A local-hosted application designed to analyze public/private repositories or local projects, identifying inefficiencies and suggesting optimizations. By leveraging LLMs (e.g., ChatGPT-01), it delivers actionable insights into code quality, structure, and scalability.
- Comprehensive Scanning: File structure, Docker configs, requirements, ML workflow, security, logging, etc.
- ChatGPT Integration: Real-time suggestions or code edits via ChatGPT, supporting:
o1-mini(default)chatgpt-01(optional, configurable via.env).
- User-Friendly Interface: Web UI (Flask or Node) or optional CLI.
- Reporting: Generate PDF, Markdown, JSON, or Excel outputs of analysis results.
- Python: Versions 3.9, 3.10, or 3.11 supported.
- Node.js: Version 16+ (optional for front-end tasks).
- Docker & Docker Compose: Optional, for containerized deployment.
- Git: Required for cloning the repository.
git clone https://github.com/steven-reyes/code-analyzer.git
cd code-analyzer- Create a virtual environment (recommended):
python -m venv code-analyzer-env source code-analyzer-env/bin/activate - Install dependencies:
pip install -r requirements.txt
- Create and activate a Conda environment:
conda env create -f environment.yml conda activate code-analyzer-env
- Ensure dependencies are installed:
conda install --file requirements.txt
- Create a virtual environment (recommended):
python -m venv code-analyzer-env code-analyzer-env\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
Create a .env file in the project root based on .env.example:
CHATGPT_API_KEY=your_openai_api_key_here
# Optional: Override default model ('o1-mini') by setting:
CHATGPT_MODEL=chatgpt-01
- Install dependencies:
npm install
- Build and run tasks:
npm run build npm run start # or npm run dev
- Build Docker image:
docker build -t code-analyzer:latest . - Run using Docker Compose:
docker-compose up --build
-
Run the Application Locally:
Ensure
.envis properly configured with your API key:CHATGPT_API_KEY=your_openai_api_key_here CHATGPT_MODEL=o1-miniThen, run the application:
python -m src.main
Visit
http://localhost:5000in your browser or use the CLI. -
Analyze a Local Project:
python -m src.main --project-path /path/to/project
-
Analyze a GitHub Repo:
python -m src.main --github-url https://github.com/username/repo
To configure the application, set the following environment variables in your .env file:
CHATGPT_API_KEY=your_openai_api_key_here # Required
CHATGPT_MODEL=o1-mini # Optional, defaults to 'o1-mini'
CHATGPT_API_KEY: Your OpenAI API key.CHATGPT_MODEL(optional): Overrides the default model. Options:o1-mini(default)chatgpt-01(for advanced use cases).
Code_Analyzer/ # Main directory for the entire project
├── .github/ # (GitHub-Specific) Contains GitHub Actions workflows, issue templates, etc.
│ ├── ISSUE_TEMPLATE/ # (Issue Templates) Standardized templates for GitHub Issues
│ └── workflows/
│ └── ci.yml # (CI/CD Workflow) Defines automated tests/builds/deployments
├── .gitignore # (Git Ignore Rules) Lists files/folders to exclude from version control
├── .env # (Environment Variables) Stores sensitive info (e.g., API keys, DB credentials)
├── .env.example # (Sample Environment Variables) Stores sensitive info (e.g., API keys, DB credentials)
├── .dockerignore # (Docker Ignore Rules) Files/folders to exclude from Docker builds
├── .editorconfig # (EditorConfig) Consistent coding style across editors
├── .prettierrc # (Prettier Config) Code formatting rules (JS/TS)
├── .eslintignore # (ESLint Ignore) Excludes certain files/folders from ESLint
├── .eslintrc.js # (ESLint Config) JavaScript/TypeScript linting rules
├── .flake8 # (Flake8 Config) Python linting rules (if using Flake8)
├── .pylintrc # (Pylint Config) Python linting rules (if using Pylint)
├── .pre-commit-config.yaml # (Pre-Commit Hooks) Defines lint/format checks before commits
├── .pytest_cache/ # (Pytest Cache) Auto-generated data for Python tests
├── coverage/ # (Coverage Reports) Generated coverage data (HTML, JSON) for tests
│ ├── coverage-final.json # (Coverage Data) Machine-readable summary
│ └── index.html # (Coverage HTML Report) Human-readable coverage visualization
├── coverage.xml # (Coverage XML) For CI tools (e.g., Cobertura, SonarQube)
├── Dockerfile # (Docker Build) Instructions to build a Docker image
├── docker-compose.yml # (Docker Compose) Multi-container orchestration
├── requirements.txt # (Python Dependencies) Pinned Python libraries
├── environment.yml # (Conda Env Config) Alternative to requirements.txt for Python deps
├── package.json # (Node.js Config) Name, version, scripts, dependencies
├── package-lock.json # (Node.js Lock File) Auto-generated by npm
├── yarn.lock # (Yarn Lock File) Auto-generated if using Yarn
├── LICENSE # (Project License) E.g., MIT, Apache, or Proprietary
├── README.md # (Project Overview / Quick Start)
│ # - High-level description of the project
│ # - Summarizes core features or goals
│ # - Often includes minimal setup instructions for a quick start
├── USER_MANUAL.md # (Detailed User Manual)
│ # - Step-by-step installation instructions (Python, Node, Docker)
│ # - How to configure and run on localhost
│ # - Usage examples and troubleshooting tips
│ # - Advanced setup or deployment guides
├── CONTRIBUTING.md # (Contribution Guidelines) Explains how to contribute
├── SECURITY.md # (Security Policy) Guidance on reporting vulnerabilities
├── CHANGELOG.md # (Release Notes) Records changes across versions
├── setup.py # (Python Packaging) For installing/distributing as a Python package
├── pyproject.toml # (PEP 518) Python build system requirements (poetry, flit, setuptools)
├── node_modules/ # (Node.js Dependencies) Auto-generated directory (npm or yarn)
│ └── ... # Contains installed packages
├── data/ # (Data Directory) Holds raw and processed datasets
│ ├── raw/
│ │ └── dataset.csv # (Raw CSV) Unmodified dataset
│ └── processed/
│ └── processed_dataset.csv # (Processed CSV) Cleaned/preprocessed dataset
├── docs/ # (Documentation) Architecture guides, user manuals, technical docs
│ ├── architecture.md # (System Architecture) Explains high-level design
│ ├── api.md # (API Documentation) Endpoints, request/response formats
│ └── ...
├── ml/ # (Machine Learning/AI) Houses ML/AI-specific code and configs
│ ├── config/
│ │ ├── model_config.json # (Model Config) Hyperparameters or paths for training
│ │ └── dataset_config.json # (Dataset Config) Info on datasets, transformations, splitting
│ ├── scripts/
│ │ ├── train.py # (Training Script) Model training logic
│ │ ├── evaluate.py # (Evaluation Script) Assesses model performance
│ │ └── inference.py # (Inference Script) Applies model to new data
│ └── notebooks/
│ └── exploratory_analysis.ipynb # (Jupyter Notebook) Data exploration, experiments
├── src/ # (Source Code) Main app logic
│ ├── __init__.py # (Python Init) Declares this dir as a Python package
│ ├── main.py # (Entry Point) Primary script to start the application
│ ├── chatgpt_integration.py # (ChatGPT-01 Integration) Logic to interact w/ ChatGPT
│ ├── ui/
│ │ ├── app.py # (UI / Flask App) Example web interface
│ │ └── setup_prompt.py # (Hosting Prompt) Localhost vs. remote environment
│ └── templates/
│ └── dashboard.html # (UI Template) Example HTML for a dashboard
│ ├── config/
│ │ ├── settings.json # (App Config) High-level app settings/environment info
│ │ ├── secrets.json # (Sensitive Config) Possibly omitted from version control
│ │ └── settings_loader.py # (Config Loader) Merges settings & secrets into one config dict
│ ├── modules/
│ │ ├── example_module.py # (Module Example) Additional functionalities/classes
│ │ ├── data_analyzer.py # (Data Analysis) Complex transformations, checks
│ │ └── report_generator.py # (Reporting) Produce PDF/Markdown/JSON/Excel
│ ├── utils/ # (Utilities & Scanners)
│ │ ├── file_utils.py # (Utility Functions) For file I/O, path ops, etc.
│ │ ├── file_editor.py # Real-time or output-only file edits
│ │ ├── missing_logic_detector.py # Detects placeholders (TODO, pass, NotImplementedError)
│ │ ├── file_structure_scanner.py # Recursively scans file/folder structure
│ │ ├── requirements_scanner.py # Checks Python deps (requirements.txt, environment.yml)
│ │ ├── docker_scanner.py # Dockerfile/docker-compose.yml analysis
│ │ ├── ml_scanner.py # ML folder checks (configs, scripts, notebooks)
│ │ ├── env_file_scanner.py # Ensures .env usage & parse
│ │ ├── security_scanner.py # Finds potential security issues/hardcoded secrets
│ │ ├── duplicate_finder.py # Detects duplicate or redundant files
│ │ ├── logging_scanner.py # Logging & monitoring usage checks
│ │ ├── testing_scanner.py # Testing frameworks, coverage configs, etc.
│ │ └── project_analyzer.py # (Master Coordinator) Orchestrates all sub-scanners
│ └── ...
├── tests/ # (Test Suite) For unit, integration, or end-to-end tests
│ ├── test_main.py # (Unit Test) Tests for main.py
│ ├── test_example_module.py # (Unit Test) Tests for example_module.py
│ ├── integration/
│ │ └── test_integration_example.py # (Integration Test) Cross-module checks
│ ├── e2e/
│ │ └── test_end_to_end_flow.py # (End-to-End Test) Tests the entire workflow
│ └── conftest.py # Shared fixtures or hooks for Pytest
├── ml/
│ ├── test_train.py # Tests for ml/scripts/train.py
│ ├── test_evaluate.py # Tests for ml/scripts/evaluate.py
│ └── test_inference.py # Tests for ml/scripts/inference.py
├── cypress/ # (Cypress E2E Tests) If using Cypress for front-end testing
│ ├── fixtures/
│ ├── integration/
│ ├── plugins/
│ └── support/
├── scripts/ # (DevOps/Automation Scripts)
│ ├── clean_data.py # (Data Cleaning) e.g., removing duplicates, nulls
│ ├── generate_configs.py # (Config Generator) Creates/updates JSON config files
│ └── deploy.sh # (Deployment Script) Automates build & deployment steps
├── output/ # (Analyzer Output) For reports/updated files if "Output Only" chosen
│ ├── updated_files/ # (Generated Files) New/modified versions of original files
│ └── reports/
│ ├── analysis_report.pdf # (PDF Report) Summaries & recommendations from Code Analyzer
│ ├── analysis_report.md # (Markdown Report) Same as PDF, in Markdown
│ ├── analysis_report.json # (JSON Report) Machine-readable summary of the analysis
│ └── analysis_report.xlsx # (Excel Report) Optional Excel format
├── .bak/ # (Backup Files) Temporary or backup directory
│ └── main.py.bak # (Backup Example) Backup of a key file
└── ...
We welcome improvements and suggestions! Please see CONTRIBUTING.md for details on how to get started.
For information on reporting vulnerabilities, please see SECURITY.md.
This project is licensed under the MIT License. See the LICENSE file for details.
- Maintainer: Your Name ([email protected])
- Security Issues: Refer to
SECURITY.md
Happy analyzing! If you have any questions, consult the USER_MANUAL.md or open an issue on GitHub.