eino-cli

English

Eino CLI is an intelligent AI Agent command-line tool based on the CloudWeGo Eino framework. It provides a powerful Agent system with support for multiple tool integrations and various AI model providers, enabling you to easily build and run custom AI Agents.

Features

• Intelligent Agent System: AI Agent based on ReAct pattern with tool calling and reasoning capabilities
• Interactive Chat Interface: TUI-based chat interface for real-time conversations with AI models and agents
• Rich Tool Ecosystem: Built-in various tools including search, browser, command line, HTTP requests, etc.
• Multi-Model Provider Support: Supports OpenAI, Claude, Gemini, Qwen, DeepSeek, Ollama, Baidu Qianfan, ByteDance Doubao, and more
• Flexible Configuration System: Manage Agents, tools, models, and chat presets through YAML configuration files
• Custom Tool Support: Supports custom HTTP and command-line tools
• MCP Server Integration: Supports Model Context Protocol (MCP) servers with both SSE and STDIO transport
• Langfuse Integration: Built-in observability with Langfuse for monitoring and tracing

Installation

Install from Source

git clone https://github.com/tk103331/eino-cli.git
cd eino-cli
go install

Usage

1. Configuration File

First, copy the configuration template and modify it as needed:

cp config.yml.example config.yml

The configuration file contains the following main sections:

• providers: AI model provider configuration (API keys, base URLs, etc.)
• models: Model configuration (temperature, max tokens, etc.)
• agents: Agent configuration (system prompts, models and tools to use)
• chats: Chat preset configuration for interactive chat mode
• tools: Tool configuration (parameters and settings for custom tools)
• mcp_servers: MCP server configuration
• settings: Global settings including Langfuse configuration

2. Interactive Agent/Chat Mode

Start an interactive session with an agent or model:

# Start an interactive agent session
eino-cli agent --agent search_agent

# Chat with a specific model
eino-cli agent --model gpt4

# Chat with tools
eino-cli agent --model gpt4 --tools duckduckgo_search,wikipedia_search

# Use a chat preset
eino-cli agent --chat search_chat

Parameter description:

• --agent, -a: Specify the agent name to run (optional)
• --chat, -c: Specify a chat preset name from configuration file (optional)
• --model, -m: Specify the model to chat with (required when not using --agent or --chat)
• --tools, -t: Specify available tools, separated by commas (optional when using --model directly)

3. Running an Agent

Use the run command to run a specified Agent:

eino-cli run --agent test_agent --prompt "Hello, please help me search for today's weather"

Parameter description:

• --agent, -a: Specify the Agent name to run (required)
• --prompt, -p: Specify the input prompt for the Agent (required)
• --config: Specify the configuration file path (optional, defaults to ~/.eino-cli/config.yml)

4. Configuration Example

Here's a complete configuration example:

# Model provider configuration
providers:
  openai:
    type: openai
    base_url: https://api.openai.com/v1
    api_key: sk-xxxxx
  claude:
    type: claude
    api_key: sk-ant-xxxxx

# Model configuration
models:
  gpt4:
    provider: openai
    model: gpt-4
    max_tokens: 4096
    temperature: 0.7
  claude_sonnet:
    provider: claude
    model: claude-3-5-sonnet-20241022
    max_tokens: 4096
    temperature: 0.7

# Chat preset configuration
chats:
  search_chat:
    model: gpt4
    system: "You are a helpful search assistant. Use search tools to find information for users."
    tools:
      - duckduckgo_search
      - wikipedia_search
  coding_chat:
    model: claude_sonnet
    system: "You are an expert programmer helping with coding tasks."
    tools:
      - commandline
      - http_request

# MCP server configuration
mcp_servers:
  # SSE type MCP server
  sse_server:
    type: mcp
    config:
      url: "http://localhost:3000/mcp"  # MCP server URL
      headers:
        "Content-Type": "application/json"
        "Authorization": "Bearer your-token"  # Optional authentication header
  # STDIO type MCP server
  stdio_server:
    type: stdio
    config:
      cmd: "python"                    # Command to execute
      args:
        - "-m"
        - "your_mcp_server"             # MCP server module
      env:
        "PYTHONPATH": "/path/to/server" # Environment variables
        "API_KEY": "your-api-key"

# Agent configuration
agents:
  search_agent:
    system: "You are a search assistant that can help users search for information"
    model: gpt4
    tools:
      - duckduckgo_search
      - wikipedia_search
    mcp_servers:                        # MCP servers that the Agent can use
      - sse_server
  # Multi-functional assistant example (including custom tools and MCP servers)
  multi_agent:
    system: "You are a multi-functional assistant that can search information, query weather, get system information, etc."
    model: gpt4
    tools:
      - duckduckgo_search
      - weather_api
      - system_info
    mcp_servers:
      - sse_server
      - stdio_server

# Tool configuration
tools:
  duckduckgo_search:
    type: duckduckgo
    config:
      max_results: 10        # Maximum number of search results, default 10
      region: "wt"           # Search region: wt(global), cn(China), us(USA), uk(UK)
      safe_search: "off"     # Safe search: off(disabled), moderate(moderate), strict(strict)
      timeout: 10            # Timeout in seconds, default 10 seconds
  # Custom HTTP tool example
  weather_api:
    type: customhttp
    description: "API tool for getting weather information"
    config:
      url: "https://api.openweathermap.org/data/2.5/weather?q={{city}}"
      method: "GET"
      headers:
        "Content-Type": "application/json"
    params:
      - name: "city"
        type: "string"
        description: "City name"
        required: true
  # Custom command-line tool example
  system_info:
    type: customexec
    description: "Get system information"
    config:
      cmd: "uname -a && df -h"
      dir: "/tmp"
      timeout: 30
    params: []

# Global settings
settings:
  langfuse:
    host: https://cloud.langfuse.com
    public_key: pk-xxx
    secret_key: sk-xxx

Supported Tools

Eino CLI comes with various built-in tools that can be used in Agents:

Search Tools

• DuckDuckGo: Web search
• Google Search: Google search (requires API key)
• Bing Search: Bing search (requires API key)
• Wikipedia: Wikipedia search

Browser Tools

• Browser Use: Browser automation tool

System Tools

• Command Line: Execute system commands
• HTTP Request: Send HTTP requests
• Sequential Thinking: Sequential thinking tool

Custom Tools

• Custom HTTP: Custom HTTP tools
• Custom Exec: Custom command execution tools

Supported Model Providers

• OpenAI: GPT-3.5, GPT-4 series
• Anthropic Claude: Claude 3 series
• Google Gemini: Gemini Pro series
• Alibaba Qwen: Qwen series
• DeepSeek: DeepSeek series
• ByteDance Doubao: Through Ark API
• Baidu Qianfan: ERNIE and others
• Ollama: Local model deployment

Main Dependencies

• CloudWeGo Eino - AI application development framework
• Cobra - Command-line interface framework
• Bubble Tea - TUI framework for interactive chat
• Various Eino extension components (models and tools)

License

MIT