR Auto Describe
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on:
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pull_request:
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types: [synchronize, reopened, labeled]

CONTRIBUTING.md

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# Contributing to OMNI 🌌
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# Contributing to OMNI
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We love your contributions! OMNI is built on a mission to make context usage as efficient as possible. Here’s how you can help:
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## 🛣 Getting Started
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## Getting Started
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1. **Fork the repo** and clone it locally.
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2. **Install dependencies**:
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- `core/src/filters/`: Join the mission by adding specialized semantic filters.
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- `src/`: Refine the MCP server or caching logic.
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## 🤝 Contribution Workflow
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## Contribution Workflow
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1. **Bug Reports & Feature Requests**: Open an issue describing the context and the problem/idea.
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2. **Pull Requests**:
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- Write tests for new filters and run `zig build test`.
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- Update `CHANGELOG.md` with your changes.
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## 🏛 Architecture
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## Development Core
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Before modifying the core, please read:
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- [DEVELOPMENT.md](docs/DEVELOPMENT.md)
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## ⚖️ Code of Conduct
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## Code of Conduct
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Be kind, respect the semantic integrity of the project, and help us build the most efficient engine for the AI era.
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INSTALL.md

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# Installing OMNI 🌌
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# Installing OMNI
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OMNI is designed to be installed locally and integrated into your MCP environment.
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## 🚀 One-Line Installation (Universal)
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## One-Line Installation (Universal)
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If you have **Zig 0.15.2** and **Node.js 18+** installed, you can set up OMNI in one step:
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brew install fajarhide/tap/omni
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```
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## 🛠 Manual Installation
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## Manual Installation
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If you prefer to install manually:
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```
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2. **Compile OMNI**:
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OMNI uses the standard Zig build system.
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OMNI uses the standard Zig build system. Build native CLI + Wasm Edge.
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```bash
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# Build native CLI + Wasm Edge
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zig build -Doptimize=ReleaseFast -p .
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zig build -Doptimize=ReleaseFast -p
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```
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3. **Verify via Native CLI**:
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./bin/omni setup
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```
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## 🔌 Integration with AI Agents
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## Integration with AI Agents
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OMNI is compatible with any tool that supports the **Model Context Protocol (MCP)**.
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### Generic MCP Agents
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For any other agent, ensure the `node` environment is available and point the transport to OMNI's entry point: `/path/to/omni/dist/index.js`.
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## 📦 Dependencies
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## Dependencies
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- **Zig 0.15.2+**: Required for the high-performance core.
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- **Node.js 18+**: Required for the MCP gateway.

ROADMAP.md

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# OMNI Roadmap 🗺️
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# OMNI Roadmap
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Project OMNI is on a mission to redefine how AI models consume information. This roadmap outlines our phased approach to becoming the universal semantic compression layer for all AI agents.
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## 📍 Phase 1: Foundation (Completed)
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## Phase 1: Foundation (Completed)
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- [x] High-performance Zig core with Wasm target.
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- [x] Initial semantic filters: Git, Build, Docker, SQL.
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- [x] **Unified Native CLI**: Subcommand architecture (report, bench, generate).
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- [x] MCP Server integration for Claude Code & Antigravity.
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- [x] Tiered LRU + TTL caching layer.
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- [x] Universal one-line installer.
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## 🚀 Phase 2: Intelligence Expansion (In-Progress)
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## Phase 2: Intelligence Expansion (In-Progress)
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- [ ] **Native Filter DSL**: Move from hardcoded filters to a lightweight declarative format.
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- [ ] **Advanced Language Filters**:
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- Python (summarizing imports, class structures, and docstrings).
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- [ ] **Adaptive Compression**: Dynamic compression ratios based on the model's remaining context window.
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- [ ] **Local LLM Integration**: Use tiny local models (like Llama-3-8B) to generate ultra-dense semantic summaries for high-complexity text.
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## Phase 3: Edge Scaling
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## Phase 3: Edge Scaling
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- [ ] **Distributed Caching**: Shared cache across multiple agents on the same local network.
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- [ ] **Streaming Distillation**: Process massive file streams in real-time without blocking the main agent execution.
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- [ ] **Mobile & Browser Targets**: Compiling OMNI to pure browser Wasm for web-based IDE integration.
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## 🎨 Phase 4: Visuals & Ecosystem
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## Phase 4: Visuals & Ecosystem
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- [ ] **OMNI Dashboard**: A lightweight local web UI to visualize token savings, latency, and system health in real-time.
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- [ ] **Plugin SDK**: A standardized way for developers to write their own filters in Zig or TypeScript.
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- [ ] **Vscode/JetBrains Extensions**: Bringing OMNI directly into the editor context.

docs/DEVELOPMENT.md

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# OMNI Development Guide 🛠
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# OMNI Development Guide
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Welcome to the Project OMNI development guide. This document outlines how to maintain the core engine and expand its semantic filtering capabilities.
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## 🏗 Architecture Overview
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## Architecture Overview
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OMNI consists of three main components:
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1. **Zig Core (Native CLI)**: A high-performance binary (`omni`) providing diagnostic and distillation subcommands.
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2. **Zig Core (Wasm)**: A portable version of the engine for MCP edge integration.
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3. **TypeScript Host**: The MCP gateway that orchestrates Wasm execution with an integrated LRU cache.
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## 🌈 Adding a New Filter
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## Adding a New Filter
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3. **Update Interface**: If the filter requires shared state, use the `ptr` field and cast it within your functions.
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## 🕸 WebAssembly Bridge
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## WebAssembly Bridge
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OMNI uses a custom-packed `u64` return to communicate between Zig and the JavaScript host.
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- **High 32 bits**: Length of the result.
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- **Low 32 bits**: Memory pointer (relative to Wasm memory).
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When modifying the `compress` export in `wasm.zig`, ensure that both memory and string encodings are correctly handled on the TypeScript side (`src/index.ts`).
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## 🧪 Testing
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## Testing
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Run native engine unit tests:
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```bash
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This will produce a small, optimized `.wasm` binary suitable for edge distribution.
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## 🚀 Official Release Workflow
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## Official Release Workflow
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This script will:
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- Update the version and SHA256 in `omni.rb`.
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- Fetch the new archive and update the checksum.
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- Fetch the new archive and update the thecksum.
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- Sync the changes to the `homebrew-omni` repository.
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3. **Manual Check**: Verify the release at [GitHub Releases](https://github.com/fajarhide/omni/releases).

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