AI Agent That Finds and Fixes Code Bugs on Its Own Tutorial - Part 1 Theory скачать в хорошем качестве

AI Agent That Finds and Fixes Code Bugs on Its Own Tutorial - Part 1 Theory

Build an autonomous AI agent that finds and fixes bugs in your code without human intervention. This tutorial shows you how to create a Cursor-style bug-fixing agent using local LLMs, function calling, and an agentic loop. 🔧 What You'll Learn: How to set up Ollama with local LLMs (qwen2.5:14b) Implementing function calling for AI agents Building an agentic loop that explores, fixes, and verifies code Creating secure file operations with path validation Handling structured and text-based tool calls Testing your agent on real bug-fixing scenarios 📚 In This Video: Introduction to Agentic AI Project setup with UV package manager Building core functions (get_files_info, get_file_content, write_file, run_python_file) Implementing the agentic loop Live demonstration fixing a temperature converter bug 🛠️ Tech Stack: Python 3.13+ Ollama (local LLM) OpenAI-compatible API UV package manager Function calling / Tool use 💻 Code Repository: https://github.com/cholakovit/bug-hun... 🌐 Visit my website for more tutorials and projects: www.cholakovit.com 👍 If you found this video helpful, please like and subscribe for more AI and coding tutorials! 📝 Full code and documentation available in the repository. --- #AI #MachineLearning #Python #Ollama #FunctionCalling #AgenticAI #AIAgent #BugFixing #CodingTutorial #PythonTutorial #LLM #LocalLLM #Qwen #OpenAI #AIDevelopment #SoftwareEngineering #CodeReview #Automation #AITools #TechTutorial #Programming #Developer #Coding #AIProgramming #AutonomousAI #CodeAgent #TechEducation