A model-agnostic AI coding assistant with a high-performance C++ engine and a Python-powered LLM brain. Right in your terminal.
Powered by LiteLLM. Hot-swap models on the fly without changing a single line of logic. Use Google Gemini, OpenAI, Anthropic Claude, Llama, DeepSeek, or run completely private local models via Ollama.
Active directory scanning with safe file boundary traversal. Navigate, find keywords, grep, and locate code symbols instantly.
Tracks full session conversations in JSONL. Automatically compacts long discussions when context windows exceed limits, preserving key data.
A native C++20 engine running under the Python shell via pybind11 bindings. Ensures lightning-fast system calls, secure boundary validation pipelines, and system checks in milliseconds.
CLIQ Code splits its responsibilities between a developer-friendly Python shell and a locked-down, high-performance C++ engine, linked via pybind11. Click on components to examine source file mappings.
Developer inputs natural queries. Outputs markdown-styled git diff previews and confirmation prompts.
LiteLLM brain routes prompts to Gemini/GPT/Claude. Manages REPL loops, interactive user input, and safety caches.
Compiles C++ bindings natively into Python modules, offering zero-cost conversion overlays for system parameters.
17 modules governing permission policies, Docker detection, bash command validators, context compaction, and JSONL logging.
The core engine handles physical operations. Compiling to native binary guarantees memory boundaries, lightning-fast regex traversing for grep commands, and strict permission sandboxing.
../)Safety is paramount when giving AI agents console access. Select a permission level below to check how the C++ Engine intercepts and restricts operations in real time.
Enables read-write permissions, but only within the initialized project boundaries.
Requests modifying files outside active workspace are filtered and rejected. Execution of destructive bash triggers safety catch.
Launch CLIQ Code in less than 2 minutes. Install Python prerequisites, set your AI environment keys, and run the agent script directly.
Download the standalone binary directly. Move it to an installation folder (e.g. C:\Program Files\cliq-code) and append that directory path to your system's PATH environment variable.
# Windows (PowerShell - permanent user profile setting):
[System.Environment]::SetEnvironmentVariable("GEMINI_API_KEY", "your-api-key-here", "User")
# macOS/Linux (Bash - append to ~/.bashrc):
export GEMINI_API_KEY="your-api-key-here"cliq-code