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Template Repo for orchestrating LLM calls using LangGraph. Includes 8 working examples, testing, CI/CD pipelines, and documentation. I designed this project to demo multi-agent coordination, memory management, and agentic patterns for my colleagues. You can use this as a template for building your own LangGraph applications.

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Greenskin44/task-MASter-LangGraph

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GitHub Configuration

This directory contains GitHub-specific configuration files for CI/CD, automation, and project management.

Contents

Workflows (.github/workflows/)

  1. ci.yml - Main CI/CD pipeline

    • Runs on: Push and PR to main and develop branches
    • Jobs:
      • test: Runs pytest test suite with API keys
      • code-quality: Runs Black, Ruff, and Mypy checks
    • Python version: 3.11
    • Caches pip dependencies for faster builds
  2. pre-commit.yml - Pre-commit hook validation

    • Runs on: Push and PR
    • Validates all pre-commit hooks in CI
    • Caches pre-commit hooks
  3. dependency-review.yml - Dependency security review

    • Runs on: Pull requests only
    • Reviews dependency changes for security issues
    • Fails on moderate or higher severity vulnerabilities
    • Posts summary comment in PR

Dependabot (dependabot.yml)

Automated dependency updates:

  • Python packages (pip):

    • Weekly updates on Mondays
    • Groups: langgraph, langchain, development tools
    • Max 5 open PRs
    • Labels: dependencies, python
  • GitHub Actions:

    • Weekly updates on Mondays
    • Max 3 open PRs
    • Labels: dependencies, github-actions

Templates

  • PULL_REQUEST_TEMPLATE.md: Standard PR template with checklist

Setup Requirements

GitHub Secrets

Configure these secrets in repository settings for CI workflows:

Settings → Secrets and variables → Actions → New repository secret

Required secrets:

  • OPENAI_API_KEY: OpenAI API key for LLM operations
  • TAVILY_API_KEY: Tavily API key for web search
  • LANGSMITH_API_KEY: LangSmith API key for tracing (optional)

Branch Protection

Recommended branch protection rules for main:

  • Require pull request reviews before merging
  • Require status checks to pass before merging:
    • test (CI workflow)
    • code-quality (CI workflow)
    • pre-commit (Pre-commit workflow)
  • Require branches to be up to date before merging
  • Require linear history

Workflow Status Badges

Add these badges to your README.md:

![CI](https://github.com/your-username/langgraph-project/workflows/CI/badge.svg)
![Pre-commit](https://github.com/your-username/langgraph-project/workflows/Pre-commit%20Checks/badge.svg)

Customization

Modifying Workflows

  1. Edit workflow files in .github/workflows/
  2. Test in a feature branch
  3. Verify workflows run successfully
  4. Merge to main after approval

Adjusting Dependabot

Edit .github/dependabot.yml to:

  • Change update frequency
  • Modify PR limits
  • Add/remove package groups
  • Change reviewers or labels

Adding New Workflows

  1. Create new .yml file in .github/workflows/
  2. Define triggers, jobs, and steps
  3. Test thoroughly
  4. Document in this README

Troubleshooting

Workflow Failures

Tests fail in CI but pass locally:

  • Check API keys are configured as secrets
  • Verify Python version matches (3.11)
  • Check for environment-specific issues

Code quality checks fail:

  • Run locally: black --check ., ruff check ., mypy graphs/
  • Fix issues and push again
  • Pre-commit hooks should catch these before push

Dependabot PRs fail:

  • Review dependency changelog for breaking changes
  • Test locally before merging
  • Pin versions if needed for stability

Permissions Issues

If workflows can't post comments or update PRs:

  • Check workflow permissions in repository settings
  • Ensure GITHUB_TOKEN has necessary permissions
  • Review workflow permissions: section

Best Practices

  1. Always use feature branches - Never commit directly to main
  2. Keep PRs focused - One feature/fix per PR
  3. Review Dependabot PRs promptly - Don't let them pile up
  4. Monitor workflow runs - Check Actions tab regularly
  5. Update workflows carefully - Test changes thoroughly

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Template Repo for orchestrating LLM calls using LangGraph. Includes 8 working examples, testing, CI/CD pipelines, and documentation. I designed this project to demo multi-agent coordination, memory management, and agentic patterns for my colleagues. You can use this as a template for building your own LangGraph applications.

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