Vision

Ch is a lightweight, fast, and powerful CLI tool for terminal-based AI interactions with full user control. As the successor to Cha, it provides direct terminal access to powerful AI models with minimal overhead, transparent operations, and explicit user control. It integrates seamlessly into developer environments, minimizing context switching and empowering users to leverage AI's full potential through flexible, user-driven interactions without automated decisions or hidden costs.

Installation

curl -fsSL https://raw.githubusercontent.com/MehmetMHY/ch/main/install.sh | bash

Demo

Features

Ch brings powerful AI capabilities directly to your terminal:

High Performance

10x faster startup than its predecessor Cha; built natively in Go for maximum efficiency.

Universal Platform Access

Connect to OpenAI, Anthropic, Gemini, Groq, and OpenRouter with seamless mid-chat switching.

Shell Native Integration

Built for the pipeline. Pipe command outputs directly to Ch, or use your preferred editor (Vim, Helix) for complex prompts.

Deep Context & Search

Load PDFs, Word docs, images (via OCR), or scrape URLs. Includes built-in Brave Search and YouTube analysis.

Advanced Context Gathering

Package entire directories for code analysis, or record terminal outputs from tools like Claude Code or Kiro.

Robust Session Management

Automatically persist sessions, backtrack through history, and search previous chats instantly using fzf-powered fuzzy matching.

Smart Model Intelligence

Real-time reasoning/thinking display, newest-first model sorting via API timestamps, and support for 22+ Amazon Bedrock regions.

Local-First & Private

Run models locally via Ollama. No API keys required, no data leaves your machine, and total transparency with zero "black box" decisions.

Pro Developer Workflow

Extract specific code blocks with proper extensions, get AI-suggested filenames during exports based on chat context, track token usage with model-aware counting, and copy responses to your cross-platform clipboard.

Documentation

For detailed usage and configuration, please refer to the GitHub repository or render the project's README below.

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