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*A no-code, easy-to-install GitHub bot that automatically analyzes new issues to suggest labels, assignees, and related issues, saving maintainers valuable time.*
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GitBit is a Python-based GitHub bot that streamlines issue management for repository maintainers. It uses natural language processing (NLP) and machine learning to automate repetitive tasks, making it an invaluable tool for managing large open-source projects.
-**🤖 Automatic Issue Linking:** Analyzes new issue descriptions to detect and link semantically related or duplicate issues, reducing clutter and improving organization.
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-**🏷️ Smart Tagging:** Suggests relevant labels (e.g., `bug`, `documentation`, `feature-request`) based on the issue's content, ensuring consistent and meaningful categorization.
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-**👤 Assignee Recommendations:** Recommends contributors to assign issues to, based on their past contributions and expertise demonstrated in previously closed issues.
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---
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## Why It’s Unique
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## 🌟 Overview
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While there are many tools for GitHub automation, GitBit combines NLP and machine learning to provide **intelligent, context-aware suggestions** tailored to each repository. Its focus on issue management—a critical yet time-consuming task—sets it apart from generic bots or static analysis tools.
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GitBit streamlines repository management by leveraging **Natural Language Processing (NLP)**to automate the tedious aspects of GitHub issue handling. Let our intelligent bot handle the triage while you focus on what matters most—building amazing software.
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## How It Works
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## ✨ Key Features
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GitBit is deployed as a GitHub Action that triggers whenever a new issue is opened in your repository. Here's the process:
| 👤 **Assignee Recommendations**| Recommends contributors based on their expertise from previously closed issues | Distributes workload efficiently to the right team members |
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| 🔗 **Automatic Issue Linking**| Scans and links semantically related or duplicate issues | Reduces clutter and centralizes related discussions |
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1.**Trigger:** A new issue is created.
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2.**Analysis:** The bot reads the issue's title and body.
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3.**Processing:**
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* It compares the new issue's text to a keyword map in your config file to suggest labels.
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* It scans recently closed issues to find which users are experts on topics related to the suggested labels.
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* It uses TF-IDF vectorization and cosine similarity to find other open issues with similar content.
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4.**Comment:** The bot posts a single, helpful comment on the new issue with all its suggestions, allowing maintainers to review and apply them with a single click.
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## 🚀 Quick Installation
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---
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Get GitBit running in your repository in just **2 minutes** with these simple steps:
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### 📋 Prerequisites
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- GitHub repository with Issues enabled
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- Repository admin access
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- No coding experience required!
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##🚀 Setup Instructions
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### 🔧 Step 1: Create Workflow File
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Setting up GitBit takes less than 5 minutes.
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Create `.github/workflows/gitbit.yml` in your repository:
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### Step 1: Create the Configuration File
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```yaml
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name: GitBit Bot
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on:
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issues:
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types: [opened]
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In the root of your repository, create a file named `.gitbit.yml`. This file controls the bot's behavior.
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jobs:
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run-gitbit:
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runs-on: ubuntu-latest
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permissions:
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issues: write
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contents: read
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steps:
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- name: Run GitBit Intelligent Issue Bot
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uses: LMLK-seal/GitBit@main
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with:
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github-token: ${{ secrets.GITHUB_TOKEN }}
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```
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**Copy and paste this template into `.gitbit.yml` and customize it for your project:**
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### ⚙️ Step 2: Create Configuration File
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Create `.gitbit.yml` in your repository root:
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```yaml
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#.gitbit.yml
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# GitBit Configuration
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# --- Smart Tagging Configuration ---
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# Map labels to keywords. The bot will suggest a label if an issue's
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# title or body contains any of the associated keywords.
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# Smart Tagging: Map labels to trigger keywords
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tag_keywords:
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bug:
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- error
@@ -52,31 +78,225 @@ tag_keywords:
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- panic
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- crash
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- fail
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- broken
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documentation:
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- docs
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- readme
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- help
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- example
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- tutorial
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- guide
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feature-request:
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- feature
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- enhance
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- improvement
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- idea
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question:
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- how to
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- what is
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- why
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# --- Assignee Recommendation Configuration ---
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# The number of recently closed issues to scan to build an expertise profile.
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