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Aizen AI Agent — A professional-grade AI coding assistant for your terminal.

Project description

Aizen AI Agent 🚀

CI

A professional-grade AI coding assistant that runs directly in your terminal. Aizen reads your code, writes files with surgical precision, runs commands safely, and helps you build faster — all from a beautifully designed CLI.

✨ Features

Core

  • Asynchronous Architecture — Fully asynchronous operations leveraging asyncio and AsyncOpenAI for concurrent processing, parallel tool runs, and streaming.
  • Rich Markdown Rendering — AI responses are rendered with full Markdown formatting (headers, code blocks, lists, bold/italic) via Rich's live display.
  • Streaming with Live Preview — Watch responses render in real-time inside a styled panel with an animated thinking spinner.
  • Surgical File Editing — The edit_file tool makes precise search-and-replace edits with color-coded diff previews, instead of rewriting entire files.
  • SQLite Session Persistence — Session storage is powered by a SQLite database (~/.aizen_sessions/aizen.db), auto-migrating older JSON sessions.
  • Project-Specific Rules — Customizes agent behavior per repository by auto-loading .aizen_rules or .cursorrules from the current working directory.
  • Smart Autocomplete@-mention files with Tab completion that respects .gitignore and supports directory traversal.

Tools

Aizen has 9 built-in tools the AI can use:

Tool Description
read_file Read file contents before making changes
write_file Create new files (with preview)
edit_file Surgical search-and-replace on existing files (with diff preview)
run_command Execute shell commands (supports background execution; safe commands auto-run, dangerous ones require approval)
check_background_task Check the status and read recent output of a command running in the background
kill_background_task Kill a running background task
list_directory List files/folders with sizes, respecting .gitignore
grep_search Search for text or regex patterns across the codebase
find_files Find files by glob pattern (e.g., *.py, Dockerfile)

Commands

Command Description
/help Show all available commands
/model [name] View or switch the active AI model (saves as default)
/clear Clear conversation history
/drop Drop attached files/URLs/commands from history to save tokens
/save [name] Save current conversation to SQLite database
/load [name] Load a previously saved conversation
/checkpoint [name] Save a conversation snapshot to memory
/restore [name] Restore a saved conversation checkpoint
/usage Show token usage, estimated session cost (USD), and statistics
/commit Auto-generate a commit message for staged/unstaged changes and commit them
/diff Show all uncommitted changes (staged, unstaged, untracked)
/compact Summarize older messages using AI (fallback to text-summarization) to save tokens
/undo Undo the last file modification
/retry Retry the last message
/copy Copy last AI response to clipboard
/export [file] Export conversation to a Markdown file
/config View current configuration
/mcp View configured MCP servers and their connection status

Safety & UX

  • Command Safety — Read-only commands (ls, cat, git status, etc.) auto-execute. Destructive commands (rm, sudo, etc.) always require confirmation.
  • --yolo Mode — Auto-approve all operations for power users.
  • Background Tasks — Run builds, tests, or other long-running tasks asynchronously while continuing to interact with Aizen.
  • File Backups — Every file modification creates a backup. Use /undo to restore.
  • Multi-line Input — End a line with \ to continue on the next line.
  • Session Persistence — Conversations auto-save on exit to SQLite. Use /save and /load to manage.
  • Cost Tracking & Token Usage — Live tracking of input/output tokens, session duration, and estimated session cost in USD.
  • Structured Logging — Rotated file logging at ~/.aizen_logs/aizen.log plus verbose console debugging logs via --verbose.
  • Graceful Error Recovery — Helpful hints for common API errors (invalid key, rate limits, timeouts).

Dependencies

  • openai — OpenAI-compatible API client
  • python-dotenv — Environment variable management
  • rich — Rich text, Markdown rendering, panels, tables, and live display
  • prompt_toolkit — Interactive command line with autocomplete

Installation

1. Python (pip / pipx) — Recommended

pipx install aizen-ai-cli
# Or:
pip install aizen-ai-cli

2. NPM (Node.js)

npm install -g aizen-ai-cli

3. Homebrew (macOS)

brew tap irtaza302/aizen
brew install aizen

4. Local Development

git clone https://github.com/irtaza302/aizen-agent.git
cd aizen-agent
pip install -r requirements.txt
python aizen.py

Usage

aizen

On first launch, you'll be prompted for your OpenRouter API key. It's saved securely to ~/.aizen_config.json.

Command Line Arguments

Flag Description
--version Show version
--model <name> Override the default model for this session
--reset-key Clear and re-enter your API key
--set-base-url <url> Set custom API base URL (e.g., http://localhost:11434/v1 for Ollama)
--yolo Auto-approve all file writes and command executions
--verbose Enable verbose logging output to the console

Attaching Context (@)

Type @ followed by a filename, directory, web URL, or command to give Aizen context. Autocomplete filters out .gitignored files:

  • Files: @aizen.py attaches the file contents.
  • Directories: @tests/ generates and attaches a visual directory tree respecting .gitignore.
  • URLs: @https://docs.python.org/... fetches the webpage, converts it to markdown, and attaches it.
  • Commands: @cmd:"pytest" or @cmd:ls securely runs the command in the background and injects its stdout and stderr directly into the prompt.
👤 You
❯ Can you refactor @aizen.py to use async?

👤 You
❯ Explain this output: @cmd:"npm run build"

Multi-line Input

End a line with \ to continue typing on the next line:

👤 You
❯ Write a function that \
⋮  takes a list of numbers \
⋮  and returns the sorted unique values

Configuration

Aizen stores its config in ~/.aizen_config.json:

{
  "OPENROUTER_API_KEY": "sk-or-...",
  "API_BASE_URL": "https://openrouter.ai/api/v1",
  "DEFAULT_MODEL": "anthropic/claude-sonnet-4"
}

Model Context Protocol (MCP) Support

Aizen supports integrating with external Model Context Protocol (MCP) servers to extend its capabilities (e.g. connecting to local databases, searching the web, or accessing custom APIs).

To configure MCP servers, add an "mcp_servers" block to your ~/.aizen_config.json:

{
  "mcp_servers": {
    "sqlite": {
      "command": "uvx",
      "args": ["mcp-server-sqlite", "--db-path", "~/test.db"]
    },
    "everything": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-everything"]
    }
  }
}

When you start Aizen, it will automatically connect to these servers and make their tools available to the AI.

Sessions are saved in a SQLite database at ~/.aizen_sessions/aizen.db, and file backups are placed in ~/.aizen_backups/.

📂 Project-Specific Rules

Aizen supports loading custom, project-specific rules files (such as .aizen_rules or .cursorrules) from the root of your project directory. When Aizen starts, it checks for these files in the current working directory in the following order:

  1. .aizen_rules
  2. .cursorrules

If one is found, Aizen automatically appends its contents to the system prompt. This allows you to enforce codebase-specific styling guidelines, coding standards, or project rules without editing Aizen's global configuration.

🔄 Background Task Management

For long-running processes (e.g., running test suites, starting local dev servers, or building bundles), you can run commands in the background asynchronously:

  • Aizen's run_command tool supports a boolean background parameter. If set to true, the tool immediately returns a unique task_id (e.g., bg_a1b2c3d4).
  • You can inspect the status and read the recent stdout/stderr output of a background task using the check_background_task tool.
  • You can terminate any active background task using the kill_background_task tool.

This allows you to continue discussing other topics or refactoring files with Aizen while your tests or builds run in parallel.

💰 Cost Tracking

Aizen dynamically estimates session costs in USD for known models based on token usage:

  • Input and output tokens are tracked in real-time.
  • The estimated session cost is displayed in the CLI status bar and summary tables (via the /usage command).
  • The cost calculations support popular models from Anthropic (Claude 3.5/3.7 Sonnet, Opus, Haiku), Google (Gemini 2.5 Pro/Flash), and OpenAI (GPT-4o, o1, o3-mini).

📌 Session Checkpoints & Restoring

You can save and restore conversation snapshots at any point during your session:

  • /checkpoint [name]: Save the current conversation messages history as a named snapshot in memory.
  • /restore [name]: Revert the conversation history to the specified checkpoint. If run without a name, it lists all currently active checkpoints.

This is extremely useful when experimenting with different implementation approaches or when recovering from an unintended direction.

📝 Structured Logging

All internal activities, tool calls, and API events are written to a rotating file logger:

  • Logs are located at ~/.aizen_logs/aizen.log.
  • Up to three rotated log files are kept (5 MB per file limit).
  • You can run Aizen with the --verbose flag to mirror log output directly to the console stderr stream.

Publishing & Development

Use the included publish.sh script to build and publish across all platforms (PyPI, NPM, and PyInstaller binaries).

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