Smart release coordination tool that automates communication and coordination tasks within software teams by connecting GitHub, JIRA, and Slack.

• Automatic GitHub pull request tracking and status monitoring
• JIRA ticket synchronization and blocker detection
• Automated Slack notifications and daily standup summaries
• Weekly changelog generation from commit history
• Team analytics and bottleneck identification
• RESTful API for integration with other tools

1. Install uv (if not already installed):

   curl -LsSf https://astral.sh/uv/install.sh | sh

2. Install dependencies:

   uv sync

3. Set up the database:

   cp .env.example .env
   # Edit .env with your Supabase credentials (see docs/database-setup.md)
   
   # Run database migrations (see setup guide for details)
   uv run python -m devsync_ai.database.migrations.runner
   
   # Verify database connection
   uv run python scripts/check_database.py

4. Configure other services:

   # Edit .env with your GitHub, JIRA, and Slack API keys

5. Run the application:

   uv run python -m devsync_ai.main

6. Access the API:

   • API documentation: http://localhost:8000/docs
   • Health check: http://localhost:8000/api/v1/health

1. Connect your GitHub repository to Render
2. Create a new Web Service with these settings:
   • Build Command: uv sync
   • Start Command: uv run python -m devsync_ai.main
   • Environment: Python 3.11+
3. Add environment variables from your .env.example file
4. Deploy! Render will automatically handle the rest

All configuration is managed through environment variables. See .env.example for all available settings.

• SUPABASE_URL and SUPABASE_SERVICE_ROLE_KEY: Database connection (see Database Setup Guide)
• GITHUB_TOKEN: GitHub API access
• JIRA_URL, JIRA_USERNAME, JIRA_TOKEN: JIRA integration
• SLACK_BOT_TOKEN, SLACK_SIGNING_SECRET: Slack integration
• SECRET_KEY: Application security

DevSync AI uses Supabase as its database. Follow the Database Setup Guide for detailed instructions on:

1. Creating a Supabase project
2. Getting your connection credentials
3. Running database migrations
4. Verifying the setup

Quick verification:

uv run python scripts/check_database.py

The project follows a modular architecture:

• devsync_ai/api/: REST API endpoints
• devsync_ai/webhooks/: Webhook handlers for external services
• devsync_ai/services/: Business logic and external API integrations
• devsync_ai/models/: Data models and validation
• devsync_ai/scheduler/: Background tasks and automation
• devsync_ai/utils/: Utility functions and helpers

MIT License