ngpt 2.2.0

A lightweight Python CLI and library for interacting with OpenAI-compatible APIs, supporting both official and self-hosted LLM endpoints.

nGPT

A lightweight Python CLI and library for interacting with OpenAI-compatible APIs, supporting both official and self-hosted LLM endpoints.

Table of Contents

• Quick Start
• Features
• Documentation
• Installation
• Usage
  • Documentation
  • CLI Tool
  • Python Library
• Configuration
  • Command Line Options
  • Interactive Configuration
  • Configuration File
  • Configuration Priority
• Contributing
• License

Quick Start

# Install
pip install ngpt

# Chat with default settings
ngpt "Tell me about quantum computing"

# Start an interactive chat session with conversation memory
ngpt -i

# Return response without streaming
ngpt -n "Tell me about quantum computing"

# Generate code
ngpt --code "function to calculate the Fibonacci sequence"

# Generate and execute shell commands
ngpt --shell "list all files in the current directory"

# Use multiline editor for complex prompts
ngpt --text

Features

• ✅ Dual Mode: Use as a CLI tool or import as a Python library
• 🪶 Lightweight: Minimal dependencies (just requests)
• 🔄 API Flexibility: Works with OpenAI, Ollama, Groq, and any compatible endpoint
• 💬 Interactive Chat: Continuous conversation with memory in modern UI
• 📊 Streaming Responses: Real-time output for better user experience
• 🔍 Web Search: Integrated with compatible API endpoints
• ⚙️ Multiple Configurations: Cross-platform config system supporting different profiles
• 💻 Shell Command Generation: OS-aware command execution
• 🧩 Clean Code Generation: Output code without markdown or explanations
• 📝 Rich Multiline Editor: Interactive multiline text input with syntax highlighting and intuitive controls

Documentation

Comprehensive documentation, including API reference, usage guides, and examples, is available at:

https://nazdridoy.github.io/ngpt/

Installation

pip install ngpt

Requires Python 3.8 or newer.

Usage

As a CLI Tool

# Basic chat (default mode)
ngpt "Hello, how are you?"

# Interactive chat session with conversation history
ngpt -i

# Show version information
ngpt -v

# Show active configuration
ngpt --show-config

# Show all configurations
ngpt --show-config --all

# List available models for the active configuration
ngpt --list-models

# List models for a specific configuration
ngpt --list-models --config-index 1

# With custom options
ngpt --api-key your-key --base-url http://your-endpoint --model your-model "Hello"

# Enable web search (if your API endpoint supports it)
ngpt --web-search "What's the latest news about AI?"

# Generate and execute shell commands (using -s or --shell flag)
# OS-aware: generates appropriate commands for Windows, macOS, or Linux
ngpt -s "list all files in current directory"
# On Windows generates: dir
# On Linux/macOS generates: ls -la

# Generate clean code (using -c or --code flag)
# Returns only code without markdown formatting or explanations
ngpt -c "create a python function that calculates fibonacci numbers"

# Use multiline text editor for complex prompts (using -t or --text flag)
# Opens an interactive editor with syntax highlighting and intuitive controls
ngpt -t

As a Library

from ngpt import NGPTClient, load_config

# Load the first configuration (index 0) from config file
config = load_config(config_index=0)

# Initialize the client with config
client = NGPTClient(**config)

# Or initialize with custom parameters
client = NGPTClient(
    api_key="your-key",
    base_url="http://your-endpoint",
    provider="openai",
    model="o3-mini"
)

# Chat
response = client.chat("Hello, how are you?")

# Chat with web search (if your API endpoint supports it)
response = client.chat("What's the latest news about AI?", web_search=True)

# Generate shell command
command = client.generate_shell_command("list all files")

# Generate code
code = client.generate_code("create a python function that calculates fibonacci numbers")

Advanced Library Usage

# Stream responses
for chunk in client.chat("Write a poem about Python", stream=True):
    print(chunk, end="", flush=True)

# Customize system prompt
response = client.chat(
    "Explain quantum computing",
    system_prompt="You are a quantum physics professor. Explain complex concepts simply."
)

# OS-aware shell commands
# Automatically generates appropriate commands for the current OS
command = client.generate_shell_command("find large files")
import subprocess
result = subprocess.run(command, shell=True, capture_output=True, text=True)
print(result.stdout)

# Clean code generation
# Returns only code without markdown or explanations
code = client.generate_code("function that converts Celsius to Fahrenheit")
print(code)

Configuration

Command Line Options

You can configure the client using the following options:

Option	Description
--api-key	API key for the service
--base-url	Base URL for the API
--model	Model to use
--list-models	List all available models for the selected configuration (can be combined with --config-index)
--web-search	Enable web search capability
-n, --no-stream	Return the whole response without streaming
--temperature	Set temperature (controls randomness, default: 0.7)
--top_p	Set top_p (controls diversity, default: 1.0)
--max_length	Set maximum response length in tokens
--config	Path to a custom configuration file or, when used without a value, enters interactive configuration mode
--config-index	Index of the configuration to use (default: 0)
--remove	Remove the configuration at the specified index (requires --config and --config-index)
--show-config	Show configuration details and exit
--all	Used with --show-config to display all configurations
-i, --interactive	Start an interactive chat session with stylish UI, conversation history, and special commands
-s, --shell	Generate and execute shell commands
-c, --code	Generate clean code output
-t, --text	Open interactive multiline editor for complex prompts
-v, --version	Show version information

Interactive Configuration

The --config option without arguments enters interactive configuration mode, allowing you to add or edit configurations:

# Add a new configuration
ngpt --config

# Edit an existing configuration at index 1
ngpt --config --config-index 1

# Remove a configuration at index 2
ngpt --config --remove --config-index 2

In interactive mode:

• When editing an existing configuration, press Enter to keep the current values
• When creating a new configuration, press Enter to use default values
• For security, your API key is not displayed when editing configurations
• When removing a configuration, you'll be asked to confirm before deletion

Configuration File

nGPT uses a configuration file stored in the standard user config directory for your operating system:

• Linux: ~/.config/ngpt/ngpt.conf or $XDG_CONFIG_HOME/ngpt/ngpt.conf
• macOS: ~/Library/Application Support/ngpt/ngpt.conf
• Windows: %APPDATA%\ngpt\ngpt.conf

The configuration file uses a JSON list format, allowing you to store multiple configurations. You can select which configuration to use with the --config-index argument (or by default, index 0 is used).

Multiple Configurations Example (ngpt.conf)

[
  {
    "api_key": "your-openai-api-key-here",
    "base_url": "https://api.openai.com/v1/",
    "provider": "OpenAI",
    "model": "gpt-4o"
  },
  {
    "api_key": "your-groq-api-key-here",
    "base_url": "https://api.groq.com/openai/v1/",
    "provider": "Groq",
    "model": "llama3-70b-8192"
  },
  {
    "api_key": "your-ollama-key-if-needed",
    "base_url": "http://localhost:11434/v1/",
    "provider": "Ollama-Local",
    "model": "llama3"
  }
]

Configuration Priority

nGPT determines configuration values in the following order (highest priority first):

1. Command line arguments (--api-key, --base-url, --model)
2. Environment variables (OPENAI_API_KEY, OPENAI_BASE_URL, OPENAI_MODEL)
3. Configuration file (selected by --config-index, defaults to index 0)
4. Default values

Contributing

We welcome contributions to nGPT! Whether it's bug fixes, feature additions, or documentation improvements, your help is appreciated.

To contribute:

1. Fork the repository
2. Create a feature branch: git checkout -b feature/your-feature-name
3. Make your changes
4. Commit with clear messages following conventional commit guidelines
5. Push to your fork and submit a pull request

Please check the CONTRIBUTING.md file for detailed guidelines on code style, pull request process, and development setup.

License

This project is licensed under the MIT License. See the LICENSE file for details.