### Download GoodQ4All Setup Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/install/INSTALL.md Direct download link for the GoodQ4All standalone Windows installer. This is the recommended installation method for most users. ```html

🚀 Download GoodQ4All Setup v1.0.0.exe

``` -------------------------------- ### Setup and Start vLLM Service Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/llm/VLLM_SYSTEMD_SETUP.md Commands to set up the necessary directory for logs, reload the systemd daemon to recognize the new service, enable the service to start on boot, and then start the service immediately. ```bash mkdir -p "${VLLM_HOME}/logs" sudo systemctl daemon-reload sudo systemctl enable vllm-llama1b.service sudo systemctl start vllm-llama1b.service ``` -------------------------------- ### Run Silent Installer Source: https://github.com/goodq02/goodq4all/blob/main/docs/agent/workflows/LAPTOP_TEST_AND_REPORT_PROTOCOL.md Execute the GoodQ4All setup executable silently to perform a clean installation. The '/S' argument ensures a non-interactive setup, and '-Wait' ensures the script pauses until the installation is complete. ```powershell Start-Process -FilePath "$env:USERPROFILE\OneDrive\One_Domingo\test_v1.0.0_package\GoodQ4All_Setup_1.0.0.exe" -ArgumentList "/S" -Wait ``` -------------------------------- ### CI/CD Environment Setup and Installation Source: https://github.com/goodq02/goodq4all/blob/main/envs/locks/README.md Example GitHub Actions workflow for creating a Conda environment, installing dependencies from a lock file, and verifying an installation. ```yaml # Example GitHub Actions - name: Create Environment run: conda create -n test_env python=3.10 -y - name: Install from Lock run: | conda run -n test_env pip install -r envs/locks/.lock.txt \ --no-cache-dir \ --no-user \ --isolated - name: Verify Installation run: conda run -n test_env python -c "import torch; print(torch.__version__)" ``` -------------------------------- ### Non-Interactive Installation Source: https://github.com/goodq02/goodq4all/blob/main/docs/bootstrap/INSTALL_BOOTSTRAP.md Run the installer with `--yes` to accept defaults and `--no-launch` to create/update the environment and local config without starting the GoodQ runtime. ```powershell python scripts/bootstrap_install.py --yes --no-launch ``` -------------------------------- ### Install GPU Support with Batch Launcher Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/gpu/GPU_SETUP.md Alternatively, use the provided Windows batch launcher script to initiate the GPU setup process. ```batch .\scripts\setup_gpu_environments.bat ``` -------------------------------- ### Install Dependencies and Setup Virtual Environment in WSL2 Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/llm/WSL2_AUDIO_SETUP.md Installs necessary audio processing dependencies and creates a Python virtual environment. Ensure you are in the WSL2 environment before running. ```bash # 1. Install dependencies sudo apt update sudo apt install python3.12-venv python3-pip ffmpeg libsndfile1 portaudio19-dev -y # 2. Create and activate venv cd ~ mkdir goodq_audio cd goodq_audio python3 -m venv venv source venv/bin/activate # 3. Install runtime packages through the repo constraints # Use the active repo setup script or constraints file. Do not install # unpinned torch/pyannote packages here. # 4. Test python -c "import torch; print('CUDA:', torch.cuda.is_available())" ``` -------------------------------- ### MCP Server Configuration Example Source: https://github.com/goodq02/goodq4all/blob/main/gemini.md Example configuration for MCP servers, including sequential thinking and a mock reference server. Ensure these runners are installed and accessible. ```json { "servers": { "sequential-thinking": { "runner": "npx -y @modelcontextprotocol/server-sequential-thinking" }, "everything": { "runner": "npx -y @modelcontextprotocol/server-everything" } } } ``` -------------------------------- ### Bootstrap Installation and Validation Source: https://github.com/goodq02/goodq4all/blob/main/docs/CHEAT_SHEET.md Use these commands to install and validate the GoodQ4All system. The PowerShell script is for installation, and the batch script is for validation. ```powershell python scripts/bootstrap_install.py ``` ```powershell .\scripts\bootstrap_validate.bat ``` -------------------------------- ### WSL2 Installation Script Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/wsl2/WSL2_BENCHMARKS.md Commands for installing WSL2 audio components, either via an automated script or a manual setup script. ```bash # Run automated installer cd .\INSTALL_WSL2_AUDIO.bat ``` ```bash # Or manual setup wsl -d -- bash /mnt///scripts/wsl2_quick_install.sh ``` -------------------------------- ### Qdrant Service Not Responding Example Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/FIRST_RUN.md This text output indicates that the Qdrant service is not responding and failed to start automatically. Manual intervention is required. ```text [!] Qdrant: Not responding Attempting to start Qdrant service... [!!] Qdrant: Failed to start - manual intervention required ``` -------------------------------- ### Install WSL2 Audio Source: https://github.com/goodq02/goodq4all/blob/main/wsl2_audio/QUICK_START.md Run the installation script to set up WSL2 Audio. This process takes approximately 30 minutes. ```cmd cd INSTALL_WSL2_AUDIO.bat ``` -------------------------------- ### Install Qdrant as a Windows Service Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/QDRANT_SETUP.md Installs Qdrant as a Windows service named 'GoodQ_Qdrant' with auto-start enabled. This is the recommended installation method for seamless integration. ```batch # Right-click and "Run as Administrator" scripts\qdrant\INSTALL_QDRANT_SERVICE.bat ``` -------------------------------- ### Launch Application Supervisor Source: https://github.com/goodq02/goodq4all/blob/main/docs/agent/workflows/LAPTOP_TEST_AND_REPORT_PROTOCOL.md Start the GoodQ4All application supervisor. This command assumes the application is installed in the default Program Files directory. ```powershell Start-Process -FilePath "$env:ProgramFiles\GoodQ4All\LAUNCH_GOODQ.exe" ``` -------------------------------- ### Install System Dependencies with Homebrew Source: https://github.com/goodq02/goodq4all/blob/main/docs/setup-macos.md Installs core system packages required by GoodQ4All using Homebrew. Ensure Homebrew is installed before running this command. ```bash # Install core system packages brew install ffmpeg poppler tesseract tesseract-lang qdrant ``` -------------------------------- ### Install Development Dependencies (Windows) Source: https://github.com/goodq02/goodq4all/blob/main/CONTRIBUTING.md Run the bootstrap installation script to set up the development environment on Windows. ```powershell python scripts/bootstrap_install.py ``` -------------------------------- ### Initialize Qdrant and Verify Health Source: https://github.com/goodq02/goodq4all/blob/main/docs/QDRANT_QUICKREF.md A sequence of batch scripts to perform the initial setup for Qdrant. This includes starting the service, initializing collections, and verifying the health status. ```batch # 1. Start Qdrant (pick one method above) scripts\qdrant\START_QDRANT.bat # 2. Initialize collections scripts\qdrant\INIT_QDRANT.bat # 3. Verify health scripts\qdrant\CHECK_QDRANT.bat ``` -------------------------------- ### Start API Server Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/general/LAUNCH_INSTRUCTIONS.md Starts the API server process. Access API documentation at http://127.0.0.1:30000/docs after it's running. ```python python -m api.server ``` ```powershell pwsh .\scripts\start_api.ps1 ``` -------------------------------- ### Start Audio Service Manually with Logging Source: https://github.com/goodq02/goodq4all/blob/main/wsl2_audio/WSL2_AUDIO_FIX_COMPLETE.md Manually start the audio service after setting up the CUDA environment, ensuring that all output is logged for debugging. ```bash cd ~/goodq_audio source setup_cuda_env.sh python3 ~/goodq_audio/audio_service.py ``` -------------------------------- ### API Server Startup Output Example Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/llm/LLM_INTEGRATION_COMPLETE.md Example output observed in the console during the API server startup after successful LLM integration. It confirms LM Studio connection and Uvicorn server status. ```text ✓ LM Studio connected! Using model: qwen/qwen3-vl-4b LLM Status: CONNECTED INFO: Started server process [XXXX] INFO: Uvicorn running on http://0.0.0.0:30000 ``` -------------------------------- ### Initialize LLM Client with Configuration Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/llm/LLM_CLIENT_GUIDE.md Demonstrates the recommended pattern for initializing the LLM client using configuration files and a model factory. Ensure `models` are built and then passed to `get_client` with runtime parameters. ```python from steps.common.config_loader import load_configs from steps.common.llm_model_factory import build_llm_models from lib.llm_client import get_client cfg = load_configs({}) models = build_llm_models(cfg) client = get_client( models=models, health_check_interval=60, max_retries=3, timeout=30, cache_ttl=300, enable_health_checks=False, ) ``` -------------------------------- ### Configuration Paths Example Source: https://github.com/goodq02/goodq4all/blob/main/docs/CLI-REFERENCE.md Illustrates the structure of path configurations resolved from `configs/config.yaml` and environment overlays. ```yaml paths: import_inbox: ${GOODQ_DATA_ROOT}/GoodQ_Data/import_inbox processing: ${GOODQ_DATA_ROOT}/GoodQ_Data/epochs//processing db_path: ${GOODQ_DATA_ROOT}/GoodQ_Data/epochs//memory.db knowledge_graph_db: ${GOODQ_DATA_ROOT}/GoodQ_Data/epochs//knowledge_graph.db log_dir: ${GOODQ_DATA_ROOT}/GoodQ_Data/epochs//logs ``` -------------------------------- ### Run the Bootstrap Installer Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/DEMO.md Execute the primary installation script to set up the project environment. For systems with limited resources or specific configurations, use the CPU-safe variant. ```bash python scripts/bootstrap_install.py ``` ```bash python scripts/bootstrap_install.py --disable-gpu --disable-wsl-audio --skip-model-prefetch ``` -------------------------------- ### Start WSL2 Audio Service (WSL2) Source: https://github.com/goodq02/goodq4all/blob/main/wsl2_audio/QUICK_REFERENCE.md Navigate to the audio directory, set up the CUDA environment, and run the audio service script in the background. ```bash # From WSL2 cd ~/goodq_audio source setup_cuda_env.sh python3 ~/goodq_audio/audio_service.py & ``` -------------------------------- ### Automated CUDA Environment Setup (Shell Script) Source: https://github.com/goodq02/goodq4all/blob/main/docs/WSL2_SCRIPTS_ADDED.md Shell script for automated CUDA environment setup on WSL2. Useful for ensuring the correct CUDA drivers and libraries are installed. ```shell setup_cuda_env.sh ``` -------------------------------- ### Get All Scenes SQL Query Source: https://github.com/goodq02/goodq4all/blob/main/docs/technical/PIPELINE_DEEP_DIVE_REPORT.md Retrieves all scene data, ordered by start time. Used for populating the scene list. ```sql -- Get all scenes SELECT id, video_hash, start, end, meta, created_at FROM scenes ORDER BY start; ``` -------------------------------- ### Run Qdrant Manually (Foreground) Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/QDRANT_SETUP.md Starts Qdrant in the foreground for testing purposes. This is a fallback option if service installation is not desired or fails. ```batch # Start Qdrant in foreground scripts\qdrant\START_QDRANT.bat ``` -------------------------------- ### Start vLLM Server with Qwen 2.5 7B Model Source: https://github.com/goodq02/goodq4all/blob/main/vllm_wsl/MODEL_SCAN_UPDATED.md This command starts the vLLM server, loading the Qwen 2.5 7B model from the specified directory and configuring it to use 90% of GPU memory on port 8000. ```bash vllm serve ~/vllm_server/models/llm/chat/Qwen2.5-7B-Instruct \ --port 8000 --gpu-memory-utilization 0.90 ``` -------------------------------- ### Example Pytest Validation Command Source: https://github.com/goodq02/goodq4all/blob/main/docs/architecture/GOODQ_EXECPLAN_PROTOCOL.md Use this command to run pytest for the bootstrap install WSL unit tests. Ensure the path is correct. ```bash python -m pytest tests/unit/test_bootstrap_install_wsl.py ``` -------------------------------- ### Run Bootstrap Installer (CPU-Safe Variant) Source: https://github.com/goodq02/goodq4all/blob/main/README.md Use this command to run the installer while disabling GPU and WSL audio acceleration, and skipping model prefetching. This is useful for CPU-only environments. ```python python scripts/bootstrap_install.py --disable-gpu --disable-wsl-audio --skip-model-prefetch ``` -------------------------------- ### Configure GPU for a Specific Device ID Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/gpu/GPU_MANAGEMENT_GUIDE.md Example for configuring GPU for a specific step on a particular GPU device ID, useful for multi-GPU setups. ```python # Configure for specific GPU config = GPUManager.configure_gpu("my_step", gpu_id=1) ``` -------------------------------- ### Verify CUDA and Hugging Face Token Setup Source: https://github.com/goodq02/goodq4all/blob/main/wsl2_audio/TEST_RESULTS.md Source the CUDA environment setup script and then run Python scripts to verify that CUDA is accessible and the Hugging Face token is correctly configured. ```bash source ~/goodq_audio/setup_cuda_env.sh python3 ~/goodq_audio/check_cuda.py python3 ~/goodq_audio/check_hf_token.py ``` -------------------------------- ### Navigate to Project Directory Source: https://github.com/goodq02/goodq4all/blob/main/README.md Change your current directory to the root of the cloned GoodQ4All project. ```bash cd goodq4all ``` -------------------------------- ### Manual Error Diagnosis with Control Agent Source: https://github.com/goodq02/goodq4all/blob/main/docs/CONTROL_AGENT.md Example of using the Control Agent's diagnose_error method to analyze an error and get recommended actions. ```python from agents.control_agent import ControlAgent agent = ControlAgent(llm_client=llm_client) # Analyze an error diagnosis = agent.diagnose_error( error_message="CUDA out of memory", context={ "step_name": "face_embed", "gpu_usage_mb": 15800, "batch_size": 32 } ) print(diagnosis) # { # "error_pattern": "cuda_oom", # "recommended_actions": ["reduce_batch_size", "switch_to_cpu"], # "auto_apply": True, # "confidence": 0.95 # } ``` -------------------------------- ### AI Agent Quick Start Section Source: https://github.com/goodq02/goodq4all/blob/main/docs/architecture/DOCUMENTATION_REORGANIZATION_PLAN.md Markdown section within an index file to guide AI agents on the recommended reading order for AI-relevant indexes. ```markdown ## 🤖 AI Agent Quick Start 1. Read this index overview 2. Check [Current System Status](../archive/status-reports/CURRENT_SYSTEM_STATUS_2025-12-02.md) 3. Review relevant section below ``` -------------------------------- ### Clone Repository and Navigate Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/DEMO.md Clone the GoodQ4All repository from GitHub and navigate into the project directory. This is the initial step for running the project from source. ```powershell git clone https://github.com/GoodQ02/goodq4all.git cd goodq4all ``` -------------------------------- ### WSL2 Environment Setup Script (Shell) Source: https://github.com/goodq02/goodq4all/blob/main/docs/WSL2_SCRIPTS_ADDED.md Shell script for setting up the WSL2 environment for audio processing. Ensures all necessary components are installed and configured within WSL2. ```shell setup_wsl2_audio.sh ``` -------------------------------- ### Qdrant Configuration Example Source: https://github.com/goodq02/goodq4all/blob/main/docs/CLI-REFERENCE.md Shows the configuration for enabling Qdrant as the canonical vector endpoint, including its host. ```yaml qdrant: enabled: true host: http://localhost:6333 ``` -------------------------------- ### Start Qwen 2.5 7B Server Source: https://github.com/goodq02/goodq4all/blob/main/vllm_wsl/MODEL_DOWNLOAD_REPORT.md Launches the vLLM server for the Qwen 2.5 7B model on port 8000. ```bash ~/vllm_server/scripts/start_qwen.sh ``` -------------------------------- ### Start vLLM Server with Startup Script Source: https://github.com/goodq02/goodq4all/blob/main/vllm_wsl/INSTALLATION_REPORT.md Launches the vLLM server using a custom startup script, which handles environment activation and logging. It accepts a model path as an argument. ```bash ~/vllm_server/scripts/start_server.sh facebook/opt-125m ``` -------------------------------- ### Setup WSL2 Environment Source: https://github.com/goodq02/goodq4all/blob/main/wsl2_audio/README.md Execute this bash script within your WSL2 Ubuntu terminal to install system dependencies, Python virtual environment, and core audio packages including PyTorch with CUDA support. ```bash cd ~/goodq_audio ./setup_wsl2_audio.sh ``` -------------------------------- ### Install CUDA-enabled PyTorch Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/wsl2/WSL2_AUDIO_FEASIBILITY_ANALYSIS.md Installs PyTorch with CUDA 12.1 support for GPU acceleration. Verifies CUDA availability after installation. ```bash pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 python3 -c "import torch; print('CUDA:', torch.cuda.is_available())" ``` -------------------------------- ### Example Progress Tracking Source: https://github.com/goodq02/goodq4all/blob/main/PLAN.md Illustrates how to track progress using a checklist with timestamps. Each step, whether completed or incomplete, should be documented. ```markdown - [x] (2025-10-01 13:00Z) Example completed step. - [ ] Example incomplete step. - [ ] Example partially completed step (completed: X; remaining: Y). ``` -------------------------------- ### Reinstall with System Site Packages Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/llm/WSL2_AUDIO_SETUP.md Creates a virtual environment that includes system site packages, which can resolve import errors for audio libraries. Use this if standard venv creation fails. ```bash # Reinstall with system site packages python3 -m venv --system-site-packages venv source venv/bin/activate pip install ``` -------------------------------- ### Login from WSL Audio Environment Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/wsl2/HF_CLI_LOGIN_GUIDE.md Source the CUDA environment setup script and then log in using the HuggingFace CLI. This is for users working within the WSL audio environment. ```bash source ~/goodq_audio/setup_cuda_env.sh hf auth login ``` -------------------------------- ### Install vLLM Service via WSL Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/llm/LLM_INFRASTRUCTURE.md Installs the vLLM service using the WSL systemd installer. Replace placeholders with your specific distribution and repository root. ```bash wsl -d -- bash /mnt///scripts/wsl/install_vllm_service.sh ``` -------------------------------- ### Download Qwen/Qwen2.5-7B-Instruct Model Source: https://github.com/goodq02/goodq4all/blob/main/vllm_wsl/MODEL_SCAN_REPORT.md Use this command to download the Qwen2.5-7B-Instruct model for vLLM. Ensure your virtual environment is activated. ```bash source ~/vllm_server/activate.sh huggingface-cli download Qwen/Qwen2.5-7B-Instruct \ --local-dir ~/vllm_server/models/Qwen2.5-7B-Instruct \ --local-dir-use-symlinks False ``` -------------------------------- ### Install GPU Support with PowerShell Source: https://github.com/goodq02/goodq4all/blob/main/docs/guides/gpu/GPU_SETUP.md Use the canonical PowerShell installer script to set up CUDA-enabled PyTorch in the maintained GPU-capable environments. The -Force flag ensures a complete installation. ```powershell pwsh scripts\install_gpu_support.ps1 -Force ``` -------------------------------- ### Install Flash Attention Source: https://github.com/goodq02/goodq4all/blob/main/docs/technical/AUDIO_GPU_OPTIMIZATION.md Install the flash-attn library to enable Flash Attention, which can significantly speed up attention mechanisms. This command activates the conda environment and installs the library with no build isolation. ```batch conda activate audio_transcribe pip install flash-attn --no-build-isolation ``` -------------------------------- ### Install PyTorch with MPS Support Source: https://github.com/goodq02/goodq4all/blob/main/docs/setup-macos.md Installs PyTorch, torchvision, and torchaudio with Metal Performance Shaders (MPS) support for Apple Silicon. Note that standard pip installs on macOS include MPS support by default. ```bash # Install PyTorch with Metal Performance Shaders (MPS) support pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu # Note: On macOS, standard pip install of torch includes MPS support out-of-the-box. pip install torch torchvision torchaudio ``` -------------------------------- ### Start API Server Source: https://github.com/goodq02/goodq4all/blob/main/README.md Launch the GoodQ4All API server using Conda. This allows interaction with the system and inspection of ingestion proofs. ```bash conda run --no-capture-output -n goodq_core python -m api.server ``` -------------------------------- ### Download microsoft/Phi-3.5-mini-instruct Model Source: https://github.com/goodq02/goodq4all/blob/main/vllm_wsl/MODEL_SCAN_REPORT.md Download the Phi-3.5-mini-instruct model using this command. Activate your vLLM server environment first. ```bash source ~/vllm_server/activate.sh huggingface-cli download microsoft/Phi-3.5-mini-instruct \ --local-dir ~/vllm_server/models/Phi-3.5-mini-instruct \ --local-dir-use-symlinks False ``` -------------------------------- ### Align Quick Install Source: https://github.com/goodq02/goodq4all/blob/main/docs/superpowers/plans/2026-05-08-wsl-wav2vec-transformers-lane.md Update the constrained install command in `wsl2_quick_install.sh` to request transformers, tokenizers, and safetensors. ```bash transformers tokenizers safetensors ``` -------------------------------- ### Commit Message Example Source: https://github.com/goodq02/goodq4all/blob/main/CONTRIBUTING.md Example of a conventional commit message for a feature, including a detailed description of changes. ```bash git commit -m "feat: Add emotion detection to audio pipeline - Integrate Wav2Vec2 emotion classifier - Add 8-class emotion output to result.json - Update audio processing documentation" ``` -------------------------------- ### Run Quick Test Suite Source: https://github.com/goodq02/goodq4all/blob/main/docs/technical/AUDIO_GPU_QUICK_START.md Execute the batch file for a quick test of the audio GPU optimization pipeline. Option 1 runs the full pipeline with integrated monitoring. ```batch TEST_AUDIO_GPU.bat ``` -------------------------------- ### Install Dependencies from Lock File Source: https://github.com/goodq02/goodq4all/blob/main/envs/locks/README.md Command to install all dependencies listed in a lock file into a specified Conda environment. ```text conda run -n pip install -r envs/locks/.lock.txt ``` -------------------------------- ### CLI Runtime Entry Points Source: https://github.com/goodq02/goodq4all/blob/main/docs/architecture/ARCHITECTURE_REFERENCE.md Lists the available command-line interface entry points for GoodQ4All, including ingestion, watchdog, monitoring, status checks, configuration printing, inbox listing, retrieval, and natural language querying. ```python python -m cli.run_ingestion ``` ```python python -m cli.watchdog ``` ```python python -m cli.monitor_ingestion ``` ```python python -m cli.system_status ``` ```python python -m cli.print_config ``` ```python python -m cli.list_inbox ``` ```python python -m cli.retrieve ``` ```python python -m cli.nl_query ```