{"name":"Local LLM Linux Troubleshoot: An AI Agent for Linux Diagnostics","description":"Local LLM Linux Troubleshoot is an AI-powered agent designed to diagnose and resolve issues on Linux systems. It leverages llama.cpp for local AI processing, offering system diagnostics, safe command execution, and support for Docker, CLI, and a web GUI. This tool provides a privacy-first approach to managing and troubleshooting your Linux environment.","github":"https://github.com/ikaganacar1/Local_LLM_Linux_Troubleshoot","url":"https://osrepos.com/repo/ikaganacar1-local_llm_linux_troubleshoot","source":"osrepos.com","sourceDescription":"This repository profile is provided by osrepos.com, an open source repository discovery platform.","repositoryProfile":"https://osrepos.com/repo/ikaganacar1-local_llm_linux_troubleshoot","generatedFor":"open source discovery and AI-assisted research","markdown":"https://osrepos.com/repo/ikaganacar1-local_llm_linux_troubleshoot.md","json":"https://osrepos.com/repo/ikaganacar1-local_llm_linux_troubleshoot.json","topics":["ai-agents","linux-troubleshooting","llama-cpp","docker","python","self-hosted","web-gui","system-diagnostics"],"keywords":["ai-agents","linux-troubleshooting","llama-cpp","docker","python","self-hosted","web-gui","system-diagnostics"],"stars":null,"summary":"Local LLM Linux Troubleshoot is an AI-powered agent designed to diagnose and resolve issues on Linux systems. It leverages llama.cpp for local AI processing, offering system diagnostics, safe command execution, and support for Docker, CLI, and a web GUI. This tool provides a privacy-first approach to managing and troubleshooting your Linux environment.","content":"## Introduction\n\nLocal LLM Linux Troubleshoot is an innovative local AI agent crafted to simplify Linux system diagnostics and troubleshooting. It integrates with `llama.cpp` to provide an intelligent assistant that can scan your host, interpret logs, explain potential issues, and propose solutions. The project emphasizes safety, requiring explicit permission before executing any system-altering commands, and supports both command-line and a user-friendly web interface.\n\n## Why Use and Benefits\n\nThis project offers a powerful set of features for anyone managing Linux systems, from homelab enthusiasts to sysadmins:\n\n*   **Comprehensive Diagnostics**: Performs read-only diagnostics across services, packages, boot processes, storage, network, display, audio, and Bluetooth.\n*   **Intelligent Explanations**: Streams model output in chat, including collapsible reasoning to help users understand the AI's thought process.\n*   **Privacy-First**: Operates locally with `llama.cpp` models, ensuring your system data remains on your machine.\n*   **Safe Command Execution**: Utilizes a safety controller that requires explicit user permission in the GUI before executing any modifying commands, logging all approved actions to a local audit trail.\n*   **Configurable**: Allows users to customize model, context, token settings, permissions, and theme directly from the web GUI.\n*   **Persistent Data**: Maintains chat history in the browser and local scan memory in a dedicated `.lta_data/` directory.\n*   **Versatile Access**: Offers both a command-line interface (CLI) for quick queries and a web GUI for a more interactive experience.\n*   **Docker Support**: Easy deployment as a local, restart-always Docker service, simplifying setup and management.\n\n## Installation\n\n### Docker Setup\n\nTo run the application as a local, restart-always Docker service, use the following commands:\n\nbash\ndocker compose up -d --build\n\n\nOnce started, open your browser to:\n\ntext\nhttp://127.0.0.1:28765/\n\n\nFor added security, you can set a local UI password:\n\nbash\nexport LTA_UI_PASSWORD='choose-a-local-password'\ndocker compose up -d --build\n\n\n### Run Without Docker\n\nIf you prefer to run the application directly, ensure you have Python 3.10+ installed and then execute:\n\nbash\nPYTHONPATH=src python3 -m linux_troubleshoot_agent.web\n\n\nYou can also set useful defaults via environment variables:\n\nbash\nexport LLAMA_CPP_BASE_URL=http://127.0.0.1:11435/v1\nexport LLAMA_CPP_MODEL=local-model\nexport LTA_MAX_TOKENS=4096\nexport LTA_TEMPERATURE=0.2\nexport LTA_TOP_P=0.95\nexport LTA_TOP_K=40\nexport LTA_REPEAT_PENALTY=1.1\n\n\n## Examples\n\n### CLI Usage\n\nAsk a troubleshooting question directly from the command line:\n\nbash\nPYTHONPATH=src python3 -m linux_troubleshoot_agent \"HDMI monitor is not detected\"\n\n\nCheck the safety classification of a command:\n\nbash\nPYTHONPATH=src python3 -m linux_troubleshoot_agent --check-command \"journalctl -p 3 -xb\"\n\n\n## Links\n\nFor more details, source code, and to contribute, visit the official GitHub repository:\n\n*   [GitHub Repository](https://github.com/ikaganacar1/Local_LLM_Linux_Troubleshoot){:target=\"_blank\"}","metrics":{"detailViews":2,"githubClicks":0},"dates":{"published":null,"modified":"2026-09-13T23:13:01.000Z"}}