wyn360-cli 0.3.58

WYN360 - An intelligent AI coding assistant CLI tool powered by Anthropic Claude

WYN360 CLI

An intelligent AI coding assistant CLI tool powered by Anthropic Claude.

GitHub Repository: https://github.com/yiqiao-yin/wyn360-cli

🎯 Overview

WYN360 CLI is an AI-powered coding assistant that helps you build projects, generate code, and improve your codebase through natural language conversations. Built with pydantic-ai and Anthropic Claude, it provides intelligent file operations, command execution, and context-aware assistance.

🏗️ System Architecture

For a detailed architecture overview including all components, layers, and data flows, see SYSTEM.md.

📦 Installation

Basic Installation

pip install wyn360-cli

Optional: Enable Browser Use (Direct Website Fetching)

If you want to use the fetch_website feature to read specific URLs directly:

# Install Playwright browser binaries (one-time setup, ~200MB)
playwright install chromium

Note: Browser use is optional. Web search and all other features work without it. Only install if you need direct URL fetching (e.g., "Read https://github.com/user/repo").

🚀 Quick Start

1. Set up your Anthropic API key (choose one method):

Option 1: Environment variable

export CLAUDE_CODE_USE_BEDROCK=0
export ANTHROPIC_API_KEY=your_key_here
export ANTHROPIC_MODEL=claude-sonnet-4-5-20250929

This option assumes you want to use Anthropic API Key and available models can be referenced from Claude Model Overview.

Option 2: .env file (recommended for local development)

# Create a .env file in your project directory
echo "ANTHROPIC_API_KEY=your_key_here" > .env

Option 3: Command-line argument

wyn360 --api-key your_key_here

Option 4: Use AWS Bedrock Credentials

export CLAUDE_CODE_USE_BEDROCK=1
export AWS_ACCESS_KEY_ID="your_access_key"
export AWS_SECRET_ACCESS_KEY="your_secret_key"
export AWS_SESSION_TOKEN="your_session_token"
export AWS_REGION=us-west-2
export ANTHROPIC_MODEL=us.anthropic.claude-sonnet-4-20250514-v1:0

This option assumes you want to use AWS Bedrock credentials which means you need a valid AWS account with access key, secret access key and session token. Additionally, this option assumes you have Bedrock access and the model is available for you.

2. Run the CLI:

wyn360

3. Start chatting:

You: Build a Streamlit app for data visualization

WYN360: I'll create a Streamlit app for you...
[Generates complete code and saves to app.py]

✨ Features

Core Capabilities

• 🤖 Interactive AI Assistant - Natural language conversations with Claude
• 📝 Code Generation - Generate production-ready Python code from descriptions
• 🔍 Project Analysis - Understand and improve existing codebases
• 📁 Smart File Operations - Context-aware file creation and updates
• ⚡ Command Execution - Run Python scripts, UV commands, shell scripts, any CLI tool
• ⌨️ Multi-line Input - Press Enter to submit, Shift+Enter for newline
• 🔒 Safety First - Confirmation prompts before executing commands

Intelligent Features (v0.2.x)

• 🧠 Intent Recognition - Understands "update" vs "create new" from natural language
• 🔄 Context-Aware Updates - Reads files before modifying them
• 🔁 Self-Correcting - Smart retry mechanism with 3 attempts
• ⏱️ Timeout Protection - Prevents infinite loops (5 min default)
• 📊 Comprehensive Output - Captures stdout, stderr, and exit codes

Context Management (v0.2.8)

• 💬 Conversation History - Maintains context across multiple interactions
• 📊 Token Tracking - Real-time monitoring of API usage and costs
• 💾 Session Save/Load - Preserve conversations for later continuation
• 🎯 Slash Commands - Quick access to history, stats, and session management

Model Selection & Optimization (v0.3.0)

• 🔄 Dynamic Model Switching - Switch between Haiku, Sonnet, and Opus mid-session
• 💰 Cost Optimization - Choose the right model for your task complexity
• 📊 Model Information - View current model, pricing, and capabilities
• ⚡ Flexible Performance - Balance between speed, capability, and cost

Configuration & Personalization (v0.3.1)

• ⚙️ User Configuration - Personal preferences via ~/.wyn360/config.yaml
• 📁 Project Configuration - Project-specific settings via .wyn360.yaml
• 🎯 Custom Instructions - Add your coding standards to every conversation
• 🏗️ Project Context - Help AI understand your tech stack automatically

Streaming Responses (v0.3.2)

• ⚡ Real-Time Output - See responses as they're generated, token-by-token
• 🎯 Immediate Feedback - Start reading while AI is still generating
• 📺 Progress Visibility - Watch code and explanations appear in real-time
• 💨 Faster Perceived Speed - Feels 2-3x faster with instant feedback

HuggingFace Integration (v0.3.3 - v0.3.13)

• 🤗 HuggingFace Authentication - Auto-login with HF_TOKEN environment variable
• 📝 README Generation - Create professional README files for Spaces
• 🚀 Space Creation - Create Streamlit/Gradio Spaces directly from CLI
• 📤 File Upload - Push your code to HuggingFace Spaces automatically
• 🎯 One-Command Deploy - From code to live Space in seconds

Automatic Test Generation (v0.3.18)

• 🧪 Test Generation - Automatically generate pytest tests for Python files
• 📊 Smart Analysis - Analyzes functions and classes to create comprehensive tests
• ⚡ Quick Setup - Creates test files with proper structure and imports
• 🎯 Code Coverage - Generates tests for edge cases and error handling

GitHub Integration (v0.3.22)

• 🔐 GitHub Authentication - Auto-login with GH_TOKEN/GITHUB_TOKEN
• 💾 Commit & Push - Stage, commit, and push changes with one command
• 🔀 Pull Requests - Create PRs with generated descriptions
• 🌿 Branch Management - Create, checkout, and merge branches seamlessly
• 🔄 Merge Operations - Smart branch merging with conflict detection

Web Search (v0.3.21, Enhanced v0.3.23)

• 🔍 Real-Time Search - Access current information from the web
• 🌦️ Weather Queries - Get current weather for any location
• 🔗 URL Reading - Fetch and summarize web page content
• 📚 Resource Finding - Find GitHub repos, libraries, and tutorials
• 📊 Current Data - Latest package versions, documentation, and trends
• 💰 Cost Effective - Limited to 5 searches per session, $10 per 1K searches

Browser Use / Direct Website Fetching (v0.3.24)

• 🌐 Direct URL Fetching - Fetch specific websites directly (not just search results)
• 📄 Full DOM Extraction - Get complete page content, not just search snippets
• 🧠 LLM-Optimized - Automatic conversion to clean, structured markdown
• ⚡ Smart Caching - 30-minute TTL cache for faster repeated access
• 📏 Smart Truncation - Preserves document structure while staying under token limits
• 🎯 Configurable - Adjust max tokens, cache settings, truncation strategy
• 💾 Cache Management - View stats, clear cache, manage storage

Vision Mode for Document Images (v0.3.30)

• 🖼️ Image Processing - Intelligently describe images in Word and PDF documents
• 📊 Chart Recognition - Extract insights from charts, graphs, and data visualizations
• 📐 Diagram Understanding - Analyze flowcharts, architecture diagrams, and technical illustrations
• 🖥️ Screenshot Analysis - Understand UI mockups and interface screenshots
• 💰 Cost Transparency - Separate tracking of vision API costs vs. text processing
• 🎯 Three Processing Modes - skip (default), describe (alt text only), vision (full AI processing)
• ⚡ Batch Processing - Efficient handling of documents with multiple images

Autonomous Vision-Based Browsing (v0.3.52 - v0.3.56) 🆕

• 🤖 Fully Autonomous - Agent navigates websites and completes tasks without manual intervention
• 👁️ Vision-Powered - Uses Claude Vision API to "see" and understand web pages
• 🎯 Multi-Step Tasks - Handles complex workflows (search, filter, compare, extract)
• 🔗 Tool Chaining - Seamlessly integrates with WebSearchTool and login_to_website
• 🔒 Authenticated Browsing - Works with saved login sessions
• 📊 Structured Extraction - Returns clean, formatted data from websites
• 🛡️ Error Resilient - Automatic retry logic and timeout handling
• 💡 Smart Decision Making - Handles popups, loading states, forms, and navigation

Example:

You: "Browse Amazon and find the cheapest wireless mouse under $20 with good reviews"

WYN360: [Launches browser, searches, filters, compares]
✅ Task Completed Successfully!
Result: Logitech M185 - $14.99, 4.5 stars, 15,234 reviews

See docs/AUTONOMOUS_BROWSING.md for complete guide, examples, and API reference.

🎮 Usage Examples

Starting a New Project

You: Create a FastAPI app with authentication

WYN360:
- Generates main.py with FastAPI setup
- Creates auth middleware
- Adds example routes
- Provides setup instructions

Updating Existing Code

You: Add logging to my script.py

WYN360:
- Reads current script.py
- Adds logging configuration
- Updates functions with log statements
- Preserves existing functionality

Executing Commands

You: Run the analysis script

WYN360: [Generates the command to run]

======================================================================
⚠️  COMMAND EXECUTION CONFIRMATION
======================================================================
Command: python analysis.py
Directory: /current/working/directory
Permissions: Full user permissions
======================================================================

>>> WAITING FOR YOUR RESPONSE <<<

Execute this command? (y/N): y

✅ Command executed successfully
[Shows output]

Note: When you see the confirmation prompt, the "thinking" spinner may still appear in the background. This is normal - just type y and press Enter to proceed, or N to cancel.

Web Search & Resource Finding

You: Find a popular GitHub repo for machine learning

WYN360: [Searches the web]

Here are some popular GitHub repositories for machine learning:

1. **tensorflow/tensorflow** ⭐ 185k stars
   https://github.com/tensorflow/tensorflow
   - End-to-end machine learning platform
   - Used by Google and industry leaders

2. **pytorch/pytorch** ⭐ 82k stars
   https://github.com/pytorch/pytorch
   - Deep learning framework by Meta
   - Popular in research and production

3. **scikit-learn/scikit-learn** ⭐ 59k stars
   https://github.com/scikit-learn/scikit-learn
   - Classic ML algorithms for Python
   - Great for beginners and experts

[Sources: GitHub search results, updated recently]

You: What's the weather in San Francisco?

WYN360: [Searches for current weather]

Current weather in San Francisco:
🌤️ 62°F (17°C), Partly cloudy
💨 Wind: 12 mph
💧 Humidity: 65%
🌅 Sunrise: 7:15 AM | Sunset: 5:02 PM

Source: [Weather service URL]

Direct Website Fetching

You: Read https://github.com/yiqiao-yin/deepspeed-course

WYN360: [Fetches the specific URL directly]

📄 **Fetched:** https://github.com/yiqiao-yin/deepspeed-course

# DeepSpeed Course Repository

## Overview
This repository contains comprehensive course materials for DeepSpeed training...

## Course Contents
1. **Distributed Training** - Multi-GPU training strategies
2. **Memory Optimization** - ZeRO optimization techniques
3. **Pipeline Parallelism** - Efficient model parallelism
4. **Performance Tuning** - Best practices and optimizations

[Full page content extracted and converted to markdown]

When to use what:

• fetch_website: When you have a specific URL → Read https://example.com
• Web Search: When you want to find something → Find ML repos

You: Show cache stats

WYN360: 📊 **Website Cache Statistics**

**Location:** `~/.wyn360/cache/fetched_sites`

**Total Entries:** 3
**Total Size:** 2.4 MB
**Expired Entries:** 0

**Cached URLs:**
- ✓ 5m old: https://github.com/yiqiao-yin/deepspeed-course
- ✓ 12m old: https://python.org/downloads
- ✓ 25m old: https://docs.anthropic.com

Document Reading with Vision Mode

You: Read quarterly_report.docx with vision mode

WYN360: [Extracts and processes document with image descriptions]

# Quarterly Report Summary

## Executive Overview
Revenue increased by 23% year-over-year, driven by strong performance in...

📊 **[Image 1]:** Bar chart showing quarterly revenue growth from Q1 to Q4.
Q4 shows the highest revenue at approximately $2.5M, representing a 23%
increase from Q3. All quarters show positive growth compared to the previous year.

## Market Analysis
Our market share expanded across all regions...

📐 **[Image 2]:** System architecture diagram depicting three layers:
frontend (React), API layer (FastAPI), and database (PostgreSQL).
Shows data flow from user requests through authentication middleware
to the backend services.

💰 **Vision API Cost:** $0.06 (2 images processed)
📊 **Token Usage:** 1,175 input tokens, 125 output tokens

[Use /tokens to see detailed cost breakdown]

Image Handling Modes:

• skip (default) - Ignore images entirely, no API calls
• describe - Extract alt text and captions only (no API calls)
• vision - Full Claude Vision API processing (costs ~$0.01-0.05 per image)

🎯 Commands

Chat Commands

Command	Description
<message>	Chat with the AI assistant
Enter	Submit your message
Ctrl+Enter	Add a new line (multi-line input)
exit or quit	End the session

Slash Commands (v0.2.8+)

Slash commands provide quick access to context management and model selection features:

Command	Description	Example
/clear	Clear conversation history and reset token counters	/clear
/history	Display conversation history in a table	/history
/save <file>	Save current session to JSON file	/save my_session.json
/load <file>	Load session from JSON file	/load my_session.json
/tokens	Show detailed token usage statistics and costs	/tokens
/model [name]	Show current model info or switch models (v0.3.0)	/model haiku
/config	Show current configuration (v0.3.1)	/config
/help	Display help message with all commands	/help

Example Usage:

You: Write a data analysis script
WYN360: [Creates analysis.py]

You: /tokens
[Shows token usage: 1,500 input tokens, 800 output tokens, $0.02 cost]

You: /model
[Shows current model: Sonnet 4, pricing: $3.00/$15.00 per M tokens]

You: /model haiku
✓ Switched to Haiku (claude-3-5-haiku-20241022)

You: /save my_analysis_session.json
✓ Session saved to: my_analysis_session.json

You: /clear
✓ Conversation history cleared. Token counters reset.

You: /load my_analysis_session.json
✓ Session loaded from: my_analysis_session.json

📚 Documentation

For comprehensive documentation:

• USE_CASES.md - Detailed use cases, examples, and workflows
• COST.md - Token usage, pricing, cost optimization, and max_tokens configuration
• SYSTEM.md - System architecture, design principles, and technical details
• ROADMAP.md - Feature roadmap and planned enhancements

🛠️ Development & Testing

Prerequisites

• Python >= 3.10
• Poetry (package manager)
• Anthropic API key

Setting Up Development Environment

1. Clone the repository:

git clone https://github.com/yiqiao-yin/wyn360-cli.git
cd wyn360-cli

2. Install Poetry (if not already installed):

curl -sSL https://install.python-poetry.org | python3 -

3. Install dependencies:

poetry install

This will:

• Create a virtual environment
• Install all production dependencies from pyproject.toml
• Install development dependencies (pytest, pytest-asyncio, pytest-mock)
• Install the package in editable mode

Running Tests

Run all tests with verbose output:

# Skip command confirmation prompts in tests
WYN360_SKIP_CONFIRM=1 poetry run pytest tests/ -v

Run tests with short traceback:

WYN360_SKIP_CONFIRM=1 poetry run pytest tests/ -v --tb=short

Run specific test file:

poetry run pytest tests/test_agent.py -v

Run specific test class:

poetry run pytest tests/test_utils.py::TestExecuteCommandSafe -v

Run with coverage report:

poetry run pytest tests/ --cov=wyn360_cli --cov-report=html

Test Structure

tests/
├── __init__.py
├── test_agent.py          # Agent and tool tests (46 tests)
├── test_cli.py            # CLI and slash command tests (33 tests)
├── test_config.py         # Configuration tests (25 tests)
└── test_utils.py          # Utility function tests (29 tests)
                           # Total: 133 tests

Expected Output

When all tests pass, you should see:

============================= test session starts ==============================
platform linux -- Python 3.10.12, pytest-8.4.2, pluggy-1.6.0
cachedir: .pytest_cache
rootdir: /home/workbench/wyn360-cli/wyn360-cli
configfile: pyproject.toml
plugins: asyncio-1.2.0, mock-3.15.1
collected 133 items

tests/test_agent.py::TestWYN360Agent::test_agent_initialization PASSED   [  1%]
tests/test_agent.py::TestHistoryManagement::test_clear_history PASSED    [ 18%]
tests/test_agent.py::TestStreaming::test_chat_stream_method_exists PASSED [ 40%]
tests/test_cli.py::TestSlashCommands::test_clear_command PASSED          [ 42%]
tests/test_config.py::TestWYN360Config::test_default_values PASSED       [ 60%]
...
tests/test_utils.py::TestExecuteCommandSafe::test_execute_python_script PASSED [100%]

============================== 133 passed in 2.64s

Building and Publishing

Build the package:

poetry build

This creates:

• dist/wyn360_cli-X.Y.Z.tar.gz (source distribution)
• dist/wyn360_cli-X.Y.Z-py3-none-any.whl (wheel)

Publish to PyPI:

poetry publish

Build and publish in one command:

poetry build && poetry publish

Version Management

Update version in these files:

• pyproject.toml - version = "X.Y.Z"
• wyn360_cli/__init__.py - __version__ = "X.Y.Z"
• USE_CASES.md - Update changelog and version number

Development Workflow

1. Create a feature branch:

git checkout -b feature/your-feature-name

2. Make changes and test:

# Make your changes
WYN360_SKIP_CONFIRM=1 poetry run pytest tests/ -v

3. Update version and documentation:

# Update version in pyproject.toml, __init__.py, USE_CASES.md

4. Commit and push:

git add .
git commit -m "feat: your feature description"
git push origin feature/your-feature-name

5. Build and publish:

poetry build && poetry publish
git push origin main

🧪 Environment Variables

Variable	Description	Default
ANTHROPIC_API_KEY	Anthropic API key (required for Anthropic API mode)	None
CLAUDE_CODE_USE_BEDROCK	Enable AWS Bedrock mode (set to 1 to enable)	0 (disabled)
AWS_ACCESS_KEY_ID	AWS access key ID (required for Bedrock mode)	None
AWS_SECRET_ACCESS_KEY	AWS secret access key (required for Bedrock mode)	None
AWS_SESSION_TOKEN	AWS session token (optional, for temporary credentials)	None
AWS_REGION	AWS region for Bedrock (e.g., us-west-2)	us-east-1
ANTHROPIC_MODEL	Model ARN for Bedrock (e.g., us.anthropic.claude-sonnet-4-20250514-v1:0)	Auto-selected
MAX_TOKEN	Maximum tokens for model output (can also use --max-token CLI arg)	4096
MAX_INTERNET_SEARCH_LIMIT	Maximum web searches per session (Anthropic API only, can also use --max-internet-search-limit CLI arg)	5
HF_TOKEN or HUGGINGFACE_TOKEN	HuggingFace API token (optional, for HF features)	None
GH_TOKEN or GITHUB_TOKEN	GitHub access token (optional, for GitHub features)	None
WYN360_SKIP_CONFIRM	Skip command execution confirmations	0 (disabled)

Setup Example (Anthropic API):

# .env file
ANTHROPIC_API_KEY=your_anthropic_key
MAX_TOKEN=4096
MAX_INTERNET_SEARCH_LIMIT=5
GH_TOKEN=ghp_your_github_token
HF_TOKEN=hf_your_huggingface_token
WYN360_SKIP_CONFIRM=0

Setup Example (AWS Bedrock):

# .env file
CLAUDE_CODE_USE_BEDROCK=1
AWS_ACCESS_KEY_ID=your_access_key
AWS_SECRET_ACCESS_KEY=your_secret_key
AWS_SESSION_TOKEN=your_session_token
AWS_REGION=us-west-2
ANTHROPIC_MODEL=us.anthropic.claude-sonnet-4-20250514-v1:0
MAX_TOKEN=4096
GH_TOKEN=ghp_your_github_token
HF_TOKEN=hf_your_huggingface_token
WYN360_SKIP_CONFIRM=0

Set WYN360_SKIP_CONFIRM=1 to skip confirmation prompts (useful for testing or automation).

📋 Requirements

• Python >= 3.10, < 4.0
• Dependencies (automatically installed):
  • click>=8.1.0 - CLI framework
  • pydantic-ai>=1.13.0 - AI agent framework with web search support
  • anthropic>=0.39.0 - Anthropic API client
  • rich>=13.0.0 - Terminal formatting
  • python-dotenv>=1.2.1 - Environment variable management
  • prompt-toolkit>=3.0.0 - Advanced input handling
  • pyyaml>=6.0.0 - Configuration file support
  • huggingface-hub>=0.20.0 - HuggingFace integration
  • crawl4ai>=0.7.6 - LLM-optimized web crawler for browser use

Note: Browser use requires Playwright browser binaries (~200MB):

playwright install chromium

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Run tests (WYN360_SKIP_CONFIRM=1 poetry run pytest tests/ -v)
4. Commit your changes (git commit -m 'feat: add amazing feature')
5. Push to the branch (git push origin feature/amazing-feature)
6. Open a Pull Request

📄 License

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

👤 Author

Yiqiao Yin

• Email: [e-mail]
• GitHub: @yiqiao-yin

🙏 Acknowledgments

• Built with Anthropic Claude - Advanced AI assistant
• Powered by pydantic-ai - Python agent framework
• CLI framework by Click
• Terminal UI by Rich

🔗 Links

• PyPI: https://pypi.org/project/wyn360-cli/
• GitHub: https://github.com/yiqiao-yin/wyn360-cli
• Documentation:
  • USE_CASES.md - Usage examples and workflows
  • COST.md - Pricing and token configuration
  • SYSTEM.md - Architecture overview
• Get API Key: https://console.anthropic.com/

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Current Version: 0.3.58 Last Updated: November 18, 2025