June - A Coding Agent with Web Interface

June AI Agent June’s web interface showing the AI coding agent in action

Have you ever wished you had a coding assistant that could just… work in the b ackground, handling the tedious parts of development while you focus on the big picture? T hat’s exactly what I was thinking when I started building June - an AI-powered co ding agent that’s become one of my most experimental and surprisingly useful project s.

What began as a simple experiment with Together.ai’s API quickly evolved into so mething much more interesting: a persistent coding assistant that could actually execut e code, save files, and provide real-time feedback through a web interface. Let m e tell you about the journey.

🤖 The AI Assistant Experiment

AI Development The evolution from simple API calls to a full-featured coding assistant

The idea for June came from a simple frustration: I was spending too much time o n boilerplate code and repetitive tasks. I’d heard about Together.ai’s API and th ought “what if I could just ask an AI to handle the boring stuff?”

But here’s the thing - most AI coding assistants are just chat interfaces. They can suggest code, but they can’t actually do anything with it. I wanted something that could take action, execute code, save files, and give me real results.

Looking at the commit history, I can see exactly where this project took off. Th e early commits show me struggling with basic API integration, but then something interesting happened in commit 24cf0631 - I added function calling capabiliti es.

That’s when June went from being a fancy chatbot to being a real coding assistan t.

🎯 Key Features

AI-Powered Coding

Together.ai integration for intelligent code generation
Task-based workflow for structured coding assistance
Automated processing of coding requests
Error handling and result management

Web Interface

Real-time status monitoring
Task management with status tracking
Live updates with automatic refresh
Form-based task submission
Activity logging for transparency

API Endpoints

GET /status: Current agent status and task counts
GET /tasks: List all tasks with statuses and results
POST /tasks: Submit new coding tasks via JSON

🛠️ Technical Implementation

Modern Python Architecture

June is built with modern Python practices:

Python 3.x with Poetry for dependency management
Flask for the web service
Together.ai API for AI-powered coding
Modular design for maintainability
Comprehensive testing with pytest

Core Components

june_agent/
├── __init__.py           # Package initialization
├── __main__.py          # Main entry point and agent loop
├── request.py           # API request handling
├── task.py              # Task management and processing
├── web_service.py       # Flask web server
├── svg.py               # SVG generation utilities
└── chart.py             # Chart generation utilities

Web Service Architecture

The Flask web service provides:

RESTful API for task management
Real-time updates through automatic refresh
Error handling for robust operation
Status monitoring for system health

🚀 Getting Started

Prerequisites

Python 3.8+
Poetry for dependency management
Together.ai API key

Installation

# Clone the repository
git clone https://github.com/rl337/june
cd june

# Install dependencies
poetry install

# Set up API key
export TOGETHER_API_KEY="your_api_key_here"

Running the Agent

# Using Poetry
poetry run python -m june_agent

# Or activate virtual environment
poetry shell
python -m june_agent

The agent will start and be available at http://localhost:8080.

🌐 Web Interface

Dashboard Features

Agent Status: Current operational status
Task Queue: Pending, processing, completed, and failed tasks
Task Submission: Form for submitting new coding tasks
Activity Log: Recent agent activities and updates

API Usage

Submit a Task

curl -X POST -H "Content-Type: application/json" \
  -d '{"description":"Write a python function to calculate factorial"}' \
  http://localhost:8080/tasks

Check Status

curl http://localhost:8080/status

List Tasks

curl http://localhost:8080/tasks

🧪 The Testing Challenge

Testing AI Testing an AI agent that can modify its own code - a unique challenge

One of the most interesting aspects of developing June was figuring out how to t est an AI system. How do you write tests for something that’s designed to be unpred ictable and creative?

The breakthrough came when I realized I needed to test the system, not the AI’ s responses. I focused on testing the function calling mechanism, the file operat ions, and the web interface - the parts that needed to work reliably regardless of wh at the AI decided to do.

Looking at commits like 43cddf7e (“Add context to scenario test assertions”), I can see the evolution of my testing approach. I started with simple unit tests, then moved to scenario-based testing where I’d give June a task and verify it c ould complete it end-to-end.

The most fascinating part? June actually helped me improve its own tests. I’d as k it to write test cases, and it would come up with scenarios I hadn’t thought of .

# Run all tests
poetry run pytest

# Run with coverage
poetry run pytest --cov=june_agent

# Run specific test files
poetry run pytest tests/test_task.py

📊 Project Status

Current Features

✅ AI-powered coding with Together.ai
✅ Web interface for task management
✅ RESTful API for programmatic access
✅ Task queuing and status tracking
✅ Error handling and result management
✅ Comprehensive testing with pytest
✅ Modern Python packaging with Poetry

Planned Features

🔄 Enhanced AI models for better code generation
🔄 Task prioritization and scheduling
🔄 Result caching for improved performance
🔄 User authentication and access control
🔄 Advanced task types beyond coding

🎯 Use Cases

June is perfect for:

Automated coding assistance for developers
Code generation for repetitive tasks
Learning and experimentation with AI coding
Prototype development and rapid iteration
Educational tools for programming courses

🔗 Links and Resources

GitHub Repository - Source code and documentation
Project README - Detailed setup and usage instructions
Together.ai Documentation - AI API documentation
Flask Documentation - Web framework documentation

💡 What I Learned About AI Development

AI Insights The surprising lessons from building an AI coding assistant

Building June taught me more about AI development than I expected. The biggest s urprise? The AI isn’t the hard part - it’s everything around it.

The Real Challenges

The Together.ai API is actually quite straightforward to use. The real challenge s were:

Function calling reliability - Making sure the AI could consistently call the right functions with the right parameters
Error handling - What happens when the AI generates invalid code or tries to access files it shouldn’t?
Security - How do you give an AI agent the ability to execute code withou t creating a security nightmare?
Testing - How do you test a system that’s designed to be unpredictable?

The Unexpected Benefits

The most surprising thing about June isn’t what it can do - it’s how it changed my own development process. Having an AI that can actually execute code and save f iles means I can offload the tedious parts of development and focus on the interesti ng problems.

I’ve used June to:

Generate boilerplate code for new projects
Write test cases for complex functions
Refactor large codebases
Debug issues by having it analyze error logs

The Name

I named it “June” because it’s like having a helpful assistant available year-ro und, but also because “June” sounds friendly and approachable - not intimidating lik e “AI Agent” or “Coding Bot.”

If you’re curious about AI-powered development tools or want to experiment with automated coding assistance, check out June. I t might just change how you think about the future of software development!