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    mega-itmo

    khrum-khrum January 29, 2026
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    Mega Hackathon ITMO 2026, AI, Coding Agents

    Final Project Report: AI-Powered SDLC Automation

    ITMO Megaschool 2026, "Coding Agents" Track

    Table of Contents

    1. Project Overview
    2. Architecture and Technologies
    3. Two Independent Agents
    4. Operating Modes: CLI and Cloud Deployment
    5. GitHub Integration via Webhooks
    6. Quality and Testing
    7. Areas for Improvement
    8. Conclusion

    Project Overview

    Assignment Link

    Pitch Link

    A full-featured automated Software Development Lifecycle (SDLC) system has been developed based on LangChain, capable of autonomously solving full development cycle tasks in GitHub:

    • Issue Analysis — understanding requirements and task context
    • Autonomous Development — exploring the codebase, making changes
    • Pull Request Creation — formatting and publishing changes
    • Code Review — automatic analysis and code quality verification
    • Iterative Development — processing feedback and improving the solution

    The system works with any programming language and can be connected to any GitHub repository via cloud deployment.

    Architecture and Technologies

    Technology Stack

    LangChain Framework

    The system is built on LangChain — a modern framework for creating agent systems:

    • create_tool_calling_agent — base agent architecture with tool calling support
    • AgentExecutor — agent execution orchestration with iteration management (up to 20 iterations for complex tasks)
    • Custom Tools — integration of custom tools via the @tool decorator
    • OpenAI-compatible LLM Integration — connectin

    Tags

    aiai-agentsclaude-codecoding-agentcursordockerdocker-composegithub-actionslangchain-pythonpython

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