AutoDoc - Git to Report 📚

AutoDoc is a simple but powerful multiplatform tool that automatically analyzes Git commits and generates structured daily CSV reports.
It leverages AI to transform commit history into meaningful documentation with context-aware summaries.

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🚀 How It Works

1. Collect Commits
   AutoDoc scans a Git repository for commits within a given period.

2. Context Injection
   A custom Context.txt file allows you to provide your project background informations for the AI model.

3. Commit Processing

   • Commits are grouped by day.
   • If a day contains many commits, they are split into smaller parts.
   • Each part is sent to the model for structured summarization.

4. AI Integration

   • Can use OpenAI APIs like (/v1/chat/completions).
   • Automatically retries failed requests and waits between calls to avoid memory overload.

5. CSV Generation
   After processing all commits for a day, AutoDoc generates a uniquely named CSV file with the results.

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⚙️ Configuration

All settings are handled in the appsettings.json file:

{
  "RepositoryPath": "C:\\Path\\To\\Your\\Repository",
  "OwnerEmail": "[email protected]",
  "OwnerName": "Your Name",
  "Culture": "en-US",
  "OutputPath": "AutoDoc-Reports",
  "CompletionsUri": "http://localhost:1234/v1/chat/completions",
  "ApiKey": "your_api_key_here",
  "DelayMilliseconds": 20000,
  "ModelTemperature": 0.5,
  "MaxRetries": 2
}

🔢 Explanation of Parameters:

• RepositoryPath → Path to the Git repository to analyze.
• OwnerEmail → Git email address for filtering commits.
• OwnerName → Who is responsible for the commits.
• Culture → Defines reporting culture/locale (e.g., pt-BR, en-US).
• OutputPath → Directory where daily CSV files are saved.
• CompletionsUri → API endpoint.
• ApiKey → API Key if applicable.
• DelayMilliseconds → Delay between requests (prevents RAM overload).
• ModelTemperature → Controls creativity of the model (0 = focused, 1 = creative).
• MaxRetries → How many times to retry if a request fails.

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📝 Context File

Inside the project, you will find Context.txt. This file is user-editable and allows you to context.

You can follows the template:

The project is called [Your Project Name], an [Your Project description].

[Talk about Your Project features]...

The project is developed in/with: [Your Project languages and tools].

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📦 Requirements

Access to an AI server. Ensure it listens on the same port as configured in appsettings.json (default: http://localhost:1234).

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▶️ Usage

1 - Go to releases: Releases

2 - Install the zip

3 - Edit appsettings.json with your repository path and preferences.

4 - Edit Context.txt with your project context.

5 - Make sure AI server is reachable.

6 - Execute AutoDoc.exe

• Option 1: [StartDate] [EndDate] | Explanation: The folllowing arguments will generate 1 month of reports.

PS C:\Users\eduar> C:\Users\eduar\Desktop\AutoDoc-win-x64\AutoDoc.exe 2025-01-01 2025-02-01

• Option 2: [Days] | Explanation: The folllowing argument will generate 1 week of reports from the current day.

PS C:\Users\eduar> C:\Users\eduar\Desktop\AutoDoc-win-x64\AutoDoc.exe 7

• Option 3: No arguments | Explanation: Will generate reports from the current day.

PS C:\Users\eduar> C:\Users\eduar\Desktop\AutoDoc-win-x64\AutoDoc.exe

7 - Check the output folder for generated CSV reports.

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📊 Example Output

After processing, AutoDoc will generate CSV files named by [repoName]-[date]-[guidV7]. Each row contains structured commit summaries enriched with AI-generated insights.

Example file: nice-api-08-14-2025-0198b3ccd15b77a295e7e23516fd3217.csv

Example file content output:

Date;Step;Activity;Description;Motivation;Process;Result;Participants
08/14/2025 13:50:16;Unit Tests;Addition of tests for PersonService;Implementation of unit tests for the 'PersonService' service layer in Nice Acesso.;Ensure the quality and correctness of the operations performed by the 'Person' entity in the access control system.;Use of the xUnit tool for the creation and execution of unit tests.;Addition of tests that validate the basic operations of the 'Person' entity in the system.;Eduardo Rezende
08/14/2025 13:51:08;Tests;Addition of tests for PersonVehicleService;Implementation of unit tests for the PersonVehicleService service layer of the Nice Acesso system.;Ensure the quality and stability of the functionalities related to the association between people and vehicles in the system.;Use of the xUnit testing library, Visual Studio, and .NET framework;Addition of a set of tests that verify the expected behavior of the PersonVehicleService service layer.;Eduardo Rezende
08/14/2025 13:51:30;Unit Tests;Addition of tests for PersonTriggerService;Creation and implementation of unit tests for the PersonTriggerService class, responsible for controlling the interactions between people and triggers in the Nice Acesso system.;Ensure code quality and prevent potential bugs in business logic.;Use of the NUnit library for the creation and execution of unit tests, along with the Visual Studio IDE.;Addition of new tests that can be executed to validate the functionality of the PersonTriggerService class.;Eduardo Rezende
08/14/2025 15:53:42;Development;Refactor: Update PersonService;Update of the GetByType method of the PersonService class to avoid returning errors when no records are found.;Improvement of the user experience by preventing unwanted exceptions.;Use of the C# language (.NET) and the Entity Framework.;Greater stability in the GetByType method call, avoiding unexpected error returns.;Eduardo Rezende
08/14/2025 15:56:58;Development;Refactor: Update PersonTypeService;Update of the Delete and Disable methods of the PersonTypeService class, so that they do not return errors when removing or disabling a person type without associated people.;Improve system safety by avoiding unexpected errors when deleting or disabling person types with associated records.;C# language, Visual Studio, Entity Framework;Delete and Disable methods updated to handle cases where a person type has no associations.;Eduardo Rezende

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💡 Note

🧰 The hardware settings used for the test:

• 12th Generation Intel(R) Core(TM) i5-12450HX Processor (2.40 GHz)

• 16.0 GB Installed RAM DDR5

• 512.0 GB SSD

• NVDIA GeForce RTX 3050 6.0 GB

🤖 The model settings used for the test:

• Publisher: NousResearch

• Model: nous-hermes-2-mistral-7b-dpo

• Params: 8B

• Quant: Q5_K_M

• Size: 5.13 GB

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🤝 Contributing

Contributions are welcome! Feel free to open issues or submit PRs with improvements.

Please for commits pattern follows: pattern

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📜 License

This project is open source and available under the MIT License.