Overview
Project Reader is a desktop application that transforms source-code projects into organized text or Markdown files. It provides a graphical interface for selecting local projects, previewing their structure, and generating output for analysis, documentation, sharing, or use with AI tools. The application runs entirely on the local machine and does not require an API key, web browser, backend server, or cloud service for its main workflow.
The tool offers three processing modes: Prepare for AI, Single file, and Separate files. In Prepare for AI mode, the project is organized into one or more token-limited Markdown or TXT parts, with an option to split large projects automatically. Single file mode combines the selected project into one organized text file, while Separate files mode creates individual text outputs for selected source files. Before generating output, users can preview the project structure and decide which files and folders to include or exclude.
Project Reader includes filtering and preference options, allowing users to configure extensions to process or ignore, folders and files to ignore, relative path rules, and other processing options. Preferences and filtering rules are saved locally and reused by the processing modes. The application also provides a History area to access previous operations and skips blocked or sensitive files where applicable.
A compiled Windows version is available through GitHub Releases, with the current release being v1.0.4, distributed as LeitorDeProjetos-1.0.4.exe. Users of the executable do not need to install Python. The application can also be run from source using Python. It is built with Python, Tkinter, JSON configuration, filesystem APIs, PyInstaller, and GitHub Actions, and is distributed under the MIT License.
Pricing
Free
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Use Cases
- Developers use Project Reader to prepare source-code projects for analysis by converting them into organized text or Markdown files.
- Teams use Project Reader to generate documentation from codebases by exporting project structure and file contents.
- Users share code projects with others by creating combined text files that include the project structure and readable file contents.
- AI practitioners use the Prepare for AI mode to send larger codebases to AI tools without manually copying files one by one.
- Developers use Project Reader to split large projects into multiple parts that fit within token limits for AI processing.
- Users preview project files and folders before generating output to decide what should be included.
- Teams exclude common generated content such as dependencies, caches, builds, and temporary folders from processing.
- Users access previous operations through the History area to review or reuse past exports.
Features
Converts source projects into text
Organizes converted project content
Prepares code for AI analysis
Prepares project content for documentation
Supports code review preparation
Runs as a desktop tool
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