flux-cli-ai 0.1.8

A powerful agentic AI coding CLI built with Python and Rich TUI

Flux-CLI

An AI coding agent built from scratch — inspired by Claude Code CLI and Gemini CLI — featuring full multi-tool orchestration, streaming responses, sub-agent delegation, MCP server integration, dynamic lifecycle hooks, safety approval policies, and a styled Rich terminal UI with gradient ASCII branding.

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Project Aim

This project is a learning initiative designed to understand and implement core concepts behind intelligent coding agents:

• How AI agents reason about problems and select appropriate tools
• Multi-tool orchestration — deciding which tools to use and in what order
• Iterative refinement — analyzing code, identifying issues, and autonomously refactoring
• Streaming capabilities — real-time response generation and token consumption
• Lifecycle Hook System — shell-based event triggers (on_start, on_success, on_error, pre_tool_use, post_tool_use, on_compaction)
• Safety & Approval Policies — user confirmation for mutating operations (on-request, auto, yolo)
• Error handling & resilience — retry logic, exponential backoff, graceful degradation
• Context management — intelligent conversation history with automatic compression
• Extensible tool system — plugin architecture with built-in, sub-agent, and MCP tools

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Features & Architecture

1. LLM Client (AsyncOpenAI Integration)

• Async OpenAI client with lazy initialization
• Support for streaming and non-streaming responses
• Stream event architecture (StreamEvent, TextDelta, TokenUsage)
• Tool call streaming — incremental TOOL_CALL_START, TOOL_CALL_DELTA, TOOL_CALL_COMPLETE events
• Error handling with retry logic:
  • Rate limit handling with exponential backoff
  • Connection error recovery
  • API error catching and reporting
• Configurable API key via .env or system config
• Support for different LLM providers (OpenRouter, OpenAI, local models via configurable base URL)

2. Response & Agent Event System

• Event-driven architecture with AgentEvent and AgentEventType
• Lifecycle: AGENT_START -> TEXT_DELTA x N -> TOOL_CALL_START/COMPLETE x N -> TEXT_COMPLETE -> AGENT_END
• Error propagation through event system (AGENT_ERROR)
• Full agentic loop with multi-turn tool calling
• Maximum turns enforcement with graceful error reporting

3. Lifecycle Hook System

• Configurable event hooks via .flux-cli/config.toml
• 6 Trigger Points:
  • on_start: Triggered when an agent turn begins
  • on_success: Triggered when an agent successfully finishes
  • on_error: Triggered on exceptions, API failures, or tool execution errors
  • pre_tool_use: Triggered before a tool executes
  • post_tool_use: Triggered after a tool completes
  • on_compaction: Triggered when context compression occurs
• Environment Variable Context: Passes FLUX_HOOK_EVENT, FLUX_MODEL, FLUX_CWD, FLUX_TOOL_NAME, FLUX_TOOL_ARGS, FLUX_TOOL_SUCCESS, FLUX_TOOL_OUTPUT, FLUX_AGENT_RESPONSE to hook processes
• Cross-Platform Execution: Windows shlex.quote bash/cmd execution support with clean process tree cleanup (taskkill /F /T /PID)

4. Safety & Approval System

• Pydantic-validated ApprovalPolicy enum: ON_REQUEST, AUTO, YOLO
• Interactive confirmation modal for mutating operations (write_file, edit, shell)
• File diff preview inside approval requests

5. Session & Configuration Management

• Session class orchestrating client, tools, context, and MCP
• Multi-level TOML configuration loading: System Config -> Project Config -> CLI Overrides
• Auto-detection of AGENT.md files for custom developer instructions
• Persistent user memory across sessions stored in OS user data directory

6. Context & Compression Engine

• ContextManager with token tracking (via tiktoken)
• System prompt construction with identity, environment, tool guidelines, security
• Automatic context compression trigger at 80% of context window limit
• ChatCompactor child LLM summarization with structured continuation prompts
• Smart tool output pruning (protects recent outputs, prunes older ones)

7. Built-in Tools (11 Core Tools)

Tool	Kind	Description
read_file	READ	Read text files with line numbers, offset/limit, binary detection
write_file	WRITE	Create/overwrite files with automatic parent directory creation
edit	WRITE	Precise surgical text replacement with uniqueness checks
shell	SHELL	Command execution with timeout, blocked command safety, environment control
list_dir	READ	Directory listing with hidden file toggle
grep	READ	Regex search across files with case-insensitive option
glob	READ	File pattern matching with recursive ** support
web_search	NETWORK	DuckDuckGo web search integration
web_fetch	NETWORK	HTTP fetch with automatic fallback to proxy on 403/5xx
todos	MEMORY	Session-scoped task tracking (add/complete/list/clear)
memory	MEMORY	Persistent user memory stored across sessions

8. Sub-Agents & MCP Protocol

• SubAgentTool: Spawns isolated child agents (codebase_investigator, code_reviewer)
• MCPManager: Model Context Protocol integration with stdio and SSE transport support

9. Styled Terminal UI (TUI)

• Multi-stop color gradient horizontal ASCII logo renderer (#e7aafb -> #a191f8 -> #8bcefc -> #7fe4eb)
• Windows UTF-8 reconfigure and VT100/ANSI legacy rendering support
• Rich theme styling (AGENT_THEME) with custom tool panels, status indicators, syntax highlighting (dracula), and diff rendering
• Interactive slash command dashboards (/help, /config, /model, /approval, /stats, /tools, /mcp, /clear, /exit)

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Project Structure

flux/
├── main.py                      # CLI entry point, Click commands, interactive REPL loop
├── agent/
│   ├── agent.py                # Agent orchestrator with multi-turn agentic loop & hook triggers
│   ├── events.py               # AgentEvent & AgentEventType definitions
│   └── session.py              # Session lifecycle (Client, Registry, Context, MCP, Hooks)
├── client/
│   ├── llm_client.py           # AsyncOpenAI client wrapper with streaming & retries
│   └── response.py             # StreamEvent, TextDelta, TokenUsage, ToolCall models
├── config/
│   ├── config.py               # Pydantic Config, ModelConfig, HookConfig, MCPServerConfig
│   └── loader.py               # Multi-level TOML loader & AGENT.md detection
├── context/
│   ├── compaction.py           # ChatCompactor context summarization engine
│   └── manager.py              # ContextManager history, token tracking, tool pruning
├── hooks/
│   ├── hook_system.py          # Cross-platform process execution & environment builder
│   └── manager.py              # HookManager event router
├── prompts/
│   └── system.py               # Dynamic system prompt builder
├── safety/
│   └── policy.py               # ApprovalPolicy enum (on-request, auto, yolo)
├── tools/
│   ├── base.py                 # Tools ABC, ToolInvocation, ToolResult, FileDiff, ToolKind
│   ├── registry.py             # ToolRegistry with built-in & MCP lookup
│   ├── discovery.py            # Custom tool discovery from .flux-cli/tools/
│   ├── subagent.py             # SubAgentTool & pre-defined sub-agents
│   ├── builtin/                # Core built-in tools (read, write, edit, shell, grep, glob, etc.)
│   └── mcp/                    # MCP client & tool adapters
├── ui/
│   └── tui.py                  # Rich TUI, gradient banner, tool panels, command dashboards
├── utils/
│   ├── errors.py               # AgentError, ConfigError
│   ├── paths.py                # Path resolution & binary file detection
│   └── text.py                 # Token counting (tiktoken) & text truncation
├── pyproject.toml              # PyPI package manifest & executable entry points
├── requirements.txt            # Project dependencies
├── ARCHITECTURE.md             # Detailed technical architecture guide
└── README.md

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Setup & Usage

Prerequisites

• Python 3.10+
• OpenRouter API key (or any OpenAI-compatible provider)

Installation (Local Development)

# Clone the repository
git clone https://github.com/manmit-s/flux-cli.git
cd flux-cli

# Create and activate virtual environment
python -m venv .venv

# On Windows:
.venv\Scripts\activate
# On macOS/Linux:
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt

Installing via Pip / Pipx (When Published)

# Recommended for CLI tools:
pipx install flux-cli-ai

# Or via standard pip:
pip install flux-cli-ai

# Launch directly from anywhere in your terminal:
flux

Configuration

Create a .env file in your workspace:

API_KEY=your_api_key_here
BASE_URL=https://openrouter.ai/api/v1  # Optional, default for OpenRouter

Or configure your global settings at ~/.config/flux-cli/config.toml (macOS/Linux) or %APPDATA%\flux-cli\config.toml (Windows):

[model]
name = "nvidia/nemotron-3-super-120b-a12b"
temperature = 0.7
context_window = 128000

max_turns = 50

[approval]
policy = "on-request"

[hooks]
enabled = true
on_start = "echo 'Agent starting...'"
on_error = "echo 'Agent encountered an error'"

[shell_environment]
exclude_patterns = ["*KEY", "*TOKEN", "*SECRET"]

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Interactive Slash Commands

While in interactive mode (flux), you can run:

Command	Action
/help	Show interactive help dashboard
/config	Show current active configuration
/model <name>	Switch LLM model at runtime
/approval <mode>	Change safety approval policy (on-request, auto, yolo)
/stats	View session token usage & turn metrics
/tools	List all registered built-in and MCP tools
/mcp	View MCP server connections
/clear	Clear active conversation history
/exit or /quit	Exit the CLI session

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Credits & Acknowledgments

Inspired by and learning from:

• Rivaan Ranawat — Educator and open-source agent innovator
• Claude Code CLI & Gemini CLI — Design aesthetics & agent orchestration inspiration